Search Results (25,685)

In this study, we investigate the usefulness of the spectral whitening procedure, devised by one of the authors as a preprocessing stage of envelope-detected single-look synthetic aperture radar (SAR) images, in application contexts where phase information is relevant. In the first experiment, each of the raw datasets of an interferometric pair of COSMO-SkyMed images, representing industrial buildings amidst vegetated areas, was individually (1) synthesized by the SAR processor without Fourier-domain Hamming windowing; (2) synthesized with Hamming windowing, used to improve the focalization of targets, with the drawback of spatially correlating speckle; and (3) processed for the whitening of complex speckle, using the data obtained in (2). The interferograms were produced in the three cases, and interferometric coherence and phase maps were calculated through 3 × 3 boxcar filtering. In (1), coherence is low on vegetation; the presence of high sidelobes in the system’s point-spread function (PSF) causes the spread of areas featuring high backscattering. In (2), point targets and buildings are better defined, thanks to the sidelobe suppression achieved by the frequency windowing, but the background coherence is abnormally increased because of the spatial correlation introduced by the Hamming window. Case (3) is the most favorable because the whitening operation results in low coherence in vegetation and high coherence in buildings, where the effects of windowing are preserved. An analysis of the phase map reveals that (3) is likely to be facilitated also in terms of unwrapping. Results are presented on a TerraSAR-X/TanDEM-X (TSX-TDX) image pair by processing the interferograms of original and whitened data using a non-local filter. The main results are as follows: (1) with autocorrelated speckle, the estimation error of coherence may attain 16% and inversely depends on the heterogeneity of the scene; and (2) the cleanness and accuracy of the phase are increased by the preliminary whitening stage, as witnessed by the number of residues, reduced by 24%. Benefits are also expected not only for differential InSAR (DInSAR) but also for any coherent analysis and processing carried out performed on SLC data. Full article

Background: Post-acute sequelae of SARS-CoV-2 infection (PASC) affects patients after recovering from acute coronavirus disease 2019 (COVID-19). This study investigates the impact of SARS-CoV-2 vaccination on PASC symptoms in children in Taiwan during the Omicron pandemic. Methods: We enrolled children under 18 years with PASC symptoms persisting for more than 4 weeks. Data collected included demographics, clinical information, vaccination status, and symptom persistence. We used logistic regression models to compare symptoms in the acute and post-COVID-19 phases and to assess the association between vaccination and these symptoms. Results: Among 500 PASC children, 292 (58.4%) were vaccinated, 282 (52.8%) were male, and the mean (SD) age was 7.6 (4.6) years. Vaccinated individuals exhibited higher odds of experiencing symptoms in the previous acute phase, such as cough (adjusted odds ratio [AOR] = 1.57; 95% confidence interval [CI]: 1.02–2.42), rhinorrhea/nasal congestion (AOR = 1.74; 95% CI: 1.13–2.67), sneezing (AOR = 1.68; 95% CI: 1.02–2.76), sputum production (AOR = 1.91; 95% CI: 1.15–3.19), headache/dizziness (AOR = 1.73; 95% CI: 1.04–2.87), and muscle soreness (AOR = 2.33; 95% CI: 1.13–4.80). In contrast, there were lower odds of experiencing abdominal pain (AOR = 0.49; 95% CI: 0.25–0.94) and diarrhea (AOR = 0.37; 95% CI: 0.17–0.78) in children who had received vaccination during the post-COVID-19 phase. Conclusions: This study revealed clinical features and vaccination effects in PASC children in Taiwan. Vaccination may reduce some gastrointestinal symptoms in the post-COVID-19 phase. Full article

Synthetic-Aperture Radar (SAR) has emerged as an important tool for monitoring tropical cyclones (TCs) due to its high spatial resolution and cloud-penetrating capability. Recent advancements in SAR technology have led to smaller and lighter satellites, yet few studies have evaluated their effectiveness in TC monitoring. This paper employs an algorithm for automatic TC center location, involving three stages: coarse estimation from a whole SAR image; precise estimation from a sub-SAR image; and final identification of the center using the lowest Normalized Radar Cross-Section (NRCS) value within a smaller sub-SAR image. Using three wide-swath miniaturized SAR images of TC Noru (2022), and TCs Doksuri and Koinu (2023), the algorithm’s accuracy was validated by comparing estimated TC center positions with visually located data. For TC Noru, the distances for the three stages were 21.42 km, 14.39 km, and 8.19 km; for TC Doksuri—14.36 km, 20.48 km, and 17.10 km; and for TC Koinu—47.82 km, 31.59 km, and 5.42 km. The results demonstrate the potential of miniaturized SAR in TC monitoring. Full article

One risk posed by hurricanes and typhoons is local inundation as ocean swell and storm surge bring a tremendous amount of energy and water flux to the shore. Numerical wave tanks are developed to understand the dynamics computationally. The three-dimensional equations of motion are solved by the software ‘Open Field Operation And Manipulation’ v2206. The ‘Large Eddy Simulation’ scheme is adopted as the turbulence model. A fifth-order Stokes wave is taken as the inlet condition. Breaking, ‘run-up’, and overtopping waves are studied for concave, convex, and straight-line seafloors for a fixed ocean depth. For small angles of inclination (<10°), a convex seafloor displays wave breaking sooner than a straight-line one and thus actually delivers a smaller volume flux to the shore. Physically, a convex floor exhibits a greater rate of depth reduction (on first encounter with the sloping seafloor) than a straight-line one. Long waves with a speed proportional to the square root of the depth thus experience a larger deceleration. Nonlinear (or ‘piling up’) effects occur earlier than in the straight-line case. All these scenarios and reasoning are reversed for a concave seafloor. For large angles of inclination (>30°), impingement, reflection, and deflection are the relevant processes. Empirical dependence for the setup and swash values for a convex seafloor is established. The reflection coefficient for waves reflected from the seafloor is explored through Fourier analysis, and a set of empirical formulas is developed for various seafloor topographies. Understanding these dynamical factors will help facilitate the more efficient designing and construction of coastal defense mechanisms against severe weather. Full article

Background: The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial to viral entry and can cause cardiac injuries. Toll-like receptor 4 (TLR4) and NOD-, LPR-, and pyrin-domain-containing 3 (NLRP3) inflammasome are critical immune system components implicated in cardiac fibrosis. The spike proteins activate NLRP3 inflammasome through TLR4 or angiotensin-converting enzyme 2 (ACE2) receptors, damaging various organs. However, the role of spike proteins in cardiac fibrosis in humans and the interactions of spike proteins with NLRP3 inflammasomes and TLR4 remain poorly understood. Methods: We utilized scratch assays, Western blotting, and immunofluorescence to evaluate the migration, fibrosis signaling, mitochondrial calcium levels, reactive oxygen species (ROS) production, and cell morphology of cultured human cardiac fibroblasts (CFs) treated with spike (S1) proteins for 24 h with or without an anti-ACE2 neutralizing antibody, a TLR4 blocker, or an NLRP3 inhibitor. Results: S1 protein enhanced CFs migration and the expressions of collagen 1, α-smooth muscle actin, transforming growth factor β1 (TGF-β1), phosphorylated SMAD2/3, interleukin 1β (IL-1β), and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB). S1 increased ROS production but did not affect mitochondrial calcium content and cell morphology. Treatment with an anti-ACE2 neutralizing antibody attenuated the effects of S1 on collagen 1 and TGF-β1 expressions. Moreover, NLRP3 (MCC950) and NF-kB inhibitors, but not the TLR4 inhibitor TAK-242, prevented the S1-enhanced CFs migration and overexpression of collagen 1, TGF-β1, and IL-1β. Conclusion: S1 activates human CFs by priming NLRP3 inflammasomes through NF-κB signaling in an ACE2-dependent manner. Full article

Background and Objectives: Recognizing the crucial gaps in our understanding of pediatric pneumonia post-SARS-CoV-2 infection, this study aimed to assess the relationship between Pediatric Pneumonia Ultrasound Scores (PedPne) and inflammatory biomarkers. The primary objective of this study is to evaluate the predictive value of PedPne in comparison with inflammatory biomarkers (IL-6 and dNLR) for the development of pneumonia in pediatric patients following SARS-CoV-2 infection. Materials and Methods: This longitudinal observational study collected data from pediatric patients diagnosed with pneumonia after an acute SARS-CoV2 infection. The study focused on analyzing changes in PedPne scores and inflammatory markers such as IL-6 and dNLR from initial admission to follow-up at 7 days. Statistical analysis involved calculating the sensitivity, specificity, and Area Under the Curve (AUC) for each biomarker, alongside regression analysis to determine their hazard ratios for predicting pneumonia development. Results: The analysis identified significant cutoff values for dNLR at 1.88 (sensitivity 77.0%, specificity 85.7%, AUC 0.802, p < 0.001), IL-6 at 6.1 pg/mL (sensitivity 70.3%, specificity 92.9%, AUC 0.869, p < 0.001), and PedPne score at 3.3 (sensitivity 75.7%, specificity 78.6%, AUC 0.794, p < 0.001). Conversely, NLR showed lower diagnostic performance (AUC 0.485, p = 0.327). Regression analysis further highlighted the strong predictive power of these markers, with IL-6 showing a fourfold increase in pneumonia risk (HR = 4.25, CI: 2.07–9.53, p < 0.001), dNLR indicating more than a twofold increase (HR = 2.53, CI: 1.19–6.97, p = 0.006), and PedPne score associated with more than a doubling of the risk (HR = 2.60, CI: 1.33–5.18, p < 0.001). Conclusions: The study conclusively demonstrated that both PedPne ultrasound scores and specific inflammatory biomarkers such as dNLR and IL-6 are significant predictors of pneumonia development in pediatric patients post-COVID-19 infection. These findings advocate for the integration of these biomarkers in routine clinical assessments to enhance the diagnostic accuracy and management of pneumonia in children following SARS-CoV-2 infection. Full article

Hand disorders can reduce wrist range of motion (ROM). The SARS-CoV-2 pandemic highlighted challenges in routine follow-up exams, making telemedicine a viable solution. This study evaluates the feasibility and accuracy of patient self-measured wrist ROM using a self-designed goniometer template. The template was designed to measure flexion/extension and radial/ulnar abduction movements. A cohort of 50 adults (25 males/25 females) participated in this prospective study. The exclusion criteria included wrist immobilization and ages outside of 18–65 years. Participants self-assessed their wrist ROM with the goniometer template. Measurements were independently performed by a student and a specialist using standard goniometry, as well as a resident using the self-designed goniometer. The results were blinded for unbiased analysis. Mean differences in ROM varied across movement directions, with minimal differences for ulnar abduction and more substantial deviations for radial abduction, extension and flexion. The patient–specialist comparison showed deviations below 5 degrees for flexion and ulnar abduction in 50% of cases. Telemedicine, expanded by the COVID-19 pandemic, offers significant potential for hand rehabilitation. Current methods of ROM assessment lack cost-effectiveness and simplicity. Our method, demonstrating comparable accuracy for most movements, provides a cost-effective, reliable alternative for remote ROM assessment, enhancing telemedicine practices in hand rehabilitation. Full article

The southern margin of the South Tian Shan has drawn attention due to the intense compressional deformation and seismic activity associated with its thrust structures. However, the deformation and seismic activity in the thick-skinned thrust sheets of the root zones are minimal. The Mw 7.1 Wushi earthquake on 23 January 2024 serves as a window to reveal these unknown aspects of the seismic mechanisms in this structural setting. Using the Leveraging Interferometric Synthetic Aperture Radar (InSAR) technique, we unlock critical insights into the coseismic deformation fields. The seismogenic fault is an unmapped segment within the Maidan Fault system, exhibiting a strike ranging from 241° to 222°. It is characterized by a shallow dip angle of 62° and a deeper dip angle of 56°. Remarkably, the seismic rupture did not propagate to the Earth’s surface. The majority of slip distribution is concentrated within a range of 4 to 26 km along the strike, indicating that this earthquake was a thrust event on a blind fault within the thick-skinned tectonics of the South Tian Shan. Coulomb stress changes indicate that aftershocks primarily occur in the stress-loading region. Interestingly, some aftershocks are very shallow, causing clear surface deformation. Inversion results show that the fault planes of two aftershocks are located above the main shock fault plane at extremely shallow depths (<6 km). Combining geophysical profile data, we infer that ruptures in the deep-seated thick-skinned structures during the main shock triggered ruptures in the shallow thrust structures. This triggering relationship highlights the potential for combined ruptures of the main shocks and aftershocks in the deep-seated thick-skinned structures beneath the South Tian Shan to result in larger disasters than typical seismic events. Full article

The IgG response against SARS-CoV-2 infection can persist for over six months (long response; LR). However, among 30% of those infected, the duration can be as short as three months or less (short response; SR). The present study assembled serological data on the anti-SARS-CoV-2 IgG response duration of two previous studies and integrated these results with the plasmatic cytokine levels and genetic profile of 10 immune-relevant SNPs that were also previously published, along with the plasmatic total IgG, IgA, and IgM levels, allowing for the genetic, clinical, immunological, and epidemiological aspects of the post-COVID-19 IgG response duration to be understood. The SR was associated with previous mild acute COVID-19 and with an SNP (rs2228145) in IL6R related to low gene expression. Additionally, among the SR subgroup, no statistically significant Spearman correlations were observed between the plasma levels of IL-17A and the Th17 regulatory cytokines IFN-γ (rs = 0.2399; p = 0.1043), IL-4 (rs = 0.0273; p = 0.8554), and IL-2 (rs = 0.2204; p = 0.1365), while among the LR subgroup, weaker but statistically significant Spearman correlations were observed between the plasma levels of IL-17A and IFN-γ (rs = 0.3873; p = 0.0016), IL-4 (rs = 0.2671; p = 0.0328), and IL-2 (rs = 0.3959; p = 0.0012). These results suggest that the Th17 response mediated by the IL-6 pathway has a role in the prolonged IgG response to SARS-CoV-2 infection. Full article

The emergence of SARS-CoV-2 has meant that pandemic preparedness has become a major focus of the global scientific community. Gathered in the historic St Edmund Hall college in Oxford, the one-day LPMHealthcare conference on emerging viruses (6 September 2023) sought to review and learn from past pandemics—the current SARS-CoV-2 pandemic and the Mpox outbreak—and then look towards potential future pandemics. This includes an emphasis on monitoring the “traditional” reservoirs of viruses with zoonotic potential, as well as possible new sources of spillover events, e.g., bats, which we are coming into closer contact with due to climate change and the impacts of human activities on habitats. Continued vigilance and investment into creative scientific solutions is required for issues including the long-term physical and psychological effects of COVID-19, i.e., long COVID. The evaluation of current systems, including environmental monitoring, communication (with the public, regulatory authorities, and governments), and training; assessment of the effectiveness of the technologies/assays we have in place currently; and lobbying of the government and the public to work with scientists are all required in order to build trust moving forward. Overall, the SARS-CoV-2 pandemic has shown how many sectors can work together to achieve a global impact in times of crisis. Full article

SARS-CoV-2 is a highly pathogenic virus responsible for the COVID-19 disease. It belongs to the Coronaviridae family, characterized by a phospholipid envelope, which is crucial for viral entry and replication in host cells. Hypericin, a lipophilic, naturally occurring photosensitizer, was reported to effectively inactivate enveloped viruses, including SARS-CoV-2, upon light irradiation. In addition to its photodynamic activity, Hyp was found to exert an antiviral action also in the dark. This study explores the mechanical properties of heat-inactivated SARS-CoV-2 viral particles using Atomic Force Microscopy (AFM). Results reveal a flexible structure under external stress, potentially contributing to the virus pathogenicity. Although the fixation protocol causes damage to some particles, correlation with fluorescence demonstrates colocalization of partially degraded virions with their genome. The impact of hypericin on the mechanical properties of the virus was assessed and found particularly relevant in dark conditions. These preliminary results suggest that hypericin can affect the mechanical properties of the viral envelope, an effect that warrants further investigation in the context of antiviral therapies. Full article

Vaccine effectiveness (VE) studies provide real-world evidence to monitor vaccine performance and inform policy. The WHO Regional Office for the Eastern Mediterranean supported a regional study to assess the VE of COVID-19 vaccines against different clinical outcomes in four countries between June 2021 and August 2023. Health worker cohort studies were conducted in 2707 health workers in Egypt and Pakistan, of whom 171 experienced symptomatic laboratory-confirmed SARS-CoV-2 infection. Test-negative design case–control studies were conducted in Iran and Jordan in 4017 severe acute respiratory infection (SARI) patients (2347 controls and 1670 cases) during the Omicron variant dominant period. VE estimates were calculated for each study and pooled by study design for several vaccine types (BBIBP-CorV, AZD1222, BNT162b2, and mRNA-1273, among others). Among health workers, VE against symptomatic infection of a complete primary series could only be computed compared to partial vaccination, suggesting a benefit of providing an additional dose of mRNA vaccines (VE: 88.9%, 95%CI: 15.3–98.6%), while results were inconclusive for other vaccine products. Among SARI patients, VE against hospitalization of a complete primary series with any vaccine compared to non-vaccinated was 20.9% (95%CI: 4.5–34.5%). Effectiveness estimates for individual vaccines, booster doses, and secondary outcomes (intensive care unit admission and death) were inconclusive. Future VE studies will need to address challenges in both design and analysis when conducted late during a pandemic and will be able to utilize the strengthened capacities in countries. Full article

Accurate wind data are crucial for successful search and rescue (SAR) operations on the sea surface in maritime accidents, as survivors or debris tend to drift with the wind. As maritime accidents frequently occur outside the range of wind stations, SAR operations heavily rely on wind forecasts generated by numerical models. However, numerical models encounter delays in generating results due to spin-up issues, and their predictions can sometimes exhibit inherent biases caused by geographical factors. To overcome these limitations, we reviewed the observations for the first 24 h of the 72-hour forecast from the ECMWF and then post-processed the forecast for the remaining 48 h. By effectively reducing the dimensionality of input variables comprising observation and forecast data using principal component analysis, we improved wind predictions with support vector regression. Our model achieved an average RMSE improvement of 16.01% compared to the original forecast from the ECMWF. Furthermore, it achieved an average RMSE improvement of 5.42% for locations without observation data by employing a model trained on data from the nearest wind station and then applying an adaptive weighting scheme to the output of that model. Full article

Simulated data play an important role in SAR target recognition, particularly under zero-shot learning (ZSL) conditions caused by the lack of training samples. The traditional SAR simulation method is based on manually constructing target 3D models for electromagnetic simulation, which is costly and limited by the target’s prior knowledge base. Also, the unavoidable discrepancy between simulated SAR and measured SAR makes the traditional simulation method more limited for target recognition. This paper proposes an innovative SAR simulation method based on a visual language model and generative diffusion model by extracting target semantic information from optical remote sensing images and transforming it into a 3D model for SAR simulation to address the challenge of SAR target recognition under ZSL conditions. Additionally, to reduce the domain shift between the simulated domain and the measured domain, we propose a domain adaptation method based on dynamic weight domain loss and classification loss. The effectiveness of semantic information-based 3D models has been validated on the MSTAR dataset and the feasibility of the proposed framework has been validated on the self-built civilian vehicle dataset. The experimental results demonstrate that the first proposed SAR simulation method based on a visual language model and generative diffusion model can effectively improve target recognition performance under ZSL conditions. Full article