Search Results (276)

Landslides pose significant threats to life and property, particularly in mountainous regions. To address this, this study develops a landslide susceptibility model integrating Earth Observation (EO) data, historical data, and Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) ground movement results. The model categorizes areas into four susceptibility classes (from Class 1 to Class 4) using a multi-class classification approach. Results indicate that the Xtreme Gradient Boosting (XGB) model effectively predicts landslide susceptibility with area under the curve (AUC) values ranging from 0.93 to 0.97, with high accuracy of 0.89 and a balanced performance across different susceptibility classes. The integration of MT-InSAR data enhances the model’s ability to capture dynamic ground movement and improves landslide mapping. The landslide susceptibility map generated by the XGB model indicates high susceptibility along the Pacific coast. The optimal model was validated against 272 historical landslide occurrences, with predictions distributed as follows: 68 occurrences (25%) in Class 1, 142 occurrences (52%) in Class 2, 58 occurrences (21.5%) in Class 3, and 4 occurrences (1.5%) in Class 4. This study highlights the importance of considering temporal changes in environmental conditions such as precipitation, distance to streams, and changes in vegetation for accurate landslide susceptibility assessment. Full article

Correlates of Protection (CoP) are biomarkers above a defined threshold that can replace clinical outcomes as primary endpoints, predicting vaccine effectiveness to support the approval of new vaccines or follow up studies. In the context of COVID-19 vaccination, CoPs can help address challenges such as demonstrating vaccine effectiveness in special populations, against emerging SARS-CoV-2 variants or determining the durability of vaccine-elicited immunity. While anti-spike IgG titres and viral neutralising capacity have been characterised as CoPs for COVID-19 vaccination, the contribution of other components of the humoral immune response to immediate and long-term protective immunity is less well characterised. This review examines the evidence supporting the use of CoPs in COVID-19 clinical vaccine trials, and how they can be used to define a protective threshold of immunity. It also highlights alternative humoral immune biomarkers, including Fc effector function, mucosal immunity, and the generation of long-lived plasma and memory B cells and discuss how these can be applied to clinical studies and the tools available to study them. Full article

Objective: SARS-CoV-2 remains the third most common cause of death in North America. We studied the effects of methotrexate and tumor necrosis factor inhibitor (TNFi) on neutralization responses after COVID-19 vaccination in immune-mediated inflammatory disease (IMID). Methods: Prospective data and sera of adults with inflammatory bowel disease (IBD), rheumatoid arthritis (RA), spondyloarthritis (SpA), psoriatic arthritis (PsA), and systemic lupus (SLE) were collected at six academic centers in Alberta, Manitoba, Ontario, and Quebec between 2022 and 2023. Sera from two time points were evaluated for each subject. Neutralization studies were divided between five laboratories, and each lab’s results were analyzed separately using multivariate generalized logit models (ordinal outcomes: absent, low, medium, and high neutralization). Odds ratios (ORs) for the effects of methotrexate and TNFi were adjusted for demographics, IMID, other biologics and immunosuppressives, prednisone, COVID-19 vaccinations (number/type), and infections in the 6 months prior to sampling. The adjusted ORs for methotrexate and TNFi were then pooled in random-effects meta-analyses (separately for the ancestral strains and the Omicron BA1 and BA5 strains). Results: Of 479 individuals (958 samples), 292 (61%) were IBD, 141 (29.4%) were RA, and the remainder were PsA, SpA, and SLE. The mean age was 57 (62.2% female). For both the individual labs and the meta-analyses, the adjusted ORs suggested independent negative effects of TNFi and methotrexate on neutralization. The meta-analysis adjusted ORs for TNFi were 0.56 (95% confidence interval (CI) 0.39, 0.81) for the ancestral strain and 0.56 (95% CI 0.39, 0.81) for BA5. The meta-analysis adjusted OR for methotrexate was 0.39 (95% CI 0.19, 0.76) for BA1. Conclusions: SARS-CoV-2 neutralization in vaccinated IMID was diminished independently by TNFi and methotrexate. As SARS-CoV-2 circulation continues, ongoing vigilance regarding optimized vaccination is required. Full article

We were tasked by Canada’s COVID-19 Immunity Task Force to describe severe adverse events (SAEs) associated with emergency department (ED) visits and/or hospitalizations in individuals with immune-mediated inflammatory diseases (IMIDs). At eight Canadian centres, data were collected from adults with rheumatoid arthritis (RA), axial spondyloarthritis (AxS), systemic lupus (SLE), psoriatic arthritis (PsA), and inflammatory bowel disease (IBD). We administered questionnaires, analyzing SAEs experienced within 31 days following SARS-CoV-2 vaccination. About two-thirds (63%) of 1556 participants were female; the mean age was 52.5 years. The BNT162b2 (Pfizer) vaccine was the most common, with mRNA-1273 (Moderna) being second. A total of 49% of participants had IBD, 27.4% had RA, 14.3% had PsA, 5.3% had SpA, and 4% had SLE. Twelve (0.77% of 1556 participants) SAEs leading to an ED visit or hospitalization were self-reported, occurring in 11 participants. SAEs included six (0.39% of 1556 participants) ED visits (including one due to Bell’s Palsy 31 days after first vaccination) and six (0.39% of 1556 participants) hospitalizations (including one due to Guillain-Barré syndrome 15 days after the first vaccination). Two SAEs included pericarditis, one involved SLE (considered a serious disease flare), and one involved RA. Thus, in the 31 days after SARS-CoV-2 vaccination in our IMID sample, very few serious adverse events occurred. As SARS-CoV2 continues to be a common cause of death, our findings may help optimize vaccination acceptance. Full article

MoMo30 is an antiviral protein isolated from aqueous extracts of Momordica balsamina L. (Senegalese bitter melon). Previously, we demonstrated MoMo30’s antiviral activity against HIV-1. Here, we explore whether MoMo30 has antiviral activity against the COVID-19 virus, SARS-CoV-2. MLV particles pseudotyped with the SARS-CoV-2 Spike glycoprotein and a Luciferase reporter gene (SARS2-PsV) were developed from a three-way co-transfection of HEK293-T17 cells. MoMo30’s inhibition of SARS2-PsV infection was measured using a luciferase assay and its cytotoxicity using an XTT assay. Additionally, MoMo30’s interactions with the variants and domains of Spike were determined by ELISA. We show that MoMo30 inhibits SARS2-PsV infection. We also report evidence of the direct interaction of MoMo30 and SARS-CoV-2 Spike from WH-1, Alpha, Delta, and Omicron variants. Furthermore, MoMo30 interacts with both the S1 and S2 domains of Spike but not the receptor binding domain (RBD), suggesting that MoMo30 inhibits SARS-CoV-2 infection by inhibiting fusion of the virus and the host cell via interactions with Spike. Full article

Large-scale man-made linear structures like high-speed railway lines have become increasingly important in modern life as a faster and more comfortable transportation option. Subsidence or longitudinal levelling deformation problems along these railway lines can prevent the line from operating effectively and, in some cases, require speed reduction, continuous maintenance or repairs. In this study, the longitudinal levelling deformation of the high-speed railway line passing through Konya province (Central Turkey) was analyzed for the first time using the Persistent Scatter Synthetic Aperture Radar Interferometry (PS-InSAR) technique in conjunction with diagnostic train measurements, and the correlation values between them were found. In order to monitor potential levelling deformation along the railway line, medium-resolution, free-of-charge C-band Sentinel-1 (S-1) data and high-resolution, but paid, X-band Cosmo-SkyMed (CSK) Synthetic Aperture Radar (SAR) data were analyzed from the diagnostic train and reports received from the relevant maintenance department. Comparison analyses of the results obtained from the diagnostic train and radar measurements were carried out for three regions with different deformation scenarios, selected from a 30 km railway line within the whole analysis area. PS-InSAR measurements indicated subsidence events of up to 40 mm/year along the railway through the alluvial sediments of the Konya basin, which showed good agreement with the diagnostic train. This indicates that the levelling deformation of the railway and its surroundings can be monitored efficiently, rapidly and cost-effectively using the InSAR technique. Full article

Landslide hazard mapping is important to urban construction and landslide risk management. Dynamic landslide hazard mapping considers landslide deformation with changes in the environment. It can show more details of the landslide process state. Landslides in highly vegetated areas are difficult to observe directly, which makes landslide hazard mapping much more challenging. The application of multi-InSAR opens new ideas for dynamic landslide hazard mapping. Specifically, landslide susceptibility mapping reflects the spatial probability of landslides. For rainfall-induced landslides, the scale exceedance probability reflects the temporal probability. Based on the coupling of them, dynamic landslide hazard mapping further considers the landslide deformation intensity at different times. Zigui, a highly vegetation-covered area, was taken as the study area. The landslide displacement monitoring effect of different band SAR datasets (ALOS-2, Sentinel-1A) and different interpretation methods (D-InSAR, PS-InSAR, SBAS-InSAR) were studied to explore a combined application method. The deformation interpreted by SBAS-InSAR was taken as the main part, PS-InSAR data were used in towns and villages, and D-InSAR was used for the rest. Based on the preliminary evaluation and the displacement interpreted by fusion InSAR, the dynamic landslide hazard mappings of the study area from 2019 to 2021 were finished. Compared with the preliminary evaluation, the dynamic mapping approach was more focused and accurate in predicting the deformation of landslides. The false positives in very-high-hazard zones were reduced by 97.8%, 60.4%, and 89.3%. Dynamic landslide hazard mapping can summarize the development of and change in landslides very well, especially in highly vegetated areas. Additionally, it can provide trend prediction for landslide early warning and provide a reference for landslide risk management. Full article

The effective monitoring of railway facilities is crucial for safety and operational efficiency. This study proposes an enhanced remote monitoring technique for railway facilities, specifically bridges, using satellite radar InSAR (Interferometric Synthetic Aperture Radar) technology. Previous studies faced limitations such as insufficient data points and challenges with topographical and structural variations. Our approach addresses these issues by analysing displacements from 30 images captured by the X-band SAR satellite, TerraSAR-X, over two years. We tested each InSAR parameter to develop an optimal set of parameters, applying the technique to a post-tensioned PSC (pre-stressed concrete) box bridge. Our findings revealed a recurring arch-shaped elevation along the bridge, attributed to temporal changes and long-term deformation. Further analysis showed a strong correlation between this deformation pattern and average surrounding temperature. This indicates that our technique can effectively identify micro-displacements due to temperature changes and structural deformation. Thus, the technique provides a theoretical foundation for improved SAR monitoring of large-scale social overhead capital (SOC) facilities, ensuring efficient maintenance and management. Full article

Monitoring slow-moving landslides is a crucial task for socioeconomic risk prevention and/or mitigation. Persistent scatterer interferometric synthetic aperture radar (PS-InSAR) is an advanced remote sensing method for monitoring ground deformation. In this research, PS-InSAR time series derived from COSMO-SkyMed (descending orbit) and Sentinel-1 (ascending orbit) are analyzed for a region in Central Apennines in Italy. The sequential turning point detection method (STPD) is implemented to detect the trend turning dates and their directions in the PS-InSAR time series within areas of interest susceptible to landslides. The monthly maps of significant turning points and their directions for years 2018, 2019, 2020, and 2021 are produced and classified for four Italian administrative regions, namely, Marche, Umbria, Abruzzo, and Lazio. Monthly global precipitation measurement (GPM) images at $0.1^{\circ }\times 0.1^{\circ }$ spatial resolution and four local precipitation time series are also analyzed by STPD to investigate when the precipitation rate has changed and how they might have reactivated slow-moving landslides. Generally, a strong correlation ($r\ge 0.7$) is observed between GPM (satellite-based) and local precipitation (station-based) with similar STPD results. Marche and Abruzzo (the coastal regions) have an insignificant precipitation rate while Umbria and Lazio have a significant increase in precipitation from 2017 to 2023. The coastal regions also exhibit relatively lower precipitation amounts. The results indicate a strong correlation between the trend turning dates of the accumulated precipitation and displacement time series, especially for Lazio during summer and fall 2020, where relatively more significant precipitation rate of change is observed. The findings of this study may guide stakeholders and responsible authorities for risk management and mitigating damage to infrastructures. Full article

Due to its unique geographical location and rapid urbanization, Xiamen is particularly susceptible to geological disasters. This study employs 80 Sentinel-1A SAR images covering Xiamen spanning from May 2017 to December 2023 for comprehensive dynamic monitoring of the land subsidence. PS-InSAR and SBAS-InSAR techniques were utilized to derive the surface deformation field and time series separately, followed by a comparative analysis of their results. SBAS-InSAR was finally chosen in this study for its higher coherence. Based on its results, we conducted cause analysis and obtained the following findings. (1) The most substantial subsidence occurred in Maluan Bay and Dadeng Island, where the maximum subsidence rate was 24 mm/yr and the maximum cumulative subsidence reached 250 mm over the course of the study. Additionally, regions exhibiting subsidence rates ranging from 10 to 30 mm/yr included Yuanhai Terminal, Maluan Bay, Xitang, Guanxun, Jiuxi entrance, Yangtang, the southeastern part of Dadeng Island, and Yundang Lake. (2) Geological structure, groundwater extraction, reclamation and engineering construction all have impacts on land subsidence. The land subsidence of fault belts and seismic focus areas was significant, and the area above the clay layer settled significantly. Both direct and indirect analysis can prove that as the amount of groundwater extraction increases, the amount of land subsidence increases. Significant subsidence is prone to occur after the initial land reclamation, during the consolidation period of the old fill materials, and after land compaction. The construction changes the soil structure, and the appearance of new buildings increases the risk of subsidence. Full article

Beijing is a city on the North China Plain with severe land subsidence. In recent years, Beijing has implemented effective measures to control land subsidence. Since this implementation, the development of time-series land subsidence in Beijing has slowed and has shown nonlinearity. Most previous studies have focused on the linear evolution of land subsidence; the nonlinear evolutionary patterns of land subsidence require further discussion. Therefore, we aimed to identify the evolution of land subsidence in Beijing, based on Envisat ASAR and Radarsat-2 images from 2003 to 2020, using permanent scatterer interferometric synthetic aperture radar (PS-InSAR) and cubic curve polynomial fitting methods. The dates of the extreme and inflection points were identified from the polynomial coefficients. From 2003 to 2020, the subsidence rate reached 138.55 mm/year, and the area with a subsidence rate > 15 mm/year reached 1688.81 km². The cubic polynomials fit the time-series deformation well, with R² ranging from 0.86 to 0.99 and the RMSE ranging from 1.97 to 60.28 mm. Furthermore, the subsidence rate at 96.64% of permanent scatterer (PS) points first increased and then decreased. The subsidence rate at 86.58% of the PS points began to decrease from 2010 to 2015; whereas the subsidence rate at 30.51% of the PS point reached a maximum between 2015 and 2019 and then decreased. The cumulative settlement continued to increase at 69.49% of the PS points. These findings imply that groundwater levels are highly correlated with the temporal evolution of subsidence in areas with pattern D (Vs+-, S+), with increasing and then decelerating rates and increasing amounts. In regions with a thickness of compressible clay layer over 210 m, subsidence follows pattern E (Vs+, S+), with increasing rates and amounts. Fractures such as the Gaoliying and Sunhe fractures significantly influence the spatial distribution of subsidence patterns, showing distinct differences on either side. Near the Global Resort Station, pattern E (Vs+, S+) intensifies in subsidence, potentially due to factors like land use changes and construction activities. Full article

Precision agriculture integrates multiple sensors and data types to support farmers with informed decision-making tools throughout crop cycles. This study evaluated Aboveground Biomass (AGB) estimates of Rye using attributes derived from PlanetScope (PS) optical, Sentinel-1 Synthetic Aperture Radar (SAR), and hybrid (optical plus SAR) datasets. Optical attributes encompassed surface reflectance from PS’s blue, green, red, and near-infrared (NIR) bands, alongside the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). Sentinel-1 SAR attributes included the C-band Synthetic Aperture Radar Ground Range Detected, VV and HH polarizations, and both Ratio and Polarization (Pol) indices. Ground reference AGB data for Rye (Secale cereal L.) were collected from 50 samples and four dates at a farm located in southern Brazil, aligning with image acquisition dates. Multiple linear regression models were trained and validated. AGB was estimated based on individual (optical PS or Sentinel-1 SAR) and combined datasets (optical plus SAR). This process was repeated 100 times, and variable importance was extracted. Results revealed improved Rye AGB estimates with integrated optical and SAR data. Optical vegetation indices displayed higher correlation coefficients (r) for AGB estimation (r = +0.67 for both EVI and NDVI) compared to SAR attributes like VV, Ratio, and polarization (r ranging from −0.52 to −0.58). However, the hybrid regression model enhanced AGB estimation (R² = 0.62, p < 0.01), reducing RMSE to 579 kg·ha⁻¹. Using only optical or SAR data yielded R² values of 0.51 and 0.42, respectively (p < 0.01). In the hybrid model, the most important predictors were VV, NIR, blue, and EVI. Spatial distribution analysis of predicted Rye AGB unveiled agricultural zones associated with varying biomass throughout the cover crop development. Our findings underscored the complementarity of optical with SAR data to enhance AGB estimates of cover crops, offering valuable insights for agricultural zoning to support soil and cash crop management. Full article

The article addresses anthropogenic and geological conditions related to the development of soil subsidence in the western zone of Recife (Brazil). Over the past 50 years, human activity has intensified in areas previously affected by soft soils (clay, silt, and sandstone) resulting in subsidence due to additional loads (landfills and constructions). The duration of the settlement process can be significantly influenced by the specific characteristics of the soil composition and geological conditions of the location. This work presents, for the first time, accurate InSAR time series maps that describe the spatial pattern and temporal evolution of the settlement, as well as the correlation with the geological profile, and validation with Global Navigation Satellite System (GNSS) data. Persistent Scatterer Interferometry (PS-InSAR) was employed in the analysis of Single Look Complex (SLC) images generated by 100 ascending COSMO-SkyMed (CSK) and 65 PAZ (32 ascending, and 33 descending) from the X-band, along with 135 descending Sentinel-1 (S1) acquisitions from the C-band. These data were acquired over the period from 2011 to 2023. The occurrence of subsidence was identified in several locations within the western region, with the most significant displacement rates observed in the northern, central, and southern areas. In the northern region, the displacement rates were estimated to be approximately −20 mm/year, with the Várzea and Caxangá neighborhoods exhibiting the highest rates. In the central region, the displacement rates were estimated to be approximately −15 mm/year, with the Engenho do Meio, Cordeiro, Torrões, and San Martin neighborhoods exhibiting the highest rates. Finally, in the southern region, the displacement rates were estimated to be up to −25 mm/year, with the Caçote, Ibura, and Ipsep neighborhoods exhibiting the highest rates. Additionally, east–west movements were observed, with velocities reaching up to −7 mm/year toward the west. These movements are related to the lowering of the land. The study highlights that anthropogenic effects in the western zone of Recife contribute to the region’s vulnerability to soil subsidence. Full article

Three years after the SARS-CoV-19 pandemic, a chronic post-COVID syndrome “LONG COVID” persists, causing fatigue and shortness of breath, along with distress, anxiety, and depression. Aim: To assess the impact of physical activity on the management and rehabilitation of LONG COVID, as well as to investigate the persistence of LONG COVID symptomatology in individuals over 40 years, beyond the pandemic. Methods: A total of 1004 participants (aged 53.45 ± 11.35) were recruited through an online snowball sampling strategy to complete a web-based survey. The following questionnaires were administered: Physical Activity Scale for Elderly (PASE), Shortness of Breath Questionnaire (SOBQ), Patient Health Questionnaire-9 item (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), and Fatigue Scale for Motor and Cognitive Functions (FSMC). Results: Significant gender differences were discovered, with women reporting higher symptoms than men (p < 0.001). Significant age differences were also found, with participants under 55 showing higher values than those over 55 (p < 0.001). No significant differences were found between aerobic and mixed physical activity (p > 0.05) while significant results emerged between physical activity groups and the no activity group (p < 0.001). The low-frequency group reported higher symptoms than the high-frequency group (all ps < 0.001). Conclusion: Regardless of the type of physical activity performed, our survey identified the frequency of training as a crucial factor to overcome LONG COVID symptoms; the challenge lies in overcoming the difficulties due to the persistent feelings of inefficiency and fatigue typical of those who have contracted the infection. Full article

Detecting slow-moving landslides is a crucial task for mitigating potential risk to human lives and infrastructures. In this research, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) time series, provided by the European Ground Motion Service (EGMS), for the province of Frosinone in Italy are employed, and Sequential Turning Point Detection (STPD) is applied to them to estimate the dates when the displacement rates change. The estimated dates are classified based on the land cover/use of the province. Moreover, local precipitation time series are employed to investigate how precipitation rate changes might have triggered the landslides. Full article