Search Results (19,918)

Background/Objectives: Patient-level factors strongly influence antimicrobial resistance (AMR) through the pressure applied to healthcare professionals to prescribe antibiotics even for self-limiting viral infections, enhanced by knowledge and attitude concerns. This includes Africa, with high levels of AMR. However, validated measurement tools for African primary healthcare (PHC) are scarce. This study evaluated the reliability, structural validity, and interpretability of the Community Antimicrobial Use Scale (CAMUS) in South Africa. Methods: A cross-sectional survey was conducted with 1283 adults across 25 diverse public PHC facilities across two provinces. The 30-item theory-based tool underwent exploratory and confirmatory factor analysis (EFA/CFA), reliability, and validity testing. Results: EFA identified a coherent five-factor structure: (F1) Understanding antibiotics; (F2) Social and behavioural norms; (F3) Non-prescribed use; (F4) Understanding of AMR; and (F5) Attitudes. Internal consistency was strongest for knowledge and misuse domains (alpha approximation 0.80). Test–retest reliability was good-to-excellent (ICC: 0.72–0.89). CFA confirmed acceptable composite reliability (CR ≥ 0.63). Although average variance extracted (AVE) was low for broader behavioural constructs, indicating conceptual breadth, it was high for AMR knowledge (0.737). Construct validity was supported by positive correlations with health literacy (r = 0.48) and appropriate use intentions (r = 0.42). Measurement error metrics (SEM = 1.59; SDC = 4.40) indicated good precision for group-level comparisons. Conclusions: CAMUS demonstrated a theoretically grounded structure with robust performance in knowledge and misuse domains. While social and attitudinal domains require refinement, we believe the tool is psychometrically suitable for group-level antimicrobial use surveillance and programme evaluation in South African PHC settings and wider to help with targeting future educational programmes among patients. Full article

Chromium (Cr) is a highly toxic heavy metal, yet its effects on soil invertebrates—particularly Caenorhabditis elegans (C. elegans)—remain insufficiently understood, especially regarding how soil properties and Cr speciation change regulate its bioavailability and toxicity. In this study, the toxicity of Cr(VI) to the growth, fertility, and reproduction of C. elegans was assessed in six representative agricultural soils following 7, 60, and 120 days of spiked soil aging, following ISO 10872 guidelines. Substantial differences in toxicity were observed among soils after 7 days of aging, with toxicity ranking from low to high as black soil < yellowish-red soil < red soil < yellow–brown soil < fluvo-aquic soil < purple soil. After 60 days of aging, Cr(VI) toxicity decreased markedly, with EC₅₀ values for growth, fertility, and reproduction increasing by 1.04–2.32, 1.04–2.34, and 1.40–2.20 times, respectively. Organic matter (OM) and amorphous aluminum oxides (Al_AO) were identified as the principal soil properties that were significantly correlated with Cr(VI) toxicity and were useful for explaining and estimating toxicity thresholds within the range of soils examined in this study. In addition, the magnitude of the aging effect showed significant positive correlations with both amorphous aluminum oxides (Al_AO) and total aluminum (Al_total), suggesting that Al-bearing minerals may contribute to the time-dependent immobilization of Cr(VI) under the experimental conditions of this study. These findings expand the ecotoxicological database for chromium, improve the prediction of toxicity thresholds under diverse soil conditions, and provide a scientific basis for refining soil environmental quality standards and developing targeted management strategies for Cr-contaminated agricultural soils. Full article

To improve the accuracy of gravimetric liquid hydrogen flow standard devices, the self-weight of the weighing tank must be minimized, because the total mass of the liquid hydrogen contained in the tank is far smaller than the structural mass of the tank itself, which severely compromises the sensitivity of gravimetric measurement. In this study, a three-dimensional finite element model of a vacuum-insulated liquid-hydrogen weighing tank was developed in ABAQUS. The inner and outer shells were modeled with 06Cr19Ni10 (304) and 06Cr17Ni12Mo2 (316) austenitic stainless steels, and Polyamide 6 (PA6) was used for the internal support. Three operating stages were considered: evacuation of the annulus (interlayer pressure reduced from 0.1 MPa to 0 MPa), pre-cooling to −253 °C, and pressurization of the inner tank (internal pressure increased from 0.1 MPa to 1 MPa). The equivalent stress and deformation were compared for different materials and wall thicknesses to evaluate structural safety and weight-reduction potential. The proposed configuration (inner shell 1.6 mm and outer shell 1.0 mm) achieves a mass reduction of more than 50% relative to the 3 mm minimum wall thickness commonly adopted for cryogenic vessels, while keeping stresses below the allowable limits. This reduction enables the use of higher-resolution load cells and thereby lowering the measurement uncertainty of the liquid hydrogen flow standard device and providing technical support for lightweight and cost-effective design, with potential applicability to other cryogenic tank systems. Full article

The increasing demand for lithium-ion batteries (LIBs) has intensified the need for efficient lithium (Li) recovery from secondary sources. This study focuses on anti-solvent crystallization for the recovery of high-purity lithium hydroxide monohydrate (LiOH·H₂O) from a Li-rich leachate, derived from the flue dust of a pilot-scale pyrometallurgical process for LIB material recycling. To optimize product yield and purity, a series of experiments were performed, focusing on the influence of parameters such as solvent type, organic-to-aqueous (O/A) volumetric ratio, crystallization time, stirring rate, and anti-solvent addition rate. Acetone was identified as the most effective anti-solvent, producing rectangular cuboid crystals with approximately 90% Li recovery and around 95% purity, under optimized conditions (O/A = 4, 3 h, 150 rpm, and solvent flow rate of 5 mL/min). The flow rate influenced crystal morphology and impurity entrapment, with 5 mL/min favoring nucleation-dominated crystallization regime, producing ~20 μm of well-dispersed crystals with reduced impurity incorporation. SEM-EDS, surface washing, and gradual dissolution of obtained LiOH·H₂O crystals revealed that the impurities sodium (Na), potassium (K), aluminum (Al), calcium (Ca) and chromium (Cr) were crystallized as conglomerates. It was found that Na, K, Al, and Ca primarily crystallized as highly soluble conglomerates, while Cr was crystallized as a lowly soluble conglomerate impurity. In contrast Zn was distributed throughout the crystal bulk, suggesting either the entrapment of soluble zincate species within the growing crystals or the formation of mixed Li-Zn phase. Therefore, to achieve battery-grade purity, further purification measures are necessary. Full article

The migration and transformation of Cr(VI) are primarily regulated by soil minerals, soil flora and fauna, hydrological conditions, and microbial communities, with these mechanisms being influenced by pH, temperature, and oxygen levels. In terms of single environmental media, relatively extensive research has been conducted on the behaviors of Cr(VI). However, studies on the migration and transformation of Cr(VI) from the perspective of the soil–groundwater multimedia system are rarely published. Therefore, this study comprehensively analyzes the migration and transformation behaviors of Cr(VI) from the perspective of the entire soil–groundwater system. By synthesizing the effects of individual factors, such as pH and organic matter, on Cr(VI) in both soil and groundwater, as well as interactions among these factors, we systematically clarify the patterns governing Cr(VI) migration and transformation under multi-factor coupling. Through the analysis of multiple factors in the complex system, the redox fluctuation zone at the soil–groundwater interface is a hot spot for Cr(VI) transformation, and the synergistic effect among climatic conditions, microbial community structure, and the aquifer interface significantly affects the transport efficiency of Cr(VI). The results of the present study could provide a theoretical framework for future research on the environmental behavioral effects of Cr(VI) at the soil–groundwater interface. Moreover, this study could provide important theoretical bases for the prevention and control of heavy metal pollution. Full article

Adventitious shoot regeneration in woody species is regulated by interactions between plant growth regulators, endogenous hormone metabolism, and environmental cues such as light quality. Here, we investigated the effects of thidiazuron (TDZ) and the cytokinin oxidase/dehydrogenase (CKX) inhibitors INCYDE and phenyladenine (PA), in combination with different light spectra, on morphogenesis in Melia volkensii leaf explants. TDZ induced the highest frequencies of callus formation and adventitious shoot regeneration, particularly under white light. INCYDE promoted localized regeneration responses, including activation of dormant meristematic regions in secondary leaf axils, whereas PA showed limited regeneration efficiency. Light quality significantly influenced morphogenesis, with white and blue light favoring organized shoot development, while red and far-red light suppressed shoot regeneration and promoted callus formation. Cytokinin profiling revealed treatment-dependent shifts in endogenous cytokinin composition, most notably in isopentenyladenine (iP)-type cytokinins, which is consistent with altered cytokinin degradation dynamics. Cis-zeatin-type cytokinins were abundant across treatments, likely reflecting regulation associated with in vitro culture conditions. These findings indicate that cytokinin metabolism and light quality jointly influence organogenic competence in Melia volkensii Gürke, providing a physiological basis for optimizing regeneration strategies in woody plants. This study provides the first integrated analysis of cytokinin-modulating compounds and light spectra on adventitious shoot regeneration in Melia volkensii. The findings establish a physiological basis for improving regeneration protocols in recalcitrant woody species and support future biotechnological applications, including genetic improvement and advanced propagation strategies. Full article

Major depressive disorder (MDD) is a leading cause of global morbidity and mortality. Although pharmacological treatments are widely used, their effects are often limited, and nearly half of patients show resistance to current antidepressants, including those unresponsive to all available therapies. These challenges highlight the need to better understand the neurobiological mechanisms driving MDD and to develop novel therapeutic strategies, especially those involving natural compounds with multitarget actions. Baicalin, a bioactive flavonoid from Scutellaria baicalensis, exhibits antioxidant, anti-inflammatory, and neuroprotective properties and has recently gained attention for its potential to improve cognitive deficits and mood disorders. In this study, we investigated baicalin’s antidepressant potential and its underlying mechanisms across multiple experimental levels. We found that oral administration of baicalin produced antidepressant-like effects in both naïve mice and those subjected to chronic restraint stress (CRS). CRS impaired hippocampal long-term potentiation (LTP), whereas baicalin restored these synaptic deficits. Importantly, intra-dorsal hippocampal microinjection of the TrkB receptor antagonist ANA-12 abolished baicalin’s antidepressant effects, indicating the involvement of BDNF–TrkB signaling. Baicalin also reduced reactive oxygen species (ROS)/H₂O₂ production in a BDNF-associated manner, demonstrating clear antioxidant activity. Molecular docking further suggested that baicalin binds more effectively to the TrkB receptor than ANA-12, supporting its capacity to activate TrkB-mediated signaling. By integrating in vivo, ex vivo, in vitro, and in silico approaches, our study shows that baicalin exerts robust antioxidant in vitro and antidepressant effects in vivo. These benefits are primarily mediated through activation of BDNF–TrkB signaling, leading to reduced ROS/H₂O₂ accumulation and alleviation of CRS-induced depression-like behaviors. Full article

The search for new therapeutic principles is essential for treating relapsed/refractory (r/r) acute myeloid leukemia (AML). Novel principles include genome-agnostic differentiation induction, controlling AML-triggering inflammation, potentiating the immune response and ‘normalizing’ AML metabolism. This review summarizes data from a phase I study (10 patients, pts) and three case reports reporting 7 pts on the treatment of r/r AML by reprogramming AML hallmarks using APA, low-dose azacitidine, pioglitazone (PPARα/γ agonist) and all-trans retinoic acid. APA reprograms the r/r AML phenotype in patients with clinically and molecularly/genetically unfavorable risk profiles (17 pts, 16 refractory, one relapsed) in a genome-agnostic manner, restoring the plasticity of AML hallmarks, thereby improving immune surveillance, attenuating inflammation-triggered promotion of AML and distant microbial inflammation (healing of fungal pneumonia during induction of complete remission (CR) with APA), while normalizing leukemia metabolism (restoring phagocytosis and ROS production in leukemic neutrophils). APA induces complete remission (CR) in 10 pts (59%), with only modest hematotoxicity following CR induction. This allows treatment to be carried out in an outpatient setting, including for elderly and comorbid patients. Triple transcriptional modulation, facilitated by epigenetic modelling with azacitidine, targets reprogramming of non-oncogene addiction networks in AML, re-establishing functionally active, closely interrelated myeloid hallmarks and AML cell death genome-agnostically. Full article

This study presents a systematic investigation of laser surface hardening of 9CrSi tool steel with the aim of establishing the relationships between processing parameters, microstructural evolution, and resulting mechanical and tribological properties under the applied laser conditions. The influence of laser power, modulation frequency, and scanning speed on the hardened layer depth, microstructure, and surface properties was analyzed. Laser treatment produced a martensitic surface layer with varying fractions of retained austenite, while the transition zone consisted of martensite, granular pearlite, and carbide particles. X-ray diffraction identified the presence of α′-Fe, γ-Fe, and Fe₃C phases, with peak broadening associated with increased lattice microstrain induced by rapid self-quenching. The surface microhardness increased from approximately 220 HV_0.1 in the untreated state to 950–1000 HV_0.1 after laser hardening, with hardened layer thicknesses ranging from about 500 to 750 µm depending on the processing regime. Instrumented indentation showed higher elastic modulus values for all hardened conditions. Tribological tests under dry sliding conditions revealed reduced coefficients of friction and more than an order-of-magnitude decrease in wear rate compared with untreated steel. The results provide a parameter–microstructure–performance map for laser-hardened 9CrSi steel, demonstrating how variations in laser processing conditions affect hardened layer characteristics and functional performance. Full article

Machine learning has been widely applied to phase prediction and property evaluation in multi-principal element alloys. In this work, a data-driven machine learning framework is proposed to predict the ultimate tensile strength (UTS) and total elongation (TE) of Fe-Co-Cr-Ni-Mn-Al-Ti multi-principal element alloys (MPEAs), offering a cost-effective route for the design of new MPEAs. A dataset was compiled through an extensive literature survey, and six different machine learning models were benchmarked, from which XGBoost was ultimately selected as the optimal model. The feature set was constructed on the basis of theoretical considerations and experimental data reported in the literature, and SHAP analysis was employed to further elucidate the relative importance of individual features. By imposing constraints on the screened features, two alloys predicted to exhibit superior performance under different heat-treatment conditions were identified and fabricated for experimental validation. The experimental results confirmed the reliability of the model in predicting fracture strength, and the errors observed in ductility prediction were critically examined and discussed. Moreover, the strengthening mechanisms of the designed MPEAs were further explored in terms of microstructural characteristics and lattice distortion effects. The alloy design methodology developed in this study not only provides a theoretical basis for exploring unexplored compositional spaces and processing conditions in multi-principal element alloys, but also offers an effective tool for developing novel alloys that simultaneously achieve high strength and good ductility. Full article

Thermoplastic starch (TPS) blended with biodegradable polyesters such as polyhydroxybutyrate (PHB), polylactic acid (PLA), polybutylene succinate (PBS), and polycaprolactone (PCL) represents a promising route toward sustainable alternatives to petroleum-based plastics. TPS offers advantages related to abundance, low cost, and biodegradability, while polyesters provide improved mechanical strength, thermal stability, and barrier performance. However, the intrinsic incompatibility between hydrophilic TPS and hydrophobic polyesters typically leads to immiscible systems with poor interfacial adhesion and limited performance. This review critically examines recent advances in the development of TPS/polyester blends, with emphasis on compatibilization strategies based on chemical modification, natural and synthetic compatibilizers, bio-based additives, and reinforcing agents. Particular attention is given to the role of organic acids, essential oils, phenolic compounds, nanofillers, and natural reinforcements in controlling morphology, crystallinity, interfacial interactions, and thermal–mechanical behavior. In addition, the contribution of bioactive additives to antimicrobial and antioxidant functionality is discussed as an emerging multifunctional feature of some TPS/polyester systems. Finally, current limitations related to long-term stability, scalability, and life cycle assessment are highlighted, identifying key challenges and future research directions for the development of advanced biodegradable materials with tailored properties. Full article

Crypto asset markets are often described as globally integrated. However, empirical evidence suggests that they remain segmented across exchanges and jurisdictions. One notable example is the Korean premium (i.e., Kimchi premium), which refers to persistent price gaps between Korean exchanges and offshore venues. The Korean market accounts for a substantial share of global crypto trading activity. Therefore, this segmentation can affect price discovery and create opportunities for systematic trading. Motivated by the Korean premium, this study introduces the Korean Venue Share Indicator (KVSI). Based on the price discovery literature, KVSI is an interpretable venue-level indicator that uses the relative trading volume share between Korean and global exchanges. This study integrates KVSI into the state space of multiple reinforcement learning algorithms to evaluate whether venue-level information improves trading decisions. The results show that the proposed model with KVSI achieves statistically significant improvements in cumulative return (CR), Sharpe ratio (SR), and maximum drawdown (MDD) compared to the baseline model without KVSI. It also achieves higher CR and mixed effects on risk metrics (SR, MDD) relative to benchmark strategies. Additional analyses indicate that the performance gains from KVSI are market-regime-dependent. Overall, the findings have practical implications for developing cross-market systematic trading strategies by leveraging a venue-level indicator as a proxy for market segmentation. Full article

Background/Objectives: This ecological study aimed to investigate changes in the time-varying reproduction number (Rt) of SARS-CoV-2 across six regions of Massachusetts from 2020 to 2022 and to evaluate the impact of various nonpharmaceutical interventions (NPIs) implemented in 2020 by examining associated changes in the Rt. Methods: COVID-19 incident case data from the Johns Hopkins University database were adjusted for reporting delays using deconvolution and for underreporting via a Poisson-distributed multiplier of 4. Negative and zero counts were corrected using imputation. Rt was estimated using R package EpiEstim (Version 2.2-4) with a 7-day sliding window from 2020 to 2022 and with non-overlapping time windows between policy changes in 2020. Results: From 2020 to 2022, Massachusetts experienced five COVID-19 surges, linked to the wild-type strain and emerging variants, with Rt exceeding 1 during each wave and stabilizing at or dropping below 1 during low-incidence phases. School closure and gathering restrictions, the first major intervention, were associated with a 14.7% statewide reduction in Rt (95% credible interval (CrI): −23.6%, −5.6%), with greater reductions in high-density areas such as Boston (−16.9%; 95% CrI: −26.9%, −7.5%). No statistically significant changes in Rt were found to be associated with other NPIs in 2020, including the mask mandate, reopening phases, travel restrictions and quarantine requirements, and curfews. Conclusions: Our findings highlight the different NPIs’ varying impacts on COVID-19 transmission dynamics across regions in Massachusetts in 2020 and underscore the importance of early interventions for future pandemic preparedness. Full article

Meibomian gland dysfunction (MGD) is a leading cause of dry eye disease, assessable through gland atrophy degree. While deep learning (DL) has advanced meibomian gland (MG) segmentation and MGD classification, existing methods treat these tasks independently and suffer from domain shift across multi-center imaging devices. We propose ADAM-Net, an attention-guided unsupervised domain adaptation multi-task framework that jointly models MG segmentation and MGD classification. Our model introduces structure-aware multi-task learning and anatomy-guided attention to enhance feature sharing, suppress background noise, and improve glandular region perception. For the cross-domain tasks MGD-1K→{K5M, CR-2, LV II}, this study systematically evaluates the overall performance of ADAM-Net from multiple perspectives. The experimental results show that ADAM-Net achieves classification accuracies of 77.93%, 74.86%, and 81.77% on the target domains, significantly outperforming current mainstream unsupervised domain adaptation (UDA) methods. The F1-score and the Matthews correlation coefficient (MCC-score) indicate that the model maintains robust discriminative capability even under class-imbalanced scenarios. t-SNE visualizations further validate its cross-domain feature alignment capability. These demonstrate that ADAM-Net exhibits strong robustness and interpretability in multi-center scenarios and provide an effective solution for automated MGD assessment. Full article

This study presents a comprehensive thermo-structural and modal analysis of a ball screw assembly. Thermal analysis revealed a maximum temperature of 29.1 °C at the ball nut, corresponding to a total rise of 7.1 °C above ambient. The resulting thermal deformation reached 77.81 μm, while the von Mises stress peaked at 53.9 MPa, both within acceptable limits. Modal simulation of 360 modes showed a sharp increase in frequency with mode number and larger deformation patterns at the higher modes. The first two modes dominate the effective mass with the first 8 modes capturing over 90% of the cumulative effective mass. Overall, the results demonstrate stable thermal performance, limited deformation, low stress, and controlled vibrations, confirming the modeling approach and the suitability of 42CrMo4 steel for high-precision ball screw assemblies. Full article