Search Results (5,346)

Mite assemblages are integral components of forest ecosystems, yet their seasonal dynamics in moss microhabitats remain poorly understood. We investigated moss-dwelling mites in a peri-urban Mediterranean forest in Greece across three sampling periods (March, May, July 2020), analyzing 150 random samples. Diversity was assessed using Hill numbers, rarefaction, and β-diversity partitioning, while Indicator Species Analysis identified taxa linked to specific months. Functional structure was further examined through trophic guilds. Results revealed strong temporal shifts: richness peaked in March, whereas May and July harbored distinct assemblages with unique indicator taxa. Functional analyses indicated seasonal changes in trophic guild representation, reflecting resource-driven dynamics. These findings highlight the importance of moss microhabitats as reservoirs of mite diversity and underscore the need for temporal perspectives in Mediterranean forest biodiversity research. Full article

Dust storms have a significant impact on the Martian atmosphere and climate. Previous studies have found that regional and global dust storms mainly occur in the Mars perihelion season. However, an anomalous spring regional dust storm occurred in the aphelion season of Martian year 35 (MY 35). The occurrence and evolution of this new type of large dust storm and its impact on the Martian atmosphere are not yet fully understood. Using Mars Climate Sounder (MCS) dust observations, this study investigates the evolutionary characteristics of the MY 35 anomalous spring storm during its pre-storm, onset, expansion, and decay phases, by comparing it with other types of regional dust storms. The evolution of the MY 35 anomalous spring dust storm is more similar to that of the MY 35 C storm, showing north–south mirror symmetry relative to the equator, suggesting that the two storms may have similar evolutionary mechanisms. Additionally, we analyze the effects of the anomalous MY 35 storm on the atmospheric thermal and dynamical structures using a combination of MCS temperature observations and LMD-GCM wind simulation results. Eastward winds in the high latitudes of both hemispheres and westward winds in the low-to-mid latitudes are significantly enhanced during the storm, corresponding to the change in the atmospheric thermal structure and the global circulation. Finally, we performed a preliminary analysis of changes in the wind field during the spring dust storm in the Chryse and Utopia plains, which are two potential landing areas for China’s Tianwen-3 Mars sample-return mission. The vertical profiles of the simulated horizonal wind in the two plains show that, during the E storm peak time, the change in daily mean wind speed is significant above 20 km, but relatively small in the atmospheric boundary layer below ~5 km. Within the boundary layer, the horizontal wind speed shows remarkable diurnal variation, remaining relatively low during the midday hours (10:00 a.m. to 4:00 p.m.). These results can provide necessary environmental parameters related to spring dust storms for China’s Tianwen-3 mission. Full article

The SARS-CoV-2 Omicron variant caused a global surge in COVID-19 cases following its emergence in November 2021, rapidly diversifying in the subsequent months. Although many studies have documented Omicron’s diversification, few have explored its impact on pediatric populations or the seasonality of other respiratory viruses in children. This study aims to investigate the diversity and circulation patterns of SARS-CoV-2 Omicron sublineages in pediatric patients in São Paulo, Brazil, and assess their co-circulation with other respiratory pathogens. Respiratory samples collected from patients under 18 years old across five hospitals between January 2022 and April 2023 were tested for different respiratory viruses using real-time RT-PCR. Whole-genome sequencing was performed on SARS-CoV-2-positive samples. Among the 7868 pediatric respiratory samples tested, 3902 were positive for viral pathogens. Respiratory Syncytial Virus accounted for the highest number of positive cases (n = 1248), exhibiting an atypical off-season peak in November 2022. SARS-CoV-2 was detected in 297 samples, of which 103 were sequenced. BA.1 and BA.5 sublineages had predominant genomic diversity and circulation time. These findings highlight the Omicron variant’s significant impact on the epidemiology and seasonal distribution of respiratory viruses in children, emphasizing the ongoing need for vaccination and robust surveillance efforts in pediatric populations. Full article

As high-energy-consumption underground public space, subway stations are responsible for a particularly significant proportion of air-conditioning energy use, especially during the cooling season, making the investigation of cooling-load characteristics highly important. However, the determination of independent influencing factors in different situations has not yet reached a consensus, and the role of interaction effects is lacking, which hinders the development of energy-saving strategies. For this purpose, this study proposes a sensitivity analysis framework based on 10 typical influencing factors from thermal parameters, meteorological parameters, internal heat disturbances, and indoor environmental setpoints. An input set was generated by integrating equal-step parameter discretization and Saltelli quasi-MonteCarlo sampling. A database containing 11,264 samples was constructed through an EnergyPlus–Python co-simulation method. Based on the Sobol global sensitivity analysis, the key influencing factors of subway station cooling load were identified and quantified, and the impact of these 10 factors was systematically analyzed. Results show that occupant density (S_i^T = 0.5605) and fresh air volume (S_i^T = 0.4546) are the dominant factors, contributing more than 50% of the load variance. In contrast, the characteristics of an underground structure significantly weaken the influence of the building-envelope heat transfer coefficient (S_i^T = 0.1482) and soil temperature (S_i^T = 0.0884). Furthermore, five groups of strong interaction effects were identified in this study, including occupant density–fresh air volume (S_ij = 0.1094), revealing a nonlinear load response mechanism driven by multi-parameter coupling. This research provides a theoretical foundation and quantitative tool for the refined design and optimized dynamic coupled operation of underground transportation hubs. Full article

Background/Objectives: Central nervous system (CNS) infections remain a significant public health challenge and require rapid and accurate diagnosis to guide clinical management. Although the incidence of bacterial meningitis has declined owing to widespread vaccination, viral etiologies continue to dominate CNS infections. The aim of this study was to assess the epidemiological trends, age distribution, and seasonality of CNS infections using multiplex PCR. Methods: A retrospective analysis was conducted on cerebrospinal fluid (CSF) samples collected between January 2021 and December 2022 from patients with CNS infections at King Abdulaziz Medical City. A BioFire FilmArray Meningitis/Encephalitis (ME) panel was used to detect pathogens. Patient demographics, pathogen distribution, and seasonal trends were analyzed. Results: A total of 2,460 CSF samples were tested, of which 130 (5%) were positive for at least one pathogen. Viral pathogens accounted for 82.3% of the infections, with human herpesvirus-6 (HHV-6) (31%) and enterovirus (EV) (20%) being the most common. Bacterial pathogens represented 17.7% of the cases, with Streptococcus pneumoniae (6%) and Escherichia coli K1 (5%) being the predominant bacterial agents. The highest infection burden was observed in infants aged 0–6 months, with a marked male predominance. Seasonal analysis revealed multiple peaks in viral infections, particularly of HHV-6 and EVs, whereas bacterial infections were sporadic, with Streptococcus agalactiae and Streptococcus pneumoniae peaking in October and November. Conclusions: Viral infections, particularly HHV-6 and EVs, dominated CNS infections, with distinct seasonal and age-related variations. These findings underscore the value of multiplex PCR in improving the rapid diagnosis of CNS infections and aiding in timely treatment and antimicrobial stewardship. Full article

Chicken anemia virus (CAV) targets the immune system of chickens, causing anemia and atrophy of the bone marrow and lymphoid organs, resulting in significant damage to poultry farming. From April 2024 to March 2025, a total of 359 liver samples were collected from broiler farms in 11 cities across Liaoning Province. CAV was detected using PCR, and 16 complete genome sequences of CAV isolates from different regions were analyzed through phylogenetic and recombination analyses. The overall CAV positivity rate was 13.9%, with spring identified as the peak season. Phylogenetic analysis and genotyping revealed that ten CAV strains clustered within subgroup C1, while the remaining six were distributed among subgroups C2 and C3, as well as Group D. Specific mutations were observed among the VP1 protein genotypes, including mutations previously associated with increased pathogenicity and transmission. One isolate, LN2511, was identified as a potential recombinant strain with its parents CAV-Shanxi7 and CAV-EG-13. During 2024–2025, CAV infection remained prevalent in Liaoning Province, with subtype C1 being the dominant genotype. Amino acid sequence analysis indicated the presence of highly pathogenic strains across the province. These findings fill a knowledge gap regarding CAV infection status and evolutionary trends in chicken populations in Liaoning, China. Full article

This study investigates stress detection in dairy cattle by integrating circadian rhythm analysis and deep learning. Behavioral biomarkers, including feeding, resting, and rumination, were continuously monitored using Nedap CowControl sensors over a 12-month period to capture seasonal variability. Circadian features were extracted using the Fast Fourier Transform (FFT), and deviations from expected 24 h patterns were quantified using Euclidean distance. These features were used to train a Long Short-Term Memory (LSTM) neural network to classify stress into three levels: normal, mild, and high. Expert veterinary observations of anomalous behaviors and environmental records were used to validate stress labeling. We continuously monitored 10 lactating Holstein cows for 365 days, yielding 87,600 raw hours and 3650 cow-days (one day per cow as the analytical unit). The Short-Time Fourier Transform (STFT, 36 h window, 1 h step) was used solely to derive daily circadian characteristics (amplitude, phase, coherence); STFT windows are not statistical samples. A 60 min window prior to stress onset was incorporated to anticipate stress conditions triggered by management practices and environmental stressors, such as vaccination, animal handling, and cold stress. The proposed LSTM model achieved an accuracy of 82.3% and an AUC of 0.847, outperforming a benchmark logistic regression model (65% accuracy). This predictive capability, with a one-hour lead time, provides a critical window for preventive interventions and represents a practical tool for precision livestock farming and animal welfare monitoring. Full article

As freely available but not yet commercially acquired biomass resource, water care material (WCM) is generated seasonally in the periodic maintenance of surface water bodies and consists of mainly aquatic and/or rural-associated biomass of the water body profile, as well as wood, soil substrate, water or other possible impurities. In addition to other recovery options, such as composting or utilization in biogas production, hydrothermal carbonization (HTC) was selected as a thermochemical process because it is suitable for converting biomass with a high content of carbon into high-quality combustibles. The biomass sample used in this investigation was obtained during a single sampling event from a small stream in the North German lowlands. The material was pretreated by shredding it to a particle size of <0.12 mm. Through a 5 L stirred reactor, hydrothermal treatments were performed under low temperature conditions (200, 220 and 240 °C), residence times (120, 180, 240 min) and solid dry matter of the sample content: 6%. Solid phase was evaluated in terms of calorific value and proximate and ultimate analysis. The results suggested that the hydrothermal carbonization of WCM gave a high heating value of 23.84 MJ/kg for its char after being dried for 24 h at 105 degrees. At the same time, biochar can be used in agriculture to improve soil properties. To understand to what extent the product is suitable for soil amendment, the surface and the nutrient content of the resulting hydrochar were analyzed in detail. As the initial material is rich in fiber contents, process temperatures up to 240 °C have a huge impact on effective particle size. Furthermore, the analysis of selected nutrients, minerals and heavy metals shows the suitability of the produced hydrochar for soils in accordance with current legislation. Full article

Apple scab poses a significant threat to wild apple orchards in the Ili region of Xinjiang, yet the pathogen responsible and its disease dynamics remain poorly understood. This study aimed to identify the causal agent of apple scab in wild apples and elucidate its disease development pattern to support effective monitoring and control strategies. Field surveys were conducted regularly from 2023 to 2025 in fixed plots and sample trees of Malus sieversii. A total of 29 isolates were obtained from diseased fruits collected in Xinyuan and Huocheng counties using tissue isolation and single-spore purification. Pathogenicity was confirmed via Koch’s postulates, and the pathogen was identified based on morphological and molecular characteristics. Scab symptoms first appeared on leaves in late April (during leaf expansion, disease index 0.34) and on fruits in early June (during fruit enlargement, disease index 0.57). The disease index peaked in late August (47.24 on leaves; 22.51 on fruits), followed by fruit drop at month-end and leaf abscission in late September. The pathogen overwintered mainly in remaining or fallen diseased leaves (isolation rate 17.71%), serving as the primary source of initial infection in the following growing season. The pathogen causing apple scab in Xinjiang wild apple orchards was identified as Venturia inaequalis. Overwintered infected leaves were confirmed as the key primary inoculum source. These findings clarify the taxonomic identity of the pathogen and its epidemic pattern, providing a theoretical basis for disease management. Full article

Background: Soccer’s varied physical demands require meticulous load monitoring, which is now being advanced by combining GPS for external metrics and NMR-based metabolomics for internal metabolic profiling. This study aimed to investigate how player position influences the metabolomic profile (as a marker of internal load) under known match effort (external load). Methods: This was a longitudinal observational descriptive study involving 12 professional soccer players from the U-20 São Paulo Football Club, enrolled in the 2022 São Paulo State Under-20 Football Championship. Players were monitored across six matches during the season, culminating in a total of 49 individual match observations from those players (4-2-3-1 formation: Central Defenders [CD], n = 9; Full Backs [FB], n = 9; Central Midfielders [CM], n = 14; Wide Midfielders [WM], n = 12; Forwards [F], n = 5). Internal load was assessed via urinary metabolomics, with urine samples collected 24 h post-match. A non-targeted, global metabolomics approach was employed using nuclear magnetic resonance (NMR) spectroscopy. External load was monitored using GPS tracking devices. Multivariate analyses included partial least squares discriminant analysis (PLS-DA), and heat maps. Results: Metabolomic analysis identified 38 metabolites with a Variable Importance in Projection (VIP) score > 1.0, revealing perturbations in carbohydrate metabolism and the tricarboxylic acid (TCA) cycle, amino acid and peptide metabolism, pyrimidine metabolism, and ketone body pathways, and effectively discriminating post-match recovery metabolic profiles. External load metrics varied significantly by player position: CMs covered greater distances below 20 km/h (8702.93 ± 1271.89 m), exhibited higher relative distance (114.29 ± 7.67 m/min), total distance (9193.21 ± 1261.35 m), and player load (945.71 ± 135.82 a.u.); CDs achieved higher peak speeds (31.78 ± 1.20 m/s); and WMs performed greater sprint distances (168.11 ± 91.69 m). Metabolomic profiles indicated that CMs showed stronger associations with markers of muscle damage and inflammation, whereas CDs and WMs were more closely linked to energy metabolism and oxidative stress. Conclusions: These results highlight the importance of a personalized approach to training load monitoring and recovery strategies, considering the distinct physiological and metabolic demands associated with each player position. Full article

Nitrogen (N) deficiency in apples (Malus × domestica Borkh.) leads to characteristic physiological symptoms, including leaf and fruit discoloration. Fertigation, i.e., the application of dissolved fertilizers, can significantly improve the growth and fruit quality of apples while optimizing nutrient uptake through a more precise and better timed application than conventional fertilization. This study therefore investigates how different fertilization treatments affect the N concentration of different age categories of apple leaves. Apples of the variety ‘Braeburn’ were grown hydroponically on the low-vigorous rootstock M9. Four fertilizer treatments were used: (1) Hoagland solution (HS); (2) HS nitrogen excluded; (3) HS iron excluded; and (4) HS magnesium excluded. Through vegetation, leaf samples were taken from three shoot positions representing different leaf ages (young, semi-young and old) and then chemically analyzed. The lowest N concentrations across all leaf ages and sampling moments were found in the treatment with N excluded (1.69–2.07% N), while the highest values occurred in the treatments where iron (2.00–2.49% N) or magnesium (1.98–2.37% N) were excluded. The seasonal changes in N concentration reflect interactions between the leaf age and the sampling moment. These results show that the N concentration of apple leaves strongly depends on the type of fertilization. Full article

Eucalyptus plantations worldwide experience significant productivity losses due to herbivory caused by the weevil Gonipterus platensis (Coleoptera: Curculionidae. Marelli 1927); however, the role of leaf nutritional status in host preference remains poorly understood. In this study, we evaluated the incidence and severity of defoliation on two seed-propagated eucalypts—Eucalyptus globulus Labill. and Eucalyptus nitens Maiden, as well as two clonally propagated E. nitens × E. globulus hybrids—at a trial site in Mulchén, Chile. Sampling occurred after peak weevil activity (December 2022) and during austral autumn (May 2023). We determined foliar concentrations of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), boron (B), carbon (C), and the carbon-to-nitrogen (C/N) ratio, and analyzed their relationships with herbivory using ANOVA, principal component analysis (PCA), and linear regression. Overall defoliation was low (<7%), but significantly higher on E. globulus, with hybrids exhibiting intermediate damage. Seasonally, N and Mg concentrations declined, while K and Ca levels increased, resulting in an elevated C/N ratio in autumn. A positive correlation was observed between leaf Ca concentration and both the incidence and severity of herbivory during peak activity in the susceptible E. globulus genotype (R² = 0.96, p < 0.05). These findings suggest that calcium accumulation may influence weevil feeding preferences. Further research should explore nutrient-mediated resistance to guide selection and fertilization strategies for developing more resilient eucalyptus varieties. Full article

Social and emotional learning (SEL) practices in schools endeavor to support wellbeing and emotional intelligence in young people; they work best when implemented well. Educational leaders in K-12 settings need to have capacities to provide SEL implementation support. Surveying SEL implementation capacity can identify specific strengths and areas for improvement and monitor progress. The current study assesses the validity and reliability of a 15-item self-report scale of capacities to support SEL implementation. A sample of 507 county-, district-, and school-level K-12 educational SEL leaders completed the scale in Fall 2023. Confirmatory factor analysis was used. The SEL capacities scale contains four unique dimensions with high internal reliability: mindsets (5 items), knowledge (3 items), skills (6 items), and efficacy (1 item). The SEL capacities scale also showed consistency (e.g., factor structure invariance) across school seasons, different educational settings, roles in the education system, years of experience among leaders, and recent levels of SEL supports received. Data generated by the SEL capacities scale can be used to inform practice decisions, make comparisons across people and over time, and unearth specific mechanisms of change related to developing adult SEL capacities to provide SEL implementation support. Full article

This study investigated water quality, metal ion concentrations, and antibiotic residues specifically enrofloxacin (ENR) and its metabolite ciprofloxacin (CIP), across six American shad (Alosa sapidissima) aquaculture sites over a one-year period. Water and sediment samples were analyzed to determine contamination levels, and ENR-degrading bacteria were isolated from the culture environment to explore their potential use in bioremediation. Findings showed that NH₃-N and total suspended solids (TSS) exceeded recommended standards at all sampling sites. Elevated levels of Li, Na (except S1), Fe, Ni (except S2 and S4), Sr, and Cu were found at site S3. Site S5 recorded the highest concentrations of Al, As, and Pb, while Cd was most abundant at S6. In sediments, S5 showed higher levels of Mg, K (except S3), Ca, Cr, Mn, Fe, Ni, As, Pb, Cu, and Zn (except S3). ENR and CIP were detected in all water and sediment samples, with a 100% detection rate. The highest ENR (16.68–3215.95 mg·kg⁻¹) and CIP (3.90–459.60 mg·kg⁻¹) concentrations in water occurred at site S6, following a seasonal pattern of autumn > winter > summer > spring. In sediments, the maximum ENR (41.43–133.67 mg·kg⁻¹) and CIP (12.36–23.71 mg·kg⁻¹) levels were observed in spring. Two ENR-degrading bacterial strains were successfully isolated and identified as Enterococcus and Bacillus. Optimal degradation was achieved at 30 °C, pH 8.0, 6% inoculum, and 3000 Lux, resulting in a 64.2% reduction in ENR after 72 h. Under slightly different conditions (25 °C, pH 10), degradation reached 58.5%. This study provides an efficient strain resource for the bioremediation of ENR pollution in the aquaculture water of American shad. Full article

Apple jam is a widely used all-season product. The quality of the jam is closely related to its sugar concentration, which affects its taste, texture, shelf life, and legal compliance with production requirements. Although traditional methods for measuring sugar, such as titration, enzymatic methods, and chromatography, are accurate, they are also invasive, destructive, and unsuitable for rapid screening. This study investigates a non-destructive and non-invasive alternative method that uses hyperspectral imaging (HSI) in combination with machine learning to estimate the sugar content in processed apple products. Eight cultivars were selected from the Central Asian region, recognized as the origin of apples and known for its rich diversity of apple cultivars. A total of 88 jam samples were prepared with sugar concentrations ranging from 25% to 75%. For each sample, several hyperspectral images were obtained using a visible-to-near-infrared (VNIR) camera. The acquired spectral data were then processed and analyzed using regression models, including the support vector machine (SVM), eXtreme gradient boosting (XGBoost), and a one-dimensional residual network (1D ResNet). Among them, ResNet achieved the highest prediction accuracy of R² = 0.948. The results highlight the potential of HSI and machine learning for a fast, accurate, and non-invasive assessment of the sugar content in processed foods. Full article