Search Results (12,239)

Plastic pollution, particularly in marine environments, has become a major global concern; therefore, monitoring and controlling these contaminants is essential to safeguard ecosystem integrity and human health. This study evaluates the ability of Posidonia oceanica spheroids to incorporate and retain plastic debris, with a particular focus on microplastics (MPs). A total of 1300 spheroids were collected along the Latium coast (Central Italy); among these, 454 (34.9%) contained plastic debris, with an average of 3.1 items per spheroid. Overall, 1415 plastic items were extracted and identified. Based on size classification, 48.7% were microplastics, 29.6% mesoplastics, and 21.9% macroplastics. Plastic items mainly consisted of filaments (40.9 ± 12.6%) and fibers (21.5 ± 5.2%). Eleven different colors were recorded, with white (28.8 ± 9.1%), transparent (13.4 ± 6.0%), and black (11.1 ± 6.8%) being the most frequent. A strong correlation was observed between the number of plastic items contained in the spheroids and proximity to wastewater treatment plants, which are known sources of synthetic fibers. Fourier transform infrared spectroscopy (FTIR) identified a total of 15 polymer materials, with nylon (18.2 ± 11.0%) and polyethylene terephthalate (PET; 17.3 ± 7.2%) being the most abundant. Structural alterations observed in FTIR spectra, together with carbonyl index values, indicate that most MPs are of secondary origin, resulting from prolonged environmental degradation. These results demonstrate that P. oceanica spheroids effectively promote plastic trapping and highlight their potential as a simple and cost-effective monitoring tool for marine plastic pollution. Full article

Background: Hashimoto’s thyroiditis (HT) is the result of a complex interplay between genetic, environmental, and epigenetic factors. The role of cellular and humoral immunity in the pathogenesis of the disease is well-established. Inflammatory infiltration of T and B lymphocytes is a key feature identified on ultrasound examination. The lack of data on the effect of L-thyroxine (LT-4) doses on the level of anti-TPO and anti-TG antibodies in Hashimoto’s thyroiditis and the relationship with anthropometric measurements resulted in the desire to fill this niche. Methods: A total of 70 Caucasian patients diagnosed with Hashimoto’s thyroiditis within the past two years were examined. The participants were divided into three groups based on their L-thyroxine dosage (≤50, 50–100, >100 μg). Results: The results revealed no correlation between the dosage of L-thyroxine and anthropometric measurements (age, height, body weight, and body fat content). No correlation was identified between the levels of anti-TPO and anti-TG and the dose of L-thyroxine in patients with Hashimoto’s thyroiditis. Conclusions: The mechanism regulating the levels of anti-TPO and anti-TG appears to be associated with a more advanced thyroid inflammation and disease process. Long-term observation of patients would be advisable. We present evidence of no effect of hormone dose on antibody levels in Hashimoto’s thyroiditis. Regardless of disease severity, immune regulation remains outside the scope of hormonal regulation. Full article

With the increasingly prominent demand for building energy efficiency and occupant-centric design, accurate and reliable personal thermal comfort models (PTCMs) are playing an important role in various residential and energy applications (e.g., building energy-saving design, indoor environmental regulation, and health and well-being improvement). In recent years, data-driven and artificial intelligence (AI) technologies have attracted considerable attention in the field of personal thermal comfort modeling. This study systematically reviews recent progress in data-driven personal thermal comfort modeling, emphasizing contact-based and non-contact data collection ways, correlation analysis of feature data, modeling methods based on machine learning and deep learning. Considering the high cost and limited scale of collection experiments, as well as noise, ambiguity, and individual differences in subjective feedback, special attention is put on the data-efficient thermal comfort modeling in data scarcity scenarios using a transfer learning (TL) strategy. Characteristics and suitable occasions of four transfer methods (model-based, instance-based, feature-based, and ensemble methods) are summarized to provide a deep perspective for practical applications. Furthermore, integration of PTCM into building environment control is summarized from aspects of the integration framework, modeling method, control strategy, actuator, and control effect. Performance of the integrated systems is analyzed in terms of improving personal thermal comfort and promoting building energy efficiency. Finally, several challenges faced by PTCMs and future directions are discussed. Full article

In recent years, the rapid development of commercial satellite projects, such as low-Earth orbit (LEO) communication and remote sensing constellations, has driven the satellite industry toward low-cost, rapid development, and large-scale deployment. Commercial off-the-shelf (COTS) components have been widely adopted across various commercial satellite platforms due to their advantages of low cost, high performance, and plug-and-play availability. However, the space environment is complex and hostile. COTS components were not originally designed for such conditions, and they often lack systematically flight-verified protective frameworks, making their reliability issues a core bottleneck limiting their extensive application in critical missions. This paper focuses on COTS solid-state drives (SSDs) onboard the Jilin-1 KF satellite and presents a full-lifecycle reliability practice covering component selection, system design, on-orbit operation, and failure feedback. The core contribution lies in proposing a full-lifecycle methodology that integrates proactive design—including multi-module redundancy architecture and targeted environmental stress screening—with on-orbit data monitoring and failure cause analysis. Through fault tree analysis, on-orbit data mining, and statistical analysis, it was found that SSD failures show a significant correlation with high-energy particle radiation in the South Atlantic Anomaly region. Building on this key spatial correlation, the on-orbit failure mode was successfully reproduced via proton irradiation experiments, confirming the mechanism of radiation-induced SSD damage and providing a basis for subsequent model development and management decisions. The study demonstrates that although individual COTS SSDs exhibit a certain failure rate, reasonable design, protection, and testing can enhance the on-orbit survivability of storage systems using COTS components. More broadly, by providing a validated closed-loop paradigm—encompassing design, flight verification and feedback, and iterative improvement—we enable the reliable use of COTS components in future cost-sensitive, high-performance satellite missions, adopting system-level solutions to balance cost and reliability without being confined to expensive radiation-hardened products. Full article

Background: Population aging has increased attention on the quality of life and successful aging of older adults. Objective: To examine urban–rural differences in subjective quality of life and self-rated successful aging, explore associations with psychosocial factors, and identify predictors of successful aging, including potential moderating effects of place of residence and chronic illness. Methods: A cross-sectional study was conducted among 403 adults aged ≥ 60 years in Eastern Croatia. Measures included a sociodemographic questionnaire, the Self-assessment of Successful Aging Scale (SSAS), and the Personal Wellbeing Index (PWI). Data were analyzed using nonparametric tests (Mann–Whitney U, Spearman’s correlation), linear regression, and moderation analyses. Significance was set at p < 0.05. Ethical approval was obtained (Class: 602-01/24-12/02; IRB: 2158/97-97-10-24-36). Results: Rural participants reported lower PWI scores (p = 0.005) and self-rated successful aging (p < 0.001) than urban participants. Active community involvement was positively associated with quality of life (Rho = 0.46; p < 0.001), whereas regret about missed opportunities and past actions was negatively associated (Rho = −0.20; p < 0.01). Regression analyses explained 48.3% of the variance in SSAS, with higher PWI scores being strongly associated with higher SSAS scores, and rural residence and chronic illness being associated with lower SSAS scores. Moderation analyses indicated that the association between PWI and SSAS was consistent across different environmental contexts and in the presence of illness. Conclusions: Older adults living in rural areas reported lower quality of life and self-rated successful aging compared with those in urban and suburban areas, with subjective wellbeing emerging as a key predictor. Promoting social engagement and addressing psychosocial barriers may enhance successful aging, particularly in rural populations. Findings suggest that social engagement and psychosocial support are associated with higher level of perceived successful aging, indicating potential areas for future community-based or healthcare interventions. Full article

An innovative dispersive liquid–liquid microextraction technique utilizing a solid dispersion was established for the quantification of triazine herbicides in environmental water samples. Naturally derived monoterpenoids were utilized as eco-friendly extraction solvents, markedly decreasing the reliance on harmful extraction solvents. A small amount of Pop Rocks candy served as a solid dispersant; the rapid release of carbon dioxide promoted the generation of fine monoterpenoid droplets, effectively replacing conventional hazardous liquid dispersants. The solidification technique of floating organic droplets facilitated the effective phase separation of monoterpenoids from aqueous samples, thereby obviating the need for centrifugation. Triazine herbicides exhibited good linearity within the concentration range of 0.008–0.8 mg/L with correlation coefficients above 0.99 and detection limits of 0.002 mg/L. The proposed method was effectively implemented on surface and groundwater samples, attaining recoveries between 86.4% and 98.0%. Molecular docking analysis suggests a spontaneous binding between the monoterpenoid and triazine herbicides. A comprehensive green assessment utilizing two evaluation tools confirmed the excellent environmental performance of the method. This technique offers superior greenness and simplicity compared with conventional techniques, demonstrating strong potential for application in the environmental analysis of pesticide residues. Full article

This study assessed the accuracy of the EXERGEN TAT-5000 temporal scanner (T_EXERGEN) (EXERGEN, Watertown, MA, USA) for estimating core body temperature (T_CORE) during rest, progressive cycling exercise, and post-exercise recovery in a hot environment. Fourteen healthy adults (7 men and 7 women) completed a laboratory protocol consisting of 10 min of rest, 60 min of cycling, and 25 min of recovery at an ambient temperature of 32 °C and a relative humidity of 60%. Gastrointestinal temperature (T_Gi), measured via telemetry capsules, served as the criterion method. A total of 5376 paired measurements were analyzed. Throughout the protocol, T_EXERGEN systematically underestimated T_CORE compared with T_Gi, with mean biases between −0.35 °C and −1.15 °C. The overall 95% confidence intervals ranged from ±0.91 to ±1.43 °C, demonstrating poor precision. Limits of agreement were wide (from −2.00 to 0.87 °C), and concordance correlation coefficients (CCC) indicated poor agreement (CCC < 0.90 in all conditions). The underestimation was more pronounced during exercise and recovery, when T_CORE remained high according to T_Gi but decreased according to T_EXERGEN. These results indicate that T_EXERGEN does not monitor T_CORE accurately under heat stress or during rapid metabolic changes. Therefore, the use of this device is not recommended during and after exercises under environmental heat stress. Full article

Coastal lakes are highly vulnerable transitional systems in which sedimentological processes and benthic ecological conditions jointly control contaminant accumulation and preservation, particularly in densely urbanized settings. A robust understanding of the physical and ecological characteristics of bottom sediments is therefore essential for the correct interpretation of contaminant distributions, including those of potentially toxic metals. In this study, an integrated sedimentological–ecological approach was applied to Lake Ganzirri, a Mediterranean shallow coastal lake located in northeastern Sicily (Italy), where recent investigations have identified localized heavy metal anomalies in surface sediments. Sediment texture, petrographic and mineralogical composition, malacofaunal assemblages, and lake-floor morpho-bathymetry were systematically analysed using grain-size statistics, faunistic determinations, GIS-based spatial mapping, and bivariate and multivariate statistical methods. The modern lake bottom is dominated by bioclastic quartzo-lithic sands with low fine-grained fractions and variable but locally high contents of calcareous skeletal remains, mainly derived from molluscs. Sediments are texturally heterogeneous, consisting predominantly of coarse-grained sands with lenses of very coarse sand, along with gravel and subordinate medium-grained sands. Both sedimentological features and malacofaunal death assemblages indicate deposition under open-lagoon conditions characterized by brackish waters and relatively high hydrodynamic energy. Spatial comparison between sedimentological–ecological parameters and previously published heavy metal distributions reveals no significant correlations with metal hotspots. The generally low metal concentrations, mostly below regulatory threshold values, are interpreted as being favoured by the high permeability and mobility of coarse sediments and by energetic hydrodynamic conditions limiting fine-particle accumulation. Overall, the integration of sedimentological and ecological data provides a robust framework for interpreting contaminant patterns and offers valuable insights for the environmental assessment and management of vulnerable coastal lake systems, as well as for the understanding of modern lagoonal sedimentary processes. Full article

Fermented grains (FGs) for Chinese strong-flavor Baijiu (CSFB) serve as both microbial habitats and flavor sources, yet the correlations among fungal communities, physicochemical properties, and volatiles during long-term fermentation remain insufficiently understood. To address this gap, this study employed Illumina HiSeq high-throughput sequencing, physicochemical analysis, and GC-MS for systematic investigation. Fermentation was divided into early, middle, and late stages based on FGs’ physicochemical dynamics and eukaryotic microbial diversity. A total of 9 fungal phyla and 195 genera were detected, with 12 dominant genera (e.g., Thermoascus, Aspergillus, Kazachstania). Forty-seven volatiles were identified, showing increasing diversity and richness. Redundancy Analysis revealed total acids exerted the most significant effect on dominant fungal succession, while network analysis screened 10 key genera (e.g., Mortierella, Trichoderma) pivotal for community structure. Additionally, Trichoderma, Fusarium and other genera correlated with important flavors like 1-butanol and 1-hexanol. This study clarifies the complex interactions in FGs, provides theoretical support for CSFB quality improvement via biofortification or environmental control, and offers a reference for revealing the ecological mechanisms underlying FG microbial community assembly. Full article

Automatic Milking Systems (AMSs) enable the continuous recording of production, milkability, behavioral, and physiological traits, offering new opportunities for genetic evaluation in dairy cattle. This study aimed to estimate variance components and genetic parameters for milk yield-related traits, milking efficiency traits, rumination time (RT), and daily average milk temperature (MTEMP) using AMS-derived data from 1252 Holstein cows. 65,475 weekly records from a single commercial herd were analyzed using repeatability animal models fitted by restricted maximum likelihood. Heritability estimates were moderate to high for milking time (MT) (0.31), milking speed (MS) (0.38), RT (0.30), and MTEMP (0.28), whereas behavioral traits such as number of milking (NoM) (0.26) and number of refused (NoREF) (0.11) showed lower but meaningful heritabilities. Repeatability was highest for MT and MS (0.77 and 0.79), indicating consistent milking performance across repeated records. MTEMP demonstrated clear seasonal variation, increasing in warmer periods and decreasing during colder months, indicating sensitivity to environmental conditions. Genetic correlations among traits revealed both favorable and unfavorable associations; however, several estimates were associated with relatively large standard errors and should therefore be interpreted with caution. The inclusion of MTEMP as a proxy physiological trait derived from AMS data showed measurable genetic variation, although its biological interpretation requires careful consideration. Overall, the results suggest that AMS-derived phenotypes may contribute useful information for genetic studies of functional traits, but the single-herd structure, limited pedigree depth, and data aggregation procedures restrict the generalizability of the findings. Further multi-herd and genomics-based studies are required to validate these results and assess their applicability in breeding programs. Full article

Sub-Saharan Africa has the potential to achieve sustainable development through facilitating green transition projects, leveraging the revenue generated from its abundant natural resources. However, the resource curse hypothesis suggests that developing nations often face problems with corruption that hinder economic development in these countries. The present study aims to investigate how environmental sustainability can be advanced in Sub-Saharan Africa using revenue from natural resources in the presence of green financial technology and clean energy. Therefore, data for Sub-Saharan Africa from 2000 to 2023 are employed in the analysis. The analysis of these data is undertaken with the ‘Method of Moments Quantile Regression’ technique, and the ‘Panel Correlated Standard Errors’ is used for robustness checks. The key findings presented in this research depict the importance of natural resource rents in supporting sustainable environments in Sub-Saharan Africa. Therefore, the revenue from natural resources can be used to support green transition projects in developing nations with high natural resource endowments. Moreover, renewable energy and green finance foster a reduction in ecological footprint, hence supporting environmental sustainability. Consequently, technological innovation and financial development do not promote the achievement of environmental sustainability, raising questions about the environmental policies and regulations in Sub-Saharan Africa. To this end, there is a need for policy reforms and corruption control in order to prevent the misallocation and misuse of resources designed to support green transition projects. Full article

Understanding how species share resources (niche dynamics) and associate with each other is crucial for maintaining stable ecological communities. Using infrared camera traps, we constructed spatial association networks for an isolated Asian elephant population. The Asian elephant (Elephas maximus), a keystone species in tropical forests, faces significant threats from habitat fragmentation and human disturbances, particularly in the isolated population of Nangunhe National Nature Reserve, Yunnan, China. Using infrared camera trapping, niche analysis, and interspecific association models, we examined the ecological role of Asian elephants and their sympatric species networks in fragmented habitats. We identified 44 species, including 11 species with higher relative abundance showing significant ecological correlations with elephants. Asian elephants exhibited the broadest spatial distribution, consistent with their role as ecological engineers due to high environmental tolerance and diverse resource utilization. Sympatric herbivores exhibited moderate spatial co-occurrence. Wild boars (Sus scrofa), red-bellied squirrels (Callosciurus erythraeus), northern pig-tailed macaques (Macaca leonina), and red junglefowl (Gallus gallus) demonstrated significant spatial associations with elephants. Lambda coefficient analysis revealed asymmetric associations reflecting spatial reliance of red-bellied squirrels and wild boars on elephant activity zones. Temporally, Asian elephants exhibited a stable bimodal activity pattern at dawn and dusk. Despite varying degrees of diel overlap with sympatric species, no significant temporal avoidance was detected, suggesting fine-scale coexistence mechanisms beyond the temporal dimension. We argue that conservation strategies are in urgent need of a transformation from single-species protection to the preservation of ecological interaction networks. This study clarifies the dominant position of Asian elephants in the community by mapping the spatial association networks between Asian elephants and sympatric species, and its findings hold substantial guiding significance for the recovery and protection of isolated Asian elephant populations. Full article

Understanding the formation mechanisms of plant hydrothermal niches is a core issue in ecology. This study focused on 362 woody plant species in eastern China to investigate the effects of leaf nitrogen (N), phosphorus (P), and their ratio (N/P) on hydrothermal niches and to assess the role of phylogenetic signals. Our results showed that all niche parameters exhibited significant yet varying strengths of phylogenetic signals, with thermal niche signals generally stronger than those of hydric niches. Leaf N and P were significantly correlated with thermal niche dimensions (e.g., breadth and lower limits), whereas leaf N/P and P primarily drove variation in hydric niche dimensions (e.g., breadth and upper limits). This study confirms the asymmetric and dimension-specific influences of leaf nutrients on hydrothermal niches, highlights the necessity of controlling for phylogenetic history in trait-niche research, and provides new perspectives for understanding plant environmental adaptation and evolution. Full article

Wheat (Triticum aestivum L.) is a strategic food crop for arid, hot regions such as the Arabian Peninsula, the Middle East, and North Africa. In these areas, production is limited by extreme environmental and agronomic conditions, leading to heavy dependence on imported wheat. Irrigation is often essential for successful cultivation, but available water sources are frequently saline. This study evaluated the comparative effects of irrigation salinity and genotype on agronomic performance, physiological responses, and grain quality. Nine Syrian wheat genotypes and one French bread-making cultivar, Florence Aurora, were grown in sandy soil under three irrigation salinity levels (2.6, 10, and 15 dS m⁻¹) across two seasons at the International Center for Biosaline Agriculture (Dubai, UAE). Salinity strongly negatively impacted yield, which decreased by 61% from the control to 15 dS m⁻¹, along with key yield components such as thousand grain weight and total biomass. Physiological traits, including carbon isotope composition (δ¹³C) and Na concentrations in roots, shoots and grains, increased significantly with salinity, while chlorophyll content showed a modest decline. Effects on grain quality were relatively minor: total nitrogen concentration and most mineral levels increased slightly, mainly due to a passive concentration effect associated with reduced TGW. Genotypes varied significantly in yield, biomass, TGW, physiological traits, and grain quality. The highest-yielding genotypes under control conditions (ACSAD 981 and ACSAD 1147) also performed best under saline conditions, and no trade-off was observed between yield and grain quality parameters (TGW, nitrogen, zinc, and iron concentrations). Separate analyses conducted for control and saline treatments identified different drivers of genotypic variability. Under control conditions, chlorophyll content, closely linked with δ¹³C, was the best predictor of genotypic differences and was positively correlated with yield across genotypes. Under salinity stress, grain magnesium (Mg) concentration was the strongest predictor, followed by grain δ¹³C, with both traits positively correlated with yield. These findings highlight key physiological traits linked to salinity tolerance and offer insights into the mechanisms underlying genotypic variability under both optimal and saline irrigation conditions. Full article

The temperature at the base of the ear is highly correlated with the core body temperature of sheep and responds sensitively to febrile conditions, making it a valuable indicator of sheep health. In northern China, the closed housing environment during winter increases the incidence of seasonal diseases such as upper respiratory infections and pneumonia, which severely affect the economic efficiency of sheep farming. To address this issue, this study proposes an early-warning method for winter diseases in sheep based on ear-base temperature. Ear temperature, body weight, and environmental data were collected, and Random Forest was employed for feature selection. Bayesian optimization was used to fine-tune the hyperparameters of a one-dimensional convolutional neural network to construct a predictive model of ear-base temperature using data from healthy sheep. Based on the predicted normal range, an early-warning strategy was established to detect abnormal temperature patterns associated with disease onset. Experimental results demonstrated that the proposed method achieved a high detection rate for common winter diseases while maintaining a low false positive rate, and validation experiments confirmed its effectiveness under practical farming conditions. Combined with low-cost temperature-sensing ear tags, the proposed approach enables real-time health monitoring and provides timely early warnings for winter diseases in large-scale sheep farming, thereby improving management efficiency and economic performance. Full article