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33 pages, 13410 KiB  
Article
Near-Time Measurement of Aerosol Optical Depth and Black Carbon Concentration at Socheongcho Ocean Research Station: Aerosol Episode Case Analysis
by Soi Ahn, Meehye Lee, Hyeon-Su Kim, Eun-ha Sohn and Jin-Yong Jeong
Remote Sens. 2025, 17(3), 382; https://doi.org/10.3390/rs17030382 - 23 Jan 2025
Viewed by 329
Abstract
This study examined the seasonal variations and influencing factors for black carbon (BC) concentrations and aerosol optical depth (AOD) at the Socheongcho Ocean Research Station (SORS) on the Korean Peninsula from July 2019 to December 2020. An AOD algorithm was developed and validated [...] Read more.
This study examined the seasonal variations and influencing factors for black carbon (BC) concentrations and aerosol optical depth (AOD) at the Socheongcho Ocean Research Station (SORS) on the Korean Peninsula from July 2019 to December 2020. An AOD algorithm was developed and validated using the Geo-KOMPSAT-2A (GK-2A) satellite. The GK-2A AOD demonstrated comparable performance to that of Low Earth Orbit satellites, including the Terra/MODIS (R2 = 0.86), Aqua/MODIS (R2 = 0.83), and AERONET AODs (R2 = 0.85). Multi-angle absorption photometry revealed that seasonal average BC concentrations were the highest in winter (0.91 ± 0.80 µg·m−3), followed by fall (0.80 ± 0.66 µg·m−3), wet summer (0.75 ± 0.55 µg·m−3), and dry summer (0.52 ± 0.20 µg·m−3). The seasonal average GK-2A AOD was higher in wet summer (0.45 ± 0.37 µg·m−3) than in winter. The effects of meteorological parameters, AERONET AOD wavelength, and gaseous substances on GK-2A AOD and BC were investigated. The SHapley Additive exPlanations-based feature importance analysis for GK-2A AOD identified temperature, relative humidity (RH), and evaporation as major contributors. BC concentrations were increased, along with PM2.5 and CO levels, due to the effects of combustion processes during fall and winter. Analysis of high-aerosol-loading cases revealed an increase in the fine-mode fraction, emphasizing the meteorological effects on GK-2A AOD. Thus, long-range transport and local BC sources played a critical role at the SORS. Full article
(This article belongs to the Special Issue Air Quality Mapping via Satellite Remote Sensing)
Show Figures

Figure 1

Figure 1
<p>The location of the Socheongcho Ocean Research Station (SORS), marked with a red star, is shown in the Yellow Sea.</p>
Full article ">Figure 2
<p>Flow chart of Geo-KOMPSAT-2A Advanced Meteorological Imager (GK-2A) aerosol optical depth (AOD) algorithm.</p>
Full article ">Figure 3
<p>Aerosol optical depth (AOD) scatterplot of (<b>a</b>) GK-2A/AMI, (<b>b</b>) Terra/MODIS, and (<b>c</b>) Aqua/MODIS against ground-based reference AERONET data for 40 sites from July 2019 to December 2020. Dotted line shows linear regression, and black line is 1:1 line.</p>
Full article ">Figure 4
<p>Seasonal scatterplots of GK-2A/AMI aerosol optical depth (AOD) against ground-based reference AERONET data for 40 sites from July 2019 to December 2020. Dotted line shows linear regression, and black line is 1:1 line.</p>
Full article ">Figure 5
<p>Seasonal (<b>a</b>,<b>b</b>) and monthly (<b>c</b>,<b>d</b>) variations in (a,<b>c</b>) GK-2A aerosol optical depth (AOD) and (<b>b</b>,<b>d</b>) GK-2A Angstrom Exponent (AE) at Socheongcho Ocean Research Station (SORS).</p>
Full article ">Figure 6
<p>Seasonal (<b>a</b>) and monthly (<b>b</b>) variation in BC at the Socheongcho Ocean Research Station (SORS).</p>
Full article ">Figure 7
<p>Pollutant distribution by wind direction and speed in Socheongcho Ocean Research Station (SORS): (<b>a</b>) GK-2A aerosol optical depth (AOD) and (<b>b</b>) BC. Seasonal distribution of (<b>c</b>) GK-2A AODs and (<b>d</b>) black carbon (BC).</p>
Full article ">Figure 8
<p>(<b>a</b>–<b>h</b>) Weighted potential source contribution function (WPSCF) results of 3-day back-trajectory of HYSPLIT Model for GK-2A aerosol optical depth (AOD) &gt; 0.5 at Socheongcho Ocean Research Station (SORS) (standard).</p>
Full article ">Figure 9
<p>(<b>a</b>–<b>h</b>) Weighted potential source contribution function (WPSCF) result of 3-day back-trajectory of HYSPLIT Model for GK-2A aerosol optical depth (AOD) &gt; 1.0 at Socheongcho Ocean Research Station (SORS) (standard).</p>
Full article ">Figure 10
<p>(<b>a</b>–<b>h</b>) Weighted potential source contribution function (WPSCF) result of 3-day back-trajectory of HYSPLIT Model for BC &gt; 1.0 μg m<sup>−3</sup> at Socheongcho Ocean Research Station (SORS) (standard).</p>
Full article ">Figure 11
<p>(<b>a</b>–<b>h</b>) Weighted potential source contribution function (WPSCF) result of 3-day back-trajectory of HYSPLIT Model for BC &gt; 2.0 μg m<sup>−3</sup> at Socheongcho Ocean Research Station (SORS) (standard).</p>
Full article ">Figure 12
<p>Time series distribution of BC (blue circle) and aerosol optical depth (AOD) from ground measurements (AERONET: red triangle) and satellites (GK-2A/AMI: pink circle, Terra/MODIS: emerald star, Aqua/MODIS: yellow circle) from July 2019 to December 2020.</p>
Full article ">Figure 13
<p>Scatter plot of GK-2A aerosol optical depth (AOD) and BC at Socheongcho Ocean Research Station (SORS) by season. Green triangle: wet summer (July, August), red square: fall (September, October), lavender triangle: winter (December, January, February), green rhombus: spring (March, April), and blue circle: dry summer (May, June).</p>
Full article ">Figure 14
<p>Time series of aerosol episode on 12–15 July 2019 and images of high-aerosol event obtained on 04:00 UTC, 14 July 2019, using (<b>a</b>) GK-2A True = RGB, (<b>b</b>) GK-2A/AMI aerosol optical depth (AOD), (<b>c</b>) Terra/MODIS AOD, (<b>d</b>) Aqua/MODIS AOD, (<b>e</b>) Suomi-NPP/VIIRS AOD, and (<b>f</b>) Suomi-NPP/VIIRS FMF.</p>
Full article ">Figure 15
<p>Time series of aerosol episode on 30 October–2 November 2019 and images of fall aerosol event obtained at 04:00 UTC on 30 October 2019, using (<b>a</b>) GK-2A True RGB, (<b>b</b>) GK-2A/AMI AOD, (<b>c</b>) Terra/MODIS AOD, (<b>d</b>) Aqua/MODIS AOD, (<b>e</b>) Suomi-NPP/VIIRS AOD, and (<b>f</b>) Suomi-NPP/VIIRS FMF.</p>
Full article ">Figure 16
<p>Time series of aerosol episode on 7–10 December 2019 and images of winter aerosol event obtained at 04:00 UTC, on 9 December 2019, using (<b>a</b>) GK-2A True RGB, (<b>b</b>) GK-2A/AMI aerosol optical depth (AOD), (<b>c</b>) Terra/MODIS AOD, (<b>d</b>) Aqua/MODIS AOD, (<b>e</b>) Suomi-NPP/VIIRS AOD, and (<b>f</b>) Suomi-NPP/VIIRS FMF.</p>
Full article ">Figure 17
<p>SHapley Additive exPlanations-based feature importance results for (<b>a</b>) GK-2A aerosol optical depth (AOD) and (<b>b</b>) black carbon (BC) during analysis period.</p>
Full article ">Figure 18
<p>Results for PHEATMAP-based feature importance analysis by (<b>a</b>) season and (<b>b</b>) month.</p>
Full article ">
36 pages, 10632 KiB  
Article
SQM Ageing and Atmospheric Conditions: How Do They Affect the Long-Term Trend of Night Sky Brightness Measurements?
by Pietro Fiorentin, Stefano Cavazzani, Andrea Bertolo, Sergio Ortolani, Renata Binotto and Ivo Saviane
Sensors 2025, 25(2), 516; https://doi.org/10.3390/s25020516 - 17 Jan 2025
Viewed by 397
Abstract
The most widely used radiance sensor for monitoring Night Sky Brightness (NSB) is the Sky Quality Meter (SQM), making its measurement stability fundamental. A method using the Sun as a calibrator was applied to analyse the quality of the measures recorded in the [...] Read more.
The most widely used radiance sensor for monitoring Night Sky Brightness (NSB) is the Sky Quality Meter (SQM), making its measurement stability fundamental. A method using the Sun as a calibrator was applied to analyse the quality of the measures recorded in the Veneto Region (Italy) and at La Silla (Chile). The analysis mainly revealed a tendency toward reductions in measured NSB due to both instrument ageing and atmospheric variations. This work compared the component due to instrumental ageing with the contribution of atmospheric conditions. The spectral responsivity of two SQMs working outdoors were analysed in a laboratory after several years of operation, revealing a significant decay, but not enough to justify the measured long-term trends. The contribution of atmospheric variations was studied through the analysis of solar irradiance at the ground, considering it as an indicator of air transparency, and values of the aerosol optical depth obtained from satellite measurements. The long-term trends measured by weather stations at different altitudes and conditions indicated an increase in solar irradiance in the Italian study sites. The comparison among the daily irradiance increase, the reduction in the aerosol optical depth, and the NSB measurements highlighted a darker sky for sites contaminated by light pollution (LP) and a brighter sky for sites not affected by LP, showing a significant and predominant role of atmospheric conditions in relation to NSB change. In the most significant case, the fraction of the variation in NSB explained by AOD changes exceeded 75%. Full article
Show Figures

Figure 1

Figure 1
<p>The test rig used to analyse the spectral responsivity of the SQMs; it is composed of an LED sphere, a spectroradiometer, and the SQM being tested.</p>
Full article ">Figure 2
<p>The x, y coordinates of the LED light in the CIE Lxy colour space (<b>a</b>); the spectral distributions of the light produced by each LED on the diffuser in the middle of the sphere (<b>b</b>).</p>
Full article ">Figure 3
<p>Maps of the sites of the ARPAV meteorological stations in the Veneto Region. The magenta dots represent the sites of the analysed SQMs (Padova, Asiago, and Passo Valles). The red dots show the sites close to them where the solar irradiance values were measured.</p>
Full article ">Figure 4
<p>The global solar radiation sensor of the ARPAV meteorological stations, model SCHENK 8102.</p>
Full article ">Figure 5
<p>Histograms of SQM difference between measurements from the two different new SQMs and a 6-year-old SQM under the sky at Padova. The sections (<b>a</b>,<b>b</b>) refer to the two new instruments.</p>
Full article ">Figure 6
<p>Output of the tested SQMs normalised to the sphere output for the 9 LEDs; the blue line corresponds to the average of 4 new SQMs and the one SQM often used as reference in outdoor comparison; the light blue line corresponds to the SQM at Padova after 6 working years; the green line corresponds to the SQM at Asiago-Pennar after 10 working years. The vertical bars represent the standard deviation among the five new instruments, while the horizontal bar represents the LED bandwidth.</p>
Full article ">Figure 7
<p>Estimated spectral responsivity of the analysed SQMs. (<b>a</b>) The continuous line represent the average responsivity of the new SQM; the black squares represent the normalised SQM measures, as in <a href="#sensors-25-00516-f006" class="html-fig">Figure 6</a>; and the blue circles show the estimates of the measures calculated from the spectral responsivity. (<b>b</b>) The continuous blue line shows the average spectral responsivity of new SQMs with its uncertainty (blue dotted lines), the red line corresponds to the SQM used at Padova after 6 years, and the magenta line represents the SQM used 10 years at Asiago-Pennar.</p>
Full article ">Figure 8
<p>Spectral responsivity of new and aged SQMs and spectra of the night sky, the spectra with lower values correspond to low light polluted skies, represented by the red line, the higher one to the most light-polluted sky, represented by the blue line (<b>a</b>). Output variations of the two aged SQMs as responses of the different sky spectra, compared to a new SQM (<b>b</b>).</p>
Full article ">Figure 9
<p>Average daily solar irradiance at the selected sites: (<b>a</b>) Legnaro, (<b>b</b>) Montecchio Precalcino, and (<b>c</b>) Passo Valles. The blue lines show the daily values, and the red lines represent the result of a moving average action with a window width of 2 years.</p>
Full article ">Figure 10
<p>Solar irradiance averaged over a 2-year sliding window at Legnaro, Montecchio Precalcino, Passo Valles, and Asiago. Asiago is the station closest to Ekar but presents a significant effect of the presence of clouds.</p>
Full article ">Figure 11
<p>Comparison of the time evolution of the solar radiation (red dots and lines) and AOD (blue dots and lines) at Padova: daily data (<b>a</b>) and long-term trends obtained by averaging daily data using a 2-year sliding window (<b>b</b>).</p>
Full article ">Figure 12
<p>Correlation between monthly average solar radiation and AOD at Padova. The blue circles represent the monthly values, and the red line shows the result of the regression analysis, whose boundary with 95% uncertainty is shown by the dashed lines.</p>
Full article ">Figure 13
<p>SQM measurements of the sky brightness at dusk versus daily solar irradiance for the three analysed Italian sites, Padova (<b>a</b>), Asiago-Ekar (<b>b</b>), and Passo Valles (<b>c</b>). A moving average with a 2-year sliding window is applied to daily data.</p>
Full article ">Figure 14
<p>(<b>a</b>) Sun irradiance averaged over a 2-year sliding window at Legnaro, Montecchio Precalcino, Passo Valles; in the legend the names of the SQM sites are shown according to <a href="#sensors-25-00516-t001" class="html-table">Table 1</a>. The starting points of the curves correspond to the first data of the related SQM stations. (<b>b</b>) Circles represent the values of the monthly mode of the SQM measures at Asiago-Ekar, and the continuous line shows the average trend over a 2-year sliding window. It is an example of the available SQM data.</p>
Full article ">Figure 15
<p>Monthly mode of NSB measured by the SQM versus the daily average solar irradiance at Padova (<b>a</b>) and at the site of Asiago-Ekar and Passo Valles (<b>b</b>). The average trends are shown by the red continuous lines. The blue curves show the behaviour of the fitting functions.</p>
Full article ">Figure 16
<p>Relationship between aerosol optical depth and sky brightness at twilight at Padova (<b>a</b>), Ekar (<b>b</b>), and Passo Valles (<b>c</b>). Both AOD and sky brightness are values obtained from a moving average with a 2-year sliding window. Data are represented by blue circles, their linear regression is represented by the continuous red line, and the dashed lines show the boundary of the regression with a 95% confidence level.</p>
Full article ">Figure 17
<p>Relationship between the aerosol optical depth and the modal values of the night sky brightness at Padova (<b>a</b>) and at Ekar and Passo Valles (<b>b</b>). The values of both AOD and the NSB mode are obtained from a moving average with a 2-year sliding window. Monthly data are represented by blue circles, their linear regression is shown by the continuous red line, and the dashed lines indicate the boundary of the regression with a 95% confidence level.</p>
Full article ">Figure 18
<p>Average sky brightness at sunset and dawn at La Silla; circles are daily values; the yellow curve represents the averaged value in a sliding window 4 months wide; the green curves represent the variability of the average, accounting for one standard deviation; the red line is the linear regression, with its boundary in blue.</p>
Full article ">Figure 19
<p>Monthly average of the values of the sky brightness at twilight (blue symbols and line) and of the aerosol optical depth at La Silla in the period from 2018 to the beginning of 2024.</p>
Full article ">Figure 20
<p>Sky brightness at twilight versus the aerosol optical depth at La Silla. The straight line represents the linear regression, and the dashed lines show the boundary with a 95% confidence level. The red circles correspond to data with AOD &gt; 0.07, not included in the regression analysis.</p>
Full article ">Figure 21
<p>Monthly mode of the values the of the sky brightness at night (blue symbols and line) and of the aerosol optical depth at La Silla in the period from 2018 and the beginning of 2024.</p>
Full article ">Figure 22
<p>Values of the mode of the night sky brightness versus the aerosol optical depth at La Silla. The straight line represents the linear regression, and the dashed lines show the boundary with a 95% confidence level. The red circles correspond to data with AOD &gt; 0.07, not included in the regression analysis.</p>
Full article ">Figure 23
<p>Sketch—not to scale—of the diffusion of the upward-directed artificial light and downward-directed natural light for sites with different positions relative to the main light pollution sources and aerosol layers. Wider or thicker arrows represent greater luminous flux involved.</p>
Full article ">Figure 24
<p>Correlation analysis of the brightness at twilight and the modal values of NSB for the four analysed sites: Padova (<b>a</b>), Asiago-Ekar (<b>b</b>), Passo Valles (<b>c</b>), and La Silla (<b>d</b>). The blue circles represent the monthly values, the solid red line shows the result of the linear regression, and the dashed lines describe the boundary of the regression with a 95% confidence level.</p>
Full article ">
18 pages, 714 KiB  
Article
Implications of the Intriguing Constant Inner Mass Surface Density Observed in Dark Matter Halos
by Jorge Sánchez Almeida
Galaxies 2025, 13(1), 6; https://doi.org/10.3390/galaxies13010006 - 9 Jan 2025
Viewed by 302
Abstract
It has long been known that the observed mass surface density of cored dark matter (DM) halos is approximately constant, independently of the galaxy mass (i.e., ρcrcconstant, with ρc and rc being the central volume [...] Read more.
It has long been known that the observed mass surface density of cored dark matter (DM) halos is approximately constant, independently of the galaxy mass (i.e., ρcrcconstant, with ρc and rc being the central volume density and the radius of the core, respectively). Here, we review the evidence supporting this empirical fact as well as its theoretical interpretation. It seems to be an emergent law resulting from the concentration–halo mass relation predicted by the current cosmological model, where the DM is made of collisionless cold DM particles (CDM). We argue that the prediction ρcrcconstant is not specific to this particular model of DM but holds for any other DM model (e.g., self-interacting) or process (e.g., stellar or AGN feedback) that redistributes the DM within halos conserving its CDM mass. In addition, the fact that ρcrcconstant is shown to allow the estimate of the core DM mass and baryon fraction from stellar photometry alone is particularly useful when the observationally expensive conventional spectroscopic techniques are unfeasible. Full article
Show Figures

Figure 1

Figure 1
<p>Compilation of values of <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> from the literature as a function of the DM halo mass of the galaxy (<math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math>). Details on the references and the processing are given in <a href="#app1-galaxies-13-00006" class="html-app">Appendix A</a>. A version of this figure, but showing the same eight orders of magnitude range for abscissae and ordinates, is shown in <a href="#galaxies-13-00006-f0A1" class="html-fig">Figure A1</a>. References: Burkert 95 [<a href="#B4-galaxies-13-00006" class="html-bibr">4</a>], Kormendy+16 [<a href="#B11-galaxies-13-00006" class="html-bibr">11</a>], Donato+09 [<a href="#B7-galaxies-13-00006" class="html-bibr">7</a>], Oh+15 [<a href="#B2-galaxies-13-00006" class="html-bibr">2</a>], Burkert 15 [<a href="#B10-galaxies-13-00006" class="html-bibr">10</a>], Spano+08 [<a href="#B6-galaxies-13-00006" class="html-bibr">6</a>], Saburova+14 [<a href="#B9-galaxies-13-00006" class="html-bibr">9</a>], Di Paolo+19 [<a href="#B12-galaxies-13-00006" class="html-bibr">12</a>], and Salucci+12 [<a href="#B8-galaxies-13-00006" class="html-bibr">8</a>]. The inset gives a color and symbol code which is the same used in <a href="#galaxies-13-00006-f003" class="html-fig">Figure 3</a>, <a href="#galaxies-13-00006-f004" class="html-fig">Figure 4</a> and <a href="#galaxies-13-00006-f005" class="html-fig">Figure 5</a>.</p>
Full article ">Figure 2
<p>Histograms with the distribution of <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> represented in <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a> and detailed in <a href="#app1-galaxies-13-00006" class="html-app">Appendix A</a>. We show three different selections: all galaxies (the blue line), galaxies with halo masses <math display="inline"><semantics> <mrow> <msub> <mi>M</mi> <mi>h</mi> </msub> <mo>&lt;</mo> <msup> <mn>10</mn> <mn>12</mn> </msup> <mspace width="0.166667em"/> <msub> <mi>M</mi> <mo>⊙</mo> </msub> </mrow> </semantics></math> (the red line), and galaxies with <math display="inline"><semantics> <mrow> <msub> <mi>M</mi> <mi>h</mi> </msub> <mo>&lt;</mo> <msup> <mn>10</mn> <mn>11</mn> </msup> <mspace width="0.166667em"/> <msub> <mi>M</mi> <mo>⊙</mo> </msub> </mrow> </semantics></math> (the green line). The last one is representative of dwarf galaxies. The inset gives the median of each distribution, as well as the range between percentiles 15.9% and 84.1% (i.e., median <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>1</mn> <mspace width="0.166667em"/> </mrow> </semantics></math>sigma).</p>
Full article ">Figure 3
<p>Central DM surface density, <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math>, as a function of the absolute magnitude of the galaxy, which is the observable employed to estimate the halo masses represented in <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a>. The absolute magnitude is <math display="inline"><semantics> <msub> <mi>M</mi> <mi>B</mi> </msub> </semantics></math> or <math display="inline"><semantics> <msub> <mi>M</mi> <mi>V</mi> </msub> </semantics></math> depending on the galaxy. The inset gives the color and symbol code, which is the same employed in <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a>, <a href="#galaxies-13-00006-f004" class="html-fig">Figure 4</a> and <a href="#galaxies-13-00006-f005" class="html-fig">Figure 5</a>.</p>
Full article ">Figure 4
<p>Observed <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> versus <math display="inline"><semantics> <msub> <mi>r</mi> <mi>c</mi> </msub> </semantics></math> (<b>top panel</b>) and <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msubsup> <mi>r</mi> <mi>c</mi> <mn>3</mn> </msubsup> </mrow> </semantics></math> versus <math display="inline"><semantics> <msub> <mi>r</mi> <mi>c</mi> </msub> </semantics></math> (<b>bottom panel</b>). Note that the latter gives the DM mass in the core and scales as <math display="inline"><semantics> <msubsup> <mi>r</mi> <mi>c</mi> <mn>2</mn> </msubsup> </semantics></math> following Equation (<a href="#FD3-galaxies-13-00006" class="html-disp-formula">3</a>), which is represented by the gray dashed line. These relations do not depend on the total DM halo mass and can be used to test theoretical explanations bypassing uncertainties in <math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math>. The insets give the color and symbol code, used also in <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a>, <a href="#galaxies-13-00006-f003" class="html-fig">Figure 3</a> and <a href="#galaxies-13-00006-f005" class="html-fig">Figure 5</a>.</p>
Full article ">Figure 5
<p>(<b>Top panel</b>): core radius <math display="inline"><semantics> <msub> <mi>r</mi> <mi>c</mi> </msub> </semantics></math> versus DM halo mass <math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math>. The dashed line is a power law with exponent <math display="inline"><semantics> <mrow> <mo>+</mo> <mn>0.4</mn> </mrow> </semantics></math> and has been included to guide the eye. (<b>Bottom panel</b>): central DM density <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>c</mi> </msub> </semantics></math> versus DM halo mass. This time, the dashed line is a power law with exponent <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>0.4</mn> </mrow> </semantics></math>. The insets give the color and symbol code, which is the same used in <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a>, <a href="#galaxies-13-00006-f003" class="html-fig">Figure 3</a> and <a href="#galaxies-13-00006-f004" class="html-fig">Figure 4</a>.</p>
Full article ">Figure 5 Cont.
<p>(<b>Top panel</b>): core radius <math display="inline"><semantics> <msub> <mi>r</mi> <mi>c</mi> </msub> </semantics></math> versus DM halo mass <math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math>. The dashed line is a power law with exponent <math display="inline"><semantics> <mrow> <mo>+</mo> <mn>0.4</mn> </mrow> </semantics></math> and has been included to guide the eye. (<b>Bottom panel</b>): central DM density <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>c</mi> </msub> </semantics></math> versus DM halo mass. This time, the dashed line is a power law with exponent <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>0.4</mn> </mrow> </semantics></math>. The insets give the color and symbol code, which is the same used in <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a>, <a href="#galaxies-13-00006-f003" class="html-fig">Figure 3</a> and <a href="#galaxies-13-00006-f004" class="html-fig">Figure 4</a>.</p>
Full article ">Figure 6
<p>Piecewise density profiles with an inner core (<math display="inline"><semantics> <mrow> <mi>m</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math> polytrope; <math display="inline"><semantics> <msub> <mi>ρ</mi> <mn>5</mn> </msub> </semantics></math> in Equation (<a href="#FD5-galaxies-13-00006" class="html-disp-formula">5</a>)) and an outer NFW profile (<math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>NFW</mi> </msub> </semantics></math>; Equation (<a href="#FD4-galaxies-13-00006" class="html-disp-formula">4</a>)). The two pieces coincide at the matching radius <math display="inline"><semantics> <msub> <mi>r</mi> <mi>m</mi> </msub> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mn>5</mn> </msub> <mrow> <mo>(</mo> <msub> <mi>r</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>ρ</mi> <mi>NFW</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>r</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> </mrow> </semantics></math>, and the total mass is the total mass of <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>NFW</mi> </msub> <mrow> <mo>(</mo> <mi>r</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (Equation (<a href="#FD8-galaxies-13-00006" class="html-disp-formula">8</a>)). The full NFW profile is shown as a black dashed line whereas profiles for different matching radii are shown with different colors as indicated in the inset.</p>
Full article ">Figure 7
<p>Dependence on <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>m</mi> </msub> <mo>/</mo> <msub> <mi>r</mi> <mi>s</mi> </msub> </mrow> </semantics></math> of <math display="inline"><semantics> <mrow> <mi>b</mi> <mo>/</mo> <msub> <mi>r</mi> <mi>s</mi> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <mo>/</mo> <msub> <mi>ρ</mi> <mi>s</mi> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <mi>b</mi> <mo>/</mo> <mrow> <mo>(</mo> <msub> <mi>ρ</mi> <mi>s</mi> </msub> <msub> <mi>r</mi> <mi>s</mi> </msub> <mo>)</mo> </mrow> </mrow> </semantics></math> as given by Equations (<a href="#FD12-galaxies-13-00006" class="html-disp-formula">12</a>) and (<a href="#FD13-galaxies-13-00006" class="html-disp-formula">13</a>). The solid lines show the actual variation whereas the dashed lines correspond to the dependence when the transition radius <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>m</mi> </msub> <mo>≪</mo> <msub> <mi>r</mi> <mi>s</mi> </msub> </mrow> </semantics></math> (Equations (<a href="#FD15-galaxies-13-00006" class="html-disp-formula">15</a>) and (<a href="#FD16-galaxies-13-00006" class="html-disp-formula">16</a>)). The orange symbol points out when <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>c</mi> </msub> <mo>=</mo> <msub> <mi>r</mi> <mi>s</mi> </msub> </mrow> </semantics></math>, which has <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>m</mi> </msub> <mo>/</mo> <msub> <mi>r</mi> <mi>s</mi> </msub> <mo>≃</mo> <mn>0.56</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <mo>/</mo> <msub> <mi>ρ</mi> <mi>s</mi> </msub> <mo>≃</mo> <mn>4.11</mn> </mrow> </semantics></math>.</p>
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<p>Relation between concentration <span class="html-italic">c</span> and halo mass <math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math> inferred from various CDM-only simulations. The three papers cited in the inset are D&amp;M 14 [<a href="#B32-galaxies-13-00006" class="html-bibr">32</a>], Correa+15 [<a href="#B33-galaxies-13-00006" class="html-bibr">33</a>], and Sorini+24 [<a href="#B34-galaxies-13-00006" class="html-bibr">34</a>]. For reference, we also show a relation obtained when baryon feedback is self-consistently treated in the simulation (the dotted dashed lines). Different redshifts (<span class="html-italic">z</span>) are included with different colors, whereas the type of line encodes the actual reference (see the inset).</p>
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<p>Predicted variation of the central mass surface density <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> as a function of <math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math> for various <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>m</mi> </msub> <mo>/</mo> <msub> <mi>r</mi> <mi>s</mi> </msub> </mrow> </semantics></math> assuming the <span class="html-italic">c</span>–<math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math> relation at redshift zero given in [<a href="#B32-galaxies-13-00006" class="html-bibr">32</a>] (the solid lines). The figure also includes the variation of <math display="inline"><semantics> <msub> <mi>r</mi> <mi>c</mi> </msub> </semantics></math> (the dashed lines) and <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>c</mi> </msub> </semantics></math> (the dashed-dotted lines) to emphasize how the increase in <math display="inline"><semantics> <msub> <mi>r</mi> <mi>c</mi> </msub> </semantics></math> with increasing <math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math> is partly balanced by the decrease in <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>c</mi> </msub> </semantics></math> to produce a fairly constant <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math>. The dotted line shows the approximate dependence of <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> on <math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math> to be expected if <span class="html-italic">c</span> were constant (Equation (<a href="#FD21-galaxies-13-00006" class="html-disp-formula">21</a>)). This power law dependence has been anchored to the observed <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> (Equation (<a href="#FD3-galaxies-13-00006" class="html-disp-formula">3</a>)) assumed to represent <math display="inline"><semantics> <mrow> <msub> <mi>M</mi> <mi>h</mi> </msub> <mo>∼</mo> <msup> <mn>10</mn> <mn>10</mn> </msup> <mspace width="3.33333pt"/> <msub> <mi>M</mi> <mo>⊙</mo> </msub> </mrow> </semantics></math>. The core density <math display="inline"><semantics> <msub> <mi>ρ</mi> <mi>c</mi> </msub> </semantics></math> and core radius <math display="inline"><semantics> <msub> <mi>r</mi> <mi>c</mi> </msub> </semantics></math> are given in units of <math display="inline"><semantics> <mrow> <msub> <mi>M</mi> <mo>⊙</mo> </msub> <mspace width="0.166667em"/> <msup> <mrow> <mi>pc</mi> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math> and <math display="inline"><semantics> <mi>pc</mi> </semantics></math>, respectively.</p>
Full article ">Figure 10
<p>Observed versus predicted <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math>. The observations are the same as those used in <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a> except that ordinates and abscissae have been forced to span the same eight orders of magnitude range. The colored lines represent the theoretical predictions, which depend on the parameter <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mi>m</mi> </msub> <mo>/</mo> <msub> <mi>r</mi> <mi>s</mi> </msub> </mrow> </semantics></math> and the redshift <span class="html-italic">z</span> from which the <span class="html-italic">c</span>–<math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math> relation was taken (see the inset). The range of <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> values for <math display="inline"><semantics> <mrow> <msub> <mi>M</mi> <mi>h</mi> </msub> <mo>&lt;</mo> <msup> <mn>10</mn> <mn>11</mn> </msup> <mspace width="0.166667em"/> <msub> <mi>M</mi> <mo>⊙</mo> </msub> </mrow> </semantics></math> given in Equation (<a href="#FD3-galaxies-13-00006" class="html-disp-formula">3</a>) is shown as the pale green region.</p>
Full article ">Figure 11
<p>Comparison between the DM halo mass in the core of galaxies computed from the stellar velocity dispersion (horizontal axis) and from photometry alone as described by Equation (<a href="#FD25-galaxies-13-00006" class="html-disp-formula">25</a>) (vertical axis). The represented points include UFDs from Richstein+24 [<a href="#B37-galaxies-13-00006" class="html-bibr">37</a>] and dSphs from Kormendy+16 [<a href="#B11-galaxies-13-00006" class="html-bibr">11</a>]. The vertical error bars represent the dispersion in <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math> (Equation (<a href="#FD3-galaxies-13-00006" class="html-disp-formula">3</a>)) whereas the horizontal error bars account for the uncertainties in <math display="inline"><semantics> <msub> <mi>σ</mi> <mrow> <mo>★</mo> <mi>c</mi> </mrow> </msub> </semantics></math>, as quoted in the original references. The one-to-one line is shown as a dashed black line. The red arrows point out upper limits in the dynamical DM halo masses.</p>
Full article ">Figure A1
<p>Figure identical to <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a> except that the range of the ordinates (<math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>c</mi> </msub> <msub> <mi>r</mi> <mi>c</mi> </msub> </mrow> </semantics></math>) has been expanded to show the same eight orders of magnitude variation as the DM halo mass range (<math display="inline"><semantics> <msub> <mi>M</mi> <mi>h</mi> </msub> </semantics></math>). For the rest of details, see <a href="#galaxies-13-00006-f001" class="html-fig">Figure 1</a>.</p>
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11 pages, 967 KiB  
Article
Effect of Exposure to Blue Light from Electronic Devices and the Mediterranean Diet on Macular Pigment
by Marta-C. García-Romera, Víctor Ponce-García, Úrsula Torres-Parejo and Alfredo López-Muñoz
J. Clin. Med. 2024, 13(24), 7688; https://doi.org/10.3390/jcm13247688 - 17 Dec 2024
Viewed by 464
Abstract
Objective: To explore the effect of time exposure to flat screen electronic devices with LED lighting and the Mediterranean diet on macular pigment optical density (MPOD). Methods: In this cross-sectional observational study, the MPOD was measured by heterochromatic flicker photometry in 164 eyes [...] Read more.
Objective: To explore the effect of time exposure to flat screen electronic devices with LED lighting and the Mediterranean diet on macular pigment optical density (MPOD). Methods: In this cross-sectional observational study, the MPOD was measured by heterochromatic flicker photometry in 164 eyes (47 of younger women aged 20–31 and 35 of older women aged 42–70). Exclusion criteria: evidence of macular degeneration and eyes with cataracts. Data on the use of electronic devices and Mediterranean diet adherence were collected through a survey. Nonparametric analysis of variance and independent sample t-tests were used to compare subjects. Results: Significant differences (p < 0.01) were found in total time of exposure to LEDs (hours per day) between both groups (9.31 ± 3.74 younger women vs. 6.33 ± 3.64 older women). The MPOD values for the younger and adult populations were significantly different: 0.38 ± 0.16 and 0.47 ± 0.15 (p < 0.01), respectively. When comparing both groups for the same time of exposure to LEDs, differences were obtained between MPOD values of both populations: For total exposures greater than 6 h per day, the MPOD values were lower in younger women than in adult ones (0.37 ± 0.14 vs. 0.50 ± 0.14, p < 0.01). On the other hand, a significantly higher adherence was found in the older women in comparison with the younger women (OW 9.23 ± 2.50 vs. YW 7.70 ± 2.08, p < 0.01), with higher MPOD values (OW (0.52 ± 0.14) vs. (YW (0.34 ± 0.18). Conclusions: Higher MPOD values are observed with decreasing exposure time to electronic devices with LED lighting screens and higher adherence to the Mediterranean diet. Full article
(This article belongs to the Special Issue Vitreoretinal Diseases: Latest Advance in Diagnosis and Management)
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Figure 1
<p>Time of exposure to SSL screens vs. population (YW: younger women, OW: older women).</p>
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<p>(<b>A</b>,<b>B</b>): Macular pigment optical density (MPOD) (mean ± 95% confidence interval) in relation to time of exposure to SSL screens (hours/day), grouped by age. (YW: younger women, OW: older women).</p>
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16 pages, 2606 KiB  
Article
Affinity Tag-Free Purification of SARS-CoV-2 N Protein and Its Crystal Structure in Complex with ssDNA
by Atanu Maiti and Hiroshi Matsuo
Biomolecules 2024, 14(12), 1538; https://doi.org/10.3390/biom14121538 - 30 Nov 2024
Viewed by 700
Abstract
The nucleocapsid (N) protein is one of the four structural proteins in SARS-CoV-2, playing key roles in viral assembly, immune evasion, and stability. One of its primary functions is to protect viral RNA by forming the nucleocapsid. However, the precise mechanisms by which [...] Read more.
The nucleocapsid (N) protein is one of the four structural proteins in SARS-CoV-2, playing key roles in viral assembly, immune evasion, and stability. One of its primary functions is to protect viral RNA by forming the nucleocapsid. However, the precise mechanisms by which the N protein interacts with viral RNA and assembles into a nucleocapsid remain unclear. Compared to other SARS-CoV-2 components, targeting the N protein has several advantages: it exhibits higher sequence conservation, lower mutation rates, and stronger immunogenicity, making it an attractive target for antiviral drug development and diagnostics. Therefore, a detailed understanding of the N protein’s structure is essential for deciphering its role in viral assembly and developing effective therapeutics. In this study, we report the expression and purification of a soluble recombinant N protein, along with a 1.55 Å resolution crystal structure of its nucleic acid-binding domain (N-NTD) in complex with ssDNA. Our structure revealed new insights into the conformation and interaction of the flexible N-arm, which could aid in understanding nucleocapsid assembly. Additionally, we identified residues that are critical for ssDNA interaction. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) Schematic representation of SARS-CoV-2 virus and its structural proteins (S, N, M, and E) with genomic RNA [created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>]. (<b>b</b>) The N protein is composed of several distinct regions: the N-terminal domain (N-NTD) and the C-terminal domain (N-CTD) connected by a flexible linker, and intrinsically disordered regions like the N-arm and the C-tail.</p>
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<p>SARS-CoV-2 N protein purified by polyethyleneimine precipitation followed by SP Sepharose ion-exchange and finally size-exclusion chromatography. (<b>a</b>) FPLC size-exclusion chromatography and SDS-PAGE analysis of the purified N protein. The blue line represents the UV absorption spectrum of the eluted protein. The dashed green box highlights the absorption of the collected pure N protein. ‘N’ indicates the purified full-length N protein, while ‘M’ represents the protein marker. (<b>b</b>) Mass photometry analysis revealed that the N protein appeared as a monodisperse dimer (~93 kD) in-solution.</p>
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<p>Comparisons of coronavirus N protein structures. (<b>a</b>) Our N protein structure (digested full-length N) showing N-NTD with part of the flexible N-arm (PDB ID:9CJ6; teal color, cartoon) in complex with ssDNA (blue, stick). A 2Fo–Fc electron density map contoured at 1σ is shown in light blue around the ssDNA. (<b>b</b>) Superimposition of our structure with other published SARS-CoV-2 N-NTD structures (PDB ID:7XWZ; light pink color, PDB ID:7CDZ; orange color, PDB ID:7N0R; limon color). (<b>c</b>) Superimposition of our structure with closely related SARS-CoV N-NTD (PDB ID: 2OFZ; navy blue color) and MERS-CoV- N-NTD (PDB ID: 4UD1; purple color) structures. N and C indicate the N- and C-terminal ends of the protein, respectively. The 5′ and 3′ represent the 5′ end and 3′ end of ssDNA. ß and η represent the ß-strand and short 3<sub>10</sub> helix, respectively.</p>
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<p>Crystal packaging of digested N protein. (<b>a</b>) In the crystal, four neighboring protein molecules are colored as teal, hot pink, split pea, and yellow-orange, showing crystal packing at different 90° angles. (<b>b</b>) The N-arm extends to neighboring molecules and is anchored between two molecules through hydrogen bonding. Gray dashed lines represent the hydrogen bonds between amino acids.</p>
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<p>Interactions of N protein with nucleic acids. (<b>a</b>) Superimposition of our structure (teal, PDB ID: 9CJ6) with the crystal structure of the N-NTD complex with dsRNA (light pink, PDB ID: 7XWZ). (<b>b</b>) Superimposition of our structure (teal, PDB ID: 9CJ6) with the NMR structure of the N-NTD complex with ssRNA (yellow, PDB ID: 7ACT). RNA is shown as a cartoon and ssDNA as a stick. ssDNA binds to N-NTD at the RNA binding pocket. (<b>c</b>) Stereo-view of detailed interaction of ssDNA with N-NTD (teal, our structure). (<b>d</b>) Stereo view of the detailed interaction of dsRNA with N-NTD (light pink, PDB ID: 7XWZ). ssDNA and RNA are represented as sticks, and water is represented as the red sphere. Gray dashed lines represent the hydrogen bonds. The nucleic acid bases of ssDNA interact with protein through direct and water-mediated hydrogen bonds. The RNA interacts with protein through hydrogen bonds in the phosphate backbone.</p>
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17 pages, 5124 KiB  
Article
Pulsation in Hot Main-Sequence Stars: Comparison of Observations with Models
by Luis A. Balona
Universe 2024, 10(12), 437; https://doi.org/10.3390/universe10120437 - 25 Nov 2024
Viewed by 660
Abstract
The locations of hot pulsating variables in the H–R diagram are found using the effective temperatures derived from spectroscopic analysis and luminosities from Gaia parallaxes. Frequency peaks extracted from TESS photometry were used to compare with model predictions. A large number of stars [...] Read more.
The locations of hot pulsating variables in the H–R diagram are found using the effective temperatures derived from spectroscopic analysis and luminosities from Gaia parallaxes. Frequency peaks extracted from TESS photometry were used to compare with model predictions. A large number of stars with pulsation frequencies similar to δ Scuti variables were found between the predicted δ Scuti and β Cephei instability regions, contrary to the models. These Maia variables cannot be explained by rapid rotation. There is a serious mismatch between the observed and predicted frequencies for stars within the known δ Scuti instability strip. In δ Scuti and Maia stars, the frequency at the maximum amplitude as a function of the effective temperature was found to have a surprisingly well-defined upper envelope. The majority of γ Doradus stars were found within the δ Scuti instability strip. This is difficult to understand unless pulsational driving is non-linear. Non-linearity may also explain the huge variety in frequency patterns and the presence of low frequencies in hot δ Scuti stars. γ Doradus stars were found all along the main sequence and into the B-star region, where they merged with SPB variables. There seemed to be no distinct instability regions in the H–R diagram. It was concluded that current models do not offer a satisfactory description of observations. Full article
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Figure 1

Figure 1
<p>The location of various classes of pulsating stars in the H–R diagram (<b>left</b> panels) and location of Dziembowski models showing unstable p and g modes (<b>right</b> panels). Only stars with spectroscopic determinations of the effective temperature are shown. The dashed line is the zero-age main sequence. Also shown are the instability regions in BCEP and SPB stars for the solar abundance models from Miglio et al. [<a href="#B40-universe-10-00437" class="html-bibr">40</a>] (solid curve) and the hot and cool edges of the DSCT and GDOR stars from Dupret et al. [<a href="#B1-universe-10-00437" class="html-bibr">1</a>] (thick black lines) and Xiong et al. [<a href="#B2-universe-10-00437" class="html-bibr">2</a>] (orange lines).</p>
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<p>The same as the left panel of <a href="#universe-10-00437-f001" class="html-fig">Figure 1</a> but with stars separated according to the way their effective temperatures were obtained. Stars with spectroscopic determinations of <math display="inline"><semantics> <msub> <mi>T</mi> <mi>eff</mi> </msub> </semantics></math> are shown in the left panel. The middle panel shows stars where <math display="inline"><semantics> <msub> <mi>T</mi> <mi>eff</mi> </msub> </semantics></math> was obtained from narrow-band photometry. Stars with less precise determinations of <math display="inline"><semantics> <msub> <mi>T</mi> <mi>eff</mi> </msub> </semantics></math> are shown in the right hand panel. Stars in the panels on the right, where for some stars, <math display="inline"><semantics> <msub> <mi>T</mi> <mi>eff</mi> </msub> </semantics></math> was estimated from the spectral type, were dithered to eliminate vertical stripes corresponding to distinct subtypes.</p>
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<p>The ratio <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>/</mo> <msub> <mi>N</mi> <mi>MS</mi> </msub> </mrow> </semantics></math> as a function of the effective temperature. <span class="html-italic">N</span> is the number of stars of the particular variability class and <math display="inline"><semantics> <msub> <mi>N</mi> <mi>MS</mi> </msub> </semantics></math> is the number of main-sequence stars within the temperature bin size. The vertical dashed lines indicate the minimum and maximum temperatures of the hot edges of the DSCT and GDOR stars predicted by various models. The cool edge of the BCEP instability region from Miglio et al. [<a href="#B39-universe-10-00437" class="html-bibr">39</a>] is also shown.</p>
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<p>The top panel shows the frequency of the largest amplitude of various types of TESS pulsating stars as a function of the effective temperature. The bottom panel shows the frequencies of unstable modes with <math display="inline"><semantics> <mrow> <mi>l</mi> <mo>≤</mo> <mn>2</mn> </mrow> </semantics></math> in non-rotating Dziembowski models.</p>
Full article ">Figure 5
<p>The top panel shows the frequency of the maximum amplitude as a function of the effective temperature for the DSCT stars. The black outline is the envelope of the highest amplitude growth rate of low-degree p modes shown in Figure 9 of Xiong et al. [<a href="#B2-universe-10-00437" class="html-bibr">2</a>]. The blue outline is the envelope of the unstable modes from the Dziembowski models. The frequencies of the unstable modes in the Dziembowski models is shown in the bottom panel.</p>
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<p>The top panel shows the locations of TESS DSCT stars in the H–R diagram enclosed by a schematic trapezium (magenta). The hot and cool edges were from Dupret et al. [<a href="#B1-universe-10-00437" class="html-bibr">1</a>] (black lines) and Xiong et al. [<a href="#B2-universe-10-00437" class="html-bibr">2</a>] (orange lines). The bottom panel shows the TESS GDOR stars enclosed by a schematic triangle (green) and corresponding hot and cool edges. The diagonal dashed line is the zero-age main sequence. In both panels, only stars with spectroscopic estimates of <math display="inline"><semantics> <msub> <mi>T</mi> <mi>eff</mi> </msub> </semantics></math> are shown.</p>
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<p>The frequency of the maximum amplitude as a function of the effective temperature. The top-left panel shows all the DSCT and MAIA stars enclosed by a triangular envelope. The other panels on the left show the stars selected according to <math display="inline"><semantics> <mrow> <mo>Δ</mo> <mi>L</mi> <mo>/</mo> <msub> <mi>L</mi> <mo>⊙</mo> </msub> </mrow> </semantics></math>, the luminosity above the zero-age main sequence. The panels on the right are the corresponding frequencies of the radial modes from the Dziembowski models.</p>
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<p>All observed frequencies in the BCEP, BCEP+SPB or pure SPB stars in the BCEP temperature range are shown in the top panel. The bottom panel shows unstable modes for <math display="inline"><semantics> <mrow> <mi>l</mi> <mo>≤</mo> <mn>2</mn> </mrow> </semantics></math> from the Dziembowski models.</p>
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12 pages, 5435 KiB  
Article
New Astronomical Observatory Design for the Detection and Tracking of Satellite Objects: The Satellite Robotic Observatory (SRO)
by Francisco Espartero, Javier Cubas, David Nespral and Santiago Pindado
Remote Sens. 2024, 16(22), 4206; https://doi.org/10.3390/rs16224206 - 12 Nov 2024
Viewed by 695
Abstract
Robotic Astronomical Observatories (RAOs) have provided very good results in different research projects in astrophysics/astronomy. Their applications in the detection, tracking, and identification of near-Earth objects have contributed to the identification of potentially dangerous objects for our security, such as near-Earth Objects (NEOs), [...] Read more.
Robotic Astronomical Observatories (RAOs) have provided very good results in different research projects in astrophysics/astronomy. Their applications in the detection, tracking, and identification of near-Earth objects have contributed to the identification of potentially dangerous objects for our security, such as near-Earth Objects (NEOs), near-Earth Asteroids (NEAs), meteors, and comets, whose trajectory changes can cause an impact on our planet. If advances in astrometry techniques (measuring the position and trajectory of Earth-orbiting objects) and photometry (variation in light curves) are considered together with the new sensors that work in the optical and near-infrared spectral ranges, a new observatory system that allows for the detection of nearby satellite objects in different spectral ranges and with better-defined optics can be developed. The present paper describes the design of a new observatory applied to the surveillance and tracking of satellites and other debris objects, the Satellite Robotic Observatory (SRO). Starting from general constraints from astronomy observatories, the design process has been determined, considering the main objectives, the necessary sensors, and several technical improvements that have contributed to a final configuration proposed for the SRO. The result is the design of a portable observatory model that can host at least two sensors to track and monitor satellite objects simultaneously. Full article
(This article belongs to the Section Engineering Remote Sensing)
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<p>Classic design of an RAO for a telescope and dome (<b>a</b>). Image of an RAO at the Sierra Nevada Astronomical Observatory (<b>b</b>).</p>
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<p>CESAR Astronomical Observatory. ESA-ESAC (Villafranca del Castillo-Madrid). RAO with open roll-off roof (<b>a</b>). S/C 12” telescopes (each one on one of the two pillars displayed in the picture) at f/10 and two CCD cameras, Atik 314 L+ and Atik 4400 (<b>b</b>). RAO with closed roll-off roof (<b>c</b>).</p>
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<p>Sequential diagram of operations to design an SRO.</p>
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<p>Image of a meteor during its entry into the Earth’s atmosphere, captured with sensor 1 and 20″ exposure (<b>a</b>). Image of bolide (meteor with an apparent brightness magnitude greater than the planet Venus) captured with sensor 2 with a 30″ exposure (<b>b</b>).</p>
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<p>Image of the trajectory of an artificial satellite captured by sensor 1 with a 10″ exposure (<b>a</b>). Image of a satellite object and an Iridium captured by sensor 2 with an 8″ exposure (<b>b</b>).</p>
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<p>Satellite traces captured with the Instituto de Astrofísica de Canarias IAC80 telescope, Smith–Cassegrain configuration, 82 cm field, with an exposure time of 3 s for each image.</p>
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<p>Composite photographs by stacking several 25″ exposure images, with a total integration time of 4 h 12′ (<b>a</b>) and 6 h 03′ (<b>b</b>). ZWO ASI 071MC Pro camera (sensor 1) and William Optics 80 mm f/4.8 refracting telescope.</p>
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<p>1.5″ exposure image sequence of a LEO satellite. ZWO ASI 183 Monochrome (sensor 2) and 10″ S/C telescope at f/10 with altazimuth mount.</p>
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<p>Prototype of an SRO, capable of housing a refracting telescope (<b>left</b>) or two wide-field and all-sky objectives (<b>a</b>). The optical systems of this SRO integrate sensors that allow capturing images of artificial satellites in different types of orbits (<b>b</b>).</p>
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<p>Sequential diagram of SRO operation (see also <a href="#remotesensing-16-04206-f009" class="html-fig">Figure 9</a>).</p>
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16 pages, 6426 KiB  
Article
Unveiling Illumination Variations During a Lunar Eclipse: Multi-Wavelength Spaceborne Observations of the January 21, 2019 Event
by Min Shu, Tianyi Xu, Wei Cai, Shibo Wen, Hengyue Jiao and Yunzhao Wu
Remote Sens. 2024, 16(22), 4181; https://doi.org/10.3390/rs16224181 - 9 Nov 2024
Viewed by 740
Abstract
Space-based observations of the total lunar eclipse on 21 January 2019 were conducted using the geostationary Earth-orbiting satellite Gaofen-4 (GF-4). This study represents a pioneering effort to address the observational gap in full-disk lunar eclipse photometry from space. With its high resolution and [...] Read more.
Space-based observations of the total lunar eclipse on 21 January 2019 were conducted using the geostationary Earth-orbiting satellite Gaofen-4 (GF-4). This study represents a pioneering effort to address the observational gap in full-disk lunar eclipse photometry from space. With its high resolution and ability to capture the entire lunar disk, GF-4 enabled both quantitative and qualitative analyses of the variations in lunar brightness, as well as spectra and color changes, across two spatial dimensions, from the whole lunar disk to resolved regions. Our results indicate that before the totality phase of the lunar eclipse, the irradiance of the Moon diminishes to below approximately 0.19% of that of the uneclipsed Moon. Additionally, we observed an increase in lunar brightness at the initial entry into the penumbra. This phenomenon is attributed to the opposition effect, providing scientific evidence for this unexpected behavior. To investigate detailed spectral variations, specific calibration sites, including the Chang’E-3 landing site, MS-2 in Mare Serenitatis, and the Apollo 16 highlands, were analyzed. Notably, the red-to-blue ratio dropped below 1 near the umbra, contradicting the common perception that the Moon appears red during lunar eclipses. The red/blue ratio images reveal that as the Moon enters Earth’s umbra, it does not simply turn red; instead, a blue-banded ring appears at the boundary due to ozone absorption and the lunar surface composition. These findings significantly enhance our understanding of atmospheric effects on lunar eclipses and provide crucial reference information for the future modeling of lunar eclipse radiation, promoting the integration of remote sensing science with astronomy. Full article
(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)
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<p>The effects of removing bad pixels and bad columns for GF-4 B2. (<b>a</b>) Before bad pixels removal; (<b>b</b>) After bad pixels removal; (<b>c</b>) before bad columns removal; (<b>d</b>) after bad columns removal.</p>
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<p>GF-4 B4 image mosaic (<b>Top</b>) and true color image mosaic (red: B4; green: B3; and blue: B2) (<b>Bottom</b>) before and after flat-field correction ((<b>Left</b>): before; (<b>Right</b>): after). The non-uniformity problems between the two stripe areas are significantly resolved.</p>
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<p>An overview of lunar radiation images obtained with a 30 ms exposure time during the lunar eclipse on 21 January 2019, presented in true color (red: B4; green: B3; and blue: B2). A 2% linear stretch was applied to these images for display enhancement to improve visibility.</p>
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<p>Disk-integrated irradiance at the standard distances during the lunar eclipse on 21 January 2019, measured by GF-4 across spectral bands B2–B5. Six sets of double-dotted lines depict each stage of the eclipse, denoted as P1–P4.</p>
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<p>Three sites in GF-4 color mosaic images captured at 02:30 UTC. (1) CE-3, (2) MS-2, and (3) Apollo-16 highlands. Due to the influence of observational geometry and fact that Site (3) is located in highlands, the brightness observed at site (3) is significantly higher than that of other sites. Consequently, a 2% linear stretch was specifically applied to Site (3) to enhance image contrast.</p>
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<p>The radiance spectra variation of CE-3 (<b>Top</b>), MS-2 (<b>Middle</b>) and Apollo 16 highlands (<b>Bottom</b>).</p>
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<p>Ratio of eclipsed irradiance to uneclipsed irradiance at corresponding phase angles over time, utilizing the lunar photometric model for GF-4 B2.</p>
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<p>Ratio images (654 nm/491 nm) from GF-4 data captured at 03:30 UTC, 03:40 UTC, 03:50 UTC, and 04:10 UTC on 21 January 2019.</p>
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17 pages, 5448 KiB  
Article
Biophysical Analysis of Vip3Aa Toxin Mutants Before and After Activation
by Pongsatorn Khunrach, Wahyu Surya, Boonhiang Promdonkoy, Jaume Torres and Panadda Boonserm
Int. J. Mol. Sci. 2024, 25(22), 11970; https://doi.org/10.3390/ijms252211970 - 7 Nov 2024
Viewed by 853
Abstract
Cry toxins from Bacillus thuringiensis are effective biopesticides that kill lepidopteran pests, replacing chemical pesticides that indiscriminately attack both target and non-target organisms. However, resistance in susceptible pests is an emerging problem. B. thuringiensis also produces vegetative insecticidal protein (Vip3A), which can kill [...] Read more.
Cry toxins from Bacillus thuringiensis are effective biopesticides that kill lepidopteran pests, replacing chemical pesticides that indiscriminately attack both target and non-target organisms. However, resistance in susceptible pests is an emerging problem. B. thuringiensis also produces vegetative insecticidal protein (Vip3A), which can kill insect targets in the same group as Cry toxins but using different host receptors, making the combined application of Cry and Vip3A an exciting possibility. Vip3A toxicity requires the formation of a homotetramer. Hence, screening of Vip3A mutants for increased stability requires orthogonal biophysical assays that can test both tetrameric integrity and monomeric robustness. For this purpose, we have used herein for the first time a combination of analytical ultracentrifugation (AUC), mass photometry (MP), differential static light scattering (DSLS) and differential scanning fluorimetry (DSF) to test five mutants at domains I and II. Although all mutants appeared more stable than the wild type (WT) in DSLS, mutants that showed more dissociation into dimers in MP and AUC experiments also showed earlier thermal unfolding by DSF at domains IV–V. All of the mutants were less toxic than the WT, but toxicity was highest for domain II mutations N242C and F229Y. Activation of the protoxin was complete and resulted in a form with a lower sedimentation coefficient. Future high-resolution structural data may lead to a deeper understanding of the increased stability that will help with rational design while retaining native toxicity. Full article
(This article belongs to the Special Issue Molecular Insights into Protein Structure and Folding)
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<p>Location of residues mutated in the Vip3Aa protoxin (PDB: 6TFJ). (<b>A</b>) Atetrameric model of Vip3Aa, where one of the monomers is shown in color and the other three only as a transparent surface. The four residues mutated are indicated (red orange) and highlighted with a dotted rectangle and arrow. The five domains (I–V) of the toxin monomer are color-coded in orange (1–198), grey (199–325), blue (326–536), yellow (537–675), and cyan (676–789), respectively. (<b>B</b>) Same as (<b>A</b>) but showing a single monomer. (<b>C</b>) A close-up of the four residues mutated, seen from the tetrameric interface, where N242, T167, and E168 were mutated to Cys and F229 to Tyr. (<b>D</b>) The top view of the protoxin tetrameric interface, where two T167 residues are in close proximity (bold) whereas the other two are too far away to interact. Nearby residues E168 and N242, which may form interactions, are also shown.</p>
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<p>Molecular mass of Vip3Aa protoxin samples measured using mass photometry. (<b>A</b>) SDS−PAGE gel corresponding to freshly purified WT Vip3Aa and mutants. The black arrow indicates the band with expected molecular mass for the monomer. (<b>B</b>) Mass photometry histograms (particle count) at the indicated mass were fitted to Gaussian distributions (solid lines). Symmetrical peaks centered at 0 kDa are typical noise peaks and were not fitted. Vertical grey lines are shown to guide the eye and indicate the expected mass of monomer, dimer, and tetramer species. For T167C, the peak at 48 kDa could not be fitted into two peaks like for the other mutants. Percentages shown are based on total counts.</p>
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<p>SV analysis of Vip3A protoxin and activated toxin. (<b>A</b>) A comparison of the tetrameric shapes of the toxin before (PDB: 6TFJ) and after activation (PDB: 6TFK). In the latter, the N-terminal fragment is missing and only reached residue 95, and therefore it was extended up to residue 25 using the predicted AF2-structure of the domains I–III (overlayed with the experimental structure). (<b>B</b>,<b>C</b>) A c(s) plot of Vip3A protoxin at 0.5 mg/mL in Tris buffer at 20 °C normalized by band height (<b>B</b>) and proportion of different oligomers (<b>C</b>) calculated from the relative area under the bands in (<b>B</b>). (<b>D</b>,<b>E</b>) Same as (<b>B</b>,<b>C</b>), but for the Vip3A activated toxin. (<b>F</b>) The c(s) plots of the protoxin, with the y-axis not normalized. (<b>G</b>) Same as (<b>F</b>) for the activated toxin. The dotted line is shown to guide the eye. Dots in panels (<b>B</b>,<b>D</b>) represent number of monomers in the oligomer.</p>
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<p>Thermal aggregation curves of protoxin WT Vip3Aa and mutants. (<b>A</b>) Light scattering intensity was normalized, plotted as a function of temperature, and fitted to the Boltzmann equation by non-linear regression to obtain the temperature of aggregation, T<sub>agg</sub>. Each curve is a representative of three independent experiments conducted. The arrow indicates the increase in aggregation temperature between the WT and mutant N242C (~11.5 °C). (<b>B</b>) Average T<sub>agg</sub> values, with error bars representing one SD (<span class="html-italic">n</span> = 3).</p>
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<p>Thermal denaturation shift assay. (<b>A</b>) Melting curves of wild-type Vip3Aa and mutants. The melting temperatures (indicated) are marked by vertical dashed lines. Tm1 and Tm2 values are summarized in (<b>B</b>) with colors to guide the eye: green: more stable than the WT; blue: similar to the WT; red: both Tm1 and Tm2 lower than in the WT.</p>
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<p>Toxicity against <span class="html-italic">S. exigua</span> results. Orange bars: graphical representation in a logarithmic scale of LC<sub>50</sub>, with fiducial limits represented by a vertical bar; cyan bars: LC<sub>50</sub> normalized for the proportion of protoxin tetramer according to AUC and mass photometry.</p>
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<p>Comparison of the possible interactions of protoxin residues 242 and 168. In the WT AF2-predicted structure, N242 forms hydrogen bonds with E168 of the same monomer (cyan), and the latter forms another via main chain atoms with Q174 of a different monomer (magenta). In the experimental structure (6TFJ), these three residues are close, although too far to form hydrogen bonds. In the E168C mutant, the AF2-predicted model shows that the introduced cysteine can form hydrogen bonds with T170 of a neighboring monomer in addition to the aforementioned interaction with Q174, also present in the AF2-predicted models of mutants N242C and the double mutant. N242C may form three possible interactions with the same monomer, one of which is with E168.</p>
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16 pages, 2578 KiB  
Article
The Photometric Testing of High-Resolution Digital Cameras from Smartphones—A Pilot Study
by Sławomir Zalewski and Krzysztof Skarżyński
Sensors 2024, 24(21), 6936; https://doi.org/10.3390/s24216936 - 29 Oct 2024
Viewed by 722
Abstract
Luminance is the fundamental photometric quantity representing the technical meaning of brightness. It is usually measured from a distance using a matrix sensor, which is the basis of the professional instrument. However, specific technical requirements must be fulfilled to achieve accurate results. This [...] Read more.
Luminance is the fundamental photometric quantity representing the technical meaning of brightness. It is usually measured from a distance using a matrix sensor, which is the basis of the professional instrument. However, specific technical requirements must be fulfilled to achieve accurate results. This paper considers whether modern high-resolution smartphone cameras are suitable for luminance measurements. Three cameras from high-end smartphones were evaluated on a dedicated laboratory stand. The sensors’ output characteristics showed relatively good linearity of the individual R, G, and B channels. Unfortunately, the spectral sensitivities were unfavorable, as the minimum error achieved was about 17%. This device is classified outside the generally accepted quality scale for photometric instruments. The presented investigation confirmed that none of the high-resolution smartphone cameras tested was suitable for use as a universal luminance camera. However, one of the test devices can be developmental if restrictively calibrated and used only in a specialistic laboratory stand. Using a smartphone (or only its camera) for luminance measurements requires proper advanced calibration. It is possible, but it limits us to only dedicated applications. The pilot study presented in this paper will help create a suitable test stand for spectacle vision systems, e.g., virtual reality equipment. Full article
(This article belongs to the Section Optical Sensors)
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<p>Relative spectral sensitivities of L, M, and S receptors and photopic vision of the human eye.</p>
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<p>The scheme of the laboratory stand: PB—photometric bench, PS—power supply, L—light source (illuminant A—2856K), L—focusing lens, B—baffle, F—interference filter, D—diffuser, S<sub>1</sub>—place for spectroradiometer head, S<sub>2</sub>—place for the smartphone, LM—luminance meter, ΔD<sub>1</sub>—changeable distance between light source and diffuser to provide proper luminance value, D<sub>2</sub>—constant distance between diffuser and smartphone, ΔL—changeable luminance (for linearity), ΔSPD (for spectral sensitivity).</p>
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<p>The spectral power densities emitted by the test surface using different interference filters.</p>
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<p>Linearity responses for channels of tested smartphones: (<b>a</b>) Smartphone 1, (<b>b</b>) Smartphone 2, (<b>c</b>) Smartphone 3.</p>
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<p>Linearity responses for channels of tested smartphones: (<b>a</b>) Smartphone 1, (<b>b</b>) Smartphone 2, (<b>c</b>) Smartphone 3.</p>
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<p>The value of the proportionality k-factor as a function of the logarithm of luminance for the smartphones tested: (<b>a</b>) Smartphone 1, (<b>b</b>) Smartphone 2, (<b>c</b>) Smartphone 3.</p>
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<p>The value of the proportionality k-factor as a function of the logarithm of luminance for the smartphones tested: (<b>a</b>) Smartphone 1, (<b>b</b>) Smartphone 2, (<b>c</b>) Smartphone 3.</p>
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<p>Matching measured R, G, and B spectral responses of particular smartphones to L, M, and S human eye receptor sensitivities: (<b>a</b>) to receptor L, (<b>b</b>) to receptor M, (<b>c</b>) to receptor S.</p>
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<p>Matching calculated smartphone spectral responses to the photopic luminous efficiency function of a human eye.</p>
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17 pages, 11904 KiB  
Article
The Mechanism of the Nucleus Accumbens–Ventral Pallidum Pathway Mediated by Drug Withdrawal-Induced High-Seeking Motivation in Cocaine Addiction
by Jiayan Tan, Yiming Meng, Wenjie Du, Lingtong Jin, Jing Liang and Fang Shen
Int. J. Mol. Sci. 2024, 25(21), 11612; https://doi.org/10.3390/ijms252111612 - 29 Oct 2024
Viewed by 860
Abstract
The reinforcement of drug-seeking motivation following drug withdrawal is recognized as a significant factor contributing to relapse. The ventral pallidum (VP) plays a crucial role in encoding and translating motivational aspects of reward. However, current research lacks a clear understanding of how the [...] Read more.
The reinforcement of drug-seeking motivation following drug withdrawal is recognized as a significant factor contributing to relapse. The ventral pallidum (VP) plays a crucial role in encoding and translating motivational aspects of reward. However, current research lacks a clear understanding of how the VP mediates drug-seeking motivation and the feedback modulation between the VP and the nucleus accumbens (NAc) following drug withdrawal. Therefore, utilizing a rat model of cocaine self-administration, we investigated the circuitry mechanisms underlying drug-seeking behavior post-drug withdrawal involving the NAc-VP pathway. Initially, we observed a significant enhancement in drug-seeking behavior 14 days after cocaine withdrawal. Subsequently, we identified the feedback mechanism through which the NAc-VP regulates this behavior. Immunofluorescence results indicated an increase in c-Fos expression levels in the ventral pallidum ventromedial (VPvm) and ventrolateral ventral pallidum (VPvl) following drug withdrawal. Calcium fiber photometry further elucidated that during the expression of high motivational drug-seeking behavior, there was a specific enhancement in VPvm neuronal activity, and retrograde tracing techniques suggested a weakened transmission function in the NAc-VPm pathway. Additionally, chemical genetic techniques demonstrated that inhibiting the activity of the NAc-VP pathway could increase the motivational level of drug-seeking behavior. These findings indicate that the reduced inhibitory function of the NAc-VP pathway following prolonged cocaine withdrawal forms the basis for heightened reactivity in VPvm neurons, thus regulating the expression of high motivational behavior triggered by drug-related cues. Our study results suggest that maintaining normal NAc-VP pathway functionality may decrease drug-seeking motivation post long-term drug withdrawal, offering new insights for interventions targeting relapse. Full article
(This article belongs to the Special Issue Neurobiological Mechanisms of Addictive Disorders)
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<p>Cocaine-seeking motivation model in rats: (<b>A</b>) Behavioral protocol; (<b>B</b>) Diagram of SA behavioral training in rats (two-way ANOVA followed by Tukey’s multiple comparisons test); (<b>C</b>) Results of the drug seeking motivation test at different times of withdrawal (WD1 is the 1st day of withdrawal; WD14 is the 14th day of withdrawal; WD28 is the 28th day of withdrawal). <span class="html-italic">n</span> = 8 for WD1 group; <span class="html-italic">n</span> = 4 for WD14 group; and <span class="html-italic">n</span> = 6 for WD28 group. * <span class="html-italic">p</span> &lt; 0.05 (WD1 vs. WD14, one-way ANOVA followed by Tukey’s multiple comparisons test).</p>
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<p>Expression of c-Fos positive cells of the VP subregions at different times during withdrawal. (<b>A</b>) Behavioral protocol; (<b>B</b>–<b>D</b>) WD1, WD14 and WD28 behavioral training diagram (two-way ANOVA followed by Tukey’s multiple comparisons test: (<b>B</b>) sides <span class="html-italic">F</span><sub>(1,80)</sub> = 154.189, <span class="html-italic">p</span> &lt; 0.0001; (<b>C</b>) sides <span class="html-italic">F</span><sub>(1,60)</sub> = 45.832, <span class="html-italic">p</span> &lt; 0.0001; (<b>D</b>) sides <span class="html-italic">F</span><sub>(1,80)</sub> = 96.565, <span class="html-italic">p</span> &lt; 0.0001, days <span class="html-italic">F</span><sub>(1,60)</sub> = 2.341, <span class="html-italic">p</span> = 0.025, sides × days <span class="html-italic">F</span><sub>(9,60)</sub> = 3.050, <span class="html-italic">p</span> = 0.005); (<b>E</b>) Amount of cocaine used during the entire training period for the three groups of rats (two-way ANOVA followed by Tukey’s multiple comparisons test); (<b>F</b>) Drug-seeking behavioral test results in the three groups of rats, * <span class="html-italic">p</span> &lt; 0.05; (<b>G</b>) Schematic representation of expression levels of c-Fos positive cells in VP subregions; (<b>H</b>–<b>J</b>) Statistical plots of c-Fos activation in different subregions of the VP, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 (WD1: <span class="html-italic">n</span> = 5; WD14: <span class="html-italic">n</span> = 4; WD28: <span class="html-italic">n</span> = 4; one-way ANOVA followed by Tukey’s multiple comparisons test).</p>
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<p>Neuronal activation in the VPvm and VPvl at different times during withdrawal. (<b>A</b>) Behavioral training and fiber photometry protocol; (<b>B</b>) Diagram of behavioral training of rats for fiber photometry (two-way ANOVA followed by Tukey’s multiple comparisons test. sides <span class="html-italic">F</span><sub>(1,220)</sub> = 152.8, <span class="html-italic">p</span> &lt; 0.0001); (<b>C</b>) Drug-seeking behavioral test in two groups of rats, * <span class="html-italic">p</span> &lt; 0.05; (<b>D</b>–<b>I</b>) Changes in neuronal calcium activity recorded in the VPvm and VPvl during the nose poking in the active side in the behavioral tests. (<b>D</b>,<b>G</b>) show positions, and (<b>E</b>,<b>H</b>) represent calcium signal changes in the VPvm during nose poking on the active side. The neuronal activation situation was characterized by calcium signaling changes within 5 s after the poking. The recorded data were calcium activity of the neuronal population, and the included data were the calcium signals in each brain side under a stable recording of calcium signal during behavioral tests. (<b>F</b>,<b>I</b>) show quantitative plots of calcium imaging results (one-way ANOVA followed by Tukey’s multiple comparisons test: (<b>F</b>) days <span class="html-italic">F</span><sub>(2,11)</sub> = 7.668, <span class="html-italic">p</span> &lt; 0.01; ** <span class="html-italic">p</span> &lt; 0.01); (<b>J</b>,<b>K</b>) Schematic diagram of the optical fiber and virus diffusion. VPvm (<b>J</b>), VPvl (<b>K</b>). (The number of animals tested was 12, and bilateral brain regions per animal, 24 calcium signal data in total, while stable recordings were included in the analysis: <span class="html-italic">n</span> = 10–11, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, one-way ANOVA followed by Tukey’s multiple comparisons test).</p>
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<p>Functional alterations in neural projections from NAc shell to VPvm detected by in vivo fiber photometry. (<b>A</b>) Behavioral training protocol; (<b>B</b>) Schematic representation of virus injection and calcium fiber embedding; (<b>C</b>) Behavioral training process of the animals; (<b>D</b>) Drug-seeking behavior test during fiber photometry, * <span class="html-italic">p</span> &lt; 0.05; (<b>E</b>,<b>F</b>) Neuronal activation in VPvm during the active nose poking before and after withdrawal, number of experimental animals: <span class="html-italic">n</span> = 8. (<b>E</b>) The dotted box shows neuronal activity 5 s after the active nose pokes. (<b>F</b>) Quantitative comparison of neuronal activity, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Retrograde tracing and c-Fos co-staining: (<b>A</b>) Flow diagram of experiment; (<b>B</b>) Schematic representation of retrograde tracing and c-Fos co-staining; (<b>C</b>,<b>D</b>) Behavioral training diagram of the WD1 (<b>C</b>) and WD14 (<b>D</b>) rats (two-way ANOVA followed by Tukey’s multiple comparisons test); (<b>E</b>) The total dosage of the WD1 and WD14 during the training, <span class="html-italic">t</span>-test; (<b>F</b>) The co-staining ratio of WD1 and WD14, <span class="html-italic">t</span>-test, ** <span class="html-italic">p</span> &lt; 0.01; (<b>G</b>) Diagram of retrograde tracing virus in WD14 and WD1 rats, the white arrows point to the co-staining cells; (<b>H</b>) Schematic of retrograde tracing virus and c-Fos co-staining on WD14 and WD1 (WD14: <span class="html-italic">n</span> = 6, WD1: <span class="html-italic">n</span> = 10).</p>
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<p>Chemogenetic inhibition of NAc to VP in drug-seeking motivation: (<b>A</b>) Flow diagram of experiment; (<b>B</b>) Schematic representation of chemogenetic inhibition of NAc to VP; (<b>C</b>,<b>D</b>) Behavioral training diagram of the chemogenetic inhibition animals (<b>C</b>) and the control animals (<b>D</b>) (two-way ANOVA followed by Tukey’s multiple comparisons test); (<b>E</b>) The total dosage of the two group animals during the training, <span class="html-italic">t</span>-test; (<b>F</b>) Drug-seeking motivation test, <span class="html-italic">t</span>-test; (<b>G</b>) Chemogenetic virus expression map; (<b>H</b>) Chemogenetic virus effect verified by the expression level of the c-Fos positive cells (up: chemogenetic inhibition, hM4Di-CNO, <span class="html-italic">n</span> = 6; down: control, hM4Di-Vehicle, <span class="html-italic">n</span> = 4).</p>
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25 pages, 943 KiB  
Article
A Survey of Dynamical and Gravitational Lensing Tests in Scale Invariance: The Fall of Dark Matter?
by André Maeder and Frédéric Courbin
Symmetry 2024, 16(11), 1420; https://doi.org/10.3390/sym16111420 - 24 Oct 2024
Viewed by 1613
Abstract
We first briefly review the adventure of scale invariance in physics, from Galileo Galilei, Weyl, Einstein, and Feynman to the revival by Dirac (1973) and Canuto et al. (1977). In the way that the geometry of space–time can be described by the coefficients [...] Read more.
We first briefly review the adventure of scale invariance in physics, from Galileo Galilei, Weyl, Einstein, and Feynman to the revival by Dirac (1973) and Canuto et al. (1977). In the way that the geometry of space–time can be described by the coefficients gμν, a gauging condition given by a scale factor λ(xμ) is needed to express the scaling. In general relativity (GR), λ=1. The “Large Number Hypothesis” was taken by Dirac and by Canuto et al. to fix λ. The condition that the macroscopic empty space is scale-invariant was further preferred (Maeder 2017a), the resulting gauge is also supported by an action principle. Cosmological equations and a modified Newton equation were then derived. In short, except in extremely low density regions, the scale-invariant effects are largely dominated by Newtonian effects. However, their cumulative effects may still play a significant role in cosmic evolution. The theory contains no “adjustment parameter”. In this work, we gather concrete observational evidence that scale-invariant effects are present and measurable in astronomical objects spanning a vast range of masses (0.5 M< M <1014M) and an equally impressive range of spatial scales (0.01 pc < r < 1 Gpc). Scale invariance accounts for the observed excess in velocity in galaxy clusters with respect to the visible mass, the relatively flat/small slope of rotation curves in local galaxies, the observed steep rotation curves of high-redshift galaxies, and the excess of velocity in wide binary stars with separations above 3000 kau found in Gaia DR3. Last but not least, we investigate the effect of scale invariance on gravitational lensing. We show that scale invariance does not affect the geodesics of light rays as they pass in the vicinity of a massive galaxy. However, scale-invariant effects do change the inferred mass-to-light ratio of lens galaxies as compared to GR. As a result, the discrepancies seen in GR between the total lensing mass of galaxies and their stellar mass from photometry may be accounted for. This holds true both for lenses at high redshift like JWST-ER1 and at low redshift like in the SLACS sample. Of note is that none of the above observational tests require dark matter or any adjustable parameter to tweak the theory at any given mass or spatial scale. Full article
(This article belongs to the Section Physics)
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Figure 1

Figure 1
<p>The red curve shows the scale factor <math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>=</mo> <msub> <mi>t</mi> <mi>in</mi> </msub> <mo>/</mo> <msub> <mi>t</mi> <mn>0</mn> </msub> </mrow> </semantics></math> at the origin of the Universe (<math display="inline"><semantics> <mrow> <mi>a</mi> <mo>(</mo> <msub> <mi>t</mi> <mi>in</mi> </msub> <mo>)</mo> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>) for flat models, with <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, as a function of the present-time <math display="inline"><semantics> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi mathvariant="normal">m</mi> </msub> </semantics></math>. The present scale factor at <math display="inline"><semantics> <msub> <mi>t</mi> <mn>0</mn> </msub> </semantics></math> is <math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> for any <math display="inline"><semantics> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi mathvariant="normal">m</mi> </msub> </semantics></math> (dashed black line). Thus, during the evolution of the Universe from the Big Bang to present time, the value of <math display="inline"><semantics> <mi>λ</mi> </semantics></math> is only vertically moving, for a given <math display="inline"><semantics> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi mathvariant="normal">m</mi> </msub> </semantics></math>, from the red curve to the black dashed line. This shows that, for increasing densities, the amplitudes of the variations of the scale factor <math display="inline"><semantics> <mi>λ</mi> </semantics></math> are very much reduced; <math display="inline"><semantics> <msub> <mi>t</mi> <mi>in</mi> </msub> </semantics></math> is given in Equation (<a href="#FD2-symmetry-16-01420" class="html-disp-formula">2</a>).</p>
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<p>Evolution of the rotation curve of the Milky Way. The gray points are the velocity averages observed by Huang et al. [<a href="#B44-symmetry-16-01420" class="html-bibr">44</a>], with their error bars. The thick red line represents a mean rotation curve. The thin dashed red line describes the flat mean of the wiggles of the velocity distribution up to a radius of 26 kpc. The brown and orange lines show, respectively, the results of Eilers et al. [<a href="#B45-symmetry-16-01420" class="html-bibr">45</a>] and by Jiao et al. [<a href="#B46-symmetry-16-01420" class="html-bibr">46</a>] for the inner galaxy. The blue lines show the rotation curves predicted by the scale-invariant theory for different ages in the past history of the Universe, starting backwards from the red curve. Calculations have been performed with no dark matter in a model with <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi mathvariant="normal">m</mi> </msub> <mo>=</mo> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi mathvariant="normal">b</mi> </msub> </mrow> </semantics></math>, where <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi mathvariant="normal">b</mi> </msub> <mo>=</mo> <mn>0.045</mn> </mrow> </semantics></math>. The thick dashed green line shows a Keplerian curve in <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>/</mo> <msqrt> <mi>r</mi> </msqrt> </mrow> </semantics></math> near the age of galaxy formation.</p>
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<p>Projected velocities <math display="inline"><semantics> <msub> <mi>υ</mi> <mi>p</mi> </msub> </semantics></math> as a function of separation <span class="html-italic">s</span> for the main sample in Figure 13 from Chae [<a href="#B62-symmetry-16-01420" class="html-bibr">62</a>]. The very small red dots are the observed values and the blue dots are the Newtonian values in the Monte-Carlo simulations. The larger dots, red (obs.) and blue (simul.) and their connecting lines are the medians and percentiles, as indicated. The central black dashed line shows the Keplerian relation in <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>/</mo> <msqrt> <mi>s</mi> </msqrt> </mrow> </semantics></math>. The green lines are additional indications of the mean deviations along the hyperbolic path of the loose systems after 1, 3, and 5 Gyr from the time, <math display="inline"><semantics> <msub> <mi>τ</mi> <mi>N</mi> </msub> </semantics></math>, the transition from Newtonian to dynamical acceleration. The direction of the effects in velocity and separation is indicated by a green arrow at the bottom left. The deviation of a given system increases linearly with time as indicated by Equation (<a href="#FD34-symmetry-16-01420" class="html-disp-formula">34</a>). The mean observed relation for the loose systems corresponds to an evolution during about 2 to 3 Gyr. In a few Gyrs, loose systems drift away from the Newtonian relation in a way compatible with the dynamical evolution. (Figure adapted from Chae [<a href="#B62-symmetry-16-01420" class="html-bibr">62</a>]).</p>
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<p>Comparisons of observations and theory for a sample of 40 very wide binaries with exceptionally precise radial velocities, with individual relative errors smaller than 0.005, as selected by Chae [<a href="#B62-symmetry-16-01420" class="html-bibr">62</a>]. The green broken lines shows the isochrones corresponding to departures from the Newtonian law after 1, 3, and 5 Gyr of evolution under the dynamical acceleration in the scale-invariant theory. The departure from Newton’s relation is progressive and tends towards a value between 3 and 5 Gyr (data are from Chae [<a href="#B62-symmetry-16-01420" class="html-bibr">62</a>]).</p>
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<p>Binned root mean square <math display="inline"><semantics> <mrow> <mo>〈</mo> <mo>Δ</mo> <mi>V</mi> <mo>〉</mo> </mrow> </semantics></math> of the relative velocities in the plane of sky as a function of the 2D projected separation <span class="html-italic">s</span> for 450 binary pairs by Hernandez [<a href="#B58-symmetry-16-01420" class="html-bibr">58</a>]. There is a partial overlap of the binned pairs. The number of binary pairs in the various means are indicated. The green lines show the isochrones corresponding to departures from the Newtonian law after 1, 3, and 5 Gyr of evolution (adapted from [<a href="#B58-symmetry-16-01420" class="html-bibr">58</a>]).</p>
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<p>The red thick curve represents the mass–luminosity relation on the zero-age sequence [<a href="#B71-symmetry-16-01420" class="html-bibr">71</a>], according to the scale indicated on the left vertical axis. The other curves describe various IMF: Chabrier [<a href="#B68-symmetry-16-01420" class="html-bibr">68</a>], Salpeter with <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>=</mo> <mn>1.35</mn> </mrow> </semantics></math> [<a href="#B73-symmetry-16-01420" class="html-bibr">73</a>], and the so-called Super-Salpeter by [<a href="#B67-symmetry-16-01420" class="html-bibr">67</a>], according to the scale indicated on the right vertical axis. Note that, in <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>(</mo> <mi>log</mi> <mi>m</mi> <mo>)</mo> </mrow> </semantics></math>, the log is a decimal. The Figure is inspired by [<a href="#B67-symmetry-16-01420" class="html-bibr">67</a>].</p>
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11 pages, 498 KiB  
Article
LAMOST Spectroscopy and Gaia Photo-Astrometry for an Interstellar Extinction Study
by Oleg Malkov, Aleksandra Avdeeva and Dana Kovaleva
Galaxies 2024, 12(5), 65; https://doi.org/10.3390/galaxies12050065 - 17 Oct 2024
Viewed by 675
Abstract
The aim of this work is to establish the present accuracy and convergence of available estimates of galactic extinction. We determine the galactic interstellar extinction in selected high-latitude areas of the sky based on Gaia DR3 astrometry and photometry and spectroscopic data from [...] Read more.
The aim of this work is to establish the present accuracy and convergence of available estimates of galactic extinction. We determine the galactic interstellar extinction in selected high-latitude areas of the sky based on Gaia DR3 astrometry and photometry and spectroscopic data from the LAMOST survey. For this purpose, we choose 42 northern high-latitude sky areas surrounding supernovae that allowed establishing the accelerated expansion of the universe. We compare our results with the estimates accepted in that paper and find that they agree well, within observational errors. Simultaneously, the estimates for galactic extinction by other authors along the same sightlines show systematic differences, which can cause the distance to the extragalactic object to change by ±3–5%. Full article
(This article belongs to the Special Issue Stellar Spectroscopy, Molecular Astronomy and Atomic Astronomy)
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Figure 1
<p>Selected areas. Galactic coordinates, Aitoff projection.</p>
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<p>Angular distance between Gaia DR3 and LAMOST objects in the selected areas.</p>
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<p>Examples of approximation of <math display="inline"><semantics> <mrow> <msub> <mi>A</mi> <mi>V</mi> </msub> <mrow> <mo>(</mo> <mi>d</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> dependence (red curves) in areas l,b = 163,−1 (<b>left</b>), l,b = 69,−1 (<b>middle</b>), and l,b = 111,−1 (<b>right</b>). Green points are stars in the area, with observational errors.</p>
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<p>Quartile values for the areas. Median (<math display="inline"><semantics> <msub> <mi>Q</mi> <mn>2</mn> </msub> </semantics></math>), upper (<math display="inline"><semantics> <msub> <mi>Q</mi> <mn>3</mn> </msub> </semantics></math>) and lower (<math display="inline"><semantics> <msub> <mi>Q</mi> <mn>1</mn> </msub> </semantics></math>) quartiles. The one-to-one relation is shown for reference (<b>left</b> panel).</p>
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<p>Standard deviation SD and interquartile range IQR for the areas. The one-to-one relation is shown for reference.</p>
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<p>Difference between the mean coordinates of all stars of the area and the coordinates of SN, in degrees vs. the number of stars in the area. See text for details.</p>
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<p><math display="inline"><semantics> <msub> <mi>A</mi> <mi>x</mi> </msub> </semantics></math> ([<a href="#B24-galaxies-12-00065" class="html-bibr">24</a>], <a href="#galaxies-12-00065-t001" class="html-table">Table 1</a>) vs. <math display="inline"><semantics> <msub> <mi>A</mi> <mi>V</mi> </msub> </semantics></math> ([<a href="#B20-galaxies-12-00065" class="html-bibr">20</a>]). According to [<a href="#B24-galaxies-12-00065" class="html-bibr">24</a>], uncertainty of 10% is assumed. The one-to-one relation is shown for reference.</p>
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<p><math display="inline"><semantics> <msub> <mi>A</mi> <mrow> <mi>g</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> </semantics></math> vs. <math display="inline"><semantics> <msub> <mi>A</mi> <mi>x</mi> </msub> </semantics></math> [<a href="#B24-galaxies-12-00065" class="html-bibr">24</a>]. The one-to-one relation is shown for reference.</p>
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<p><math display="inline"><semantics> <msub> <mi>A</mi> <mrow> <mi>g</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>A</mi> <mo>(</mo> <mi>S</mi> <mi>F</mi> <mn>11</mn> <mo>)</mo> </mrow> </semantics></math> [<a href="#B21-galaxies-12-00065" class="html-bibr">21</a>]. The one-to-one relation is shown for reference.</p>
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<p><math display="inline"><semantics> <msub> <mi>A</mi> <mrow> <mi>g</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>A</mi> <mo>(</mo> <mi>S</mi> <mi>T</mi> <mi>I</mi> <mi>L</mi> <mi>I</mi> <mi>S</mi> <mi>M</mi> <mo>)</mo> </mrow> </semantics></math> [<a href="#B9-galaxies-12-00065" class="html-bibr">9</a>]. The one-to-one relation is shown for reference.</p>
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<p><math display="inline"><semantics> <msub> <mi>A</mi> <mrow> <mi>g</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>A</mi> <mo>(</mo> <mi>G</mi> <mn>23</mn> <mo>)</mo> </mrow> </semantics></math> [<a href="#B7-galaxies-12-00065" class="html-bibr">7</a>]. According to Gontcharov (private communication), uncertainty of <math display="inline"><semantics> <mrow> <mn>0</mn> <msup> <mo>.</mo> <mi>m</mi> </msup> <mn>06</mn> </mrow> </semantics></math> for <math display="inline"><semantics> <mrow> <mi>A</mi> <mo>(</mo> <mi>G</mi> <mn>23</mn> <mo>)</mo> </mrow> </semantics></math> is assumed. The one-to-one relation is shown for reference.</p>
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<p>Limiting distance <span class="html-italic">d</span>, pc (<b>left</b>) and galactic extinction <math display="inline"><semantics> <msub> <mi>A</mi> <mi>V</mi> </msub> </semantics></math>, mag (<b>right</b>) as functions of galactic latitude <span class="html-italic">b</span> in G23 [<a href="#B7-galaxies-12-00065" class="html-bibr">7</a>].</p>
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26 pages, 52439 KiB  
Article
Photometry and Models of Seven Main-Belt Asteroids
by Jun Tian, Haibin Zhao, Bin Li, Yongxiong Zhang, Jian Chen, Leonid Elenin and Xiaoping Lu
Universe 2024, 10(10), 395; https://doi.org/10.3390/universe10100395 - 14 Oct 2024
Viewed by 975
Abstract
The China Near-Earth Object Survey Telescope (CNEOST) conducted four photometric surveys from 2015 to 2018 using image processing and aperture photometry techniques to obtain extensive light curve data on asteroids. The second-order Fourier series method was selected for its efficiency in determining the [...] Read more.
The China Near-Earth Object Survey Telescope (CNEOST) conducted four photometric surveys from 2015 to 2018 using image processing and aperture photometry techniques to obtain extensive light curve data on asteroids. The second-order Fourier series method was selected for its efficiency in determining the rotation periods of the observed asteroids. Our study successfully derived rotation periods for 892 asteroids, with 648 of those matching values recorded in the LCDB (for asteroids with U > 2). To enhance the reliability of the derived spin parameters and shape models, we also amassed a comprehensive collection of published light curve data supplemented by additional photometric observations on a targeted subset of asteroids conducted using multiple telescopes between 2021 and 2022. Through the application of convex inversion techniques, we successfully derived spin parameters and shape models for seven main-belt asteroids (MBAs): (2233) Kuznetsov, (2294) Andronikov, (2253) Espinette, (4796) Lewis, (1563) Noel, (2912) Lapalma, and (5150) Fellini. Our thorough analysis identified two credible orientations for the rotational poles of these MBAs, shedding light on the prevalent issue of “ambiguity in pole direction” that often accompanies photometric inversion processes. CNEOST continues its observational endeavors, and future collected data combined with other independent photometric measurements will facilitate further inversion to better constrain the spin parameters and yield more refined shape models. Full article
(This article belongs to the Special Issue Space Missions to Small Bodies: Results and Future Activities)
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Figure 1
<p>The left panel shows the <math display="inline"><semantics> <msup> <mi>χ</mi> <mn>2</mn> </msup> </semantics></math> distribution of rotation periods fitted using a second-order Fourier series, with the minimum <math display="inline"><semantics> <msup> <mi>χ</mi> <mn>2</mn> </msup> </semantics></math> corresponding to a rotation period of <math display="inline"><semantics> <mrow> <mi>P</mi> <mo>=</mo> <mn>7.4249</mn> </mrow> </semantics></math> h. The right panel shows folded light curves of (2253) Espinette from a single apparition, with an epoch of <math display="inline"><semantics> <mrow> <mi>J</mi> <msub> <mi>D</mi> <mn>0</mn> </msub> </mrow> </semantics></math> = 2,459,295.649215. Different markers represent photometric data collected on various observing nights (refer to <a href="#universe-10-00395-t0A2" class="html-table">Table A2</a>). The <span class="html-italic">x</span>-axis represents the rotation phase, while the <span class="html-italic">y</span>-axis shows the apparent magnitude.</p>
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<p>The left panel displays a plot of asteroid diameters versus rotation frequency, with the red, blue, and black dots respectively representing asteroids with U = 3, U = 2, and other uncertainty codes in our samples. The right panel provides a comparative illustration of the rotation periods for the same set of asteroids, as recorded in both the LCDB and CNEOST; the red shaded area highlights where the relative error between the rotation periods reported by CNEOST and LCDB is within 10%.</p>
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<p>The <math display="inline"><semantics> <msup> <mi>χ</mi> <mn>2</mn> </msup> </semantics></math> values for all spin axis solutions plotted on a longitude–latitude plane using an Aitoff projection of the sky in ecliptic coordinates. The plot reveals two local minima for the pole position, with the minimum <math display="inline"><semantics> <msup> <mi>χ</mi> <mn>2</mn> </msup> </semantics></math> value highlighted in white for better visibility. These minima correspond to the initial spin pole values of (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>138</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>33</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) and (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>315</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>33</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>), where <math display="inline"><semantics> <mi>λ</mi> </semantics></math> and <math display="inline"><semantics> <mi>β</mi> </semantics></math> represent the ecliptic longitude and latitude of the pole, respectively.</p>
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<p>Convex shape models for (2233) Kuznetsov are shown from the equatorial view (<span class="html-italic">y</span>-axis on the left and <span class="html-italic">x</span>-axis at the center, <math display="inline"><semantics> <msup> <mn>90</mn> <mo>∘</mo> </msup> </semantics></math> apart) and pole-on (<span class="html-italic">z</span>-axis on the right). The shape on the left is reconstructed from the light curves using the best-fit spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mspace width="3.33333pt"/> <mo>=</mo> <mspace width="3.33333pt"/> <mrow> <mo>(</mo> <mn>5.030425</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>147</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>68</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>, while the shape on the right is reconstructed using the second-best spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.030425</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>330</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>59</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>As in <a href="#universe-10-00395-f004" class="html-fig">Figure 4</a>, the convex shape models of (2294) Andronikov are reconstructed using spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.002242</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>313</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>50</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.002243</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>113</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>54</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>As in <a href="#universe-10-00395-f004" class="html-fig">Figure 4</a>, the convex shape models of (2253) Espinette are reconstructed using spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>7.443344</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>144</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>34</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>7.443345</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>322</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>35</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 7
<p>As in <a href="#universe-10-00395-f004" class="html-fig">Figure 4</a>, the convex shape models of (4796) Lewis are reconstructed using spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.508346</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>73</mn> <mo>∘</mo> </msup> <mo>,</mo> <msup> <mn>35</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.508346</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>253</mn> <mo>∘</mo> </msup> <mo>,</mo> <msup> <mn>27</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 8
<p>As in <a href="#universe-10-00395-f004" class="html-fig">Figure 4</a>, the convex shape models of (1563) Noel are reconstructed using spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.548785</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>117</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>54</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.548784</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>292</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>68</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 9
<p>As in <a href="#universe-10-00395-f004" class="html-fig">Figure 4</a>, the convex shape models of (2912) Lapalma are reconstructed using spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.710868</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>60</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>67</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.710865</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>231</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>56</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 10
<p>As in <a href="#universe-10-00395-f004" class="html-fig">Figure 4</a>, the convex shape models of (5150) Fellini are reconstructed using spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.195763</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>115</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>38</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.195770</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>302</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>48</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 11
<p>Example light curves of (2253) Espinette (black dots) alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>7.443344</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>144</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>34</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A1
<p>As in <a href="#universe-10-00395-f003" class="html-fig">Figure 3</a>, the two initial pole coordinates for (2233) Kuznetsov are (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>141</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>63</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) and (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>327</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>54</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>).</p>
Full article ">Figure A2
<p>The light curves (black dots) of (2233) Kuznetsov are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.03425</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>147</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>68</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A3
<p>The light curves (black dots) of (2253) Espinette are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>7.443344</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>144</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>34</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A3 Cont.
<p>The light curves (black dots) of (2253) Espinette are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>7.443344</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>144</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>34</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A4
<p>As in <a href="#universe-10-00395-f003" class="html-fig">Figure 3</a>, the two initial pole coordinates for (4796) Lewis are (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>69</mn> <mo>∘</mo> </msup> <mo>,</mo> <msup> <mn>42</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) and (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>249</mn> <mo>∘</mo> </msup> <mo>,</mo> <msup> <mn>33</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>).</p>
Full article ">Figure A5
<p>The light curves (black dots) of (4796) Lewis are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.508346</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>73</mn> <mo>∘</mo> </msup> <mo>,</mo> <msup> <mn>35</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A6
<p>As in <a href="#universe-10-00395-f003" class="html-fig">Figure 3</a>, the two initial pole coordinates for (2294) Andronikov are (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>108</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>54</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) and (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>315</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>51</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>).</p>
Full article ">Figure A7
<p>The light curves (black dots) of (2294) Andronikov are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.151167</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>190</mn> <mo>∘</mo> </msup> <mo>,</mo> <msup> <mn>28</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A7 Cont.
<p>The light curves (black dots) of (2294) Andronikov are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.151167</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>190</mn> <mo>∘</mo> </msup> <mo>,</mo> <msup> <mn>28</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A8
<p>As in <a href="#universe-10-00395-f003" class="html-fig">Figure 3</a>, the two initial pole coordinates for (1563) Noel are (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>117</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>27</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) and (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>291</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>45</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>).</p>
Full article ">Figure A9
<p>The light curves (black dots) of (1563) Noel are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.548785</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>117</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>54</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A9 Cont.
<p>The light curves (black dots) of (1563) Noel are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>3.548785</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>117</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>54</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A10
<p>As in <a href="#universe-10-00395-f003" class="html-fig">Figure 3</a>, the two initial pole coordinates for (2912) Lapalma are (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>60</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>69</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) and (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>237</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>57</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>).</p>
Full article ">Figure A11
<p>The light curves (black dots) of (2912) Lapalma are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.710868</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>60</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>67</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A11 Cont.
<p>The light curves (black dots) of (2912) Lapalma are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.710868</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>60</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>67</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure A12
<p>As in <a href="#universe-10-00395-f003" class="html-fig">Figure 3</a>, the two initial pole coordinates for (5150) Fellini are (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>114</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>27</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) and (<math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>,</mo> <mi>β</mi> </mrow> </semantics></math>) = (<math display="inline"><semantics> <mrow> <msup> <mn>303</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>42</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>).</p>
Full article ">Figure A13
<p>The light curves (black dots) of (5150) Fellini are shown alongside the synthetic light curves (red dashed curves) produced by the convex shape model with spin parameters <math display="inline"><semantics> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>,</mo> <mi>λ</mi> <mo>,</mo> <mi>β</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>5.195770</mn> <mspace width="4pt"/> <mi mathvariant="normal">h</mi> <mo>,</mo> <msup> <mn>302</mn> <mo>∘</mo> </msup> <mo>,</mo> <mo>−</mo> <msup> <mn>48</mn> <mo>∘</mo> </msup> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">
15 pages, 2407 KiB  
Article
Salinity Tolerance Mechanism of Crithmum maritimum L.: Implications for Sustainable Agriculture in Saline Soils
by Bihter Colak Esetlili, Lale Yildiz Aktas, M. Tolga Esetlili, Tugba Oztekin, Cenk Ceyhun Kılıc and Yusuf Kurucu
Sustainability 2024, 16(18), 8165; https://doi.org/10.3390/su16188165 - 19 Sep 2024
Viewed by 1067
Abstract
Edible halophytes are attracting attention due to their potential for agriculture in saline and marginal areas. The salt tolerance mechanism was analyzed in Crithmum maritimum L., based on ionic, osmotic, and redox homeostasis strategies under salt stress. The methodology involved growing C. maritimum [...] Read more.
Edible halophytes are attracting attention due to their potential for agriculture in saline and marginal areas. The salt tolerance mechanism was analyzed in Crithmum maritimum L., based on ionic, osmotic, and redox homeostasis strategies under salt stress. The methodology involved growing C. maritimum seeds in pots under controlled greenhouse conditions and exposing them to different NaCl concentrations (0, 100, 200, and 300 mM) for five months. High salinity levels decreased plant length and biomass, but the shoot-to-root length and biomass ratio increased significantly. Photosynthetic pigments (chlorophyll and carotenoids) were quantified using spectrophotometric analysis, while macro- and micro-nutrient contents were determined via the Kjeldahl method, flame photometry, and atomic absorption spectrophotometry. Osmolyte accumulation, including proline and glycine betaine, was analyzed using specific biochemical assays, and antioxidant enzyme activities (SOD, CAT, and POX) were measured to assess redox homeostasis. Photosynthetic pigments in C. maritimum leaves slightly increased at 100 mM NaCl, but significantly declined at 200 and 300 mM NaCl. A high Na content in the shoots indicated no restriction in mineral uptake in the roots. Nitrogen and phosphorus slightly decreased under high salinity. The cation content in the shoots varied: potassium decreased, while calcium and magnesium increased with salinity, although the Mg+2/Na+ and K+/Na+ ratios showed similar declining patterns. The micro-nutrients iron and manganese increased in the shoots, while copper remained unchanged. The content of osmolytes proline and glycine betaine significantly increased under the 200 and 300 mM NaCl treatments. Antioxidant enzyme activities (SOD, CAT, and POX) decreased at 100 and 200 mM NaCl, but were strongly induced at 300 mM NaCl. The total antiradical activity of the leaves increased with higher salinity levels. Our results indicated that the facultative halophyte characteristics of C. maritimum emerged after exposure to 200 mM NaCl. Increased calcium content may be a key factor in salinity tolerance. We concluded that C. maritimum employs strong osmotic adjustment and redox homeostasis mechanisms, making it a promising candidate for cultivation in saline environments. Full article
(This article belongs to the Special Issue Advances in Sustainable Agricultural Crop Production)
Show Figures

Figure 1

Figure 1
<p>Analysis of 123 articles on <span class="html-italic">Crithmum maritimum</span> published between 2014 and 2024 based on subject headings from WOS database.</p>
Full article ">Figure 2
<p>Distribution of <span class="html-italic">Crithmum maritimum</span> populations across the study area, highlighting the Aegean Sea coast at Ahmetbeyli, Menderes, Izmir, Türkiye.</p>
Full article ">Figure 3
<p>Growth phenotype of <span class="html-italic">Crithmum maritimum</span> under 300 mM NaCl stress for 5 months.</p>
Full article ">Figure 4
<p>Effects of salinity on total chlorophyll and carotenoid contents of <span class="html-italic">Crithmum maritimum</span> treated with 0 (control), 100, 200, and 300 mM NaCl for 5 months. Values are expressed as means standard deviation; different letters represent significant differences at <span class="html-italic">p</span> &lt; 0.05, as per the results of the LSD test.</p>
Full article ">Figure 5
<p>Effect of different salt treatments on Ca<sup>+2</sup> content of <span class="html-italic">Crithmum maritimum</span> shoots and roots. Values are expressed as means standard deviation; different letters represent significant differences at <span class="html-italic">p</span> &lt; 0.05, as per the results of the LSD test.</p>
Full article ">Figure 6
<p>Effect of different salt treatments on proline (<b>A</b>) and glycine betaine (<b>B</b>) contents of <span class="html-italic">C. maritimum</span> leaves. Values are expressed as means standard deviation; different letters represent significant differences at <span class="html-italic">p</span> &lt; 0.05, as per the results of the LSD test.</p>
Full article ">Figure 7
<p>Effect of different salt treatments on antioxidant enzyme activities (SOD (<b>A</b>), CAT (<b>B</b>), POX (<b>C</b>)) and antiradical activity (<b>D</b>) of <span class="html-italic">Crithmum maritimum</span> leaves. Values are expressed as means standard deviation; different letters represent significant differences at <span class="html-italic">p</span> &lt; 0.05, as per the results of the LSD test.</p>
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