Search Results (1,617)

Contrails, or condensation trails, left by aircraft, significantly contribute to global warming by trapping heat in the Earth’s atmosphere. Despite their critical role in climate dynamics, the environmental impact of contrails remains underexplored. This research addresses this gap by focusing on the use of CubeSats for real-time contrail monitoring, specifically over major air routes such as the Europe–North Atlantic Corridor. The study proposes a 3 × 3 CubeSat constellation in highly eccentric orbits, designed to maximize coverage and data acquisition efficiency. Simulation results indicate that this configuration can provide nearly continuous monitoring with optimized satellite handovers, reducing blackout periods and ensuring robust multi-satellite visibility. A machine learning-based system integrating space-based humidity and temperature data to predict contrail formation and inform flight path adjustments is proposed, thereby mitigating environmental impact. The findings emphasize the potential of CubeSat constellations to revolutionize atmospheric monitoring practices, offering a cost-effective solution that aligns with global sustainability efforts, particularly the United Nations Sustainable Development Goal 13 (Climate Action). This research represents a significant step forward in understanding aviation’s non-CO₂ climate impact and demonstrates the feasibility of real-time contrail mitigation through satellite technology. Full article

Background/Objectives: Congenital rubella syndrome (CRS) is a constellation of serious multi-organ birth defects following rubella virus infection during early pregnancy. Countries in which rubella vaccination has not yet been introduced can have a high burden of this disease. Data on CRS burden and epidemiology are needed to guide the introduction of a rubella vaccine and monitor progress for rubella elimination, but the multi-system nature of CRS manifestations and required specialized testing creates a challenge for conducting CRS surveillance in developing settings such as Sudan. To enhance data quality, we designed and tested a simplified approach for CRS surveillance in Sudan. Methods: Seven CRS surveillance sentinel sites were set up at general pediatric, eye, and cardiology hospitals in Sudan, using standard definitions for reporting and classifying infants with CRS clinical manifestations. Between 2014 and 2017, we evaluated the system using WHO CRS surveillance monitoring indicators, comparing simplified approaches against a comprehensive one. The simplified approaches included (1) an ophthalmic-focused approach; (2) a heart-focused approach; and (3) a cataract-only approach. Results: Surveillance identified 179 infants with suspected CRS via the comprehensive approach, with 25 infants classified as laboratory-confirmed and 6 as clinically compatible. Surveillance sensitivity was highest for the simplified ophthalmic approach, while cataract-based surveillance had the highest proportion of confirmed cases. Conclusions: Simplified CRS surveillance, particularly focusing on detecting cataracts, can significantly contribute to monitoring the impact of rubella vaccine introduction. It could serve as an initial step towards comprehensive CRS surveillance, providing robust evidence to support rubella and CRS elimination efforts. Full article

In this research, a feedback nonlinear control law was designed and tested to perform acquisition and station-keeping maneuvers for a lunar navigation constellation. Each satellite flies an Elliptical Lunar Frozen Orbit (ELFO) and is equipped with a steerable and throttleable low-thrust propulsion system. Lyapunov stability theory was employed to design a real-time feedback control law, capable of tracking all orbital elements (including the true anomaly), expressed in terms of modified equinoctial elements (MEEs). Unlike previous research, control synthesis was developed in the complete nonlinear dynamical model, and allows for driving the spacecraft toward a time-varying desired state, which includes correct phasing. Orbit propagation was performed in a high-fidelity framework, which incorporated several relevant harmonics of the selenopotential, as well as third-body effects due to the gravitational pull of the Earth and Sun. The control strategy at hand was successfully tested through two Monte Carlo campaigns in the presence of nonnominal flight conditions related to estimation errors of orbit perturbations, accompanied by the temporary unavailability and misalignment of the propulsive thrust. Full article

Satellite remote sensing complements rain gauges and ground radars as the primary sources of precipitation data. While significant advancements have been made in spaceborne precipitation estimation since the 1960s, the emergence of multi-sensor precipitation estimation (MPE) in the early 1990s revolutionized global precipitation data generation by integrating infrared and microwave observations. Among others, Global Precipitation Measurement (GPM) plays a crucial role in providing invaluable data sources for MPE by utilizing passive microwave sensors and geostationary infrared sensors. MPE represents the current state-of-the-art approach for generating high-quality, high-resolution global satellite precipitation products (SPPs), employing various methods such as cloud motion analysis, probability matching, adjustment ratios, regression techniques, neural networks, and weighted averaging. International collaborations, such as the International Precipitation Working Group and the Precipitation Virtual Constellation, have significantly contributed to enhancing our understanding of the uncertainties associated with MPEs and their corresponding SPPs. It has been observed that SPPs exhibit higher reliability over tropical oceans compared to mid- and high-latitudes, particularly during cold seasons or in regions with complex terrains. To further advance MPE research, future efforts should focus on improving accuracy for extremely low- and high-precipitation events, solid precipitation measurements, as well as orographic precipitation estimation. Full article

Fragile X Syndrome (FXS) presents with a constellation of phenotypes, including trouble regulating emotion and aggressive behaviors, disordered sleep, intellectual impairments, and atypical physical development. Genetic study of the X chromosome revealed that substantial repeat expansion of the 5′ end of the gene fragile X messenger ribonucleoprotein 1 (FMR1) promoted DNA methylation and, consequently, silenced expression of FMR1. Further analysis proved that shorter repeat expansions in FMR1 also manifested in disease at later stages in life. Treatment and therapy options do exist, but they only manage symptoms. Up to now, no cure for FMR1 disorders exists. In this review, we aim to provide an overview of FMR1 biology and the latest research focused on developing therapeutic interventions that can potentially prevent and/or reverse FXS. Full article

Existing validation of mean wind speed estimates via reflectometry from global navigation systems of satellites (GNSS-R)—has been largely limited in spatial coverage to equatorial buoys or tropical cyclone events near continental United States. Two alternative validation techniques are presented for the Cyclone GNSS (CYGNSS) mission using surface-based observations along coasts and coral reefs instead of buoys, and triple collocation analysis (TCA) instead of a 1:1 gridded comparison for tropical cyclone (TC) events. For the surface-based analysis, Fully Developed Seas (FDS) v3.2 and NOAA v1.2 were compared to anemometer data provided by the Australian Bureau of Meteorology across the Australia and Pacific regions. Overall, the products performed similarly to previous studies with NOAA having higher correlations and lower errors than FDS, though FDS performed better than NOAA over the Australian dataset for high wind speed events. TCA was used to validate NOAA v1.2 and Merged v3.2 datasets with other satellite remotely sensed products from the Soil Moisture Active Passive (SMAP) mission and Synthetic Aperture Radar (SAR). Both additive and multiplicative error models for TCA were applied. The performance overall was similar between the two products, with NOAA producing higher errors. NOAA performed better than Merged for mean winds above 17 m/s as the large temporal averaging reduced sensitivity to high winds. For SMAP winds above 17 m/s, NOAA’s average bias (−2.1 m/s) was significantly smaller than the average bias in Merged (−4.4 m/s). Future ideas for rapid intensification detection and constellation design are discussed. Full article

In the era of industrial evolution, satellites are being viewed as swarm intelligence that does not rely on a single system but multiple constellations that collaborate autonomously. This has enhanced the potential of the Global Navigation Satellite System (GNSS) to contribute to improving position, navigation, and timing (PNT) services. However, multipath (MP) and non-line-of-sight (NLOS) receptions remain the prominent vulnerability for the GNSS in harsh environments. The aim of this research is to investigate the impact of MP and NLOS receptions on GNSS performance and then propose a Received Signal Quality Monitoring (RSQM) algorithm. The RSQM algorithm works in two ways. Initially, it performs a signal quality test based on a fuzzy inference system. The input parameters are carrier-to-noise ratio (CNR), Normalized Range Residuals (NRR), and Code–Carrier Divergence (CCD), and it computes the membership functions based on the Mamdani method and classifies the signal quality as LOS, NLOS, weak NLOS, and strong NLOS. Secondly, it performs an adaptive navigation strategy to exclude/mask the affected range measurements while considering the satellite geometry constraints (i.e., $DOP\le 2$). For this purpose, comprehensive research to quantify the multi-constellation GNSS receiver with four constellation configurations (GPS, BeiDou, GLONASS, and Galileo) has been carried out in various operating environments. This RSQM-based GNSS receiver has the capability to identify signal quality and perform adaptive navigation accordingly to improve navigation performance. The results suggest that GNSS performance in terms of position error is improved from 5.4 m to 2.3 m on average in the complex urban environment. Combining the RSQM algorithm with the GNSS has great potential for the future industrial revolution (Industry 5.0), making things automatic and sustainable like autonomous vehicle operation. Full article

Kaposi sarcoma-associated herpes virus (KSHV), also known as human herpes virus 8 (HHV-8), is the primary etiologic cause of Kaposi sarcoma (KS) and KSHV Inflammatory Cytokine Syndrome (KICS). Patients with KICS demonstrate symptoms of systemic inflammation, high KSHV viral load, elevation of inflammatory markers, and increased mortality. Management requires rapid diagnosis, treatment of underlying HIV, direct treatment of KS, and addressing the hyperimmune response. While a case definition based on clinical presentation, imaging findings, laboratory values, KSHV viral load, and lymph-node biopsy has been proposed, some of the required investigations are frequently unavailable in resource-constrained settings. Due to these challenges, KICS likely remains underdiagnosed and undertreated in these settings. We report a case of a 19-year-old woman living with HIV, and intermittent adherence to her ART, who presented with hypotension and acute hypoxemic respiratory failure. She was found to have high KSHV and HIV viral loads, low CD4 count, anemia, thrombocytopenia, hypoalbuminemia, and elevated inflammatory markers. On bedside ultrasound, she was found to have bilateral pleural effusions, ascites, an enlarged spleen, and hyperechoic splenic lesions. The diagnosis of KICS was made based on this constellation of findings. Weighing the risk and benefits of steroid administration in KS patients, the patient was successfully treated by the continuation of ART and the initiation of paclitaxel chemotherapy and steroids. We propose an adapted case definition relevant to the resource-constrained context. Due to the dual burden of KSHV and HIV in sub-Saharan Africa, additional cases of KICS are likely, and this syndrome will contribute to the burden of early mortality in newly diagnosed HIV patients. Addressing the diagnostic and therapeutic challenges of KICS must be a part of the overall management of the HIV pandemic. Full article

Multipath is a source of error that limits the Global Navigation Satellite System (GNSS) positioning precision in short baselines. The tightly combined model between systems increases the number of observations and enhances the strength of the mathematical model owing to the continuous improvement in GNSS. Multipath mitigation of the multi-GNSS tightly combined model can improve the positioning precision in complex environments. Interoperability of the multipath hemispherical map (MHM) models of different systems can enhance the performance of the MHM model due to the small multipath differences in single overlapping frequencies. The adoption of advanced sidereal filtering (ASF) to model the multipath for each satellite brings computational challenges owing to the characteristics of the multi-constellation heterogeneity of different systems; the balance efficiency and precision become the key issues affecting the performance of the MHM model owing to the sparse characteristics of the satellite distribution. Therefore, we propose a modified MHM method to mitigate the multipath for single-frequency multi-GNSS tightly combined positioning. The method divides the hemispherical map into 36 × 9 grids at 10° × 10° resolution and then searches with the elevation angle and azimuth angle as independent variables to obtain the multipath value of the nearest point. We used the k-d tree to improve the search efficiency without affecting precision. Experiments show that the proposed method improves the mean precision over ASF by 10.20%, 10.77%, and 9.29% for GPS, BDS, and Galileo satellite single-difference residuals, respectively. The precision improvements of the modified MHM in the E, N, and U directions were 32.82%, 40.65%, and 31.97%, respectively. The modified MHM exhibits greater performance and behaves more consistently. Full article

This study aims to contribute to the ongoing Pauline discourse by presenting Alain Badiou’s infusion of his own thinking of event theory into Pauline thinking of Jesus’ Resurrection and explores a constellation of Alain Badiou’s conceptualization and contemporization of Paul. Badiou’s reading of Paul constitutes a constellation of Paul’s position as a “universalist”, “anti-misogynist”, “anti-philosopher”, “anti-dialectician”, “revolutionist”, “politician”, “militant”, “activist”, “poet-thinker”, “militant artist”, “theoretician”, “analogist”, “inventor”, and “founder”, along with diverse figures pervading his writing in Paul’s context such as Lenin, Mao, Nietzsche, Wittgenstein, Spinoza, Marx, Mallarme, Dickinson, Picasso, Schoenberg, Lacan, and Cantor. As for the methodology, this study tracks the trajectory in Badiou’s thinking based on events, truth, fidelity, love, and subjectivation, together with relevant Badiouian connections, and traces Badiou’s theoretical framing of Paul. Tracing the cluster of Pauline representations within Badiou’s space of thought offers an alternative understanding of the scope of Paul’s role in Badiou’s criticism of progressive politics in search of a new militant figure and Paul’s enduring influence and relevance within contemporary socio-political discourse. Full article

This study evaluated the reliability of satellite-derived atmospheric temperature and humidity profiles derived from occultations of Fengyun-3D (FY-3D), the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), the Meteorological Operational Satellite program (METOP), and the microwave observations of NOAA Polar Orbital Environmental Satellites (POES) using various conventional sounding datasets from 2020 to 2021. Satellite-derived profiles were also used to explore the precursors of severe convective precipitations in terms of the atmospheric boundary layer (ABL) characteristics and convective parameters. It was found that the satellite-derived temperature profiles exhibited high accuracy, with RMSEs from 0.75 K to 2.68 K, generally increasing with the latitude and decreasing with the altitude. Among these satellite-derived profile sources, the COSMIC-2-derived temperature profiles showed the highest accuracy in the middle- and low-latitude regions, while the METOP series had the best performance in high-latitude regions. Comparatively, the satellite-derived relative humidity profiles had lower accuracy, with RMSEs from 13.72% to 24.73%, basically increasing with latitude. The METOP-derived humidity profiles were overall the most reliable among the different data sources. The ABL temperature and humidity structures from these satellite-derived profiles showed different characteristics between severe precipitation and non-precipitation regions and could reflect the evolution of ABL characteristics during a severe convective precipitation event. Furthermore, some convective parameters calculated from the satellite-derived profiles showed significant and rapid changes before the severe precipitation, indicating the feasibility of using satellite-derived temperature and humidity profiles as precursors to severe convective precipitation. Full article

The satellite Internet can cover up to 70% of the surface of our planet Earth to provide network services for nearly 3 billion people. As such, it is promising to become the building block of future 6G networks. The satellite Internet is capable of providing uniform communication capacity to every part of the Earth’s surface, due to its uniform and symmetrical constellation structure, while the uneven distribution of ground populations leads to globally uneven traffic delivery requests, incurring a mismatch between the capacity and traffic transmission demands. As such, traditional single-criteria (e.g., shortest delay) routing algorithms can lead to severe network congestion and cannot provision delay-deterministic data delivery. To overcome this bottleneck, we propose a multi-criteria routing and scheduling scheme to redirect time-tolerant data, thus preventing congestion for time-sensitive data, based on the spatiotemporal distribution of data traffic. First, we construct a traffic spatiotemporal distribution model, to indicate the network load status. Next, we model the satellite network multi-criteria routing problem as an integer linear programming one, which is NP-hard and challenging to solve within polynomial time. A novel link weight design based on both the link delay and load is introduced, transforming the mathematical programming problem into a routing optimization problem. The proposed correlation scheduling algorithm fully utilizes idle network link resources, significantly improving network resource utilization and eliminating resource competition between non-time-sensitive and time-sensitive services. Simulation results show that compared with traditional algorithms, the proposed method can increase the throughput of time-sensitive data by up to 20.8% and reduce the packet loss rate of time-sensitive services by up to 76.8%. Full article

The BeiDou-3 navigation satellite system (BDS-3) has officially provided positioning, navigation, and timing (PNT) services to global users since 31 July 2020. With the application of inter-satellite link technology, global integrity monitoring becomes possible. Nevertheless, the content of integrity monitoring is still limited by the communication capacity of inter-satellite links and the layout of ground monitoring stations. Low earth orbit (LEO) satellites have advantages in information-carrying rate and kinematic velocity and can be used as satellite-based monitoring stations for navigation satellites. Large numbers of LEO satellites can provide more monitoring data than ground monitoring stations and make it easier to obtain full-arc observation data. A new challenge of redundant data also arises. This study constructs multi-source observation links with satellite-to-ground, inter-satellite, and satellite-based observation data, proposes an integrity monitoring method with optimization of observation links, and verifies the performance of integrity monitoring with different observation links. The experimental results show four findings. (1) Based on the integrity status of BDS-3, the proposed system-level integrity mode can realize full-arc anomaly diagnosis in information and signals according to the observation conditions of the target satellite. Apart from basic navigation messages and satellite-based augmentation messages, autonomous messages and inter-satellite ranging data can be used to evaluate the state of the target satellite. (2) For a giant LEO constellation, only a small number of LEO satellites need to be selected to construct a minimum satellite-based observation unit that can realize multiple returns of navigation messages and reduce the redundancy of observation data. With the support of 12 and 30 LEO satellites, the minimum number of satellite-based observation links is 1 and 4, respectively, verifying that a small amount of LEO satellites could be used to construct a minimum satellite-based observation unit. (3) A small number of LEO satellites can effectively improve the observation geometry of the target satellite. An orbit determination observation unit, which consists of chosen satellite-to-ground and/or satellite-based observation links based on observation geometry, is proposed to carry out fast calculations of satellite orbit. If the orbit determination observation unit contains 6 satellite-to-ground monitoring links and 6/12/60 LEO satellites, the value of satellite position dilution of precision (SPDOP) is 38.37, 24.60, and 15.71, respectively, with a 92.95%, 95.49%, and 97.12% improvement than the results using 6 satellite-to-ground monitoring links only. (4) LEO satellites could not only expand the resolution of integrity parameters in real time but also augment the service accuracy of the navigation satellite system. As the number of LEO satellites increases, the area where UDRE parameters can be solved in real time is constantly expanding to a global area. The service accuracy is 0.93 m, 0.88 m, and 0.65 m, respectively, with augmentation of 6, 12, and 60 LEO satellites, which is an 8.9%, 13.7%, and 36.3% improvement compared with the results of regional service. LEO satellites have practical application values by improving the integrity monitoring of navigation satellites. Full article

Cancer discovery is directed at the identification of a specific cancer type which allows for specific therapeutic interventions. Background/Objectives: Recently, similar immune checkpoint therapeutics have been applied with success across several cancer types, opening the field for other immune disruptive interventions that have practical applications. Methods: We have discovered an innate immune system (InImS) biomarker that allows for the characterization of allied cancer subtypes and outliers that might aid with diagnosis, treatment, and prognostication. Results: These InImS biomarkers are related to PD-L1 treatment outcomes and can be potentially manipulated by dietary means. Conclusions: The FERAD (ferritin–fecal p87) and absolute neutrophil/lymphocyte (aNLR) ratios are two such InImS biomarkers and we show herein, that they allow for the discovery of diagnosis and prognostication patterns, as demonstrated by this study. Full article

Flood disasters are among the most severe natural calamities worldwide and typically occur in densely populated areas with abundant lakes and high rainfall. These disasters cause significant damage to the environment and human settlements. Therefore, accurately monitoring and understanding the occurrence and evolution of floods, as well as studying the influencing factors, is of great importance. This study employs CYGNSS satellite data from a constellation of small satellites equipped with reflective radar, which observe the Earth’s surface with high spatial and temporal resolution. Such systems effectively monitor the distribution of water bodies and hydrological processes on land surfaces. By collecting and analyzing CYGNSS data, we can map the distribution of water bodies during flood events to assess the extent and severity of the flooding. Additionally, this study examines various factors influencing flooding, including rainfall, land use, and topography. By compiling relevant meteorological, geographical, and hydrological data, we aim to develop a model that elucidates the impacts of these factors on the initiation and progression of floods. Ultimately, this research offers a comprehensive analysis based on CYGNSS data for monitoring floods and their influencing factors. The goal is to yield significant insights and explore the potential of using CYGNSS data in flood monitoring efforts. In the context of global climate change and the increasing frequency of flood disasters, these findings are expected to provide a crucial scientific basis for improving flood prevention and management strategies, thereby helping to mitigate losses and enhance our warning and disaster response capabilities. Full article