Search Results (2,260)

Soil salinization poses a severe threat to agricultural sustainability in the Yellow River Delta, where conventional spectral indices are limited by vegetation interference and seasonal dynamics in coastal saline-alkali landscapes. To address this, we developed an inversion framework integrating spectral indices and vegetation temporal features, combining multi-temporal Sentinel-2 optical data (January 2024–March 2025), Sentinel-1 SAR data, and terrain covariates. The framework employs Savitzky–Golay (SG) filtering to extract vegetation temporal indices—including NDVI temporal extremum and principal component features, capturing salt stress response mechanisms beyond single-temporal spectral indices. Based on 119 field samples and Variable Importance in Projection (VIP) feature selection, three ensemble models (XGBoost, CatBoost, LightGBM) were constructed under two strategies: single spectral features versus fused spectral and vegetation temporal features. The key results demonstrate the following: (1) The LightGBM model with fused features achieved optimal validation accuracy (R² = 0.77, RMSE = 0.26 g/kg), outperforming single-feature models by 13% in R². (2) SHAP analysis identified vegetation-related factors as key predictors, revealing a negative correlation between peak biomass and salinity accumulation, and the summer crop growth process affects soil salinization in the following spring. (3) The fused strategy reduced overestimation in low-salinity zones, enhanced model robustness, and significantly improved spatial gradient continuity. This study confirms that vegetation phenological features effectively mitigate agricultural interference (e.g., tillage-induced signal noise) and achieve high-resolution salinity mapping in areas where traditional spectral indices fail. The multi-temporal integration framework provides a replicable methodology for monitoring coastal salinization under complex land cover conditions. Full article

Wave-induced silty seabed liquefaction is one of the key threats to offshore infrastructure stability. The excess pore pressure (EPP) response is the key parameter for judging seabed liquefaction. Many studies have examined the EPP response to surface waves in initially well-consolidated seabed; few works have explored initially less-consolidated seabed, which is widely distributed in estuaries due to the massive river sediment discharge and, thereafter, rapid accumulation. Here, we investigate the EPP response of silty seabed with various initial consolidation degrees using wave flume experiments. We found that (1) in initially liquefied seabed, the EPP magnitude monotonically increases with wavelength, while in initially consolidated seabed, there is a maximal response wavelength which is inversely related to consolidation degree. (2) Furthermore, we found two opposite EPP responses to cyclic surface wave loading under varying seabed conditions in initially liquefied and consolidated seabeds. That is, under the same waves, the EPP magnitude is inversely related to the consolidation degree in initially liquefied seabed, while the EPP magnitude is positively related to the consolidation degree in initially consolidated seabed. In other words, the influence of initial seabed consolidation degree on EPP magnitude behaves like a “√” shaped curve. Our findings provide some implications for further understandings of wave-induced silty seabed liquefaction. Full article

Dielectric dispersion and its interpretation process through clay-bearing shales is very complicated, which makes the saturation evaluation of clay-bearing shales difficult. This paper focuses on developing a model that considers the clay effect on the dielectric dispersion of clay-bearing shales. The effects of water saturation, clay content, and other factors on the dielectric dispersion characteristics of clay-bearing shale rocks are analyzed. By combining a dielectric dispersion response database with backpropagation neural network (BPNN) models, this paper develops a calculation model that can simultaneously calculate five petrophysical parameters, i.e., the water salinity, rock cementation exponent, clay content, clay moisture content, and water saturation. The results indicate that the newly developed dielectric dispersion model can characterize the effects of clay content and clay moisture content. The correlation coefficients of the five parameters can all exceed 99% for each sub-sample database and reach an average of 95.06% in an application case, and the calculation efficiency is also very satisfactory, which significantly outperforms the traditional optimization algorithms. The proposed method provides a practical alternative to traditional inversion approaches for shale evaluation. Full article

To address the technical challenges in dynamic monitoring of grout diffusion patterns under complex geological conditions, in this study, a distributed parallel grouting monitoring system based on electrical resistivity tomography was developed. The system achieves three-dimensional visualization of grout propagation through hardware architecture innovation and the integration of inversion algorithms. At the hardware level, a cascadable distributed data acquisition terminal was designed, employing a dynamic optimization strategy for electrode combinations. This breakthrough overcomes traditional serial acquisition limitations. Algorithmically, a Bayesian estimation-based geological unit merging inversion model was proposed; it dynamically calculates merging thresholds through the noise posterior probability, achieving an improvement of more than 30% in the inversion boundary resolution compared with traditional least squares methods. Numerical simulations and physical experiments demonstrated that dipole arrays with 0.5 m electrode spacing exhibit optimal sensitivity to variations in grout resistivity, accurately capturing electrical response characteristics during diffusion. In practical roadbed grouting applications, the system yielded a grout diffusion radius showing only a 0.3 m deviation from the core sampling verification results, with three-dimensional imaging clearly depicting the diffusion morphology. This system provides reliable technical support for the precise control and quality assessment of underground engineering grouting processes. Full article

Background: Circadian Syndrome (CircS) encompasses a range of cardiometabolic risk factors that contribute to an increased susceptibility to cardiovascular diseases and type 2 diabetes. Understanding the factors that underpin CircS is essential. This study primarily aims to examine the association between hypothyroidism and CircS in adults. A secondary analysis compares this association with that between hypothyroidism and Metabolic Syndrome (MetS). Additionally, the dose–response relationship between serum free thyroxine (FT4) levels and CircS probability is explored. Methods: This cross-sectional study includes 4050 National Health and Nutrition Examination Survey (NHANES) participants (2007–2012). Hypothyroidism was classified into (1) drug-managed, (2) non-drug-managed (NDM) primary, and (3) NDM central hypothyroidism, based on self-reported medication use and serum TSH/FT4 levels. CircS was defined as having ≥5 of its eight components, including MetS criteria, depression, short sleep, and non-alcoholic fatty liver disease. Results: Our results showed that hypothyroidism was significantly associated with CircS (OR: 1.58, 95% CI 1.26–1.98) and MetS (OR: 1.19, 95% CI 1.01–1.42). An inverse, non-linear relationship between serum FT4 levels and the probability of CircS was observed. Conclusions: The results underscore a significant association between hypothyroidism and CircS and MetS, with FT4 levels inversely related to CircS probability. These findings highlight hypothyroidism’s potential role in CircS pathogenesis and prevention. Full article

Conventional wildfire assessment products emphasize regional-scale ignition likelihood and potential spread derived from fuels and weather. While useful for broad planning, they do not directly support boundary-aware, scenario-specific decision-making for localized threats to communities in the Wildland–Urban Interface (WUI). This limitation constrains the ability of fire managers to effectively prioritize mitigation efforts and response strategies for ignition events that may lead to severe local impacts. This paper introduces WUI-BTI—a scenario-based, simulation-driven boundary-threat index for the Wildland–Urban Interface that quantifies consequences conditional on an ignition under standardized meteorology, rather than estimating risk. WUI-BTI evaluates ignition locations—referred to as Fire Amplification Sites (FAS)—based on their potential to compromise the defined boundary of a community. For each ignition location, a high-resolution fire spread simulation is conducted. The resulting fire perimeter dynamics are analyzed to extract three key metrics: (1) the minimum distance of fire approach to the community boundary ($D_{min}$) for non-breaching fires; and for breaching fires, (2) the time required for the fire to reach the boundary ($T_p$), and (3) the total length of the community boundary affected by the fire ($L_c$). These raw outputs are mapped through monotone, sigmoid-based transformations to yield a single, interpretable score: breaching fires are scored by the product of an inverse-time urgency term and an extent term, whereas non-breaching fires are scored by proximity alone. The result is a continuous boundary-threat surface that ranks ignition sites by their potential to rapidly and substantially compromise a community boundary. By converting complex simulation outputs into scenario-specific, boundary-aware intelligence, WUI-BTI provides a transparent, quantitative basis for prioritizing fuel treatments, pre-positioning suppression resources, and guiding protective strategies in the WUI for fire managers, land use planners, and emergency response agencies. The framework complements regional hazard layers (e.g., severity classifications) by resolving fine-scale, consequence-focused priorities for specific communities. Full article

In recent years, unmanned aerial vehicle (UAV) quantitative remote sensing technology has demonstrated significant advantages in fields such as agricultural monitoring and ecological environment assessment. However, achieving the goal of quantification still faces major challenges due to the angle effect. This effect, caused by the bidirectional reflectance distribution function (BRDF) of surface targets, leads to significant spectral response variations at different observation angles, thereby affecting the inversion accuracy of physicochemical parameters, internal components, and three-dimensional structures of ground objects. This study systematically reviewed 48 relevant publications from 2000 to the present, retrieved from the Web of Science Core Collection through keyword combinations and screening criteria. The analysis revealed a significant increase in both the number of publications and citation frequency after 2017, with research spanning multiple disciplines such as remote sensing, agriculture, and environmental science. The paper comprehensively summarizes research progress on the angle effect in UAV quantitative remote sensing. Firstly, its underlying causes based on BRDF mechanisms and radiative transfer theory are explained. Secondly, multi-angle data acquisition techniques, processing methods, and their applications across various research fields are analyzed, considering the characteristics of UAV platforms and sensors. Finally, in view of the current challenges, such as insufficient fusion of multi-source data and poor model adaptability, it is proposed that in the future, methods such as deep learning algorithms and multi-platform collaborative observation need to be combined to promote theoretical innovation and engineering application in the research of the angle effect in UAV quantitative remote sensing. This paper provides a theoretical reference for improving the inversion accuracy of surface parameters and the development of UAV remote sensing technology. Full article

Polymer network-based nanogels (NGs) and microgels (MGs) have emerged as highly versatile platforms for advanced drug delivery, owing to their tunable architecture, biocompatibility, and responsiveness to diverse stimuli. This review presents a comprehensive and structured analysis of NG/MGs, encompassing their classification based on polymer origin, crosslinking mechanisms, composition, charge, stimuli-responsiveness, and structural architecture. We detail synthesis strategies—including inverse microemulsion and radiation-induced polymerization—and highlight key characterization techniques essential for evaluating physicochemical and functional properties. Emphasis is placed on the design-driven applications of NG/MGs in overcoming biological barriers and enabling targeted therapies, particularly in cancer, inflammation, diabetes, and viral infections. Multifunctional NGs integrating therapeutic and diagnostic capabilities (theranostics), as well as emerging platforms for immunotherapy and personalized medicine, are critically discussed. Finally, we address translational challenges and future directions, including scalable manufacturing, regulatory considerations, and integration with smart diagnostics. This review aims to serve as a foundational resource for researchers and clinicians developing next-generation NG/MG-based therapeutics. Full article

Inflammation and immune evasion promote tumorigenesis and progression. Elevated systemic inflammation response index (SIRI) is associated with poor progression-free survival (PFS) and overall survival (OS) in non-small cell lung cancer (NSCLC) patients. Low Human Leukocyte Antigen-DR (HLA-DR) expression on monocytes is also associated with poor prognosis in NSCLC. We aimed to investigate the relationship between these two indicators and develop a predictive model based on them. SIRI was calculated and monocyte HLA-DR expression was measured by flow cytometry in 58 advanced (stage IIIB-IV) NSCLC patients. The log-rank test and multivariate Cox proportional hazard regression model were used for analysis. We confirmed that both high SIRI and low monocyte HLA-DR expression were associated with poor PFS and OS, respectively. We found a significant inverse correlation between SIRI and monocyte HLA-DR expression. In the multivariable Cox regression model, both SIRI and monocyte HLA-DR expression were identified as independent prognostic markers for PFS and OS. We also developed a nomogram for predicting PFS and OS. In conclusion, we demonstrated that the systemic inflammation response of advanced NSCLC patients, estimated by SIRI, was associated with reduced HLA-DR expression on circulating monocytes, which may influence their antigen-presenting function. Consequently, the integration of these two biomarkers into one prognostic model improves short term survival prediction in advanced NSCLC. To our knowledge, this is the first integration of SIRI and HLA-DR into a combined prognostic nomogram. Full article

Worldwide, colorectal cancer (CRC) is the third-most common cancer and the second-leading cause of cancer-related deaths. The inflammatory response initiated by pathogens, environmental and dietary factors, and inflammatory bowel diseases can promote the formation of colorectal tumors. The hygiene hypothesis proposes an inverse link between inflammatory diseases and early childhood exposure to pathogens, with a significant negative correlation between chronic inflammatory diseases and helminth infections. On the other hand, it is also known that several pathogens may influence or even cause the development of cancer, including helminth infections. How do helminth infections influence CRC outcomes? The existing literature presents two different perspectives. Experimental studies in CRC models suggest that helminths may accelerate disease progression and lead to worse outcomes (such as Schistosoma and Trichuris sp.), while others indicate that helminths could help reduce tumor burden (such as Taenia sp.). This review focuses on helminths’ pro- and anti-tumorigenic effects and their derivatives, specifically in CRC. We provide a comprehensive understanding of how helminths impact the macroscopic, histopathological, immunological, and molecular aspects of CRC. Full article

The influence of back-gate (BG) bias on the breakdown voltage (BV) of lateral SOI power devices is investigated using TCAD simulations. A reference SOI-LDMOS structure with BVREF = 73.7 V, optimized based on RESURF and charge-sharing principles, is selected as the baseline for analysis. The BV response to BG bias is shown to fall into three distinct regimes: (i) a linear decrease with increasing magnitude of negative BG bias (−65 V ≤ VG2 ≤ −5 V), (ii) an invariant region where the BV reaches its maximum value (−5 V ≤ VG2 ≤ +10 V), and (iii) a sharp reduction under increasing magnitude of positive BG bias (+10 V ≤ VG2 ≤ +65 V). Qualitative analysis of impact ionization and charge distribution confirms that inversion, depletion, and accumulation conditions in the drift region govern these behaviors. Furthermore, parametric variations in drift doping, drift thickness, and buried oxide thickness reveal significant shifts in the optimum design window, with the buried oxide thickness emerging as a critical factor for ensuring robustness of BV under BG bias. These results provide valuable design guidelines for achieving stable high-voltage performance in practical SOI-LDMOS power devices. Full article

Carbon dioxide (CO₂) is a non-toxic asphyxiant gas that, once released, can pose severe risks, including suffocation, poisoning, frostbite, and even death. As a critical component of carbon capture, utilization, and storage (CCUS) technology, CO₂ pipeline transportation requires reliable leakage detection and precise localization to safeguard the environment, ensure pipeline operational safety, and support emergency response strategies. This study proposes an inversion model that integrates wireless sensor networks (WSNs) with the Gaussian plume model for CO₂ pipeline leakage monitoring. The WSN is employed to collect real-time CO₂ concentration data and environmental parameters around the pipeline, while the Gaussian plume model is used to simulate and invert the dispersion process, enabling both leak source localization and emission rate estimation. Simulation results demonstrate that the proposed model achieves a source localization error of 12.5% and an emission rate error of 3.5%. Field experiments further confirm the model’s applicability, with predicted concentrations closely matching the measurements, yielding an error range of 3.5–14.7%. These findings indicate that the model satisfies engineering accuracy requirements and provides a technical foundation for emergency response following CO₂ pipeline leakage. Full article

Background/Objectives: The associations of statins and testosterone replacement therapy (TTh) with the risk of obesity-related cancers (ORC, breast [BrCa], colorectal [CRC], ovarian, and endometrial cancers) in older women remain poorly understood. This study examined the associations between the use of statins and TTh with risk of ORC and its cancer-specific sites in women aged 65 years and older. Methods: A retrospective cohort study was conducted using 2007–2015 SEER-Medicare data, including 142,772 women aged ≥ 65 years. We identified 52,086 women with incident ORC (BrCa [n = 32,707], CRC [n = 11,070], ovarian [n = 2601], and endometrial [n = 5708] cancers). The primary exposures were use of statins and TTh. Weighted multivariable time-dependent Cox proportional hazards and models were conducted to estimate hazard ratios (HRs) of incident ORC. Results: We found an inverse association of statins with incident [HR, 0.76; 95% CI: 0.74, 0.78], high-grade [HR, 0.75; 95% CI: 0.72, 0.78], and advanced-stage [HR, 0.91; 95% CI: 0.88, 0.95] ORC. Concurrent use of statins and TTh was associated with a reduced incidence of ORC and high-grade ORC. Similar associations were observed with BrCa. Statins were inversely associated with high-grade ovarian cancer and endometrial cancer (incident, high-grade, and advanced-stage). Conclusions: Use of statins was inversely associated with ORC, BrCa, and endometrial cancer (high-grade and advanced-stage) and high-grade ovarian cancer in older women. Concurrent use of statins and TTh was inversely associated with ORC and BrCa and their high-grade disease. Future prospective studies are needed to substantiate these findings, especially with a focus to examine time– and dose–response associations and to identify underlying biological mechanisms through which statins and TTh influence incidence of ORC. Full article

This study systematically investigated the dose–response relationship of resistant starch type 2 (RS2; Hi-maize 260; 0–15 g/L) on gut microbial composition, short-chain fatty acid (SCFA)/gas output, and tryptophan catabolism using an in vitro fermentation model. The highest RS2 concentration (15 g/L) elicited optimal metabolic outcomes, including maximal SCFA production; significant H₂S reduction; and redirected tryptophan metabolism from potentially detrimental indoles toward neuroprotective metabolites. Microbial profiling revealed dose-dependent enrichment of saccharolytic taxa (Bifidobacterium, Lactobacillus) with concomitant suppression of proteolytic pathobionts (e.g., Escherichia-Shigella). Correlation analyses revealed strong positive associations between beneficial microbes and both SCFAs and neuroprotective metabolites, whereas pathogenic taxa correlated inversely with these compounds. Collectively, these findings establish that functionally relevant microbiome modulation requires a sufficiently high, dose-tailored intake of RS2, providing a rational basis for precision dietary strategies aimed at improving host metabolic and gut health. Full article

Understanding the immune response to SARS-CoV-2 vaccination in cancer patients remains a critical priority given their immunocompromised status. In this prospective observational study, we evaluated humoral and cellular immunity across three time points—baseline, post-second dose, and post-booster—in 23 breast cancer patients undergoing active treatment. IgG antibody levels showed a significant increase following vaccination, with a 300-fold rise after the second dose and a 2200-fold increase post-booster, indicating a strong humoral response. CD19⁺ B cells also increased significantly, supporting B cell-mediated activation. Although overall T cell frequencies remained stable, we observed a shift toward memory phenotypes, with decreased naïve CD4⁺ and CD8⁺ T cells and increased central and peripheral memory subsets after the booster. Notably, CD8⁺ TEMRA cells expanded significantly, suggesting cytotoxic memory formation. Correlation analyses linked peripheral memory CD4⁺ T cells with anti-SARS-CoV-2 IgG titers, while CD8⁺ TEMRA cells showed an inverse association. Antigen-specific CD8⁺ T cell response was evaluated using APC-labeled MHC I Dextramer reagents. After the booster, 55.5% of patients developed detectable antigen-specific CD8⁺ T cells, whereas 44.5% did not. Importantly, one patient who failed to develop antigen-specific CD8⁺ T cells experienced a mild SARS-CoV-2 infection, suggesting that the absence of this response may increase susceptibility despite high IgG levels. These findings indicate that antigen-specific CD8⁺ T cell responses and antibody levels may act as complementary but not directly correlated arms of immunity. Microbiota profiling via sPLS-DA suggested weak but distinct microbial signatures associated with immune responsiveness, particularly enrichment of taxa such as Alistipes and Romoutsia among high-antibody responders. These findings emphasize that SARS-CoV-2 vaccination is immunogenic and well tolerated in breast cancer patients under therapy and highlight the need to further explore microbiota–immune interactions to optimize vaccination strategies in oncology. Full article