Search Results (1,930)

The ocean heat content (“OHC”)—the heat energy within the ocean integrated to a reference depth—has physical drivers spanning spatial and temporal scales, including seasonality, the El Niño/Southern Oscillation (ENSO), and others. The present article investigates changes in the OHC100 during the period 1994–2020 using GLORYS12 monthly averaged ocean reanalysis. OHC100–ENSO correlation patterns are explored to glean insights about the oceanic mechanisms that facilitate the ENSO’s global teleconnections. After extracting known seasonality and ENSO signals using the Oceanic Niño Index (ONI), the OHC100 residual is analyzed to investigate multidecadal drivers of the OHC100. Lagged ENSO–OHC100 correlations (±12 months) reveal basin-scale oscillations in the sign of ENSO influence likely attributable to Rossby waves. The OHC100 is increasing globally (in total, 2.4 × 10²² J decade⁻¹), with the greatest increases near western boundary currents (WBCs). Some regions are decreasing, notably the Atlantic main development region (MDR) for tropical cyclones (TCs). Correlations and multidecadal variability in the OHC100 tendency (OHCT) and zonal and meridional advections of the OHC100 (ZAO and MAO) support the hypothesis that upper-ocean dynamics mediate ENSO teleconnections as well as exert independent control on OHC100 variability. Local increases in the OHC100 would support the observed TC rapid intensification irrespective of the ENSO phase as the TC-supporting region expands. Full article

Traffic crashes remain a critical public safety issue and are among the leading causes of mortality worldwide. Understanding, analyzing, and forecasting crash trends are essential for implementing effective countermeasures and reducing injury severity. In response to the growing number of crashes and their associated economic and social costs, this study presents a geospatial analytical framework for prioritizing and classifying roadway segments based on crash trends. The framework focuses on a major freeway corridor in the United States, covering a four-year period across 20 counties. This methodology employs spatiotemporal analysis, which integrates both spatial (geographic) and temporal (time-based) dimensions to better understand how crash patterns evolve over time and space. A central component of the analysis is Space–Time Cube (STC) modeling, a three-dimensional GIS-based visualization, and an analytical approach that organizes data into spatial locations (x and y) across a sequence of temporal bins (z-axis) to reveal patterns that may not be evident in a two-dimensional analysis. Additionally, emerging pattern analysis, specifically Emerging Hotspot Analysis (EHA), is used to identify statistically significant trends in crash frequency over time. The results indicate a significant spatial clustering of crashes, with high-risk segments predominantly located in densely populated urban areas with high traffic volumes. Crash hotspots were classified into five distinct categories: persistent, intensifying, new, sporadic, and diminishing, enabling transportation agencies to tailor interventions based on temporal dynamics. The proposed geospatial framework enhances decision making for roadway safety improvements and can be adapted for use in other regional corridors to support infrastructure investment and advance public safety. Full article

This paper proposes a radar mainlobe anti-jamming method based on Space-Time Coding (STC) and Blind Source Separation (BSS). Addressing the performance degradation issue of traditional BSS methods under low Signal-to-Noise Ratio (SNR) and insufficient spatial resolution, this study first establishes the airborne SAR imaging geometric model and the jamming signal mixing model. Subsequently, STC technology is introduced to construct more equivalent phase centers and increase the system’s spatial Degrees of Freedom (DOF). Leveraging the increased DOFs, a JADE-based blind source separation algorithm is then employed to separate the mixed jamming signals. The separation of these signals significantly enhances the anti-jamming capability of the radar system. Simulation results demonstrate that the proposed method effectively improves BSS performance. As compared to traditional BSS schemes, this method provides an additional jamming suppression gain of approximately 10 dB in point target scenarios and about 3 dB in distributed target scenarios, significantly enhancing the radar system’s mainlobe anti-jamming capability in complex jamming environments. This method provides a new insight into radar mainlobe anti-jamming by combining the STC scheme and BSS technology. Full article

The prediction of stock prices is challenging due to their volatility, irregular patterns, and complex time-series structure. Reliably forecasting stock market data plays a crucial role in minimizing financial risk and optimizing investment strategies. However, traditional models often struggle to capture temporal dependencies and extract relevant features from noisy inputs, which limits their predictive performance. To improve this, we developed an enhanced recursive feature elimination (RFE) method that blends the importance of impurity-based features from random forest and gradient boosting models with Kendall tau correlation analysis, and we applied SHapley Additive exPlanations (SHAP) analysis to externally validate the reliability of the selected features. This approach leads to more consistent and reliable feature selection for short-term stock prediction over 1-, 3-, and 7-day intervals. The proposed deep learning (DL) architecture integrates a temporal convolutional network (TCN) for long-term pattern recognition, a gated recurrent unit (GRU) for sequence capture, and multi-head attention (MHA) for focusing on critical information, thereby achieving superior predictive performance. We evaluate the proposed approach using daily stock price data from three leading companies—HDFC Bank, Tata Consultancy Services (TCS), and Tesla—and two major stock indices: Nifty 50 and S&P 500. The performance of our model is compared against five benchmark models: temporal convolutional network (TCN), long short-term memory (LSTM), GRU, Bidirectional GRU, and a hybrid TCN–GRU model. Our method consistently shows lower error rates and higher predictive accuracy across all datasets, as measured by four commonly used performance metrics. Full article

 COVID-19 infection is often accompanied by psychological symptoms, which may persist long after the end of the infection (long COVID). The symptoms include fatigue, cognitive impairment, and anxiety. The reason for these long-term effects is currently unclear. Therapeutic approaches have included cognitive rehabilitation therapy, physical activity, and serotonin reuptake inhibitors (SSRIs) if depression co-exists. The neuropsychological evaluation of subjects with suspected cognitive issues is essential for the correct diagnosis. Most of the COVID-19 studies used the Montreal Cognitive Assessment (MoCA) or the Mini Mental State Examination (MMSE). However, MoCA scores can be confusing if not interpreted correctly. For this reason, we have developed an original technique to map cognitive domains and motor performance on various brain areas in COVID-19 patients aiming at improving the follow-up of long-COVID-19 symptoms. To this end, we retrospectively reanalyzed data from a cohort of 40 patients hospitalized for COVID-19 without requiring intubation or hemodialysis. Cognitive function was tested during hospitalization and six months after. Global cognitive function and cognitive domains were retrieved using MoCA tests. Laboratory data were retrieved regarding kidney function, electrolytes, acid–base, blood pressure, TC score, and P/F ratio. The dimensionality of cognitive functions was represented over cortical brain structures using a transformation matrix derived from fMRI data from the literature and the Cerebroviz mapping tool. Memory function was linearly dependent on the P/F ratio. We also used the UMAP method to reduce the dimensionality of the data and represent them in low-dimensional space. Six months after hospitalization, no cases of severe cognitive deficit persisted, and the number of moderate cognitive deficits reduced from 14% to 4%. Most cognitive domains (visuospatial abilities, executive functions, attention, working memory, spatial–temporal orientation) improved over time, except for long-term memory and language skills, which remained reduced or slightly decreased. The Cerebroviz algorithm helps to visualize which brain regions might be involved in the process. Many patients with COVID-19 continue to suffer from a subclinical cognitive deficit, particularly in the memory and language domains. Cerebroviz’s representation of the results provides a new tool for visually representing the data.  Full article

An extensive study on the interactions between O-phosphorylethanolamine (PEA) and O-phosphorylcholine (PPC), Cu²⁺ and Zn²⁺, is thoroughly described. The formation constants were determined at different temperatures (15 ≤ t/°C ≤ 37) and ionic strengths (0.15 ≤ I/mol L⁻¹ ≤ 0.97) by potentiometric titrations. For the Zn²⁺-PEA/-PPC systems, speciation models were also confirmed by ¹H NMR titrations at t = 25 °C and I = 0.15 mol L⁻¹ in NaCl. Sequestering abilities were calculated under different temperatures and physiological conditions. Density Functional Theory (DFT) calculations along with enhanced sampling of the conformational space were performed aimed to better elucidate the Cu²⁺-, Zn²⁺- PEA/PPC molecular interactions and their relative stabilities. Overall, both experiments and computer simulations showed that the complex species involved in the Cu²⁺–PEA system exhibited a significant and selective stability, particularly in conditions simulating cerebrospinal fluid. While the binding molecular mechanisms were elucidated via DFT supplemented by automized conformational search, the computational binding energies trend qualitatively follows the experimental logK behavior across the Cu²⁺-, Zn²⁺- PEA/PPC complexes. These results highlight the potential physiological role of PEA in modulating free copper levels and regulating its redox activity in pathological conditions, such as Wilson’s Disease (WD). Full article

Skin color is a crucial phenotypic trait in poultry that influences consumer preference, market value, and breed identification. However, the mechanisms underlying skin color variation in Lingshan chickens remain poorly understood. This study aimed to elucidate the physiological, metabolic, and microbial characteristics associated with skin color differences in male Lingshan chickens. A total of 210 castrated male Lingshan chickens were categorized into white-shanked (WS), yellow-shanked (YS), and red-shanked (RS) groups based on the Roche color fan scores. The results showed that chickens in the YS and RS groups exhibited significantly higher body weights and pigmentation levels in the shank, breast, and abdominal skin compared to those in the WS group (p < 0.05). Serum concentrations of triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and very-low-density lipoprotein (VLDL) were markedly elevated in RS chickens. Additionally, carotenoid profiles revealed higher deposition of lutein and β-carotene in the skin and adipose tissues of YS and RS birds. Gene expression analysis indicated differential regulation of carotenoid transport and metabolism-related genes among groups. Furthermore, 16S rRNA sequencing of cecal microbiota revealed significant compositional shifts in microbial communities associated with shank pigmentation. Collectively, these findings suggest that differences in shank color in Lingshan chickens are closely linked to lipid metabolism, carotenoid transport, and gut microbiota composition. This study provides novel insights into the biological mechanisms driving skin pigmentation, offering valuable implications for breeding and functional trait selection in indigenous chicken populations. Full article

Titanium dioxide nanotubes (TiO₂ NTs) decorated with lead sulfide nanoparticles (PbS NPs) were synthesized using the Successive Ionic Layer Adsorption and Reaction (SILAR) method at different number (n) of cycles (where n = 3, 5, and 8) and evaluated for tetracycline (TC) photodegradation under UV light. PbS NPs/TiO₂ NTs heterojunctions prepared with 5 SILAR cycles showed optimal photocatalytic activity. Also, under optimized conditions, pure TiO₂ NTs achieved complete TC photodegradation (99%) within 5 h under UV irradiation, with a proposed degradation mechanism based on holes (h⁺) and hydroxyl radicals (•OH) as dominant reactive species. Full article

Crop productivity can be affected by biotic and abiotic stressors, and plant growth-promoting bacteria (PGPB) from the genera Bacillus and Burkholderia have the potential to maintain fruit yield and quality, as these bacteria can promote plant growth by solubilizing nutrients, fixing atmospheric nitrogen, producing phytohormones, and exhibiting antagonistic activity against pathogens. This study aimed to evaluate the effects of inoculating plants with Bacillus subtilis and Burkholderia seminalis on their morphological characteristics, fruit technological attributes and yield of common cherry tomatoes (Solanum lycopersicum L.) subjected to induced water deficit. The study was arranged on a split-plot randomized block design, with four water replacement levels (40%, 60%, 80% and 100% of crop evapotranspiration, ETc) and three inoculation treatments (Bacillus subtilis ATCC 23858, Burkholderia seminalis TC3.4.2R3 and non-inoculation). Data were subjected to analysis of variance using the F-test and compared using Tukey’s test (p < 0.05) and multivariate statistics from principal component analysis. Inoculation with Burkholderia seminalis increased the plant fresh and dry shoot and root mass, as well as root volume. Inoculation with Bacillus subtilis increased carotenoid and chlorophyll b contents. Both inoculations enhanced leaf water content in plants experiencing severe water deficit (40% of ETc). The use of these strains as PGPB increased the fruit soluble solids content. Higher productivity in inoculated plants was achieved through a greater number of fruits per cluster, despite the individual fruits being lighter. Treatments with higher water replacement levels resulted in greater yield. Inoculations showed biotechnological potential in mitigating water deficit in cherry tomatoes. Full article

The widespread detection of antibiotics in aquatic environments has raised significant concerns due to their potential risks to human health. Photocatalytic technology has emerged as an effective approach for antibiotic degradation, with cadmium sulfide (CdS) being a promising semiconductor photocatalyst. However, the practical application of CdS is limited by its tendency to aggregate, which reduces the number of accessible active sites and consequently lowers its photocatalytic degradation efficiency. In this study, a series of GO/CdS composites were synthesized via a two-step hydrothermal method for the efficient degradation of tetracycline (TC) antibiotics in aquatic solutions. Results showed that GO/CdS can effectively remove TC via photocatalytic degradation rather than adsorption. The optimized photocatalytic composite achieved a 95% degradation of TC (20 mg L⁻¹) under 60 min of illumination. The corresponding rate constant (k) was 2.87 times higher than that of pristine CdS. After three cycles, the degradation rate still achieved 93%. Moreover, the composite exhibited a wide pH tolerance range from pH 2 to 10, with a removal rate of over 89%. Superoxide radicals (·O₂⁻) were identified as the primary reactive species responsible for TC degradation, and three possible TC degradation pathways were proposed. This work extends the application of GO and offers a novel strategy for constructing GO-based composite materials, providing valuable insights into the mechanisms and pathways of antibiotic degradation. Full article

Frequent and severe droughts intensify water scarcity in arid and semi-arid regions, creating an urgent need for alternative water resources in agriculture. Treated wastewater (TWW) has emerged as a sustainable option; however, its long-term use may alter soil properties and pose risks if not carefully managed. This study tested the hypothesis that long-term TWW irrigation increases soil salinity, alters fertility, and affects microbial quality, with rainfall partially mitigating these effects. Soil samples (n = 96 at each time point) were collected from two calcareous soils in Jordan, silt loam (Mafraq) and silty clay loam (Ramtha), under four treatments (control and 2, 5, and 10 years of TWW irrigation) at three depths (0–30, 30–60, and 60–90 cm). Sampling was conducted at two intervals, before and after rainfall, to capture the seasonal variation. Soil indicators included the pH, electrical conductivity (EC), sodium (Na⁺), chloride (Cl⁻), calcium (Ca²⁺), magnesium (Mg²⁺), exchangeable sodium percentage (ESP), sodium adsorption ratio (SAR), organic matter (OM), total nitrogen (TN), and microbial parameters (total coliforms (TC), fecal coliforms (FC), and Escherichia coli). Data were analyzed using a linear mixed-effects model with repeated measures, and significant differences were determined using Tukey’s Honest Significant Difference (HSD) test at p < 0.05. The results showed that rainfall reduced Na⁺ by 70%, Cl⁻ by 86%, EC by 73%, the ESP by 28%, and the SAR by 30%. Furthermore, the TC and FC concentrations were diminished by almost 96%. Moderate TWW irrigation (5 years) provided the most balanced outcomes across both sites. This study provides one of the few long-term field-based assessments of TWW irrigation in semi-arid calcareous soils of Jordan, underscoring its value in mitigating water scarcity while emphasizing the need for monitoring to ensure soil sustainability. Full article

Background: Taekwondo (TKD) and Tai Chi (TC) are promising interventions for enhancing health and physical function in older people, yet few studies have compared their effects across multiple domains. This study aimed to compare the effects of TKD versus TC on health status in independent older women. Methods: A randomized controlled trial was conducted with two parallel groups: TKD (n = 11) and TC (n = 10). Both groups trained three times per week for 8 weeks. Pre- and post-intervention assessments included anthropometry, submaximal CPX, 2-min step test, Timed Up-and-Go (TUG), isometric mid-thigh pull (IMTP), maximal isometric handgrip strength (MIHS), 30 s chair stand, 30 s arm curl, sit-and-reach, and back scratch. Results: Compared with TC, the TKD group showed significantly greater improvements in several cardiorespiratory outcomes, including VO₂ at VT1 and VT2, power output, VO₂/HR, OUES, and VE/VCO₂ slope (p < 0.05 to p < 0.001; d = 0.69–1.29). TKD participants also exhibited superior gains in maximal and relative IMTP, MIHS, relative MIHS, 30 s arm curl repetitions, and TUG performance (p < 0.05 to p < 0.001; d = 0.61–1.26). Both groups improved similarly in the 30 s chair stand test (p < 0.05). Flexibility outcomes diverged, with TKD improving sit-and-reach and TC showing greater gains in the back scratch test (p < 0.05). Conclusions: TKD was more effective than TC in improving cardiorespiratory fitness, muscle strength, and balance in older women and may represent a valuable health-oriented training strategy for this population. Full article

Community detection is a fundamental task for understanding network structures, crucial for identifying groups of nodes with close connections. However, existing methods generally treat all connections in networks as equally important, overlooking the inherent inequality of connection strengths in social networks, and often require large quantities of labeled data. To address these challenges, we propose a few-shot community detection framework, Strong Triadic Closure Community Detection with Prompt (STC-CDP), which combines the Strong Triadic Closure (STC) principle, Graph Neural Networks, and prompt learning. The STC principle, derived from social network theory, states that if two nodes share strong connections with a third node, they are likely to be connected with each other. By incorporating STC constraints during the pre-training phase, STC-CDP can differentiate between strong and weak connections in networks, thereby more accurately capturing community structures. We design an innovative prompt learning mechanism that enables the model to extract key features from a small number of labeled communities and transfer them to the identification of unlabeled communities. Experiments on multiple real-world datasets demonstrate that STC-CDP significantly outperforms existing state-of-the-art methods under few-shot conditions, achieving higher F1 scores and Jaccard similarity particularly on Facebook, Amazon, and DBLP datasets. Our approach not only improves the precision of community detection but also provides new insights into understanding connection inequality in social networks. Full article

Background/Objectives: In a previous study, we observed significantly prolonged hepatic and pulmonary first-pass transit times (TTs) for ^99mTc-pertechnetate absorbed through the colorectal mucosa during per-rectal portal scintigraphy (PRPS). This decrease in radiotracer flow velocity was not seen when ^99mTc-pertechnetate was administered into the spleen during trans-splenic portal scintigraphy or injected intravenously in radionuclide angiocardiography. We hypothesized that ^99mTc-pertechnetate, an artificial compound, is recognized during colorectal absorption as a potentially hazardous chemical (PHC), with its hepatic and pulmonary slowdown aiding elimination. A similar sudden decrease in portal flow occurs during early metastasis of colorectal cancer (CRC), as shown by a pathological rise in the hepatic perfusion index. We aimed to study the hepatic and pulmonary vasoactive responses triggered by PHCs after they pass through the gut mucosa and evaluate the potential activation of this mechanism in early CRC metastasis. Methods: We measured transit times to determine whether hepatic and pulmonary vasoconstriction occur in response to radiotracers administered at different sites. We performed PRPS with in vivo ^99mTc-labelled RBC to evaluate the liver transit time (LTT) and right heart to liver circulation time (RHLT). Liver angioscintigraphy (LAS) was used to assess RHLT following the intravenous injection of ^99mTc-pertechnetate and ^99mTc-HDP (hydroxyethylene-diphosphate). Lower rectum transmucosal dynamic scintigraphy (LR-TMDS) was conducted to measure RHLT of ^99mTc-pertechnetate delivered into the lower rectum submucosa. LAS was performed to assess LTT for ^99mTc-HDP intravenously injected and delivered to the gut mucosa via arterial flow. Results: In healthy volunteers, PRPS showed notably increased LTT, ranging from 23.5 to 25.5 s, and RHLT (between 39.5 and 42.5 s) for in vivo ^99mTc-labelled RBC. Significantly lower RHLT values ranging from 9 to 13.5 were observed for ^99mTc-pertechnetate and ^99mTc-HDP administered intravenously during LAS, as well as for ^99mTc-pertechnetate at LR–TMDS (between 12 and 15 s). The LTT assessed at LAS for ^99mTc-HDP ranged from 22 to 27 s. Conclusions: An intense vasoconstriction occurs in the liver and lungs in response to substances recognized by the body as PHCs when they pass through the gut mucosa, aiding their elimination. Full article

To express and purify staphylococcal enterotoxin M (SEM) using immobilized metal affinity chromatography (IMAC), a signal peptide-truncated (ΔNsp) wild-type SEM (SEM_WT) was N-terminally fused in pET-28a(+) to a polyhistidine tag (His_6×-) and thrombin cleavage site (TCS; LVPR↓GS), generating His_6×-TCS-ΔNspSEM_WT. Unexpectedly, 4 °C desalting reduced the fusion protein’s molecular weight by ~2.0 kDa on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). N-terminal sequencing and mass spectrometry identified cleavage specifically at the arginine (R) and glycine (G) peptide bond (R–G bond) within the TCS motif. AlphaFold 3 revealed an exposed serine protease catalytic triad: histidine 172, serine 178, and aspartic acid 212 (H₁₇₂/S₁₇₈/D₂₁₂) in the β-grasp domain, suggesting intrinsic thrombin-like activity (TLA). Sequential IMAC and size-exclusion high-performance liquid chromatography (SE-HPLC) purification eliminated contaminant concerns, while chromogenic substrate S-2238 (S-2238) assays demonstrated increasing specific activity and purification fold, supporting intrinsic TLA. Critically, the mutation of serine at position 178 to alanine (His_6×-TCS-ΔNspSEM_S178A) abolished TLA but preserved the secondary/tertiary structure, confirming the activity’s origin within the wild-type construct. Molecular dynamics (MD) simulations probed the atomistic mechanism for specific R–G bond cleavage. This work establishes a foundation for understanding ΔNspSEM_WT’s TLA. Full article