Search Results (113,530)

Soil heavy metal contamination has emerged as a global environmental and public health challenge. Among them, cadmium (Cd) is of particular concern due to its high mobility and ecotoxicity. To identify the key limiting factors and their nonlinear threshold effects for Cd accumulation in maize grains (Grain-Cd) in heterogeneous soil environments, a coordinated sampling campaign of soil and maize was conducted at the municipal scale in Chongqing, China. A total of 499 paired soil–maize samples were obtained, and the correlations between Grain-Cd concentrations and soil physicochemical properties, as well as soil Cd pollution characteristics, were quantitatively evaluated using the integrated Random Forest (RF) model and SHAP (SHapley Additive exPlanations) algorithm instead of traditional linear statistical methods. The results showed that the average Cd content in the soil of maize-growing areas in Chongqing City was 0.30 mg·kg⁻¹, with a variation coefficient (CV) of 53%, and the spatial heterogeneity was significant. The average Cd content in maize grains was 0.03 mg·kg⁻¹, with an exceedance rate of 9.6% over the Chinese National Standard (0.10 mg·kg⁻¹), indicating a certain food safety risk. The RF model achieved a high predictive accuracy for Grain-Cd (R² = 0.815, RMSE = 0.028 mg·kg⁻¹, MAE = 0.013 mg·kg⁻¹), which was significantly superior to the traditional linear regression model (R² = 0.526, RMSE = 0.0459 mg·kg⁻¹). The available Cd (avlCd) in the soil was identified as the core controlling factor for the Grain-Cd content, while total soil Cd (SCd) only showed its positive contribution at contents higher than 0.5 mg·kg⁻¹. Soil pH, CEC (cation exchange capacity), and total phosphorus (TP) exerted significant influences on the Grain-Cd by regulating soil avlCd. The dependence of Grain-Cd on these soil factors was typically nonlinear, and an obvious turning point (threshold) existed for each factor with its occurring level in soil, determined by SHAP analyses as avlCd: 0.29 mg·kg⁻¹, pH: 6.58, CEC: 18.9 cmol (+)/kg, and TP: 0.5 g·kg⁻¹, respectively. This study clarifies the nonlinear regulatory mechanisms of key soil factors on Cd accumulation in maize grains in Chongqing, and the established RF-SHAP framework and identified soil factor thresholds lay a scientific foundation for the interpretable quantification of the soil–maize Cd system, while providing a scientific basis for the precise, targeted remediation of Cd-contaminated dryland farmland and the assurance of regional maize production safety. Full article

The rapid adoption of immersive and adaptive digital technologies is redefining sustainability education, but the mechanisms by which these technologies support perceived sustainability outcomes remain unclear. This paper models the Digital Experiential Learning Ecosystem (DELE), including simulation, AR/VR, gamification, AI personalization, and collaborative digital platforms, as a higher-order construct. It discusses its role in Perceived Sustainability Outcomes through learning engagement. Basing the study on the Stimulus-Organism-Response framework, the study hypothesizes that the digital ecosystem design can be viewed as an environmental stimulus, engagement as the organismic processing state, and Perceived Sustainability Outcomes as the developmental response. The results, obtained using Partial Least Squares Structural Equation Modeling (PLS-SEM), indicate that DELE is positively associated with learning engagement and Perceived Sustainability Outcomes. Learning engagement is found to be the leading mechanism through which digital experiential environments are converted into perceived sustainability outcomes, but a smaller yet significant direct structural relationship also remains. These findings indicate that digital transformation within the education sector creates sustainable value not only through technological sophistication but also through carefully planned engagement-based learning environments that support systems thinking, applied problem-solving, and adaptive readiness to work in multifaceted environments. The research also advances the body of research on sustainability education by developing a model of digital learning as an integrated ecosystem and by explaining the psychological and structural processes of perceived sustainability outcomes. Full article

Monitoring thermal effluent is critical for assessing aquatic ecosystem health, yet traditional satellite remote sensing and in situ point measurements often fail to capture fine-scale thermal dynamics in narrow streams and complex coastal areas due to spatiotemporal resolution limitations. This study establishes a high-precision surface water temperature mapping protocol using a low-cost Unmanned Aerial Vehicle (UAV) equipped with an uncooled thermal infrared sensor (FLIR Vue Pro R) to overcome these observational gaps. We investigated two distinct hydrological environments—an inland stream and a coastal sea—to provide initial evidence for the applicability of an in situ-based linear regression calibration model across contrasting aquatic settings. The initial uncalibrated radiometric temperatures exhibited significant bias errors reaching up to 9.2 °C in the stream and 9.4 °C in the coastal area, primarily driven by atmospheric attenuation and environmental factors. However, the proposed calibration method dramatically reduced these discrepancies, achieving Root Mean Square Errors (RMSE) of 0.43 °C and 0.42 °C, respectively, with high determination coefficients (R² > 0.87). The derived high-resolution thermal maps successfully visualized the detailed diffusion patterns of thermal plumes, revealing a steep temperature gradient of approximately 13 °C in the stream discharge zone and a distinct 5 °C elevation in the coastal effluent area relative to the ambient water. These findings demonstrate that UAV-based thermal remote sensing, when coupled with a rigorous radiometric calibration strategy, can serve as a cost-effective and reliable tool for environmental monitoring, bridging the critical scale gap between local point measurements and regional satellite observations. Full article

Background/Objectives: Central Nervous System (CNS) relapse represents a severe and often fatal complication of Diffuse Large B-Cell Lymphoma (DLBCL). This study aimed to evaluate clinical, biological, and treatment-related factors associated with progression-free survival (PFS) until CNS relapse in patients with DLBCL. Methods: A retrospective cohort study was conducted using clinical data from adult DLBCL patients evaluated and treated at the Regional Institute of Oncology, Iași, Romania, between 2015 and 2023. Associations between clinical, biological, and treatment-related variables and CNS relapse were evaluated using univariate and multivariable Cox proportional hazards models, Fine–Gray competing-risk analyses, and propensity score-based methods to address confounding by indication for CNS prophylaxis. Results: Twenty-six CNS relapse events (6.3%) and 72 deaths without prior CNS relapse occurred over a median follow-up of 12 months. In the prespecified reduced multivariable Cox model, non-R-CHOP regimens (HR 4.57, 95% CI 1.67–12.52; p = 0.003) and high CNS-IPI scores (HR 4.70, 95% CI 1.14–19.46; p = 0.033) were independently associated with CNS relapse. The 20-month cumulative incidence of CNS relapse was 7.0% in the R-CHOP-like group versus 35.2% in the non-R-CHOP group (Gray’s test p < 0.001). Fine–Gray modeling confirmed the association for non-R-CHOP regimens (SHR 3.38, 95% CI 1.21–9.45; p = 0.02). Cell-of-origin subtype, double-expressor phenotype, and Ki-67 were not significantly associated with CNS relapse. Conclusions: High CNS-IPI and treatment with non-R-CHOP regimens independently predicted earlier CNS relapse. Future multicenter studies with molecular profiling are needed to refine CNS risk stratification. Full article

Microalgae dewatering is a major bottleneck for the industrial deployment of microalgal biorefineries due to its high energy and water requirements. This study investigates the optimization and modeling of an industrial-scale aerated submerged ultrafiltration (UF) system for microalgae pre-concentration under real operating conditions. A submerged hollow-fibre Koch LE8 UF module (348 m², 0.03 µm) was operated directly on Chlorella sp. cultures produced in an 800 m² outdoor photobioreactor. Filtration–backwash cycles were experimentally optimized, identifying an optimal sequence of 8.33 min filtration and 1 min backwash, enabling up to 80% net water removal per cycle while maintaining fouling largely reversible under the tested conditions. Long-term trials (6–7 h) achieved stable concentration factors of 3.6–4.3 with complete biomass retention and sustained permeate flux despite increasing solids concentration. Reuse of permeate for backwashing eliminated freshwater consumption without compromising membrane performance. A dynamic resistance-in-series (RIS) model, incorporating mass balances and an empirically derived concentration-polarisation resistance, accurately reproduced permeate flux and biomass concentration dynamics (R² > 0.83) using a single fitted parameter. The validated model was further applied as a digital twin to simulate operation up to the theoretical concentration factor of 10, quantifying the associated energy and water demands. The system exhibited a low estimated specific energy consumption of 1.25 kWh·kg⁻¹ biomass and a water demand of 0.30 m³·kg⁻¹, demonstrating that aerated submerged UF is a robust, scalable, and energy-efficient solution for industrial microalgae harvesting. Full article

Background and objectives: Articular cartilage provides low-friction articulation across joint surfaces, distributes loads, and absorbs stress, all of which are crucial mechanical functions of joints. Changes in the mechanical characteristics of cartilage are among the first signs of degenerative joint disease, and they are especially important for athletes who are subjected to high-impact, high-magnitude loading on a regular basis. The objective of this study was to: (i) compare the mechanical characteristics of tibiofemoral cartilage in healthy and osteoarthritic conditions across medial and lateral anatomical compartments; and (ii) use nonlinear phenomenological viscoelastic modeling in conjunction with unconfined compression testing to characterize compartment-specific viscoelastic behavior. Materials and Methods: Forty-six human tibiofemoral cartilage samples were collected during knee surgeries and classified as healthy (n = 17) or osteoarthritic (n = 29) and as medial (n = 26) or lateral (n = 20). Quasi-static unconfined compression tests were performed at 1 mm/min to obtain stress–strain responses, Young’s modulus, maximum compressive stress, and energy absorption. Viscoelastic behavior was analyzed using a nonlinear phenomenological viscoelastic model. Appropriate parametric or non-parametric statistical tests and effect size measures were applied. Results: Osteoarthritic cartilage’s stiffness and energy absorption were significantly higher than those of healthy tissue (p < 0.05). Medial cartilage exhibited significantly greater stiffness and stress than lateral cartilage (p < 0.001). The nonlinear phenomenological viscoelastic model provided an excellent fit (R² > 0.999). Conclusion: The mechanical profile of osteoarthritic tibiofemoral cartilage is characterized by pathological mechanical remodeling and increased stiffness. Greater mechanical susceptibility in the medial compartment supports the significance of cartilage biomechanical properties as sensitive indicators of early degeneration and osteoarthritis risk in athletic populations. Full article

During a study of cyanobacterial colonization on coal ash dumps at the Apatity Thermal Power Plant (Murmansk Region, NW Russia), two strains of Nostoc-like morphotypes were collected, cultivated, and examined using a polyphasic approach. Both strains KPABG–133801 and KPABG–133804 exhibited high similarity in the 16S rRNA gene (99.93%) and identical 16S–23S ITS regions. Phylogenetically, they provided robustly supported affinity to the genus Pseudoaliinostoc, which currently comprises eight species predominantly distributed in Southeast Asia. The similarity of the 16S rRNA gene (95.74–97.25%), the divergence in the 16S–23S ITS rRNA region (18.56–26.28%), and the unique hypothetical secondary structures of conserved helices (D1–D1′, Box–B, V3) strongly suggest that these Arctic strains represent a new species, Pseudoaliinostoc murmanicum, which is described and illustrated in this study. The species forms bright blue-green colonies that gradually turn olive-green with age and is characterized by elongated cells in young trichomes, vegetative cell width of less than 3.2 µm, and the presence of akinetes wider than 3.5 µm. Full article

Automated pig-welfare monitoring needs scalable, non-invasive signals that work across ages and individuals. A key methodological contribution of this study is the use of subject-wise validation, which ensures generalization to unseen animals and prevents inflated accuracy caused by growth-related and individual ‘voice’ differences. Vocalizations can help, but growth and individual “voice” differences can confound distress patterns and overstate accuracy without subject-wise validation. In our study, we explicitly accounted for individual variability by including animal identity as a random effect in mixed models and by using grouped cross-validation, where models were tested only on pigs not seen during training. This approach ensures that the reported accuracy reflects generalization across different individuals rather than memorization of specific vocal signatures. We analyzed 2221 vocal samples from 40 pigs (20 males, 20 females) recorded across four growth phases (farrowing, nursery, growing, finishing) under six conditions (pain, hunger, thirst, cold stress, heat stress, normal). Acoustic features extracted in Praat included energy, duration, intensity, pitch, and formants (F1–F4). Using blockwise variance decomposition, we quantified contributions of distress exposure, growth phase, and sex, and estimated the additional variance explained by animal identity. Distress exposure dominated intensity and spectral traits, particularly Formant 2, whereas the growth phase produced systematic shifts in duration and pitch. Animal identity added a modest but consistent increment in explained variance (~+0.02–0.03 R² beyond sex, phase, and distress). For prediction, we used 5-fold cross-validation grouped by animal. A Random Forest achieved a modest balanced accuracy of 0.609 and macro-F1 of 0.597; pain was most separable (recall 0.825), while other states showed moderate recall, indicating overlap. These results support hierarchical acoustic encoding of distress and establish a benchmark for precision welfare monitoring. Furthermore, they highlight that resolving complex physiological overlaps, such as heat stress and resource competition, requires a shift from unimodal acoustic models to multimodal Precision Livestock Farming (PLF) systems that integrate bioacoustics with continuous environmental and behavioral data streams. Full article

Objectives: We aimed to investigate the association between musculoskeletal fitness (MF) and cardiovascular risk factors in adolescents with congenital heart disease (ConHD). Methods: This cross-sectional study included 355 adolescents with ConHD (median age 12.4 years [range: 5.7–21.7]; 43.4% female). Participants completed musculoskeletal fitness (MF) tests, including handgrip strength (HGS), curl-ups, push-ups, and trunk lifts, and underwent an assessment of anthropometric indices, blood pressure, pulse wave velocity (PWV), and carotid intima–media thickness (cIMT). To account for body size, HGS was allometrically scaled to body mass with adjustment for age, sex, and ConHD severity. Clustered MF was derived by calculating z-scores for allometric HGS, curl-ups, push-ups, and trunk lifts. Results: Allometric HGS was inversely associated with anthropometric indices: waist circumference [WC] (β = −4.467, p = 0.014), waist-to-hip ratio [WHR] (β =−0.039, p = 0.005), waist-to-height ratio [WHtR] (β = −0.052, p = 0.001), and BMI (β = −3.115, p = 0.001). Push-ups were inversely related to all anthropometric indices (p < 0.05). Trunk lift showed positive associations with multiple anthropometric indices except WHR (all p < 0.05). Clustered MF was negatively associated with WHR (β = −0.004, p = 0.008) and WHtR (β = −0.006, p = 0.001). HGS (β = 0.18, p = 0.033), push-ups (β = 0.004, p = 0.041), and clustered fitness (β = 0.028, p = 0.006) were inversely associated with PWV. Conclusions: Systematically increasing MF in rehabilitation may provide a feasible strategy to mitigate CVD risk in adolescents with ConHD. Full article

The increasing integration of renewable energy sources increases the variability and uncertainty of power systems, requiring advanced prediction-based control strategies. This paper proposes an integrated AutoML–MPC framework for a hybrid renewable energy system (HRES) combining solar and wind generation, biomass, battery energy storage, and a hydrogen chain (electrolyzer and fuel cell). Short-term load and generation forecasts are made using H2O AutoML models, and the energy flow allocation is optimized using model-based control (MPC) formalized in the form of mixed-integer linear programming (MILP). The objective function minimizes electricity imports from the grid and the associated ${\mathrm{C}\mathrm{O}}_2$ emissions, subject to technological constraints. The results obtained showed a clear distribution of short-term (battery) and long-term (hydrogen) storage functions in time: during periods of excess generation, the electrolyzer operated close to nominal mode, and in the deficit phase, the fuel cell was activated, reducing the need for grid imports. The battery ensured fast short-term balancing, while the hydrogen system compensated for the longer-term energy shortage. The forecast models were characterized by high accuracy ($R^2>0.98$), which allowed for reliable planning of energy flows over the MPC horizon. The proposed methodology allows for effective coordination of storage technologies of different time scales, maximum use of renewable generation and reducing the system’s dependence on the external grid. Full article

In recent years, fractional HIV models have received increasing attention. This study derives a fractional HIV model using the continuous-time random walk (CTRW) method, endowing the mathematical model with physical significance. Based on the transmission characteristics of HIV, the proposed model considers extrinsic infectivity, intrinsic infectivity, and drug control, specifically as follows: the extrinsic infectivity is a constant independent of the infection time; the intrinsic infectivity is a power-law function that depends on drug efficacy and infection time; the drug efficacy rate follows a Mittag–Leffler distribution with a long-term effect. Based on these considerations, a fractional HIV model with drug control is established in this paper. In addition, the global asymptotic stability of the equilibrium and the sensitivity analysis of the basic reproduction number $R_0$ are studied, and the theoretical results are verified by numerical simulations. The results show that reducing extrinsic infectivity, controlling intrinsic infectivity, and the drug efficacy rate are crucial in controlling the spread of HIV. Full article

Parental identity, the extent to which individuals integrate parenting roles into their self-concept, is associated with subjective well-being (SWB). However, research has largely focused on current parents, with limited attention to those with alternative caregiving roles. Companion dogs often act as caregiving figures, but their role in shaping identity and well-being processes has not been fully explored. This cross-sectional, survey-based study examined whether parental identity is associated with SWB, regardless of parental status, and whether the human–dog bond moderates any association in older women. Women dog owners aged 40 years and over (N = 296, M age = 51.6) completed an online survey including the Parental Identity and Enjoyment Scale, the Dog Owner Relationship Scale, the Satisfaction With Life Scale, and the Flourishing Scale. Parental identity was positively associated with life satisfaction, r = 0.38, p < 0.001, and flourishing, r = 0.23, p < 0.001, and moderated regression models were significant for both (p < 0.001). However, interaction effects between parental identity and the human–dog bond were not significant. These findings extend identity theory, demonstrating that parental identity predicts SWB across diverse pathways and independently of parental status. The results contribute to emerging research on caregiving identities and highlight the importance of considering identity processes, rather than parental status alone, when examining well-being in older women. Full article

This work presents an enhancement to the Dynamic Traffic Management (DTM) framework aimed at reducing signaling overhead between SDN controllers in multi-domain cloud environments. This extension is based on the ability to transmit information regarding the amount of balanced traffic and the optimal transfer pattern. In the baseline periodic mode, the system regularly exchanges the compensation vector ($\overrightarrow{C}$) and the reference pattern ($\overrightarrow{R}$). To minimize communication, we define non-periodic modes that restrict $\overrightarrow{C}$ updates and eliminate $\overrightarrow{R}$ transmission entirely. Within these restricted signaling modes, we further distinguish between reactive and proactive operational schemes. Our experimental results demonstrate that reducing the visibility of optimization goals ($\overrightarrow{R}$ and only sign of $\overrightarrow{C}$) and cutting signaling frequency in this manner maintains a comparable level of cost-efficiency. Specifically, the initial evaluation shows that DTM typically decreases transit costs by 8% to 15%, with maximum savings reaching up to 29% when compared to the worst-case default BGP path scenario. These findings suggest that the DTM mechanism can maintain its economic efficiency even with significantly reduced inter-domain coordination. Full article

Background: Identifying multimodal interventions to counteract age-related physiological decline is a critical public health priority. This study investigated the impact of an 8-week Mat Pilates intervention (MPT) on the interplay between core stability, pulmonary function, and cardiorespiratory fitness in older adults, specifically examining the mechanistic link between trunk stabilization and respiratory mechanics. Methods: Twenty older adults (18 females, 2 males; age 60—77 years) were randomized (stratified by sex, age, and baseline stability) into an MPT group (n = 10; 60-min sessions, 3×/week) or a control group (CON, n = 10). Primary outcomes included core stability (plank test), functional flexibility (sit-and-reach; back-scratch), pulmonary function (FVC, FEV₁, FEV₁/FVC, FEF_25–75%, MVV), and cardiorespiratory fitness (6-min walk test; 6MWT). Results: Post-intervention, the MPT group demonstrated significant improvements in core stability, flexibility, and all pulmonary variables (FVC, FEV₁, FEF_25–75%, MVV) compared to the CON group (p < 0.001). A significant reduction in body weight was also observed (p < 0.001). Notably, MPT participants achieved superior 6MWT distances and reduced perceived exertion (p = 0.006). Correlation analysis revealed strong positive associations between core stability gains and pulmonary function (r = 0.892, p < 0.01), supporting the mechanistic link between trunk stabilization, enhanced ventilatory mechanics, and functional aerobic capacity. Conclusions: Mat Pilates is a potent intervention for older adults, facilitating a physiological synergy where core strengthening optimizes pulmonary function and cardiorespiratory endurance. These findings suggest MPT is a comprehensive modality for maintaining musculoskeletal and respiratory health, proving superior to habitual activity alone in promoting functional independence. Full article