Search Results (16,358)

Lumpy Skin Disease (LSD) is a transboundary bovine viral disease. It has a significant economic impact and is caused by the Lumpy Skin Disease Virus (LSDV). Effective surveillance tools are essential for the early detection of infection, outbreak control, and assessment of vaccination coverage in endemic regions such as India. In this study, an in-house ELISA based on inactivated whole-virus antigen (WVA) was developed, optimized, and validated for the detection of LSDV antibodies in cattle. Its field applicability was assessed through a cross-sectional seroprevalence survey conducted across five Indian states. A local field isolate of LSDV (strain 5-Chitra) was cultured in MDBK cells, inactivated using binary ethylenimine (BEI), and used as the antigen source. The assay was optimized by checkerboard titration and evaluated against the Serum Neutralization Test (SNT). Diagnostic sensitivity and specificity were evaluated using the receiver operating characteristic (ROC) curve and area under the curve (AUC) analyses, while cross-reactivity was assessed using sera positive for HS, IBR, BQ, MCF, GTP, SPP, CE, FMD, and Brucellosis. Assay reproducibility was confirmed through inter- and intra-laboratory validation. For the seroprevalence study, 3230 cattle serum samples were collected using a stratified random sampling design across five Indian states, and logistic regression analysis of a subset of 1302 samples was performed to assess the influence of age and sex on LSDV seropositivity. Checkerboard titration identified optimal ELISA conditions at 50 ng of antigen per well, a 1:150 serum dilution, and a 1:10,000 dilution of anti-bovine HRP-conjugated secondary antibody. The WVA-ELISA demonstrated excellent diagnostic performance, with 100% sensitivity, 95% specificity, and no cross-reactivity with other ruminant bacterial or viral pathogens, and showed high laboratory reproducibility (κ > 0.96). Seroprevalence ranged from 50.6% to 71.1% across the five states, indicating widespread exposure to LSDV. Risk factor analysis revealed significantly higher odds of seropositivity among calves (≤1 year old) and female cattle, suggesting age- and sex-dependent susceptibility. Full article

The western Kuqa Foreland Basin exhibits complex hydrocarbon distribution with unclear accumulation processes. This study integrated seismic data, microscopic observations, crude oil properties, and basin modelling to establish a dynamic hydrocarbon migration model for the study area. The results indicated two distinct accumulation phases. During the early phase (16–5 Ma), hydrocarbons migrated eastward along a single unconformity and accumulated in the buried-hill reservoir of well E937 in the southern part of the Baicheng hydrocarbon-generating depression. In contrast, the southwestern region failed to accumulate hydrocarbons because of its distance from the Triassic source rock hydrocarbon generation centre and complex migration pathways. During the late phase (5–0 Ma), the Jurassic hydrocarbon generation centre shifted westward, and hydrocarbons migrated through a composite conduit system comprising faults, weathered crust, and sandstone structural ridges. This process promoted the expansion of the eastern E937 well trap, whereas well WEN54 and other southwestern wells exhibited hydrocarbon accumulation potential. The simulation results predicted that hydrocarbon reservoirs in the eastern region were mainly concentrated in the Qiulitage structural belt east of well E938. This study provides a theoretical basis and predictive guidance for hydrocarbon exploration in this area. Full article

Ensuring household food security through climate resilient and sustainable crop production continues to be a central challenge for rural farming households in Kenya. Therefore, the adoption of adaptation strategies to a changing climate is crucial in maize-growing regions. A multivariate probit model was deployed to understand determinants of the adoption of climate adaptation strategies and drought-tolerant maize varieties among 819 smallholder farmers in arid and semi-arid areas. The survey was conducted in four major maize-growing counties in Kenya. Results show that most climate change adaptation strategies implemented by maize-dependent smallholders are complementary. Multivariate logistic coefficients showed a significant inverse relationship between marital status and the adoption of soil and water conservation strategy in Machakos (−2.321; p = 0.01). Secondary education was significantly associated with the adoption of water harvesting in Machakos (2.538; p = 0.001), while it was associated with soil and water conservation in Homa Bay (2.208; p = 0.0001) and Migori (1.538; p = 0.01), respectively. Unemployment was positively (21.726; p = 0.01) linked with the adoption of water harvesting in Machakos, with the probability of a farmer adopting water harvesting strategies in Machakos (1.460; p = 0.01). Remarkably, soil and water conservation strategies in Machakos (1.807; p = 0.001) and Migori (2.458; p = 0.0001) positively correlated with food insecurity. Incidentally, only farmers in Migori County had a significant (1.024; p = 0.01) likelihood of adopting drought-tolerant maize varieties with increasing land size. In the same county, the source of maize variety was positively associated with the adoption of drought-tolerant varieties. There is a need to promote policies like informal and formal education and awareness creation to enhance smallholder farmers’ capacity to adopt multiple sustainable climate-smart adaptation strategies that can promote the continued adoption of drought-tolerant maize varieties. Full article

Agricultural non-point-source pollution poses a significant threat to water quality and sustainable water resource management, a challenge intensified by climate change-induced increases in rainfall intensity. In this study, we quantified how rainfall intensity controls runoff and the export of key pollutants (COD, TN, and TP) from paddy fields. Controlled simulation experiments with two rainfall intensities (40 mm/h, S40; 120 mm/h, S120) were conducted in the Yangtze River Basin. The results showed that high-intensity rainfall (S120) nearly doubled the surface runoff volume and coefficient compared to S40. A notable finding was the observed asymmetric response between pollutant concentration and export load. Despite a marked dilution effect under high-intensity rainfall that sometimes led to lower concentrations of COD and TP, the total export loads of all pollutants increased sharply due to the overwhelming increase in runoff volume. Specifically, COD export rose from 2.21 kg/ha (S40) to 4.90 kg/ha (S120), and TN export increased from 211.71 to 585.16 g/ha. In May, TP export under S120 was 2.5 times greater than that under S40. These results provide critical evidence and a mechanistic basis for developing climate-adaptive, sustainable nutrient management strategies aimed at mitigating water pollution and enhancing the environmental sustainability of rice production systems in the Yangtze River Basin and similar monsoon-affected regions. Full article

Currently, ω-3 polyunsaturated fatty acids (PUFAs), which have become popular as dietary supplements, are limited by a shortage in supply. Thus, finding safe, effective alternatives is crucial. Echium seed oil (ESO), rich in α-linolenic acid (ALA, 18:3ω-3) and stearidonic acid (SDA, 18:4ω-3), surpasses many other botanical seed oils. In this study, a pseudotargeted approach was applied to characterize the lipidomic profile of two unexplored Echium species from the Mediterranean region. Our findings established Echium glomeratum as a rich source of ω-3 fatty acids (FAs), exceeding many other species in both quality and quantity. E. glomeratum possesses different FAs and triglyceride (TG) profiles compared to E. judaeum, with the ω-3:ω-6 ratio being 3.5 and 1.3, respectively. This corresponds to higher quantities of ALA (45.50%) and SDA (12.59%) in E. glomeratum. Triglycerides (TGs) comprise 93% of the total lipid content in ESO. This study also profiled the most abundant TGs (50–60 carbons) from both species through comprehensive assignment of the olefination patterns. The E. glomeratum oil profile, containing a higher ω-3 PUFA concentration, was further screened for cytotoxic and antioxidant activities. Our preliminary results demonstrated that E. glomeratum ESO may significantly suppress colon cancer cell growth. Full article

Based on continuous field observations conducted at the Shangdianzi Regional Atmospheric Background Station from 21 October to 20 November 2024 and from 1 December 2024, to 2 January 2025, this study systematically analyzed the concentration levels, seasonal variations, diurnal patterns, and ozone formation potential (OFP) of 24 carbonyl compounds (OVOCs) in the atmosphere during autumn and winter. Source apportionment was further investigated using characteristic ratios, correlation analysis, and multiple linear regression. The results indicate that the average concentration of Σ24OVOCs during the observation period was 2.70 ± 1.55 ppb. Formaldehyde, acetone, and acetaldehyde were the dominant species, accounting for 94.5% of the total concentration in this background area. A significant seasonal difference in carbonyl concentrations was observed, with the average concentration in autumn (3.68 ± 1.66 ppb) being approximately 2.1 times higher than that in winter (1.78 ± 0.58 ppb). The diurnal variation in most carbonyls exhibited a pattern of nighttime accumulation and daytime depletion, which was consistent with the trend of NO₂. The OFP results show that the average OFP of Σ24OVOCs was 30 ± 16 μg/m³, with formaldehyde contributing 86.9%, identifying it as a key precursor for ozone formation in the background region. Source analysis revealed that carbonyl compounds in autumn were influenced by combined natural, vehicular, and industrial sources, with significant secondary formation (27–36%) observed for C2 (acetaldehyde) and C3 (mainly acetone and propanal) species. In winter, anthropogenic contributions to carbonyls increased, with C2 and C3 species primarily originating from combustion sources, vehicle emissions, and industrial releases. This study provides the first insights into the pollution characteristics and source profiles of carbonyl compounds during autumn and winter at the Shangdianzi background site, offering a scientific basis for understanding regional atmospheric oxidative capacity and formulating integrated air pollution control strategies. Full article

The control of 400 Hz Ground Power Units (GPUs) in the range of several hundreds of kW poses distinct challenges, as the switching frequency ($f_{sw}$) must be constrained to limit switching losses. This constraint typically results in low ratios of the switching and LC filter natural frequencies ($f_n$) relative to the fundamental frequency. Notably, without mitigation, such systems often face stability issues or non-minimum phase behavior when $f_n<f_s/3$ (where $f_s$ is the sampling frequency). To address these challenges, this paper introduces a single-loop voltage control strategy for a 400 Hz voltage-source inverter (VSI) featuring a robust voltage decoupling scheme. Crucially, this decoupling allows the system to maintain minimum phase characteristics and operate with positive gains even when $f_n<f_s/3$, effectively solving the stability problems inherent to this operating region. The proposed architecture employs a proportional-resonant (PR) controller, with parameters systematically tuned to achieve maximum system damping based on stability regions dependent on the ratio between the sampling and natural frequencies. Validated through simulation and experimental procedures, the proposed method demonstrates precise voltage tracking and a robust dynamic response, proving its suitability for high-power, high-fundamental-frequency applications. Full article

Disentangling the impacts of ecological restoration from climate change is an ongoing challenge in remote sensing since the traditional correlative approaches often cannot elucidate causal mechanisms. To overcome this, we introduce a Causal Remote Sensing Framework that uses multi-source satellite data (2000–2020), machine learning (XGBoost, SHAP) and causal inference (T-Learner) to build pixel-level counterfactuals. Using this framework, we assessed the Return Grazing to Grassland Program (RGGP) on the Qinghai–Tibet Plateau. Our results demonstrate that a warming and wetting climate improved Water yield (WY) while at the same time decreasing sand fixation (SF) in 83.6% of the region. Notably, the restoration project became the main factor that slowed this decline. After controlling for observational selection bias, the program had a net positive effect of (+6.02 t hm⁻²), reducing degradation in 64.6% of treated areas. This framework provides a practical way for the remote sensing community to go beyond change monitoring to allow the diagnosis of the causal mechanisms in complex human-environment systems. Full article

Reduced soil moisture (SM) together with elevated vapor pressure deficit (VPD) suppresses gross primary productivity (GPP) and thus weakens the capacity of the terrestrial carbon pool. Against the backdrop of global climate change, soil and atmospheric drought exert a more profound impact on vegetation growth, and their combined impacts remain unclear. Based on multi-source remote sensing observations and reanalysis datasets, three vegetation remote sensing indices, GPP, SIF, and NDVI (collectively referred to as Vegetation Remote Sensing Indices, VSI), are employed in this study to assess the relative impacts of soil and atmospheric drought on terrestrial vegetation. First, Copula-based conditional probabilities are applied to identify which factor (reduced SM or high VPD) plays a dominant role under conditions of declining vegetation productivity and to determine their corresponding thresholds. Furthermore, the underlying driving mechanisms are elucidated by utilizing Structural Equation Modeling (SEM) for path analysis to clarify how climatic factors indirectly affect vegetation productivity by influencing SM and VPD. The results suggest that vegetation growth in China’s different climatic zones is affected by distinct factors. Specifically, SM is the primary factor influencing vegetation productivity, dominating 71.16% of the nation’s vegetated areas. Its influence is particularly pronounced in arid and semi-arid regions. In contrast, the impact of VPD is predominantly concentrated in semi-humid plain regions. Furthermore, the critical thresholds for SM in different climate zones are identified: the threshold averages approximately 0.33 m³/m³ in humid and plateau regions and 0.13 m³/m³ in arid and semi-arid regions. The SEM analysis further reveals the complex pathways by which climatic variables influence vegetation growth. In SM-dominated regions, higher SM directly promotes vegetation growth; in VPD-dominated regions, drier air imposes a stronger suppression on vegetation growth. Nonetheless, the plateau temperate semi-arid zone demonstrates distinct hydrometeorological characteristics. Attributed to the region’s unique hydrometeorological conditions, the negative effects of higher VPD are generally outweighed by the favorable conditions for photosynthesis with which it co-occurs. These findings clarify the intricate impacts of SM and VPD on vegetation productivity, providing a foundational framework for the development of tailored ecological management strategies and drought early warning systems. Full article

This paper investigates the complex flow characteristics and parameter prediction methods for axial-inlet cover-plate cavities in pre-swirl systems numerically. Using a full-annulus three-dimensional computational model, the flow mechanisms of cover-plate cavities are compared between axial and radial inlet configurations. The analysis reveals that the axial-inlet configuration exhibits intensified non-axisymmetric vortex pairs in the low-radius region due to axial inflow inertia. These vortex structures enhance radial angular momentum exchange, leading to a substantial inlet angular momentum deficit that consequently reduces swirl ratios and pressure coefficients relative to the radial-inlet configuration. Furthermore, parametric studies demonstrate that small gap ratio amplifies circumferential flow non-uniformity through strong impingement effects, while elevated inlet swirl ratio significantly extends the source region boundary by strengthening centrifugal forces. To address the prediction discrepancies in existing models, this work proposes a modified correlation for the effective inlet swirl ratio that account for the inlet momentum loss and develops a new predictive model for the edge of source region incorporating centrifugal effects. These physics-based corrections, validated against simulation data, significantly improve the prediction accuracy for axial-inlet cover-plate cavities compared to conventional models. Full article

Urban flood information enables managers to rapidly synthesize comprehensive flood event profiles, serving as critical evidence for flood control decision making. Compared with traditional methods, public data offer unprecedented spatiotemporal granularity due to its high volume, multidimensionality, and real-time nature. In this paper, we investigated public data’s usefulness and generalizability of spatial feature differences using multi-source social media data as an entry point. We selected rainstorm events that occurred in three cities located in the North China Plain, the Southeast Coastal Region, and the Western Region of China, with vastly different developmental statuses in 2023. Then, multi-platform data from the events were collected and analyzed through crawling and topic mining. The results indicate that: (1) social media data from different sources are complementary to each other and can collectively extract plenty of neglected waterlogging points to supplement official data, with a supplementary rate reaching 171% on average; and (2) social media data has significant value in spatial characterization, which means that its availability remains constant despite geographical differences and can self-adapt to local geography, inhabitant profiles and social development levels. To address the issues of limited available data and essential information lacking during the analysis process, we propose recommendations for data processing and city managers to enhance the scientific value of social media data utilized in practice. Full article

Forest structural parameters, such as canopy closure, stand density, diameter at breast height, tree height, leaf area index, stand age, and biomass, are fundamental for quantifying forest ecosystem functioning and supporting sustainable forest management. Remote sensing has become an indispensable tool for forest structural parameter estimation. Commonly used data sources include optical imagery, synthetic aperture radar (SAR), light detection and ranging (LiDAR), unmanned aerial vehicles (UAVs), and multisource data fusion. Correspondingly, modeling approaches have evolved from empirical and statistical methods to machine learning, deep learning, and hybrid physical-data-driven models, enabling improved characterization of nonlinear and complex forest structures. Each data source and modeling strategy offers unique strengths and limitations with respect to accuracy, scalability, interpretability, and transferability. This review provides a concise synthesis of recent advances in remote sensing data sources and model algorithms for forest structural parameter estimation, evaluates the strengths and limitations of different sensors and algorithms, and highlights key challenges related to uncertainty, scalability, transferability, and model interpretability. Finally, future research directions are discussed, emphasizing cross-scale integration, multisource data fusion, and physically informed deep learning frameworks as promising pathways toward more accurate, robust, and ecologically interpretable forest structural parameter modeling at regional to global scales. Full article

Land desertification poses a major ecological challenge and threatens agricultural productivity. This study investigated the seed endophytic microbiomes of desert plants as a potential resource for mitigating salt stress in crops. Using high-throughput sequencing, we characterized the bacterial and fungal communities within seeds of 12 desert plant species. Dominant taxa included Firmicutes (particularly Bacillus), Bacteroidota, Proteobacteria, Ascomycota, and Basidiomycota. Culturable bacteria were subsequently isolated from Haloxylon ammodendron (C.A.Mey.) Bunge (HB) and Hedysarum scoparium Fisch. & C.A.Mey. (HSA) seeds. These isolates were screened for plant growth-promoting (PGP) traits and tolerance to salt (NaCl) and alkali (NaHCO₃). Selected strains, including the high indole-3-acetic acid (IAA)-producing Bacillus sp. HB-4, were used to inoculate wheat (Triticum aestivum L.) under 150 mM NaCl or 150 mM NaHCO₃ stress. Inoculation with strain HB-4 significantly improved wheat growth under stress. This improvement was associated with increased chlorophyll and proline content, enhanced activities of the antioxidant enzymes catalase and peroxidase, and reduced levels of malondialdehyde, a marker of oxidative damage. Our results demonstrate that desert plant seeds harbor taxonomically distinct and functionally resilient endophytes. The successful application of a desert-adapted Bacillus strain to alleviate salt stress in wheat highlights the potential of such microbiomes as a novel source of inoculants for sustainable agriculture in saline-affected regions. Full article

This study proposes an efficient numerical scheme for simulating heat transfer governed by the diffusion equation with moving singular sources. The work addresses two-dimensional problems with line sources and three-dimensional problems with plane sources, which are prevalent in irreversible thermodynamic processes. Developed within a finite difference framework, the method employs a partitioned discretization strategy to accurately resolve the solution singularity near the heat source—a region critical for precise local entropy production analysis. In the immediate vicinity of the source, we analytically derive and incorporate the solution’s “jump” conditions to construct specialized finite difference approximations. Away from the source, standard second-order-accurate schemes are applied. This hybrid approach yields a globally second-order convergent spatial discretization. The resulting sparse system is efficient for large-scale simulation of dissipative systems. The accuracy and efficacy of the proposed method are demonstrated through numerical examples, providing a reliable tool for the detailed study of energy distribution in non-equilibrium thermal processes. Full article

The Tibetan Plateau is highly sensitive to global climate change and characterized by pronounced ecological fragility, making vegetation net primary productivity (NPP) a key indicator for assessing ecosystem functioning and regional ecological security. This study aims to characterize the spatiotemporal dynamics of NPP and to disentangle the multiple natural and land-use drivers shaping its variability across the Tibetan Plateau. MODIS-derived NPP data for the period 2001–2022 are integrated with multi-source datasets on climate, topography, normalized difference vegetation index (NDVI), and land use (CLCD), and analyzed using trend and correlation analyses, land-use transfer matrices, an optimal-parameter geographical detector, and partial least squares structural equation modeling (PLS-SEM). The results indicate that NPP exhibits a significant but fluctuating upward trend (0.52 gC·m⁻²·a⁻¹, p < 0.01), with higher values in the southeast and lower values in the northwest, the Yunnan Plateau evergreen broadleaf and pine forest region (VA5) and the southern Himalayan montane forest region (VA6) function as high-value centers, and regions such as the Kunlun high-cold desert region (HID1) represent low-value centers. The mutual conversion between forestland and grassland and bare land constitutes a key process driving regional NPP changes, with the net expansion of forestland making a substantial contribution to NPP increases (net gain of 2606.88 TgC). Geographic detector analysis indicates that NDVI (q = 0.741) and land use type (q = 0.741) are the primary factors governing the spatial differentiation of NPP, followed by precipitation, slope, and temperature. Moreover, interactions between any two factors enhance their explanatory power, with the interaction between aspect and land use type exhibiting the strongest effect (q approaching 1). PLS-SEM path analysis further quantifies the driving pathways, revealing that mean annual precipitation and land use type are the most direct drivers of NPP, while climatic and topographic factors influence NPP indirectly through their effects on vegetation cover and land use type. This study advances the understanding of the multifactorial driving mechanisms of ecosystem productivity on the Tibetan Plateau and provides a scientific basis for zoned and differentiated ecological restoration and climate adaptation strategies. Full article