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20 pages, 7294 KiB  
Article
Prelaunch Reflective Solar Band Radiometric Performance of JPSS-3 and -4 VIIRS
by Amit Angal, David Moyer, Xiaoxiong Xiong, Qiang Ji and Daniel Link
Remote Sens. 2024, 16(24), 4799; https://doi.org/10.3390/rs16244799 - 23 Dec 2024
Viewed by 389
Abstract
The Joint Polar Satellite System 3 (JPSS-3) and -4 (JPSS-4) Visible Infrared Imaging Radiometer Suite (VIIRS) instruments are the last in the series (S-NPP VIIRS launched in October 2011, JPSS-1 VIIRS launched in November 2017, and JPSS-2 VIIRS launched in November 2022) of [...] Read more.
The Joint Polar Satellite System 3 (JPSS-3) and -4 (JPSS-4) Visible Infrared Imaging Radiometer Suite (VIIRS) instruments are the last in the series (S-NPP VIIRS launched in October 2011, JPSS-1 VIIRS launched in November 2017, and JPSS-2 VIIRS launched in November 2022) of highly advanced polar-orbiting environmental satellites. Both instruments underwent a comprehensive sensor-level thermal vacuum (TVAC) testing at the Raytheon Technologies El Segundo facility to characterize the spatial, spectral, and radiometric aspects of the VIIRS sensor performance. This paper focuses on the radiometric performance of the 14 reflective solar bands (RSBs) that cover the wavelength range from 0.41 to 2.3 µm. Key instrument calibration parameters such as instrument gain, signal-to-noise ratio (SNR), dynamic range, and radiometric calibration uncertainty were derived from the TVAC measurements for both the primary and redundant electronics at three instrument temperature plateaus: cold, nominal, and hot. This paper shows that all the JPSS-3 and -4 VIIRS RSB detectors have been well characterized, with key performance metrics comparable to the previous VIIRS instruments on-orbit. The radiometric calibration uncertainty of the RSBs is within the 2% requirement, except in the case of band M1 of JPSS-4. Comparison of the radiometric performance to sensor requirements, as well as a summary of key instrument testing and performance issues, is also presented. Full article
(This article belongs to the Collection The VIIRS Collection: Calibration, Validation, and Application)
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Figure 1

Figure 1
<p>Schematic of the optical paths into the VIIRS rotating telescope assembly (RTA) and SDSM during solar observations. The angles and positions are not drawn to scale and are for illustrative purposes.</p>
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<p>Comparison of the on-orbit solar spectral irradiance profile and the SIS-100 radiance profile.</p>
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<p>Cartoon of the TVAC test chamber setup. The Blackbody calibration source (BCS), SVS, TMC-SIS, and SIS-100 sources are shown with respect to the instrument location within the chamber.</p>
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<p>(<b>a</b>–<b>c</b>) dn vs. L with the fits, fractional residuals, tau vs. radiance for band M4H from J3 TVAC. The blue dotted lines represent Lmin and Lmax and the pink dotted line represents Ltyp.</p>
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<p>(<b>a</b>–<b>c</b>) dn vs. L with the fits, fractional residuals, tau vs. radiance for band M4H from J4 TVAC. The blue dotted lines represent Lmin and Lmax and the pink dotted line represents Ltyp.</p>
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<p>(<b>a</b>–<b>c</b>) dn vs. radiance with the fits, fractional residuals, tau vs. radiance for band M4L from J3 TVAC. The blue dotted lines represent Lmin and Lmax and the pink dotted line represents Ltyp.</p>
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<p>(<b>a</b>–<b>c</b>) dn vs. radiance with the fits, fractional residuals, tau vs. radiance for band M4L from J4 TVAC. The blue dotted lines represent Lmin and Lmax and the pink dotted line represents Ltyp.</p>
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<p>(<b>a</b>–<b>c</b>) tau, c0/c1, and c2/c1 coefficients with 2-sigma error bars for band M4H from J3 TVAC.</p>
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<p>(<b>a</b>–<b>c</b>) tau, c0/c1, and c2/c1 coefficients with 2-sigma error bars for band M4L from J3 TVAC.</p>
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<p>(<b>a</b>–<b>c</b>) tau, c0/c1, and c2/c1 coefficients with 2-sigma error bars for band M4H from J4 TVAC.</p>
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<p>(<b>a</b>–<b>c</b>) tau, c0/c1, and c2/c1 coefficients with 2-sigma error bars for band M4L from J4 TVAC.</p>
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<p>(<b>a</b>,<b>b</b>) SNR vs. L for M4H and M4L from J3 TVAC.</p>
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<p>(<b>a</b>,<b>b</b>) SNR vs. L for M4H and M4L from J4 TVAC.</p>
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<p>(<b>a</b>,<b>b</b>) Normalized gain (band-averaged) versus the VNIR FPA and ASP temperatures for JPSS-3 VIIRS.</p>
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<p>(<b>a</b>,<b>b</b>) Normalized gain (band-averaged) versus the VNIR FPA and ASP temperatures for JPSS-4 VIIRS.</p>
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39 pages, 9779 KiB  
Article
The 3Cat-4 Spacecraft Thermal Analysis and Thermal Vacuum Test Campaign Results
by Jeimmy Nataly Buitrago-Leiva, Ines Terraza-Palanca, Luis Contreras-Benito, Lara Fernandez, Guillem Gracia-Sola, Cristina del Castillo Sancho, Lily Ha, David Palma, Malgorzata Solyga and Adriano Camps
Aerospace 2024, 11(10), 805; https://doi.org/10.3390/aerospace11100805 - 30 Sep 2024
Cited by 1 | Viewed by 987
Abstract
3Cat-4 is the fourth member of the CubeSat series of UPC’s NanoSat Lab, and it was selected by the ESA Academy’s Fly Your Satellite! program in 2017. This mission aims at demonstrating the capabilities of nano-satellites, and in particular those based in [...] Read more.
3Cat-4 is the fourth member of the CubeSat series of UPC’s NanoSat Lab, and it was selected by the ESA Academy’s Fly Your Satellite! program in 2017. This mission aims at demonstrating the capabilities of nano-satellites, and in particular those based in the 1-Unit CubeSat standard, for challenging Earth Observation (EO) using Global Navigation Satellite System-Reflectometry (GNSS-R) and L-band microwave radiometry, as well as for Automatic Identification Systems (AIS). The following study presents the results of the thermal analysis carried out for this mission, evaluating different scenarios, including the most critical cases at both high and low temperatures. The results consider different albedos and orbital parameters in order to establish the optimal temperatures to achieve the best mission performance within the nominal temperatures, and in all operational modes of the satellite. Simulation results are included considering the thermal performance of other materials, such as Kapton, as well as the redesign of the optical properties of the satellite’s solar panels. The correlation with the thermal model and the TVAC test campaign was conducted at the ESA ESEC-GALAXIA facilities in Belgium. Full article
(This article belongs to the Special Issue Small Satellite Missions)
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Figure 1
<p>Image of <sup>3</sup>Cat-4 during its integration [<a href="#B1-aerospace-11-00805" class="html-bibr">1</a>].</p>
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<p>Internal stack of <sup>3</sup>Cat-4: 1—ZADS, 2—COMMS &amp; ADCS board, 3—EPS, 4—OBC, 5—FMPL-1, 6—NADS, 7—Structure with deployment switches (kill switches) and 8—Solar Panels.</p>
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<p>Temperature definitions for the TCS [<a href="#B13-aerospace-11-00805" class="html-bibr">13</a>].</p>
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<p>Examples of contact between components.</p>
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<p>Some examples of the components of the detailed thermal model. Note: In (<b>d</b>) The red components are the batteries, the black and grey bricks the electrical components. The battery holders in black are between both batteries.</p>
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<p>Comparison of results in Cold case, minimum temperature in Detumbling (DT) and Sun Safe (Mode) with heater OFF and hysteresis temperature [<a href="#B13-aerospace-11-00805" class="html-bibr">13</a>].</p>
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<p>Thermal design proposal workflow.</p>
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<p>Results during the Thermal Simulation: (<b>a</b>–<b>d</b>) illustrate the variations in temperature throughout the orbital position, represented by different colors and rotation respectively. The screenshot captures one of the last orbits in the Cold Case, Nominal mode 2.5°/s, with a hysteresis temperature with heater OFF.</p>
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<p>Test campaign flowchart [<a href="#B27-aerospace-11-00805" class="html-bibr">27</a>].</p>
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<p>Set-up for the first health check, with the blue non-vacuum-compliant TC connectors [<a href="#B27-aerospace-11-00805" class="html-bibr">27</a>].</p>
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<p>TRP (green) and TC (blue) placement over <sup>3</sup>Cat-4.</p>
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<p>TCs locations.</p>
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<p>Thermal vacuum test campaign. ESA’s facilities of ESEC, Belgium.</p>
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<p>TVAC test sequence diagram.</p>
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<p>Thermal test.</p>
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<p>Hot Thermal Balance: Different thermal dissipation cases.</p>
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<p>Cold Thermal Balance: At heater nominal operating temperature.</p>
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<p>Test execution.</p>
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<p>Pre and post venting temperature profiles.</p>
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<p>Hot Thermal Balance: Results Test VS Thermal Model.</p>
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<p>Cold Thermal Balance: Results Test VS Thermal Model.</p>
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<p>Temperature difference between the Hot Thermal Balance and the Cold Thermal Balance correlation.</p>
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18 pages, 11580 KiB  
Article
Landsat 9 Thermal Infrared Sensor-2 (TIRS-2) Pre- and Post-Launch Spatial Response Performance
by Rehman Eon, Brian N. Wenny, Ethan Poole, Sarah Eftekharzadeh Kay, Matthew Montanaro, Aaron Gerace and Kurtis J. Thome
Remote Sens. 2024, 16(6), 1065; https://doi.org/10.3390/rs16061065 - 18 Mar 2024
Cited by 3 | Viewed by 1952
Abstract
The launch of Landsat 9 (L9) on 27 September 2021 marks the ongoing commitment of the Landsat mission to delivering users with calibrated Earth observations for fifty years. The two imaging sensors on L9 are the Thermal Infrared Sensor-2 (TIRS-2) and the Operational [...] Read more.
The launch of Landsat 9 (L9) on 27 September 2021 marks the ongoing commitment of the Landsat mission to delivering users with calibrated Earth observations for fifty years. The two imaging sensors on L9 are the Thermal Infrared Sensor-2 (TIRS-2) and the Operational Land Imager-2 (OLI-2). Shortly after launch, the image data from OLI-2 and TIRS-2 were evaluated for both radiometric and geometric quality. This paper provides a synopsis of the evaluation of the spatial response of the TIRS-2 instrument. The assessment focuses on determining the instrument’s ability to detect a perfect knife edge. The spatial response was evaluated both pre- and post-launch. Pre-launch testing was performed at NASA Goddard Space Flight Center (GSFC) under flight-like thermal vacuum (TVAC) conditions. On orbit, coastline targets were identified to evaluate the spatial response and compared against Landsat 8 (L8). The pre-launch results indicate that the spatial response of the TIRS-2 sensor is consistent with its predecessor on board L8, with no noticeable decline in image quality to compromise any TIRS science objectives. Similarly, the post-launch analysis shows no apparent degradation of the TIRS-2 focus during the launch and the initial operational timeframe. Full article
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Figure 1
<p>Graphical illustration to construct the oversampled ESF from a slanted-edge target.</p>
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<p>A schematic layout of the CGSE and TIRS-2.</p>
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<p>The CGSE mounted in the TVAC chamber during the lab geometric characterization and calibration of the TIRS-2 sensor at the NASA GSFC facilities.</p>
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<p>(<b>a</b>) TIRS-2 raw image of circular target used for spatial analysis, (<b>b</b>) normalized cross-sections of all rows through the target, (<b>c</b>) all peak response cross-sections for the 80 images acquired during the sub-pixel movement.</p>
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<p>(<b>a</b>) Cross-sections from <a href="#remotesensing-16-01065-f004" class="html-fig">Figure 4</a>c shifted to a common reference frame, (<b>b</b>) the left edge of the response, and (<b>c</b>) the calculated MTF of the system.</p>
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<p>Workflow describing the estimation of the (<b>b</b>,<b>c</b>) ESF, (<b>d</b>) LSF and (<b>e</b>) MTF using the modified Fermi function applied to (<b>a</b>) simulated sinc function for on-orbit spatial assessment of the TIRS-2 sensor.</p>
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<p>The location of the 6 naturally occurring target edge sites to perform the spatial assessment of the TIRS-2 sensor on orbit.</p>
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<p>The measured edge slope for band 10 across the FOV of the sensor during TVAC1 and TVAC2 for both the across- (<b>upper</b>) and along- (<b>lower</b>) track direction. The edge slope requirement of 0.47 for TIRS-2 is shown by the dashed red line.</p>
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<p>The measured edge slope for band 11 across the FOV of the sensor during TVAC1 and TVAC2 for both the across- (<b>upper</b>) and along- (<b>lower</b>) track direction. The edge slope requirement of 0.47 for TIRS-2 is shown by the dashed red line.</p>
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<p>The measured edge extent for band 10 across the FOV of the sensor during TVAC1 and TVAC2 for both the across- (<b>upper</b>) and along- (<b>lower</b>) track direction. The edge extent requirement of 240-m for TIRS-2 is shown by the dashed red line.</p>
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<p>The measured edge extent for band 11 across the FOV of the sensor during TVAC1 and TVAC2 for both the across- (<b>upper</b>) and along- (<b>lower</b>) track direction. The edge extent requirement of 240-m for TIRS-2 is shown by the dashed red line.</p>
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<p>The ESF, LSF, and MTF measured for the edge site location #6 for the TIRS sensor on board L9 (<b>a</b>–<b>d</b>) and L8 (<b>e</b>–<b>h</b>).</p>
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<p>The ESF, LSF, and MTF measured for the edge site location #1 for the TIRS sensor on board L9 (<b>a</b>–<b>d</b>) and L8 (<b>e</b>–<b>h</b>).</p>
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<p>The measured MTF for the (<b>a</b>) L9 and (<b>b</b>) L8 TIRS sensor at the native 100 m resolution for all 6 target sites.</p>
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<p>The measured (<b>a</b>) edge slope, (<b>b</b>) FWHM, and (<b>c</b>) MTF at Nyquist for the TIRS-2 sensor on board L9 for the 6 selected sites from November 2021 to April 2023. The figure demonstrates the consistent performance of TIRS-2 spatial quality across various sites and over time.</p>
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12 pages, 766 KiB  
Article
Immunity from NK Cell Subsets Is Important for Vaccine-Mediated Protection in HPV+ Cancers
by Madison P. O’Hara, Ananta V. Yanamandra and K. Jagannadha Sastry
Vaccines 2024, 12(2), 206; https://doi.org/10.3390/vaccines12020206 - 17 Feb 2024
Viewed by 2220
Abstract
High-risk human papillomaviruses (HPVs) are associated with genital and oral cancers, and the incidence of HPV+ head and neck squamous cell cancers is fast increasing in the USA and worldwide. Survival rates for patients with locally advanced disease are poor after standard-of-care chemoradiation [...] Read more.
High-risk human papillomaviruses (HPVs) are associated with genital and oral cancers, and the incidence of HPV+ head and neck squamous cell cancers is fast increasing in the USA and worldwide. Survival rates for patients with locally advanced disease are poor after standard-of-care chemoradiation treatment. Identifying the antitumor host immune mediators important for treatment response and designing strategies to promote them are essential. We reported earlier that in a syngeneic immunocompetent preclinical HPV tumor mouse model, intranasal immunization with an HPV peptide therapeutic vaccine containing the combination of aGalCer and CpG-ODN adjuvants (TVAC) promoted clearance of HPV vaginal tumors via induction of a strong cytotoxic T cell response. However, TVAC was insufficient in the clearance of HPV oral tumors. To overcome this deficiency, we tested substituting aGalCer with a clinically relevant adjuvant QS21 (TVQC) and observed sustained, complete regression of over 70% of oral and 80% of vaginal HPV tumors. The TVQC-mediated protection in the oral tumor model correlated with not only strong total and HPV-antigen-specific CD8 T cells, but also natural killer dendritic cells (NKDCs), a novel subset of NK cells expressing the DC marker CD11c. Notably, we observed induction of significantly higher overall innate NK effector responses by TVQC relative to TVAC. Furthermore, in mice treated with TVQC, the frequencies of total and functional CD11c+ NK cell populations were significantly higher than the CD11c− subset, highlighting the importance of the contributions of NKDCs to the vaccine response. These results emphasize the importance of NK-mediated innate immune effector responses in total antitumor immunity to treat HPV+ cancers. Full article
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Figure 1
<p>Differential efficacy of TVAC vs. TVQC in the oral HPV tumor model. Syngeneic C57Bl/6 mice were injected with mEER tumor cells as indicated and treated with intranasal (IN) delivery of the indicated E6/E7 HPV peptide therapeutic vaccine formulations on days 5 and 11 post-tumor implantation (<b>A</b>). Untreated mice (UNTR) and mice vaccinated with single adjuvants (TVA, TVC, TVQ) served as controls. Mice in all the groups were monitored over time, and Kaplan–Meier survival curves are shown for mice treated with TVAC (<b>B</b>) and TVQC (<b>C</b>). The Mantel–Cox log-rank test, ** <span class="html-italic">p</span> &lt; 0.005, **** <span class="html-italic">p</span> &lt; 0.0001 (<span class="html-italic">n</span> = 5–25 mice per group), shows a significant regression of mEER oral tumors with the TVQC vaccine. The oral tumor volume for mice in the untreated and TVQC-treated groups, as determined using magnetic resonance imaging (MRI) analyses on day 18, showed a significant reduction in tumor size in vaccinated mice (<b>D</b>). Elevated frequencies of antigen-specific CD8 T cells were observed in the tumors with both vaccine formulations (<b>E</b>). Significance was determined using an ordinary one-way ANOVA * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.0005, **** <span class="html-italic">p</span> &lt; 0.0001 (<span class="html-italic">n</span> = 5–6 mice per group).</p>
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<p>TVQC induces a more robust innate effector response than TVAC in mice with oral HPV tumors. Syngeneic C57Bl/6 mice were injected with mEER tumor cells as indicated and treated with intranasal (IN) delivery of TVAC, TVQC or untreated (UNTR). TVQC induced significantly elevated frequencies of total and functional (granzyme B- and/or IFNg-expressing) NK cells (<b>A</b>) and NKDCs (<b>B</b>) in the TME. Significance was determined using an ordinary one-way ANOVA * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005 (<span class="html-italic">n</span> = 5–6 mice per group). Within the TVQC-vaccinated mice, the total and functional CD11c−/+ NK cells were compared with the CD11c+ subset (NKDCs) exhibiting a higher frequency and functionality in the TME (<b>C</b>). Significance was determined using a Wilcoxon matched pairs test **** <span class="html-italic">p</span> &lt; 0.0001, *** <span class="html-italic">p</span> &lt; 0.0001 (<span class="html-italic">n</span> = 19 mice).</p>
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<p>Syngeneic C57BL/6 female mice were implanted with intravaginal TC-1luc tumors, as described in the Materials and Methods, and treated with intranasal HPV peptide therapeutic vaccine formulations as indicated on days 5 and 11 post-tumor implantation (<b>A</b>). Intravaginal TC-1 tumor size was monitored by luciferase imaging using the IVIS bioluminescence imaging system, and tumor growth curves for the indicated groups are shown (<b>B</b>). Survival curves are shown for intravaginal TC-1 tumor-bearing mice as indicated (<b>C</b>). A Mantel–Cox log-rank test was used to determine the significance between the groups, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005 (<span class="html-italic">n</span> = 10–13 mice per group). Immune responses associated with vaccine efficacy were assessed by flow cytometric analysis of TILs on day 16 following tumor implantation. The frequencies of the total and IFNg+ E7 tetramer+ CD8 T cells (<b>D</b>) and NKDCs expressing granzyme B, IFNg or both are shown (<b>E</b>). Significance was determined using an unpaired <span class="html-italic">t</span>-test, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 (representative data from one experiment with <span class="html-italic">n</span> = 3 mice per group; the experiment was repeated one more time).</p>
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34 pages, 28538 KiB  
Article
Monitoring of Composite Structures for Re-Usable Space Applications Using FBGs: The Influence of Low Earth Orbit Conditions
by Thibault Juwet, Geert Luyckx, Alfredo Lamberti, Frank Creemers, Eli Voet and Jeroen Missinne
Sensors 2024, 24(1), 306; https://doi.org/10.3390/s24010306 - 4 Jan 2024
Cited by 2 | Viewed by 1762
Abstract
Fiber Bragg grating sensors (FBGs) are promising for structural health monitoring (SHM) of composite structures in space owing to their lightweight nature, resilience to harsh environments, and immunity to electromagnetic interference. In this paper, we investigated the influence of low Earth orbit (LEO) [...] Read more.
Fiber Bragg grating sensors (FBGs) are promising for structural health monitoring (SHM) of composite structures in space owing to their lightweight nature, resilience to harsh environments, and immunity to electromagnetic interference. In this paper, we investigated the influence of low Earth orbit (LEO) conditions on the integrity of composite structures with embedded optical fiber sensors, specifically FBGs. The LEO conditions were simulated by subjecting carbon fiber-reinforced polymer (CFRP) coupons to 10 cycles of thermal conditioning in a vacuum (TVac). Coupons with embedded optical fibers (OFs) or capillaries were compared with reference coupons without embedded OFs or capillaries. Embedded capillaries were necessary to create in situ temperature sensors. Tensile and compression tests were performed on these coupons, and the interlaminar shear strength was determined to assess the influence of TVac conditioning on the integrity of the composite. Additionally, a visual inspection of the cross-sections was conducted. The impact on the proper functioning of the embedded FBGs was tested by comparing the reflection spectra before and after TVac conditioning and by performing tensile tests in which the strain measured using the embedded FBGs was compared with the output of reference strain sensors applied after TVac conditioning. The measured strain of the embedded FBGs showed excellent agreement with the reference sensors, and the reflection spectra did not exhibit any significant degradation. The results of the mechanical testing and visual inspection revealed no degradation of the structural integrity when comparing TVac-conditioned coupons with non-TVac-conditioned coupons of the same type. Consequently, it was concluded that TVac conditioning does not influence the functionality of the embedded FBGs or the structural integrity of the composite itself. Although in this paper FBG sensors were tested, the results can be extrapolated to other sensing techniques based on optical fibers. Full article
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Figure 1

Figure 1
<p>Schematic overview of the working principle of FBGs. Courtesy of FBGS [<a href="#B39-sensors-24-00306" class="html-bibr">39</a>].</p>
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<p>The cross-section of 2 coupons (lay-up [0/90]<sub>3S</sub>) with embedded Teflon (<b>a</b>) or glass (<b>b</b>) capillary.</p>
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<p>(<b>a</b>) Schematic overview of the produced test plate and how the coupons for the tensile test were cut out. The location of the embedded OFs is shown with the red dashed line. The FBG was located in the middle of the coupon between two 0° degree layers. (<b>b</b>) The produced plate just before it was cut into individual coupons for the tensile test. The yellow lines showed where the OFs with FBG sensors were embedded. (<b>c</b>) A schematic overview of the produced test plate and how the coupons for the compression and ILSS tests were cut out. Dummy OFs (red dashed line) without FBGs and glass capillaries (yellow line) were embedded at the indicated locations between two 90° layers. (<b>d</b>) The produced plate just before it was cut into coupons for compression and ILSS testing. The yellow lines indicated where the OFs or capillaries were embedded.</p>
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<p>Photo showing some of the coupons used for (<b>a</b>) the tensile test, (<b>b</b>) compression test, and (<b>c</b>) ILSS test. The direction of the embedded OF/capillary is shown with the yellow line. The direction of the applied force during the test is shown by the red arrows. For the ILSS test, the force was applied out of plane.</p>
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<p>The measured temperature and pressure inside the autoclave during the TVac conditioning of the coupons. The dashed lines indicate the desired minimum and maximum temperature and maximum desired pressure. The yellow curve shows the measured pressure in the autoclave during TVac conditioning. The blue, orange, and grey curves show the temperature as measured with three thermocouples inside the autoclave. Two of these were taped to a coupon, and the third one was taped to the platform in the autoclave.</p>
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<p>A tensile test coupon mounted in the test machine (<b>a</b>) before and (<b>b</b>) after the tensile testing. The FBG installed in extensometer principle after TVac conditioning can be seen. The optical fiber was glued to the surface of the coupon on both sides of the FBG sensor ((<b>a</b>), glue zone), leaving the FBG itself free. As such, two anchors were created, which strained the FBG sensor during the experiment. (<b>b</b>) shows the fracture after tensile testing.</p>
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<p>A coupon clamped in the test machine and a close-up before (<b>a</b>,<b>b</b>) and after (<b>c</b>) test. The green arrow in (<b>b</b>) shows the length over which the FBG is glued to the edge of the coupon. The FBG itself is located in the middle and is only 8 mm in length. The red arrows (<b>a</b>,<b>b</b>) show the free length of the coupon.</p>
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<p>(<b>a</b>) Shows an ILSS test coupon mounted in the 3-point bending test setup. (<b>b</b>) shows a close-up of the mounted coupon. The support span L<sub>S</sub> was 10 mm. The red dot indicates the position of the embedded OF or capillary, which was positioned in the middle between the support and loading point.</p>
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<p>Comparison of the reflection spectra of the embedded FBGs in the 5 tensile test coupons taken before and after TVac conditioning at room temperature. No degradation of the spectra was observed.</p>
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<p>Example of 2 polished compression test coupons with an integrated 250/360 µm capillary.</p>
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<p>Example of 2 polished samples from the ILSS test coupons with an integrated 106/160 µm capillary.</p>
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<p>Example of 2 polished samples from the ILSS test coupons with an integrated 80/120 µm OF.</p>
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<p>Example of 2 polished samples from the ILSS test coupons without an embedded OF or capillary.</p>
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<p>The stress–strain curve as a result of the tensile test obtained by combining the load data from the test bench with the strain measurements from the FBGs applied in extensometer principle. (<b>a</b>) Shows the results for the reference coupons (“ST-REF”, no embedded OF or capillary). (<b>b</b>) Shows the results for coupons with embedded OF (“ST-FIB”).</p>
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<p>(<b>a</b>) The tensile failure strength and (<b>b</b>) tensile strain at failure obtained from the quasi-static tension testing. Coupons with (“ST-FIB”) and without (“ST-REF”) embedded OF after TVac conditioning were compared.</p>
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<p>The stress–strain curves resulting from the quasi-static compression tests for the compressive test coupons. The stress was measured by the load cell, and the strain was obtained with the FBG sensors.</p>
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<p>(<b>a</b>) Compressive failure strength and (<b>b</b>) compressive strain at failure obtained from quasi-static compression testing. TVac-conditioned coupons without embedded structures and with embedded OFs and capillaries are compared as well as coupons with embedded capillaries but which were not TVac conditioned.</p>
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<p>Bar chart of the apparent interlaminar shear strength for the different types of coupons.</p>
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<p>Tensile test coupons overview. (<b>a</b>) Reference coupons without embedded OF/capillary. (<b>b</b>) Coupons with 80/120 µm fiber embedded along the yellow line.</p>
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<p>Cross-sections of the tensile test coupons taken after TVac conditioning.</p>
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<p>Cross-sections of the tensile test coupons taken after TVac conditioning.</p>
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<p>Compression test reference coupons without embedded OF/capillary.</p>
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<p>Cross-sections of the compression test reference coupons without embedded OFS/capillary taken after TVac conditioning.</p>
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<p>Compression test coupons with 80/120 µm fiber embedded along the yellow line.</p>
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<p>Cross-sections of the compression test coupons with embedded OF taken after TVac conditioning.</p>
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<p>Compression test coupons with 250/360 µm capillary embedded along the yellow line.</p>
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<p>Cross-sections of the compression test coupons with embedded capillary. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>)) are from the coupons that were not TVac conditioned. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>)) are taken after TVac conditioning.</p>
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<p>Cross-sections of the compression test coupons with embedded capillary. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>)) are from the coupons that were not TVac conditioned. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>)) are taken after TVac conditioning.</p>
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<p>ILSS reference coupons without embedded OF/capillary.</p>
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<p>Cross-sections of the ILSS test reference coupons without embedded OF/capillary. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>)) are from coupons after TVac conditioning. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>)) are from coupons that were not TVac conditioned. Note that the cross-section of ILSS-REF-03 is missing.</p>
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<p>ILSS test coupons with 80/120 µm fiber embedded along the yellow line.</p>
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<p>Cross-sections of the ILSS test coupons without embedded OF. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>k</b>,<b>m</b>,<b>o</b>)) are from coupons after TVac conditioning. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>,<b>l</b>,<b>n</b>,<b>p</b>)) are from coupons that were not TVac conditioned.</p>
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<p>Cross-sections of the ILSS test coupons without embedded OF. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>k</b>,<b>m</b>,<b>o</b>)) are from coupons after TVac conditioning. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>,<b>l</b>,<b>n</b>,<b>p</b>)) are from coupons that were not TVac conditioned.</p>
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<p>Cross-sections of the ILSS test coupons without embedded OF. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>k</b>,<b>m</b>,<b>o</b>)) are from coupons after TVac conditioning. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>,<b>l</b>,<b>n</b>,<b>p</b>)) are from coupons that were not TVac conditioned.</p>
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<p>ILSS test coupons with 106/160 µm fiber embedded along the yellow line.</p>
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<p>Cross-sections of the ILSS test coupons without embedded capillary. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>h</b>)) are from coupons after TVac conditioning. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>)) are from coupons that were not TVac conditioned.</p>
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<p>Cross-sections of the ILSS test coupons without embedded capillary. The figures on the (<b>left</b> (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>h</b>)) are from coupons after TVac conditioning. The figures on the (<b>right</b> (<b>b</b>,<b>d</b>,<b>f</b>)) are from coupons that were not TVac conditioned.</p>
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30 pages, 2668 KiB  
Article
Applying Particle Swarm Optimization Variations to Solve the Transportation Problem Effectively
by Chrysanthi Aroniadi and Grigorios N. Beligiannis
Algorithms 2023, 16(8), 372; https://doi.org/10.3390/a16080372 - 3 Aug 2023
Cited by 8 | Viewed by 1787
Abstract
The Transportation Problem (TP) is a special type of linear programming problem, where the objective is to minimize the cost of distributing a product from a number of sources to a number of destinations. Many methods for solving the TP have been studied [...] Read more.
The Transportation Problem (TP) is a special type of linear programming problem, where the objective is to minimize the cost of distributing a product from a number of sources to a number of destinations. Many methods for solving the TP have been studied over time. However, exact methods do not always succeed in finding the optimal solution or a solution that effectively approximates the optimal one. This paper introduces two new variations of the well-established Particle Swarm Optimization (PSO) algorithm named the Trigonometric Acceleration Coefficients-PSO (TrigAc-PSO) and the Four Sectors Varying Acceleration Coefficients PSO (FSVAC-PSO) and applies them to solve the TP. The performances of the proposed variations are examined and validated by carrying out extensive experimental tests. In order to demonstrate the efficiency of the proposed PSO variations, thirty two problems with different sizes have been solved to evaluate and demonstrate their performance. Moreover, the proposed PSO variations were compared with exact methods such as Vogel’s Approximation Method (VAM), the Total Differences Method 1 (TDM1), the Total Opportunity Cost Matrix-Minimal Total (TOCM-MT), the Juman and Hoque Method (JHM) and the Bilqis Chastine Erma method (BCE). Last but not least, the proposed variations were also compared with other PSO variations that are well known for their completeness and efficiency, such as Decreasing Weight Particle Swarm Optimization (DWPSO) and Time Varying Acceleration Coefficients (TVAC). Experimental results show that the proposed variations achieve very satisfactory results in terms of their efficiency and effectiveness compared to existing either exact or heuristic methods. Full article
(This article belongs to the Special Issue Metaheuristic Algorithms in Optimal Design of Engineering Problems)
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<p>The number of optimal solutions that every method achieved.</p>
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<p>Average percentage deviation for each method.</p>
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<p>Accuracy for 20 particles.</p>
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<p>Accuracy for 40 particles.</p>
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<p>Accuracy for 50 particles.</p>
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26 pages, 8567 KiB  
Article
Landsat 9 Geometric Commissioning Calibration Updates and System Performance Assessment
by Michael J. Choate, Rajagopalan Rengarajan, James C. Storey and Mark Lubke
Remote Sens. 2023, 15(14), 3524; https://doi.org/10.3390/rs15143524 - 12 Jul 2023
Cited by 6 | Viewed by 1953
Abstract
Starting with launch of Landsat 7 (L7) on 15 April 1999, the USGS Landsat Image Assessment System (IAS) has been performing calibration and characterization operations for over 20 years on the Landsat spacecrafts and their associated payloads. With the launch of Landsat 9 [...] Read more.
Starting with launch of Landsat 7 (L7) on 15 April 1999, the USGS Landsat Image Assessment System (IAS) has been performing calibration and characterization operations for over 20 years on the Landsat spacecrafts and their associated payloads. With the launch of Landsat 9 (L9) on 27 September 2021, that spacecraft and its payloads, the Operational Land Imager-2 (OLI-2) and Thermal Infrared Sensor-2 (TIRS-2), were added to the existing suite of missions supported by the IAS. This paper discusses the geometric characterizations, calibrations, and performance analyses conducted during the commissioning period of the L9 spacecraft and its instruments. During this time frame the following calibration refinements were performed; (1) alignment between the OLI-2 and TIRS-2 instruments and the spacecraft attitude control system, (2) within-instrument band alignment, (3) instrument-to-instrument alignment. These refinements, carried out during commissioning and discussed in this paper, were performed to provide an on-orbit update to the pre-launch calibration parameters that were determined through Ground System Element (GSE) testing and Thermal Vacuum Testing (TVAC) for the two instruments and the L9 spacecraft. The commissioning period calibration update captures the effects of launch shift and zero-G release, and typically represents the largest changes that are made to the on-orbit geometric calibration parameters during the mission. The geometric calibration parameter updates performed during commissioning were done prior to releasing any L9 products to the user community. This commissioning period also represents the time frame during which focus is more strictly placed on the spacecraft and instrument performance, ensuring that system and instrument requirements are met, as contrasted with the post commissioning time frame when a greater focus is placed on the products generated, their behavior and their impact on the user community. Along with the calibration updates discussed in this paper key geometric performance requirements with respect to geodetic accuracy, geometric accuracy, and swath width are presented, demonstrating that the geometric performance of the L9 spacecraft and its’ instruments with respect to these key performance requirements are being met. Within the paper it will be shown that the absolute geodetic accuracy is met for OLI-2 and TIRS-2 with a margin of approximately 79% and 65% respectively while the geometric accuracy is met for OLI-2 and TIRS-2 with a margin of approximately 68% and 43% respectively. Full article
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<p>OLI-2 focal plane. Bands are staggered in the along track direction. The nominal 185 km field of view is achieved by 14 Sensor Chip Assemblies (SCAs) in the across track direction.</p>
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<p>TIRS-2 Focal Plane. The two bands, a 10.9 µm and 12 µm band, are staggered in the along track direction. The nominal 185 km field of view is achieved by three Sensor Chip Assemblies (SCAs) in the across track direction.</p>
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<p>Operational Land Imager-2 (OLI-2) nominal detector Line-of-Sight (LOS) angular projection of the focal plane. The Sensor Chips Assembly (SCA) for each band is shown. Results shown are post-commissioning and represent the final calibration numbers at the end of the commissioning period.</p>
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<p>Thermal Infrared Sensor-2 (TIRS-2) nominal detector Line of Sight (LOS) angular projection of the focal plane. Each Sensor Chip Assembly (SCA) for each band is shown. Results shown are post-commissioning and represent the final calibration numbers at the end of the commissioning period.</p>
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<p>Landsat 9 pre World Reference System-2 (WRS-2) image acquisition and an acquisition once the spacecraft has reached its final WRS-2 orbit. The imagery marked with the scene identifier LC91030762021318LGN01 on the left was acquired prior to the satellite being set in its nominal WRS-2 orbit. The imagery marked with the scene identifier LC91030762021342LGN01 on the right was acquired with the satellite residing in its nominal WRS-2 orbit.</p>
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<p>Distribution of Geometric Supersites. Images are mosaics of high-resolution Digital Ortho Photo Quadrangles, Satellite pour l’Observation de la Terre, or Geoscience Australia Reference Imagery. Images are of 15-m resolution from which 15 m Ground Control Chips are extracted.</p>
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<p>Density of the Global Land Survey (GLS) Ground Control Chips (GCPs). Chips are 30 m in resolution. These GCPs are used in generating USGS Landsat products for distribution to the user community.</p>
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<p>Red, green, blue (RGB) image created from the Operational Land Imager-2 (OLI-2) blue, Short Wave Infrared (SWIR-2) band and the Thermal Infrared Sensor-2 (TIRS-2) 10.9-µm band. This RGB image demonstrates that the TIRS-2 field of view is contained within that of the OLI-2 instrument.</p>
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<p>Operational Land Imager-2(OLI-2) Sensor Chip Assembly (SCA) overlap based on the Legendre Line of Sight (LOS) polynomials as listed in the Calibration Parameter File (CPF). The nominal outmost and innermost detectors for adjacent SCAs are compared to determine the amount of angular overlap between the two detectors.</p>
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<p>Thermal Infrared Sensor-2 (TIRS-2) Sensor Chip Assembly (SCA) overlap based on the Legendre Line of Sight (LOS) polynomials as listed in the Calibration Parameter File (CPF). The nominal outmost and innermost detectors for adjacent SCAs are compared to determine the amount of angular overlap between the two detectors.</p>
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<p>Mean deltas between pre-launch and post-commissioning along track Line of Sight (LOS) polynomials for each Sensor Chip Assembly (SCA) of each band of the Landsat 9 Operational Land Imager-2 (OLI-2). Values are given in terms of micro-radians. Adjustments post-commissioning were less than one multispectral OLI-2 pixel which has a nominal Instantaneous Field of View (IFOV) of 42.5 micro radians.</p>
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<p>Mean deltas between pre-launch and post-launch across track Line of Sight (LOS) polynomials for each Sensor Chip Assembly (SCA) of each band of the Landsat 9 Operational Land Imager-2 (OLI-2). Values are given in terms of micro radians. Adjustments post-launch were less than one multispectral OLI-2 pixel which has a nominal Instantaneous Field of View (IFOV) of 42.5 micro radians.</p>
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<p>Mean deltas between pre-launch and post-launch along track Line-of-Sight (LOS) polynomials for each Sensor Chip Assembly (SCA) of each band of the Landsat 9 Thermal Infrared Sensor-2 (TIRS-2). Values are given in terms of micro radians. Adjustments post-launch were less than two thermal TIRS-2 pixels which has a nominal Instantaneous Field of View (IFOV) of 141.86 micro radians.</p>
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<p>Mean deltas between pre-launch and post-launch across track Line-of-Sight (LOS) polynomials for each Sensor Chip Assembly (SCA) of each band for the Landsat 9 Thermal Infrared Sensor-2 (TIRS-2). Values are given in terms of micro radians. Adjustments post-launch were less than three thermal TIRS-2 pixels which has a nominal Instantaneous Field of View (IFOV) of 141.86 micro radians.</p>
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<p>Focal Plane Calibration post-calibration mean residuals. The standard deviation of those means are shown as error bars. Results are based on running the calibrated data through the Focal Plane Alignment algorithm, with the remaining fit offsets demonstrating any residual alignment post-calibration.</p>
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<p>TIRS-2 to OLI-2 alignment post-calibration mean residuals. The standard deviation of the means are shown as error bars. Results are based on running the calibrated data through the TIRS-2 to OLI-2 Alignment algorithm, with the remaining fit offsets demonstrating any residual alignment post-calibration.</p>
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<p>Absolute geodetic accuracy results for the Operational Land Imager-2 based on the Geometric Supersite control. Scenes were acquired in late 2021 during the spacecraft and instrument commissioning time frame. The day of year (DOY) during that commissioning period is shown on the <span class="html-italic">x</span>-axis. The measured Circular Error 90% (CE90) is shown along with the instrument requirement or specification (Spec) of 65 m which is also defined in terms of CE90 and plotted as a red dotted line within the figure.</p>
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<p>Absolute geodetic accuracy results for the Operational Land Imager-2 based on the Landsat Global Land Survey control. Scenes were acquired in late 2021 during the spacecraft and instrument commissioning time frame. The day of year (DOY) during that commissioning period is shown on the <span class="html-italic">x</span>-axis. The measured Circular Error 90% (CE90) is shown along with the instrument requirement or specification (Spec) of 65 m which is also defined in terms of CE90 and plotted as a red dotted line within the figure.</p>
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<p>Relative geodetic accuracy pre-fit standard deviation results for the Operational Land Imager-2 based on the Geometric Supersite control. Scenes were acquired in late 2021 during the spacecraft and instrument commissioning time frame. The day of year (DOY) during that commissioning period is shown on the <span class="html-italic">x</span>-axis. The pre-fit standard deviation numbers are used to determine the relative, within scene, accuracy of the instrument and data products.</p>
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<p>Relative geodetic accuracy pre-fit standard deviation results for the Operational Land Imager-2 based on the Global Land Survey ground control. Scenes were acquired in late 2021 during the spacecraft and instrument commissioning time frame. The day of year (DOY) during that commissioning period is shown on the <span class="html-italic">x</span>-axis.</p>
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<p>Operational Land Image-2 band registration accuracy assessment. Each band combination is assessed. The band-to-band requirement or specification (Spec), absent an assessment involving the cirrus band, is 4.5 m Linear Error 90% (LE90) which is shown as a dotted red line in the plot.</p>
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<p>Thermal Infrared Sensor-2 (TIRS-2) within band registration accuracy assessment along with TIRS-2 to Operational Land Imager-2 (OLI-2) between instrument, per band, registration accuracy assessment. The TIRS-2 to OLI-2 band registration requirement or specification (Spec) which is 30-m Linear Error 90% (LE90) is shown as a dotted red line in the plot.</p>
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<p>Operational Land Imager-2 geometry accuracy results based on Geometric Supersites. Scenes were acquired during the Landsat 9 commissioning period. Scenes with less than 4% cloud cover and that kept more than 50 ground control points are shown in the plot. The Landsat 9 requirement or specification (Spec) for geometric accuracy of 12 m Circular Error 90% (CE90) is shown in the plot as a dotted red line.</p>
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<p>Operational Land Image-2 (OLI-2) geometric accuracy results based on Global Land Survey ground control. Scenes were acquired during the Landsat 9 commissioning period. Scenes with less than 4% cloud cover, less 4% snow cover, were acquired at mid-to-low latitudes, were consistent with the 30-m Level-1 Terrain Precision threshold and that kept at least 50 points in the mensuration step are shown in the plot. The Landsat 9 requirement of specification (Spec) for geometric accuracy of 12 m Circular Error 90% (CE90) is shown in the plot as a dotted red line.</p>
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15 pages, 3831 KiB  
Article
Nonlinear Adaptive Back-Stepping Optimization Control of the Hydraulic Active Suspension Actuator
by Lizhe Wu, Dingxuan Zhao, Xiaolong Zhao and Yalu Qin
Processes 2023, 11(7), 2020; https://doi.org/10.3390/pr11072020 - 6 Jul 2023
Cited by 3 | Viewed by 1292
Abstract
The displacement tracking performance of the electro-hydraulic servo actuator is critical for hydraulic active suspension control. To tackle the problem of slow time-varying parameters in the existing actuator dynamics model, a nonlinear adaptive back-stepping control (ABC) approach is adopted. Simultaneously, the parameters of [...] Read more.
The displacement tracking performance of the electro-hydraulic servo actuator is critical for hydraulic active suspension control. To tackle the problem of slow time-varying parameters in the existing actuator dynamics model, a nonlinear adaptive back-stepping control (ABC) approach is adopted. Simultaneously, the parameters of the nonlinear ABC are difficult to configure, resulting in a poor control effect. An enhanced particle swarm optimization (PSO) approach integrating crazy particles (CP) and time-varying acceleration coefficients (TVAC) is suggested to optimize the controller settings. Furthermore, in order to obtain satisfactory dynamic characteristics of the transition process, the absolute value of the error time integral performance index is used as the minimum performance index function of parameter selection, and the square term of the control input is added to the performance index function to prevent excessive controller energy. Finally, it can be observed from the simulation results of the highest value emax of the displacement tracking error, the average value eμ of error, and the standard deviation eσ of error that the performance of the ABC parameters optimized by PSO+CP+ATVC is superior to the manually given ABC parameters. Therefore, this control method significantly improves the stability and speed of the control system. It provides a new research idea for the parameter optimization of controllers. Full article
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<p>Hydraulic active suspension actuator system schematic diagram.</p>
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<p>Flowchart showing PSO+CP+TVAC optimization of ABC parameters <math display="inline"><semantics><mrow><msub><mrow><mi>k</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow></semantics></math>, <math display="inline"><semantics><mrow><msub><mrow><mi>k</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math> and <math display="inline"><semantics><mrow><msub><mrow><mi>k</mi></mrow><mrow><mn>3</mn></mrow></msub></mrow></semantics></math>.</p>
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<p>ABC controller parameter <math display="inline"><semantics><mrow><msub><mrow><mi>k</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow></semantics></math>.</p>
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<p>ABC controller parameter <math display="inline"><semantics><mrow><msub><mrow><mi>k</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math>.</p>
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<p>ABC controller parameter <math display="inline"><semantics><mrow><msub><mrow><mi>k</mi></mrow><mrow><mn>3</mn></mrow></msub></mrow></semantics></math>.</p>
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<p>Convergence curves of PSO+CP+TVAC, PSO+CP, and PSO fitness value <math display="inline"><semantics><mrow><mi>J</mi></mrow></semantics></math>.</p>
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<p>PSO+CP+ATVC-ABC and ABC displacement tracking.</p>
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<p>PSO+CP+ATVC-ABC and ABC displacement tracking error.</p>
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21 pages, 11505 KiB  
Article
Modified Particle Swarm Optimization Based Powertrain Energy Management for Range Extended Electric Vehicle
by Omkar Parkar, Benjamin Snyder, Adibuzzaman Rahi and Sohel Anwar
Energies 2023, 16(13), 5082; https://doi.org/10.3390/en16135082 - 30 Jun 2023
Cited by 6 | Viewed by 1589
Abstract
The efficiency of hybrid electric powertrains is heavily dependent on energy and power management strategies, which are sensitive to the dynamics of the powertrain components that they use. In this study, a Modified Particle Swarm Optimization (Modified PSO) methodology, which incorporates novel concepts [...] Read more.
The efficiency of hybrid electric powertrains is heavily dependent on energy and power management strategies, which are sensitive to the dynamics of the powertrain components that they use. In this study, a Modified Particle Swarm Optimization (Modified PSO) methodology, which incorporates novel concepts such as the Vector Particle concept and the Seeded Particle concept, has been developed to minimize the fuel consumption and NOx emissions for an extended-range electric vehicle (EREV). An optimization problem is formulated such that the battery state of charge (SOC) trajectory over the entire driving cycle, a vector of size 50, is to be optimized via a control lever consisting of 50 engine/generator speed points spread over the same 2 h cycle. Thus, the vector particle consisted of the battery SOC trajectory, having 50 elements, and 50 engine/generator speed points, resulting in a 100-D optimization problem. To improve the convergence of the vector particle PSO, the concept of seeding the vector particles was introduced. Additionally, further improvements were accomplished by adapting the Time-Varying Acceleration Coefficients (TVAC) PSO and Frankenstein’s PSO features to the vector particles. The MATLAB/SIMULINK platform was used to validate the developed commercial vehicle hybrid powertrain model against a similar ADVISOR powertrain model using a standard rule-based PMS algorithm. The validated model was then used for the simulation of the developed, modified PSO algorithms through a multi-objective optimization strategy using a weighted sum fitness function. Simulation results show that a fuel consumption reduction of 12% and a NOx emission reduction of 35% were achieved individually by deploying the developed algorithms. When the multi-objective optimization was applied, a simultaneous reduction of 9.4% fuel consumption and 7.9% NOx emission was achieved when compared to the baseline model with the rule-based PMS algorithm. Full article
(This article belongs to the Section E: Electric Vehicles)
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<p>Range Extended Electric Vehicle’s (REEV) powertrain architecture.</p>
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<p>Reversed-looking approach on vehicle subsystems.</p>
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<p>The output of the developed model.: drive cycle, battery SOC, and engine speed.</p>
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<p>The output from the ADVISOR model: drive cycle, battery SOC, emissions, and engine power.</p>
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<p>Flow diagram of Particle Swarm Optimization Algorithm.</p>
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<p>Pareto front approximation and the true pareto front. Points a and b belong to the pareto front approximation because they are nondominated (none of them is better than the other on both objectives). Point c is dominated by both point a and b [<a href="#B32-energies-16-05082" class="html-bibr">32</a>].</p>
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<p>Swarm movement of the proposed system for 30 vector particles, indicated by the colored lines. (<b>a</b>) Initial positions; (<b>b</b>) Converged position.</p>
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<p>Optimal PMS for Fuel Consumption Minimization: SOC Tracking (<b>left</b>) and Engine Speed Tracking (<b>right</b>).</p>
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<p>Engine Performance with Fuel Minimization: BSFC Performance (<b>left</b>) and BSNOx Performance (<b>right</b>).</p>
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<p>Optimal PMS for NOx Emissions Minimization: SOC Tracking (<b>left</b>) and Engine Speed Tracking (<b>right</b>).</p>
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<p>Engine Performance with NOx Minimization: BSFC Performance (<b>left</b>) and BSNOx Performance (<b>right</b>).</p>
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<p>Pareto Front Plot for Single Objective Optimization results.</p>
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<p>Axes for directions of Multi-Objective Optimization.</p>
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<p>Pareto Front Plot for Multi-Object Optimization Results.</p>
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25 pages, 8227 KiB  
Article
JPSS-2 VIIRS Pre-Launch Reflective Solar Band Testing and Performance
by David Moyer, Amit Angal, Qiang Ji, Jeff McIntire and Xiaoxiong Xiong
Remote Sens. 2022, 14(24), 6353; https://doi.org/10.3390/rs14246353 - 15 Dec 2022
Cited by 8 | Viewed by 2359
Abstract
The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on-board the Suomi National Polar-orbiting Partnership (S-NPP) and Joint Polar Satellite System (JPSS) spacecrafts 1 and 2 provides calibrated sensor data record (SDR) reflectance, radiance, and brightness temperatures for use in environment data record (EDR) [...] Read more.
The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on-board the Suomi National Polar-orbiting Partnership (S-NPP) and Joint Polar Satellite System (JPSS) spacecrafts 1 and 2 provides calibrated sensor data record (SDR) reflectance, radiance, and brightness temperatures for use in environment data record (EDR) products. The SDRs and EDRs are used in weather forecasting models, weather imagery and climate applications such as ocean color, sea surface temperature and active fires. The VIIRS has 22 bands covering a spectral range 0.4–12.4 µm with resolutions of 375 m and 750 m for imaging and moderate bands respectively on four focal planes. The bands are stratified into three different types based on the source of energy sensed by the bands. The reflective solar bands (RSBs) detect sunlight reflected from the Earth, thermal emissive bands (TEBs) sense emitted energy from the Earth and the day/night band (DNB) detects both solar and lunar reflected energy from the Earth. The SDR calibration uses a combination of pre-launch testing and the solar diffuser (SD), on-board calibrator blackbody (OBCBB) and space view (SV) on-orbit calibrator sources. The pre-launch testing transfers the National Institute of Standards and Technology (NIST) traceable calibration to the SD, for the RSB, and the OBCBB, for the TEB. Post-launch, the on-board calibrators track the changes in instrument response and adjust the SDR product as necessary to maintain the calibration. This paper will discuss the pre-launch radiometric calibration portion of the SDR calibration for the RSBs that includes the dynamic range, detector noise, calibration coefficients and radiometric uncertainties for JPSS-2 VIIRS. Full article
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<p>VIIRS scan section diagram illustrating the different collection regions and their angles during a single scan.</p>
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<p>Diagram of the VIIRS solar diffuser calibration. This includes the VIIRS scanner that looks at the Earth and solar diffuser (<math display="inline"><semantics> <mrow> <mi>S</mi> <mi>D</mi> </mrow> </semantics></math>) when illuminated by the Sun through an attenuation screen and the solar diffuser stability monitor (SDSM) that views the Sun through a screen and the <math display="inline"><semantics> <mrow> <mi>S</mi> <mi>D</mi> </mrow> </semantics></math> while it is illuminated.</p>
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<p>A comparison of the on-orbit solar spectral irradiance profile and the SIS100 radiance profile. The OOB Relative Spectral Response (RSR) contributions are not weighted the same in on-orbit and prelaunch applications.</p>
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<p>Band M4 dynamic range measurements for all detectors, legend in the upper right, for HAM side A. The points to the left of the first vertical line are high gain measurements. The band switches to low gain after a radiance of ~100. The first and second vertical red lines are for high and low gain Lmax, respectively. The y-axis is offset subtracted VIIRS response, and the x-axis is the SIS100 radiance during the measurement.</p>
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<p>Band I3 dynamic range measurements for all detectors, legend in the upper right, for HAM side A. The y-axis is offset subtracted VIIRS response, and the x-axis is the SIS100 radiance during the measurement. The second vertical red line corresponds to Lmax. The rollover in the response is due to saturation of the focal plane electronics. This causes two unique radiance levels to produce the same VIIRS digital number.</p>
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<p>The signal-to-noise ratio (SNR) of band M8 for all detectors (colored symbols) as a function of SIS100 radiance (W/m<sup>2</sup>/µm/sr). The three vertical red lines are for Lmin (left), Ltyp (middle) and Lmax (right).</p>
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<p>The signal-to-noise ratio (SNR) of band M10 for all detectors (colored symbols) as a function of SIS100 radiance (W/m<sup>2</sup>/µm/sr). The three vertical red lines are for Lmin (left), Ltyp (middle) and Lmax (right). Digital quantization noise is impacting the low signal levels in the bottom left corner of the image.</p>
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<p>Band M1 high gain fit coefficients for all detectors (x-axis) and TVAC/electronics configurations (colors and symbols). The columns are tau, <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>0</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>2</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math>, respectively. The rows are HAM A and B, respectively.</p>
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<p>Band M1 low gain fit coefficients for all detectors (x-axis) and TVAC/electronics configurations (colors and symbols). The columns are tau, <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>0</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>2</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math>, respectively. The rows are HAM A and B, respectively.</p>
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<p>Band M8 fit coefficients for all detectors (x-axis) and TVAC/electronics configurations (colors and symbols). The columns are tau, <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>0</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>2</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math>, respectively. The rows are HAM A and B, respectively.</p>
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<p>Comparison of the tau coefficient for all RSBs at nominal TVAC plateau. The upper left are the I-bands, upper right high gain VNIR M-bands, lower left the SWIR M-bands, and the lower right the low gain VNIR M-bands. The x-axis is detector, and the colors/symbols correspond to a particular RSB.</p>
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<p>Comparison of the <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>0</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math> coefficient for all RSBs at nominal TVAC plateau. The upper left are the I-bands, upper right high gain VNIR M-bands, lower left the SWIR M-bands, and the lower right, the low gain VNIR M-bands. The x-axis is detector, and the colors/symbols correspond to a particular RSB.</p>
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<p>Comparison of the <math display="inline"><semantics> <mrow> <mfrac> <mrow> <msub> <mi>c</mi> <mn>2</mn> </msub> </mrow> <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> </mrow> </mfrac> </mrow> </semantics></math> coefficient for all RSBs at nominal TVAC plateau. The upper left are the I-bands, upper right high gain VNIR M-bands, lower left the SWIR M-bands, and the lower right the low gain VNIR M-bands. The x-axis is detector, and the colors/symbols correspond to a particular RSB.</p>
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<p>Band M1 temperature sensitivity (dL) as a function of electronics module (EM) temperature change between nominal and hot plateau for each detector (colors and symbols).</p>
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<p>Band M1 temperature sensitivity (dL) as a function of focal plane assembly (FPA) temperature change between nominal and hot plateau for each detector (colors and symbols).</p>
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<p>VIIRS top level radiometric calibration uncertainty tree.</p>
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14 pages, 863 KiB  
Article
The Feasibility Assessment of Power System Dispatch with Carbon Tax Considerations
by Whei-Min Lin, Chia-Sheng Tu, Sang-Jyh Lin and Ming-Tang Tsai
Processes 2022, 10(11), 2321; https://doi.org/10.3390/pr10112321 - 8 Nov 2022
Cited by 2 | Viewed by 1337
Abstract
Traditional economic dispatch methods, which are used to minimize fuel costs, have become inadequate because they do not consider the environmental impact of emissions in the optimization process. By taking into account the horizon year load and carbon taxes, this paper examines the [...] Read more.
Traditional economic dispatch methods, which are used to minimize fuel costs, have become inadequate because they do not consider the environmental impact of emissions in the optimization process. By taking into account the horizon year load and carbon taxes, this paper examines the operation and dispatch of power units in a power system. The objective function, including the cost of fuels and the cost of carbon taxes, is solved by the modified particle swarm optimization with time-varying acceleration coefficient (MPSO-TVAC) method under operational constraints. Based on different load scenarios, the influences of various carbon taxes for the dispatch of units are simulated and analyzed. The efficiency and ability of the proposed MPSO-TVAC method are demonstrated using a real 345KV system. Simulation results indicate that the average annual CO2 emissions are 0.36 kg/kwh, 0.41 kg/kwh, and 0.44 kg/kwh in 2012, 2017 and 2022, respectively. As the capacity of gas-fired plants was increased in 2017 and 2022, the average cost in 2017 and 2022 doubled or tripled compared with the average cost in 2012. Reasonable solutions provide a practical and flexible framework for power sectors to perform feasibility assessments of power system dispatch. They can also be used to assist decision-makers in reaching minimal operation cost goals under the policies for desired emissions. Full article
(This article belongs to the Section Environmental and Green Processes)
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<p>Flowchart of the proposed methodology.</p>
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<p>The relationship between emissions and time in the analysis of Case 1.</p>
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<p>The relationship between emissions and time in the analysis of Case 2.</p>
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12 pages, 1169 KiB  
Article
The Optimal Operation and Dispatch of Commerce Air-Conditioning System by Considering Demand Response Strategies
by Ching-Jui Tien, Chung-Yuen Yang, Ming-Tang Tsai and Chin-Yang Chung
Inventions 2022, 7(3), 69; https://doi.org/10.3390/inventions7030069 - 18 Aug 2022
Cited by 4 | Viewed by 2264
Abstract
The purpose of this paper is to discuss an optimal operation and schedule of commerce air-conditioning system by considering the demand response in order to obtain the maximal benefit; this paper first collects the operating data of the chiller units in commercial users, [...] Read more.
The purpose of this paper is to discuss an optimal operation and schedule of commerce air-conditioning system by considering the demand response in order to obtain the maximal benefit; this paper first collects the operating data of the chiller units in commercial users, calculates the cooling load of each unit, and derives the relationship between the cooling loads and power consumption of each unit. The weather information, such as temperature and humidity of inside/outside, are collected in the EXECL database, and the cooling load of the mall’s space is simulated by using the Least Square Support Vector Machine (LSSVM). Under the selected plan of power reduction, the requirement of space cooling loads, and the various operation constraints, the dispatch model of the commerce air-conditioning system with demand response strategies is formulated to minimize the total cost. A Modify Particle Swarm Optimization with Time-Varying Acceleration Coefficients (MPSO-TVAC) is proposed to solve the daily economic dispatch of the air-conditioning system. In the MPSO-TVAC procedure, the dynamic control parameters are embedded in the particle swarm of the PSO-TVAC in order to improve the behavior patterns of each particle swarm and increase its search efficiency in high dimensions. Different modifications in moving patterns of MPSO-TVAC are proposed to search the feasible space more effectively. By using MPSO-TVAC, it provides an optimal mechanism for variables regulated to increase the efficiency of the performing search and look for the probability of an optimal solution. Simulation results also provide an efficient method for commercial users to reduce their electricity bills and raise the ability of the market’s competition. Full article
(This article belongs to the Special Issue Data Analytics in the Energy Sector)
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<p>The system architecture studied in this paper.</p>
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<p>The cooling load forecasting of shopping mall by using the LSSVM.</p>
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<p>Flowchart of the solution algorithm.</p>
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<p>The cooling load of air-conditioner per hour in August 2020.</p>
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<p>The power consumption of air-conditioner per hour in August 2020.</p>
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27 pages, 2541 KiB  
Article
Cellular Positioning in an NLOS Environment Applying the COPSO-TVAC Algorithm
by Stevo Lukić and Mirjana Simić
Electronics 2022, 11(15), 2300; https://doi.org/10.3390/electronics11152300 - 23 Jul 2022
Viewed by 1442
Abstract
Non-Line-of-Sight (NLOS) conditions are created by blocking the direct path between the transmitter and receiver, resulting in an increased signal propagation path. To mitigate the Time of Arrival (TOA) measured errors caused by the NLOS phenomenon in cellular radio positioning, we use the [...] Read more.
Non-Line-of-Sight (NLOS) conditions are created by blocking the direct path between the transmitter and receiver, resulting in an increased signal propagation path. To mitigate the Time of Arrival (TOA) measured errors caused by the NLOS phenomenon in cellular radio positioning, we use the Maximum Likelihood (ML) estimation method in this work. The cost function of the ML estimator is usually a high-dimensional, nonlinear, and multimodal function, where standard deterministic optimization techniques cannot solve such problems in real-time and without significant computing resources. In this paper, effective metaheuristic algorithms based on the enhanced variants of Particle Swarm Optimization (PSO) are applied for the optimal solution of the ML problem and efficiently determine the mobile station location. Time-Varying Acceleration Coefficients (TVAC) are introduced into the standard PSO algorithm to enhance the global search and convergence properties. The resulting algorithm is known as PSO-TVAC. To further improve the performance of the metaheuristic optimization, we suggest adding Chaos Search (CS), Opposition-Based Learning (OBL), and TVAC strategy to the PSO process. The simulation results show that the proposed metaheuristic algorithm named the Chaotic Opposition-based PSO-TVAC (COPSO-TVAC) can reach the Generalized Cramer–Rao Lower Bound (GCRLB) and surpass the original PSO, PSO-TVAC, and the presented conventional optimization algorithms. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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<p>Location geometry with the four TOA circles [<a href="#B24-electronics-11-02300" class="html-bibr">24</a>].</p>
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<p>The considered cellular system with the four BSs [<a href="#B24-electronics-11-02300" class="html-bibr">24</a>].</p>
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<p>RMSE [m] in the function of the number of the NLOS BSs: the suburban environment.</p>
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<p>RMSE [m] in the function of the number of the NLOS BSs: the urban environment.</p>
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<p>CDF of the location error in the scenario with 2 NLOS BSs: (<b>a</b>) the suburban environment; (<b>b</b>) the urban environment.</p>
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<p>CDF of the location error in the scenario with 3 NLOS BSs: (<b>a</b>) the suburban environment; (<b>b</b>) the urban environment.</p>
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<p>CDF of the location error in the scenario with 4 NLOS BSs: (<b>a</b>) the suburban environment; (<b>b</b>) the urban environment.</p>
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<p>The convergence properties of the proposed metaheuristic algorithms in the scenario with 2 NLOS BSs: (<b>a</b>) the suburban environment; (<b>b</b>) the urban environment.</p>
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<p>The convergence properties of the proposed metaheuristic algorithms in the scenario with 3 NLOS BSs: (<b>a</b>) the suburban environment; (<b>b</b>) the urban environment.</p>
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<p>The convergence properties of the proposed metaheuristic algorithms in the scenario with 4 NLOS BSs: (<b>a</b>) the suburban environment; (<b>b</b>) the urban environment.</p>
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15 pages, 4820 KiB  
Article
Surface Measurement of a Large Inflatable Reflector in Cryogenic Vacuum
by Henry Quach, Hyukmo Kang, Siddhartha Sirsi, Aman Chandra, Heejoo Choi, Marcos Esparza, Karlene Karrfalt, Joel Berkson, Yuzuru Takashima, Art Palisoc, Jonathan W. Arenberg, Christopher Walker, Christian Drouet d’Aubigny and Daewook Kim
Photonics 2022, 9(1), 1; https://doi.org/10.3390/photonics9010001 - 21 Dec 2021
Cited by 14 | Viewed by 4086
Abstract
The metrology of membrane structures, especially inflatable, curved, optical surfaces, remains challenging. Internal pressure, mechanical membrane properties, and circumferential boundary conditions imbue highly dynamic slopes to the final optic surface. Here, we present our method and experimental results for measuring a 1 m [...] Read more.
The metrology of membrane structures, especially inflatable, curved, optical surfaces, remains challenging. Internal pressure, mechanical membrane properties, and circumferential boundary conditions imbue highly dynamic slopes to the final optic surface. Here, we present our method and experimental results for measuring a 1 m inflatable reflector’s shape response to dynamic perturbations in a thermal vacuum chamber. Our method uses phase-measuring deflectometry to track shape change in response to pressure change, thermal gradient, and controlled puncture. We use an initial measurement as a virtual null reference, allowing us to compare 500 mm of measurable aperture of the concave f/2, 1-meter diameter inflatable optic. We built a custom deflectometer that attaches to the TVAC window to make full use of its clear aperture, with kinematic references behind the test article for calibration. Our method produces 500 × 500 pixel resolution 3D surface maps with a repeatability of 150 nm RMS within a cryogenic vacuum environment (T = 140 K, P = 0.11 Pa). Full article
(This article belongs to the Special Issue Advances in Optical Metrology)
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<p>An inflatable membrane mirror is constructed by clamping two Mylar sheets between three machined aluminum rings (<b>a</b>). During inflation, the rear aluminized Mylar becomes the concave reflecting surface of interest, while the clear convex Mylar front surface helps hold pres-sure (<b>b</b>). The convex Mylar surface is known as the canopy. In the final full-sized assembly, the canopy will be black polyimide, which is opaque in the visible but transparent with some loss in the target operation wavelengths (~80–660 µm).</p>
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<p>Between an illumination source, a camera, and a UUT, the law of specular reflection is satisfied. Here, the direction <math display="inline"><semantics> <mover accent="true"> <mi>z</mi> <mo>^</mo> </mover> </semantics></math> is parallel to the optical axis of a spherical optic, the direction <math display="inline"><semantics> <mover accent="true"> <mi>y</mi> <mo>^</mo> </mover> </semantics></math> in the tangential meridional plane, and the direction <math display="inline"><semantics> <mover accent="true"> <mi>x</mi> <mo>^</mo> </mover> </semantics></math> in the sagittal plane. The coordinates <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>m</mi> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>s</mi> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>c</mi> </msub> </mrow> </semantics></math> represent the y-coordinates of the mirror, source, and a pinhole camera as related by the law of specular reflection. <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mrow> <mi>m</mi> <mn>2</mn> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mrow> <mi>m</mi> <mn>2</mn> <mi>c</mi> </mrow> </msub> </mrow> </semantics></math> represent the absolute distances between the mirror and screen and mirror and camera, and <math display="inline"><semantics> <mrow> <msub> <mi>z</mi> <mrow> <mi>m</mi> <mn>2</mn> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>z</mi> <mrow> <mi>m</mi> <mn>2</mn> <mi>c</mi> </mrow> </msub> </mrow> </semantics></math> represent the distances of these physical locations along the direction <math display="inline"><semantics> <mover accent="true"> <mi>z</mi> <mo>^</mo> </mover> </semantics></math>. <math display="inline"><semantics> <mrow> <mi>W</mi> <mrow> <mo>(</mo> <mrow> <msub> <mi>x</mi> <mi>m</mi> </msub> <mo>,</mo> <msub> <mi>y</mi> <mi>m</mi> </msub> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math> is the sag of the optic.</p>
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<p>A unique aspect of inflatable optics is that the tensioning ring is a static datum between all varifocal states of the optic. The location of the aperture edge is stationary; only the surface slopes and height change within this circular area. Since the position of the UUT within the field of view of the camera does not change, <math display="inline"><semantics> <mrow> <mover accent="true"> <mrow> <msub> <mi>v</mi> <mn>1</mn> </msub> </mrow> <mo stretchy="true">^</mo> </mover> <mo>≅</mo> <msup> <mover accent="true"> <mrow> <msub> <mi>v</mi> <mn>1</mn> </msub> </mrow> <mo stretchy="true">^</mo> </mover> <mo>′</mo> </msup> </mrow> </semantics></math>. In the diagram, rays are reverse traced from the camera to UUT for a more intuitive visualization of ray slope deflection.</p>
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<p>We examine the effects of a plane window between a room temperature and pressure environment (RTP) and a cryogenic vacuum (<b>a</b>). A camera focuses through the plate and transparent Mylar canopy to the reflective Mylar surface. The circular meniscus window is 254 mm in diameter, while the full UUT aperture is 1 m. Rays from the UUT generally intercept the plate at non-normal incidence and introduce transverse displacement deviation <math display="inline"><semantics> <mrow> <msub> <mi>ε</mi> <mi>y</mi> </msub> </mrow> </semantics></math> as a function of ray slope <math display="inline"><semantics> <mrow> <mover accent="true"> <mrow> <msub> <mi>v</mi> <mn>2</mn> </msub> </mrow> <mo stretchy="true">^</mo> </mover> </mrow> </semantics></math>. The ray slope <math display="inline"><semantics> <mrow> <mover accent="true"> <mrow> <msub> <mi>v</mi> <mn>2</mn> </msub> </mrow> <mo stretchy="true">^</mo> </mover> <msup> <mrow/> <mo>′</mo> </msup> <mo>≠</mo> <mover accent="true"> <mrow> <msub> <mi>v</mi> <mn>2</mn> </msub> </mrow> <mo stretchy="true">^</mo> </mover> </mrow> </semantics></math> for any PPP tilt,<math display="inline"><semantics> <mrow> <mo> </mo> <mi>θ</mi> </mrow> </semantics></math>, and wedge, <math display="inline"><semantics> <mi>α</mi> </semantics></math>, as seen in (<b>b</b>). In absence of the plate, the screen y-intercept position would be <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>s</mi> </msub> </mrow> </semantics></math>, rather than the plate-displaced <math display="inline"><semantics> <mrow> <mi>y</mi> <msub> <msup> <mrow/> <mo>′</mo> </msup> <mi>s</mi> </msub> </mrow> </semantics></math>. The ray path from the camera to the UUT is also deviated by the plate, but its detail is not highlighted in this schematic.</p>
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<p>Four team members pull the reflective surface taut before clamping it the frame (<b>a</b>). One tooling ball just barely touches the rear side of the reflective mylar UUT (<b>b</b>). The full optomechanical mounting scheme for the 1 m mirror is described in detail [<a href="#B18-photonics-09-00001" class="html-bibr">18</a>].</p>
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<p>The mechanical deflectometer frame consists of two 356 mm × 356 mm aluminum plates with mounting holes to allow flexible mounting for a camera and illumination screen (<b>a</b>). Standoffs fastened through aluminum slots allow for longitudinal adjustment. The plates were fastened to existing 3/8” bolts. The deflectometer assembly was rotated 22 degrees about the window normal in order to match the orientation of the in-situ bolt hole pattern (<b>b</b>). A design choice of 100 pixels per black/white fringe, 7-step phase shifts, and 3 averages per shot was optimized on-site.</p>
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<p>The inflated test article is mounted at back of the chamber cylinder (<b>a</b>). The scale of the entire test configuration was nearly 4 m, which places the deflectometer approximately at the radius of curvature of the inflated optic at its inflation pressure range of 500–700 Pa (<b>b</b>). During testing, the first Fresnel reflection at the acrylic window interface was faint enough to not significantly reduce signal contrast at the camera detector. Diffuse machined internal surfaces scatter the illumination from outside the chamber, also slightly reducing reconstruction signal contrast.</p>
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<p>Three differential deflectometry measurements show the repeatability of the central 525 mm aperture. Changes within the first two minute-separated acquisitions resemble coma but flip in sign. At the end of the third minute acquisition, fluctuations damped significantly. Experience with the inflation unit hints that the pressure control unit strongly converges towards the setpoint, but sufficient iterative convergence occurs on longer timescales. Here, the 700 Pa pressure setpoint was met and held to the 10 Pa resolution indicated by the unit.</p>
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<p>Shape differences were observed successively on the timescale of hundreds of seconds. It is interesting that the proximity of the heat source to the northern region of the UUT did not produce local non-uniformity at the center aperture region despite local temperature differences. In this experiment, the inflatant gas was Argon, which most recently expelled a mix of Helium, Argon, and Xenon from the lenticular UUT volume.</p>
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<p>After the unpunctured reflector (first subplot) is pierced, the number of fringes increases (second subplot). With knowledge of the testing distance (<math display="inline"><semantics> <mrow> <mi>z</mi> <mo>≈</mo> <mn>3800</mn> <mo> </mo> <mi>mm</mi> </mrow> </semantics></math>) and fringe width at the screen (<math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>≈</mo> <mn>9.62</mn> <mo> </mo> <mi>mm</mi> </mrow> </semantics></math> ), one can count the number of fringes passing through a given pixel to coarsely estimate the slope change in y-direction. In the third subfigure, a shadow precludes slope measurement at this local surface region, indicating that the slope change exceeds the measurable dynamic range of the deflectometer in its current position. The shadow shrinks and grows at a low temporal frequency until it fully recovers and is measurable again without the subaperture data void. Chamber pressure increased from 0.84 Pa to 7.07 Pa after puncture.</p>
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<p>The second puncture showed recovery without substantial dynamic change over tens of minutes. Chamber pressure increased from 7.07 Pa to 10.66 Pa after the second puncture. A third puncture brought the chamber pressure to 13.33 Pa.</p>
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12 pages, 1519 KiB  
Article
Intranasal Therapeutic Peptide Vaccine Promotes Efficient Induction and Trafficking of Cytotoxic T Cell Response for the Clearance of HPV Vaginal Tumors
by Gloria Sierra, Stephanie Dorta-Estremera, Venkatesh L. Hegde, Sita M. K. Nookala, Ananta V. Yanamandra and K. Jagannadha Sastry
Vaccines 2020, 8(2), 259; https://doi.org/10.3390/vaccines8020259 - 29 May 2020
Cited by 8 | Viewed by 3863
Abstract
Human papillomavirus (HPV)-induced cancers continue to affect millions of women around the world, and the five year survival rate under the current standard of care for these cancers is less than 60% in some demographics. Therefore there is still an unmet need to [...] Read more.
Human papillomavirus (HPV)-induced cancers continue to affect millions of women around the world, and the five year survival rate under the current standard of care for these cancers is less than 60% in some demographics. Therefore there is still an unmet need to develop an effective therapy that can be easily administered to treat established HPV cervical cancer lesions. We sought to investigate the potential of an intranasal HPV peptide therapeutic vaccine incorporating the combination of α-Galactosylceramide (α-GalCer) and CpG-ODN adjuvants (TVAC) against established HPV genital tumors in a syngeneic C57BL/6J mouse model. We obtained evidence to show that TVAC, delivered by the mucosal intranasal route, induced high frequencies of antigen-specific CD8 T cells concurrent with significant reduction in the immunosuppressive regulatory T cells and myeloid derived suppressor cells in the tumor microenvironment (TME), correlating with sustained elimination of established HPV genital tumors in over 85% of mice. Inclusion of both the adjuvants in the vaccine was necessary for significant increase of antigen-specific CD8 T cells to the tumor and antitumor efficacy because vaccination incorporating either adjuvant alone was inefficient. These results strongly support the utility of the TVAC administered by needle-free intranasal route as a safe and effective strategy for the treatment of established genital HPV tumors. Full article
(This article belongs to the Section Human Papillomavirus Vaccines)
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Figure 1

Figure 1
<p>Human papillomavirus (HPV) peptide therapeutic vaccine formulated with the combination of α-GalCer and CpG-ODN adjuvants (TVAC) induces durable regression of established HPV genital tumors. (<b>A</b>) Female C57BL/6J mice (<span class="html-italic">n</span> = 10 to 22) were hormonally synchronized and challenged with 2 × 10<sup>4</sup> TC-1-Luc cells into the vaginal cavity. Intranasal immunizations using HPV peptide therapeutic vaccine formulated with either α-GalCer, CpG-ODN, or both α-GalCer and CpG-ODN (TVA, TVC, or TVAC, respectively) were administered on days 5 and 11 after tumor cell implantation; control groups included untreated or immunized mice with the mixture of adjuvants without peptides (adjuvants only). (<b>B</b>) Mice were size matched on day 5 prior to immunization based on luciferase expression readout, in terms of ROI units. (<b>C</b>) Tumor size was measured using luciferase expression (ROI units). The numbers of mice with complete tumor regression over total per group (minimum 10 mice per group) are shown in each panel for the different groups. (<b>D</b>) Survival advantage was recorded between each treatment group as well as the appropriate controls. An additional group of mice receiving intranasal TVA and systemic immunotherapy with agonistic antibody to 4–1BB was included as a positive control based on our earlier published studies for comparing survival rate with that in the TVAC group. Significance in survival proportions was measured using the log-rank test. <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.00005 (****), ns. = not significant.</p>
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<p>Increases in antigen-specific and overall CD8 T cell responses correlate with efficacy of the therapeutic HPV peptide vaccine. (<b>A</b>) Tumor infiltrating lymphocytes (TILs) isolated one week after the last immunization (marked with arrows and the oval) were analyzed by multi-parameter flow cytometry. (<b>B</b>) The frequency of granzyme B expressing (GzmB+) total and antigen-specific (E7 tetramer+) CD8 T cells are plotted as percent of live lymphocytes. (<b>C</b>) Numbers of antigen-specific CD8 T cells (E7 tetramer+) per milligram of tumor are shown. (<b>D</b>) Percentages of tumor infiltrating CD8+T cells, Tregs and myeloid derived suppressor cells (MDSCs) were calculated by dividing each population by the sum of CD8+Treg+MDSC counts per mouse and averaged by treatment group. Statistical significance between treatment groups was calculated via one-way ANOVA. <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.005 (**), <span class="html-italic">p</span> &lt; 0.00005 (****).</p>
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<p>TVAC efficacy is dependent on CD8 T cells. Antibody for the depletion of CD8 T cells was administered by the intraperitoneal route every three days beginning one day prior to tumor induction as described in the methods. Depletion of CD8 T cells in the blood over time was ascertained via flow cytometry and representative flow plots are shown (<b>A</b>). Tumor growth and survival were recorded over time (<b>B</b>,<b>C</b>). Significance in survival proportions was measured using the log-rank test. <span class="html-italic">p</span> &lt; 0.005 (**).</p>
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<p>Intranasal vaccination using α-GalCer and CpG-ODN adjuvants affords significant increase of antigen-specific CD8 T cells to the female reproductive tract (FRT). Adoptively transferred OT-I cells were analyzed by flow cytometry in spleen and FRT one week after intranasal ovalbumin immunization using α-GalCer and CpG-ODN adjuvants individually or together. Representative dot plots for spleen (<b>A</b>) and FRT (<b>C</b>) along with cumulative data from multiple mice in two independent experiments are shown (<b>B</b>,<b>D</b>). Statistical significance was calculated using ordinary one-way ANOVA with multiple comparisons (B) and the Brown–Forsythe and Welch ANOVA with multiple comparisons (D), <span class="html-italic">p</span> &lt; 0.005 (**), <span class="html-italic">p</span> &lt; 0.00005 (****).</p>
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