Search Results (3,071)

Soil salinisation is a critical problem in northern China’s arid and semi-arid irrigated regions, posing a substantial impediment to the sustainable advancement of agriculture in these areas. This research utilises the Donghaixin Irrigation District, located on the southern bank of the Yellow River in Inner Mongolia, as a case study. This study examines the spatial distribution and determinants of soil salinisation through macro-environmental variables and micro-ion composition, integrating regression models and groundwater ion characteristics to elucidate the patterns and causes of soil salinisation systematically. The findings demonstrate that soil salinisation in the study region displays notable spatial clustering, with surface water-irrigated regions exhibiting greater salinisation levels than groundwater-irrigated areas. More than 80% of the land exhibits moderate salinity, predominantly characterised by the ions Cl⁻, HCO₃⁻, and SO₄²⁻. The hierarchy of ion concentration variation with escalating soil salinity is as follows: Na⁺ > K⁺ > SO₄²⁻ > Cl⁻ > Mg²⁺ > HCO₃⁻ + CO₃²⁻ > Ca²⁺. The susceptibility of ions to soil salinisation is ordered as follows: Ca²⁺ > Na⁺ > HCO₃⁻ + CO₃²⁻ > Mg²⁺ > K⁺ > Cl⁻ > SO₄²⁻. In contrast to the ordinary least squares (OLS) model, the geographic weighted regression (GWR) model more effectively elucidates the geographical variability of salinity, evidenced by an adjusted R² of 0.68, particularly in high-salinity regions, where it more precisely captures the trend of observed values. Ecological driving elements such as organic matter (OM), pH, groundwater depth (GD), total dissolved solids (TDS), digital elevation model (DEM), normalised difference vegetation index (NDVI), soil moisture (SM), and potential evapotranspiration (PET) govern the distribution of salinisation. In contrast, anthropogenic activities affect the extent of salinisation variation. Piper’s trilinear diagram demonstrates that Na cations mainly characterise groundwater and soil water chemistry. In areas irrigated by surface water, the concentration of SO₄²⁻ is substantially elevated and significantly affected by agricultural practises; conversely, in groundwater-irrigated regions, Cl⁻ and HCO₃⁻ are more concentrated, primarily driven by evaporation and ion exchange mechanisms. Full article

In recent years, Out-of-Stock (OOS) occurrences have posed a persistent challenge for both retailers and manufacturers. In the context of grocery retail, an OOS event represents a situation where customers are unable to locate a specific product when attempting to make a purchase. This study analyzes the issue from the manufacturer’s perspective. The proposed system, named the “Multi-modal yield eSTimation System of in-prOmotion Commercial Key-ProductS” (MySTOCKS) platform, is a sophisticated multi-modal yield estimation system designed to optimize inventory forecasting for the agrifood and large-scale retail sectors, particularly during promotional periods. MySTOCKS addresses the complexities of inventory management in settings where Out-of-Stock (OOS) and Surplus-of-Stock (SOS) situations frequently arise, offering predictive insights into final stock levels across defined forecasting intervals to support sustainable resource management. Unlike traditional approaches, MySTOCKS leverages an advanced deep learning framework that incorporates transformer models with self-attention mechanisms and domain adaptation capabilities, enabling accurate temporal and spatial modeling tailored to the dynamic requirements of the agrifood supply chain. The system includes two distinct forecasting modules: TR1, designed for standard stock-level estimation, and TR2, which focuses on elevated demand periods during promotions. Additionally, MySTOCKS integrates Elastic Weight Consolidation (EWC) to mitigate the effects of catastrophic forgetting, thus enhancing predictive accuracy amidst changing data patterns. Preliminary results indicate high system performance, with test accuracy, sensitivity, and specificity rates approximating 93.8%. This paper provides an in-depth examination of the MySTOCKS platform’s modular structure, data-processing workflow, and its broader implications for sustainable and economically efficient inventory management within agrifood and large-scale retail environments. Full article

Abnormal epigenetic reprogramming of nuclear-transferred (NT) embryos leads to the limited efficiency of producing cloned animals. Trichostatin A (TSA), a histone deacetylase inhibitor, improves NT embryo development, but its role in histone acetylation in porcine embryos cloned with mesenchymal stem cells (MSCs) is not fully understood. This study aimed to compare the effects of TSA on embryo development, histone acetylation patterns, and key epigenetic-related genes between in vitro fertilization (IVF), NT-MSC, and 40 nM TSA-treated NT-MSC (T-NT-MSC). The results demonstrated an increase in the blastocyst rate from 13.7% to 32.5% in the T-NT-MSC, and the transcription levels of CDX2, NANOG, and IGF2R were significantly elevated in T-NT-MSC compared to NT-MSC. TSA treatment also led to increased fluorescence intensity of acH3K9 and acH3K18 during early embryo development but did not differ in acH4K12 levels. The expression of epigenetic-related genes (HDAC1, HDAC2, CBP, p300, DNMT3a, and DNMT1) in early pre-implantation embryos followed a pattern similar to IVF embryos. In conclusion, TSA treatment improves the in vitro development of porcine embryos cloned with MSCs by increasing histone acetylation, modifying chromatin structure, and enhancing the expression of key genes, resulting in profiles similar to those of IVF embryos. Full article

Sleep–wake disturbances are common in post-COVID-19 syndrome but lack extensive objective characterization. This study evaluated sleep–wake patterns in 31 patients with post-COVID-19 syndrome referred for fatigue and excessive daytime sleepiness (EDS). Assessments included questionnaires (the fatigue severity scale, the Epworth sleepiness scale, and the Beck Depression Index-II), video polysomnography (V-PSG), the multiple sleep latency test (MSLT, n = 15), and actigraphy (n = 29). Patients (70% female, mean age 45 years) had mostly mild acute SARS-CoV-2 infections and were assessed a median of 31 weeks post-infection. Fatigue (fatigue severity scale, median 6.33), sleepiness (the Epworth sleepiness scale, median 15), and depression (Beck depression inventory-II, median 20) scores were elevated. V-PSG showed moderate sleep apnea in 35.5%, increased arousal index in 77.4%, and median sleep stage percentages of NREM1 (12%), NREM2 (37%), NREM3 (19%), and REM (15.8%). MSLT revealed only 13.3% with sleep latencies under 8 min and no sleep-onset REM periods. Actigraphy indicated increased inactivity index in 96.6%, with high variability in time in bed. These findings highlight a polysomnographic and actigraphic profile of increased arousal and clinophilia, alongside moderate sleep apnea and limited objective sleepiness on MSLT. Addressing these multifactorial sleep disturbances is crucial in managing post-COVID-19 syndrome. Full article

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO₂) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits. Full article

During the post-harvest storage of citrus, the flavor of fruit gradually fade. In this study, we investigated the effects of different treatments—control check (CK), heat treatment (HT), salicylic acid treatment (SA), and 1-methylcyclopropene treatment (1-MCP)—on the quality of ‘Newhall’ navel oranges, particularly focusing on sucrose metabolism and related gene expression during storage. Combining the experimental data, we compared the three different treatments with CK. The results showed that the oranges subjected to HT had a significantly higher flavonoid content (26.40 μg) and total phenolic content (19.42 μg) than those used for the CK at the late storage stage, and was also the most effective in slowing the decline in sugar, titratable acid and other indexes, followed by SA, with 1-MCP performing poorly. Quantitative results showed that the three treatments contributed to the increase in sucrose content by elevating the expression of the SPS1 and SPS2 genes involved in sucrose synthesis compared to the CK. However, no clear pattern was observed between the genes involved in sucrose catabolism (SUS1 and SUS3) and sucrose content. These results provided a rationale for the selection of post-harvest treatments to extend the storage life and maintain the quality of ‘Newhall’ navel oranges, with broader implications for the citrus industry. Full article

Background/Objectives: We aimed to explore long-term trajectories of thyroid-stimulating hormone receptor antibody (TRAb) in patients with Graves’ disease (GD) and to identify key factors associated with TRAb normalization. We also investigated whether these trajectories correlate with Graves’ orbitopathy (GO) comorbidity. Methods: We retrospectively reviewed 403 patients with GD who had an initial TRAb level ≥ 1.5 IU/L between 2010 and 2021, monitoring their TRAb levels for at least 3 years. K-means clustering was performed to categorize patients into distinct TRAb change patterns (A, B, C, D). We employed a Cox regression–based time-to-event model, expressing results as “Survival ratio” rather than the conventional Hazard ratio, to reflect the proportion of patients achieving TRAb normalization over time. Key variables included age, sex, initial TRAb, and GO comorbidity. Results: Four unique TRAb patterns emerged, differing primarily in baseline TRAb levels, duration of GD, and treatment approaches. Pattern A demonstrated the highest TRAb normalization rate (96%), whereas Patterns B (80%), C (29%), and D (13%) showed lower probabilities. Regrouping into A vs. BCD further emphasized the distinct normalization profile of Pattern A. A higher “Survival ratio” was observed in female patients and those with baseline TRAb < 6.14 IU/L. In contrast, patients whose TRAb levels were ≥6.14 IU/L frequently exhibited persistently elevated values over a decade. GO comorbidity did not significantly differ among the four patterns. Conclusions: K-means clustering revealed four unique TRAb change patterns in GD, with baseline TRAb (stratified by the median of 6.14 IU/L) and sex emerging as significant predictors of normalization. These findings highlight the importance of early TRAb monitoring and tailored therapeutic strategies, particularly for those with persistently elevated TRAb levels. Full article

Tropospheric aerosols play an important role in the notable warming phenomenon and climate change occurring in the Arctic. The accuracy of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol optical depth (AOD) and the distribution of Arctic AOD based on the CALIOP Level 2 aerosol products and the Aerosol Robotic Network (AERONET) AOD data during 2006–2021 were analyzed. The distributions, trends, and three-dimensional (3D) structures of the frequency of occurrences (FoOs) of different aerosol subtypes during 2006–2021 are also discussed. We found that the CALIOP AOD exhibited a high level of agreement with AERONET AOD, with a correlation coefficient of approximately 0.67 and an RMSE of less than 0.1. However, CALIOP usually underestimated AOD over the Arctic, especially in wet conditions during the late spring and early summer. Moreover, the Arctic AOD was typically higher in winter than in autumn, summer, and spring. Specifically, polluted dust (PD), dust, and clean marine (CM) were the dominant aerosol types in spring, autumn, and winter, while in summer, ES (elevated smoke) from frequent wildfires reached the highest FoOs. There were increasing trends in the FoOs of CM and dust, with decreasing trends in the FoOs of PD, PC (polluted continental), and DM (dusty marine) due to Arctic amplification. In general, the vertical distribution patterns of different aerosol types showed little seasonal variation, but their horizontal distribution patterns at various altitudes varied by season. Furthermore, locally sourced aerosols such as dust in Greenland, PD in eastern Siberia, and ES in middle Siberia can spread to surrounding areas and accumulate further north, affecting a broader region in the Arctic. Full article

This study investigates weekend price gaps in three major stock market indices—the Dow Jones Industrial Average (DJIA), NASDAQ, and Germany’s DAX—from 2013 to 2023, using high-frequency (5 min) data to explore whether gap movements arise from random volatility or reflect systematic market tendencies. We examine 205 weekend gaps in the DJIA, 270 in NASDAQ, and 406 in the DAX. Two principal hypotheses guide our inquiry as follows: (i) whether price movements into the gap are primarily driven by increased volatility and (ii) whether larger gaps are associated with heightened volatility. Employing Chi-square tests for the independence and linear regression analyses, our results show no strong, universal bias towards closing gaps at shorter distances across all three indices. However, at medium-to-large distances, significant directional patterns emerge, particularly in the DAX. This outcome challenges the assumption that weekend gaps necessarily “fill” soon after they open. Moreover, larger gap sizes correlate with elevated volatility in both the DJIA and NASDAQ, underscoring that gaps can serve as leading indicators of near-term price fluctuations. These findings suggest that gap-based anomalies vary by market structure and geography, raising critical questions about the universality of efficient market principles and offering practical insights for risk management and gap-oriented trading strategies. Full article

Cardiovascular diseases are the leading cause of morbidity and mortality worldwide. These conditions, characterized by multifactorial etiology, are associated with arterial stiffness, and adequate sleep serves as a preventive factor. Professionals engaged in night work are at an increased risk of premature vascular aging due to potential disruption of the sleep–wake cycle and sleep restriction. The aim of this study was to assess the relationship between duration of exposure to night work and arterial stiffness in nursing professionals. A total of 63 nursing professionals working rotating shifts participated in the study. Arterial stiffness was measured using oscillometric pulse wave velocity, and sleep–wake patterns were monitored using actigraphy. Path analysis revealed no direct association between duration of night work exposure and arterial stiffness in the professionals studied. However, an increase of 1 standard deviation (SD) in social jet lag duration was significantly associated with a 0.212 SD increase in perceived stress (p = 0.047). Furthermore, an increase of 1 SD in social jet lag duration was significantly associated with a 0.093 SD increase in the highest pulse wave velocity (p = 0.034). Thus, an association was found between increased social jet lag and elevated pulse wave velocity, an independent predictor of higher cardiovascular risk. Full article

The Tibetan Plateau, a critical regulator of the global water cycle and climate system, represents a highly sensitive region to environmental changes, with significant implications for sustainable development. This study focuses on Nam Co Lake, the third largest lake on the Tibetan Plateau, and investigates the hydrochemical evolution of the lake and the driving mechanisms in regard to the lake–river–groundwater system within the Nam Co Basin over the last 20 years. Our findings provide critical insights for sustainable water resource management in regard to fragile alpine lake ecosystems. The hydrochemical analyses revealed distinct temporal patterns in the total dissolved solids, showing an increasing trend during the 2000s, followed by a decrease in the 2010s. Piper diagrams demonstrated a gradual change in the anion composition from the Cl type to the HCO₃ type over the study period. The ion ratio analyses identified rock weathering (particularly silicate, halite, sulfate, and carbonate weathering), ion exchange, and evaporation processes as primary controlling processes, with notable differences between water bodies: while all four weathering processes contributed to the lake’s water chemistry, only halite and carbonate weathering influenced river and groundwater compositions. The comparative analysis revealed more pronounced ion exchange processes in lake water than in river and groundwater systems. Climate change impacts were manifested through two primary mechanisms: (1) enhanced evaporation, leading to elevated ion concentrations and isotopic enrichment; and (2) temperature-related effects on the water chemistry through increased dilution from precipitation and glacial meltwater. Understanding these mechanisms is essential for developing adaptive strategies to maintain water security and ecosystem sustainability. The relationships established between climate drivers and hydrochemical responses provide a scientific basis for predicting future changes and informing sustainable management practices for inland lake systems across the Tibetan Plateau. Full article

While automated-driving technology is advancing rapidly, human-centered research is still in its early stages. Research on negative user responses to automated driving is particularly limited in complex roadway environments such as roundabouts, where driving decisions typically depend on driver judgment and traffic conditions. In these environments, automated-driving vehicles may exhibit unstable behaviors, such as sudden stops or forced intersection entries. Since successful interaction between users and automated systems is critical for widespread adoption, understanding when and how automated driving negatively affects users is essential. This study investigated user psychological responses and corresponding physiological changes during unstable automated-driving situations. Using a virtual environment driving simulator, we compared two scenarios: sensor-only automated driving (A.D(S)), which exhibited unstable driving patterns; and cooperative automated driving (A.D(C)), which achieved more stable performance through infrastructure communication. We analyzed the responses of 30 participants using electromyography (EMG) measurements and pupil diameter tracking, supplemented by qualitative evaluations. Results showed that A.D(S) participants experienced higher levels of frustration during prolonged waiting times compared to A.D(C) participants. In addition, sudden braking events elicited startle responses characterized by pupil dilation and elevated arm-muscle EMG readings. This research advances our understanding of how automated-driving behaviors affect user experience and emphasizes the importance of human factors in the development of automated-driving technologies. Full article

The relative influence of climate and Indigenous cultural burning on past forest composition in southern New England, US, remains debated. Employing varied analyses, this study compared data on Indigenous settlements from over 5000 years before present (YBP) with relative tree abundances estimated from pollen and land survey records. Results suggested that fire-tolerant vegetation, mainly oak (Quercus spp.), was more abundant near Indigenous settlements from 4955 to 205 YBP (i.e., 86–91% fire-tolerant trees), and significantly (p < 0.05) higher from 3205 to 205 YBP; fire-tolerant vegetation was less abundant away from settlements, where it also experienced greater fluctuations. Correlative models showed that warmer temperatures and distance to Indigenous settlement, which are both indicators of fire, were important predictors in the 17th–18th centuries of fire-tolerant tree abundance; soil variables were less important and their relationships with vegetation were unclear. A marked increase in oak abundance occurred above 8 °C mean annual temperature and within 16 km of major Indigenous settlements. Pyrophilic vegetation was most correlated with distance to Indigenous villages in areas with 7–9 °C mean annual temperature, typical of higher latitudes and elevations that usually supported northern hardwoods. Widespread burning in warmer areas potentially weakened relationships between distance and pyrophilic abundance. Indigenous land use imprinted upon warmer areas conducive to burning created patterns in fire-tolerant vegetation in southern New England, plausibly affecting most low-elevation areas. Results imply that restoration of fire-dependent species and of barrens, savannas, and woodlands of oak in southern New England benefit from cultural burning. Full article

The effect of the gut microbiota extends beyond their habitant place from the gastrointestinal tract to distant organs, including the cardiovascular system. Research interest in the relationship between the heart and the gut microbiota has recently been emerging. The gut microbiota secretes metabolites, including Trimethylamine N-oxide (TMAO), short-chain fatty acids (SCFAs), bile acids (BAs), indole propionic acid (IPA), hydrogen sulfide (H₂S), and phenylacetylglutamine (PAGln). In this review, we explore the accumulating evidence on the role of these secreted microbiota metabolites in the pathophysiology of ischemic and non-ischemic heart failure (HF) by summarizing current knowledge from clinical studies and experimental models. Elevated TMAO contributes to non-ischemic HF through TGF-ß/Smad signaling-mediated myocardial hypertrophy and fibrosis, impairments of mitochondrial energy production, DNA methylation pattern change, and intracellular calcium transport. Also, high-level TMAO can promote ischemic HF via inflammation, histone methylation-mediated vascular fibrosis, platelet hyperactivity, and thrombosis, as well as cholesterol accumulation and the activation of MAPK signaling. Reduced SCFAs upregulate Egr-1 protein, T-cell myocardial infiltration, and HDAC 5 and 6 activities, leading to non-ischemic HF, while reactive oxygen species production and the hyperactivation of caveolin-ACE axis result in ischemic HF. An altered BAs level worsens contractility, opens mitochondrial permeability transition pores inducing apoptosis, and enhances cholesterol accumulation, eventually exacerbating ischemic and non-ischemic HF. IPA, through the inhibition of nicotinamide N-methyl transferase expression and increased nicotinamide, NAD+/NADH, and SIRT3 levels, can ameliorate non-ischemic HF; meanwhile, H₂S by suppressing Nox4 expression and mitochondrial ROS production by stimulating the PI3K/AKT pathway can also protect against non-ischemic HF. Furthermore, PAGln can affect sarcomere shortening ability and myocyte contraction. This emerging field of research opens new avenues for HF therapies by restoring gut microbiota through dietary interventions, prebiotics, probiotics, or fecal microbiota transplantation and as such normalizing circulating levels of TMAO, SCFA, BAs, IPA, H₂S, and PAGln. Full article

Utilizing daily data gathered from 63 meteorological stations across Sichuan Province between 1970 and 2022, this study investigates the spatial and temporal shifts in extreme precipitation patterns, alongside the connections between changes in extreme precipitation indices (EPIs) and the underlying drivers, such as geographic characteristics and atmospheric circulation influences, within the region. The response of precipitation to these factors was examined through various methods, including linear trend analysis, the Mann–Kendall test, cumulative anomaly analysis, the Pettitt test, R/S analysis, Pearson correlation analysis, and wavelet transformation. The findings revealed that (1) Sichuan Province’s EPIs generally show an upward trend, with the simple daily intensity index (SDII) demonstrating the most pronounced increase. Notably, the escalation in precipitation indices was more substantial during the summer months compared to other seasons. (2) The magnitude of extreme precipitation variations showed a rising pattern in the plateau regions of western and northern Sichuan, whereas a decline was observed in the central and southeastern basin areas. (3) The number of days with precipitation exceeding 5 mm (R5mm), 10 mm (R10mm), and 20 mm (R20mm) all exhibited a significant change point in 2012, surpassing the 95% significance threshold. The future projections for EPIs, excluding consecutive dry days (CDDs), align with historical trends and suggest a continuing possibility of an upward shift. (4) Most precipitation indices, with the exception of CDDs, demonstrated a robust positive correlation with longitude and a negative correlation with both latitude and elevation. Except for the duration indicators (CDDs, CWDs), EPIs generally showed a gradual decrease with increasing altitude. (5) Atmospheric circulation patterns were found to have a substantial impact on extreme precipitation events in Sichuan Province, with the precipitation indices showing the strongest associations with the Atlantic Multidecadal Oscillation (AMO), the Sea Surface Temperature of the East Central Tropical Pacific (Niño 3.4), and the South China Sea Summer Monsoon Index (SCSSMI). Rising global temperatures and changes in subtropical high pressure in the western Pacific may be deeper factors contributing to changes in extreme precipitation. These insights enhance the understanding and forecasting of extreme precipitation events in the region. Full article