The trifluoroacetate-bridged methylnaphthyl complex [Pd(1-MeNAP)TFA]2 is introduced as a bench-stable, highly soluble palladium source that consistently delivers exceptional catalytic activity. It reacts within minutes with even the most sterically demanding ligands to form monoligated Pd complexes and, upon exposure to nucleophiles, including weak, non-reducing N-nucleophiles, rapidly generates reactive Pd(0) species with the release of inert naphthalene derivatives. Across 15 representative transformations, catalysts generated in situ from [Pd(1-MeNAP)TFA]2 enable substantial reductions in reaction temperature, often by 80°C, while preserving established ligands and reaction conditions, thereby providing a drop-in solution to existing reactivity limitations. As a result, arylations of amides, carbamates, sulfonamides, amidines, ureas, cyclopropylamines, and trifluoroethylamines can be performed at room-temperature with markedly improved functional-group tolerance and compatibility with sensitive, coordinating heterocycles. Mechanistic studies reveal that catalyst activation, rather than catalytic turnover, has been the principal bottleneck in many cross-coupling reactions.
Faults in aero-engine rotating components account for more than 60% of total failures, and their early features are easily masked by noise under complex conditions. Traditional single-sensor diagnosis suffers from low feature utilization, poor interpretability, and weak cross-condition generalization. This paper proposes a multi-source fault diagnosis method for aero-engines based on an explainable boosted tree, integrating spatiotemporal attention (STA) and adaptive feature selection (AFS). We collect multi-domain data from four standard core sensors widely used in existing engine health management systems and extract multi-dimensional features to build a heterogeneous feature set. Adaptive feature selection is implemented using mutual information and a variance inflation factor. A spatiotemporal attention mechanism is introduced to weight and fuse features effectively. The fused features are used to train an XGBoost classifier, and SHAP values are adopted to quantify feature contributions and improve model interpretability. Uncertainty sources and sensitivity boundaries are quantitatively analyzed to support engineering acceptance. The method achieves high sensitivity to early weak faults and stable uncertainty under complex operating conditions. Tests on a fault simulation test rig show that the proposed method achieves 99.2% diagnosis accuracy and 97.5% cross-condition generalization accuracy, outperforming conventional models. It can identify early weak fault signatures, clarify key fault indicators, and provide a quantitative basis for fault tracing and maintenance decision-making. The method employs a standard sensor suite without additional hardware costs, features lightweight computation and low inference overhead, and delivers clear economic benefits by reducing false alarms, avoiding unplanned downtime, and optimizing maintenance resources. It offers a reliable, cost-effective solution for aero-engine fault diagnosis under complex operating conditions.
With low melting points and viscosities, linear ether-based solvents effectively lower the Na+ desolvation energy barrier in low-temperature sodium metal batteries. Among them, 1,2-diethoxyethane (DEE) is considered a promising solvent due to its relatively weak solvating ability at low temperatures; however, its two oxygen atoms remain electronically isolated, forming quasi-chelating bidentate coordination structures with Na+ and still triggering a high desolvation energy barrier under extremely cold conditions. Herein, a novel electrolyte based on the concept of synergistic-competitive coordination is designed by introducing dimethoxymethane (DMM) as a cosolvent into the DEE-based electrolyte, where the lone-pair electrons on oxygen atoms in DMM are partially delocalized, thus reducing its electron-donating capability toward Na+ and reconstructing the Na+ solvation structure. Molecular dynamics simulations reveal that DMM competes with DEE for Na+ coordination sites, thereby weakening the Na+-DEE interaction, lowering the desolvation energy barrier, and promoting anion-involved coordination under severe cold conditions. Consequently, Na||Na symmetric cells run stably for over 3500 h at -40°C, while Na||Cu cells show 99.7% coulombic efficiency over 200 cycles at -20°C. Moreover, NaFe1/3Ni1/3Mn1/3O2||Na full cell retains 78.7% capacity after 200 cycles at -20°C, while Na3V2(PO4)3||Na full cell maintains an impressive 99.2% reversible capacity over 300 cycles at -40°C.
BackgroundCerebral palsy (CP) football is an adapted version of mainstream football in which para-athletes with neuromuscular impairments compete, characterized by intermittent physical demands such as linear and curvilinear sprints.PurposeThis study aimed to examine inter-limb performance during curvilinear running sprints by analyzing the differences and relationships between linear and curvilinear sprinting, and by comparing sprint performance between footballers with CP and able-bodied players.Research DesignA descriptive cross-sectional study was conducted, evaluating linear and curvilinear sprint capabilities.Study Sample and Data CollectionTwenty-eight male football players completed a 17-m linear sprint and two trials per side of a curvilinear sprint for intra- and inter-group comparisons.ResultsSignificant differences were observed between footballers with and without CP in linear (p < 0.01) and curvilinear sprint performance on both the good (p < 0.01) and weak sides (p < 0.01). No between-group differences were found for the curvilinear sprint deficit (p > 0.05). Inter-limb comparisons during the curvilinear sprint test showed significant differences in time and velocity for both the CP group and CG (p < 0.01). Across both groups, 17-m linear sprint time was significantly faster than curvilinear sprint performance on either side (p < 0.05). A significant association was found between the good and weak sides in curvilinear sprint performance (p < 0.01). In the CP group, linear sprint performance was significantly associated with curvilinear sprints on both sides (p < 0.05), whereas no such association was found in the CG (p > 0.05).ConclusionsIn conclusion, this study highlights inter-limb differences and reduced sprint performance in footballers with CP compared to an able-bodied group of players. Identifying specific differences in curvilinear and linear sprint performance may inform targeted training programs, support coaching and training decisions, and inform future classification research based on impairment-related performance effects.
The timing of spring onset is a widely used indicator of climate change impacts, yet estimates of phenological trends depend critically on the choice of reference climate period. Using long-term daily air temperature records from 21 meteorological stations across Estonia, this study examines how different climatological normals influence estimates of spring onset timing and its change. Spring onset was defined as the sustained transition of mean daily air temperature above 5 °C and analysed across four overlapping reference periods (1965-1990, 1971-2000, 1981-2010, and 1991-2020). Mean spring onset dates vary substantially among reference periods, demonstrating that the concept of an "average" spring is sensitive to the selected normal. Cumulative changes derived from linear trends reveal a widespread advancement of spring onset over 1965-2020, with particularly strong shifts at several inland and coastal stations. When contrasting equal-length 30-year normals (1971-2000 vs. 1991-2020), trend magnitudes are generally weaker in the most recent period and, at some stations, near zero or positive. Comparison across reference periods indicates pronounced temporal heterogeneity in phenological responses. While some stations exhibit strong advances during the late twentieth century followed by weakening in the most recent climate normal, others show sustained strong change or weak and inconsistent responses. These patterns cannot be adequately described by a single linear trend and do not follow a simple geographic gradient. The results demonstrate that reference period selection can substantially affect both the magnitude and interpretation of phenological trends. It is therefore recommended that phenological studies explicitly report reference periods and, where possible, compare trend estimates across multiple climatological normals to improve the robustness and transparency of climate impact assessments.
Systemic inflammation is influenced by regular physical activity and diet. While moderate exercise can transiently alter inflammatory markers, high-intensity activity may increase muscle turnover without substantially elevating systemic inflammation. The combined effects of physical activity and dietary inflammatory potential in healthy young men remain poorly defined. In this cross-sectional observational study, 233 healthy men aged 18-30 years were categorized according to physical activity level: low (NA, n = 52), moderate (A, n = 93), and high (S, n = 88). Anthropometry and body composition were assessed using bioelectrical impedance. Dietary intake was recorded over 4 days and used to calculate the Dietary Inflammatory Index (DII). Blood samples were collected and analyzed for complete blood counts, high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA), and creatine kinase (CK). Differences between groups were evaluated using the Kruskal-Wallis test with Dunn's post hoc correction, and principal component analysis (PCA) was performed to explore multivariate inflammatory patterns. The highest BMI, fat percentage, and DII were observed in low-activity men, whereas fat-free mass and CK activity were greatest in highly active men. Slightly higher systemic inflammatory markers (hs-CRP and SAA) were observed in moderately active men compared to other groups. PCA revealed two principal axes: PC1 representing systemic inflammation and PC2 representing leukocyte distribution. Weak associations were found between DII and these components, indicating a limited link between dietary inflammatory potential and circulating inflammatory biomarkers. Body composition is strongly influenced by physical activity, with high activity promoting lean mass and moderate activity associated with modest elevations in inflammatory markers. Dietary inflammatory potential was only weakly associated with systemic inflammation, suggesting that exercise-induced physiological stress may play a more prominent role in shaping inflammatory profiles in healthy young men.
Camel production plays a crucial role in supporting the livelihoods and food security of pastoral and agro-pastoral communities across Ethiopia, Kenya, Somalia, and Djibouti in the Horn of Africa. This review systematically synthesizes peer-reviewed studies and regional reports published between 2000 and 2026, identified through structured database searches and screened using defined inclusion criteria, to evaluate camel milk production systems, traditional utilization, physicochemical and nutritional quality, safety, and value chain dynamics across the region. Camel milk is widely consumed raw or fermented and serves as a key dietary resource. Traditional practices across the region involve spontaneous fermentation for product formation, the production of sour milk products and camel milk tea, and the incorporation of camel milk into various local dishes; however, systematic documentation of these practices remains limited. Compared with bovine and caprine milk, camel milk generally contains lower fat and lactose levels, higher vitamin C and mineral concentrations, and distinct protein characteristics, including lower κ-casein content and the absence of β-lactoglobulin, which influence digestibility and processing properties. Reported fat content ranges from approximately 2.5 to 4.5% and protein from 2.5 to 3.9%, while vitamin C levels substantially exceed those of bovine milk. These features confer nutritional advantages but also create technological challenges, such as weak coagulation and extended fermentation time. Despite increasing urban and cross-border demand, the sector remains constrained by feed shortages, limited veterinary services, inadequate processing facilities, informal marketing systems, and hygiene limitations that contribute to microbial contamination. Key gaps include a lack of harmonized quality standards, limited comparative data on milk composition and microbiological safety, weak cold-chain infrastructure, and poor value-chain coordination. Strengthened hygiene, standardized quality protocols, improved processing and cold-chain systems, and coordinated institutional support are essential to enhance commercialization, safety, and regional integration.
In order to explore the effect of pH value of the solution on the growth characteristics of electro-hydro mixed branches of cross-linked polyethylene (XLPE) cables, an electro-hydro mixed branch experimental platform with different pH values was built to accelerate the aging of XLPE cables. The growth characteristics of electro-hydro mixed branches under different pH environments were systematically observed and analyzed by combining macroscopic dielectric properties test with microscopic morphology detection. The macroscopic test results show that the aging degree of the cable is more serious in the acidic or alkaline environment. When there are electrical tree defects in the insulation, acidic or alkaline solutions with different pH values will promote the accelerated aging of mixed branches, and the acceleration effect of acidic environment is more significant. After microscopic detection of sample slices with different acidity and alkalinity, it was found that both acidic and alkaline environments could accelerate the growth of mixed branches. On the basis of electrical trees, the strong acid and strong alkali environment was more suitable for the development of mixed branches than the weak acid and weak alkali environment, and the promotion effect of acidic solution was more prominent. At the same time, this study also deeply analyzed the conversion mechanism of electrical tree to water tree in cables under different pH conditions. Finally, through the correlation analysis between the dielectric performance parameters and the branch density of different groups of samples, the fitting model of the branch density on the macroscopic dielectric performance parameters is obtained by curve fitting, which provides an effective non-destructive testing method for cable multi-branch aging. These results reflect the structure-property relationship of XLPE polymer under acid-base corrosion and electric field coupling and reveal the microstructure degradation mechanism of polyethylene insulation.
The incorporation of plastic waste into cement-based materials offers a promising strategy for improving sustainability; however, it is often associated with reduced mechanical performance due to weak interfacial bonding. This study investigates the effect of metakaolin on the interfacial transition zone (ITZ) and mechanical properties of cement mortars modified with polyethylene terephthalate (PET) flakes used for the partial replacement of natural sand. Mortars containing 10 and 50 wt% metakaolin (as cement replacement) and 5 vol.% PET flakes (as sand replacement) were prepared and tested after 28 days of curing. Compressive and flexural strength were evaluated, and microstructural analysis was conducted using scanning electron microscopy (SEM) with a focus on the ITZ. The results indicate that the incorporation of PET flakes leads to a reduction in mechanical properties due to the formation of a porous and weak ITZ. However, the addition of 10 wt% metakaolin significantly improved mechanical properties, enabling PET-modified mortars to achieve strength comparable to the reference mix. SEM observations revealed that metakaolin contributed to the refinement of the microstructure and reduction in ITZ porosity, which enhanced interfacial bonding and improved stress transfer between PET particles and the cement matrix. These findings demonstrate that metakaolin can effectively mitigate the negative effects associated with PET incorporation by improving the microstructural characteristics of the ITZ, thereby enhancing the performance of sustainable cement-based composites.
Predicting missing segments in partially observed functions is challenging due to infinite-dimensionality, complex dependence within and across observations, and irregular noise. These challenges are further exacerbated by the existence of two distinct sources of variation in functional data, termed amplitude (variation along the y -axis) and phase (variation along the x -axis). While registration can disentangle them from complete functional data, the process is more difficult for partial observations. Thus, existing methods for functional data prediction often treat phase variation as negligible. Furthermore, they typically require precise model specifications and/or rely on computationally intensive tools, such as bootstrapping, to construct prediction intervals. We propose a unified registration and prediction approach for partially observed functions using conformal prediction. Our method integrates registration and prediction in one algorithm while ensuring exchangeability through carefully constructed predictor-response pairs. Using a neighborhood smoothing algorithm, the framework produces pointwise prediction bands with finite-sample marginal coverage guarantees under weak assumptions. The method is easy to implement, computationally efficient, and permits simple parallelization. Numerical studies and real-world data examples demonstrate the effectiveness and practical utility of our method. Supplementary materials for this article are available online.
Autism spectrum disorder (ASD) has been associated with alterations in the gut microbiota and its metabolites, particularly short-chain fatty acids (SCFAs) and microbiota-derived tryptophan catabolites, which may influence neurodevelopment through immune and epigenetic mechanisms. We investigated whether stool SCFAs and tryptophan-pathway metabolites differ between children with ASD and typically developing controls, and whether these metabolites associate with ASD severity and systemic biochemical signatures. In this cross-sectional study, we analyzed stool samples from 229 children (160 with ASD, 69 controls) with complete SCFA and tryptophan-metabolite data, while urine metabolomics data were available for a subset and were used for exploratory stool-urine integration analyses. Children with ASD and controls were similar in age, but the ASD group had a higher proportion of males. Absolute concentrations of individual SCFAs, total SCFAs, and derived indices were broadly comparable between groups; nominal differences in propionate/acetate ratio and caproate did not remain significant after false discovery rate correction. Similarly, stool tryptophan-pathway metabolites reported as ng/a.u. based on the NanoDrop-derived proxy (tryptophan, kynurenine, indole-3-acetic, indole-3-lactic, indole-3-propionic, indole-3-aldehyde, N-acetyl-tryptophan, serotonin, melatonin, tryptamine) and functional ratios (kynurenine/tryptophan, indole-derived/tryptophan, serotonin/tryptophan) showed no robust ASD-control differences; N-acetyl-tryptophan was nominally higher in ASD but did not survive multiple-testing correction. In the ASD subgroup with available Childhood Autism Rating Scale (CARS) data (n = 34), SCFA and tryptophan indices showed only weak, non-significant correlations with global ASD severity. In contrast, correlation analyses revealed two coherent metabolic modules, i.e., an SCFA block with very strong internal correlations among individual SCFAs and total SCFAs and a tryptophan block with strong correlations between metabolites and their normalized ratios, while cross-module correlations were modest. These results indicate that stool SCFA and microbiota-derived tryptophan profiles do not robustly distinguish ASD from controls in this cohort, but they form stable metabolic modules compatible with microbiome-epigenome frameworks.
Lodging is a major constraint limiting grain yield in dry direct seeding rice (DDSR), yet the key traits and phenotypic relationships governing lodging resistance in japonica varieties adapted to this system remain poorly understood. This study evaluated 79 japonica accessions over two years in Shenyang, Northeast China, to dissect phenotypic variation in lodging index and identify ideotypes for breeding. Based on hierarchical clustering, varieties were classified into strong lodging resistance (SLR), medium lodging resistance (MLR), and weak lodging resistance (WLR) types, with SLR varieties achieving lodging indices 27.4-31.8% lower than those of MLR and 63.2-83.8% lower than those of WLR varieties. SLR varieties reduced lodging risk by coordinately balancing whole-plant bending moment and stem breaking resistance: plant height and center-of-gravity height were 5.2-10.7% lower, while basal internode bending stress was 27.9-81.9% higher than in other types. Structural equation modeling identified culm dry weight, inner diameter, and culm phenotype index as primary determinants of lodging variation. Notably, despite 11.0-13.7% fewer spikelets per panicle, SLR varieties maintained grain yields comparable to those of WLR varieties through compensatory increases in grain-filling rate (6.7-7.3%) and 1000-grain weight (8.1-8.7%). These findings demonstrate that optimizing basal internode structure and enhancing culm tissue density can simultaneously improve lodging resistance and preserve yield potential, providing a practical framework for breeding lodging-resistant, high-yielding japonica varieties for DDSR systems in Northeast China.
Mine disasters require urgent lifeline setup in confined tunnels, but manual rescue in unstable accident zones carries huge safety risks. Coal mine rescue robots (CMRRs) have become key equipment to replace manual rescue. However, traditional remote-controlled CMRRs suffer from low autonomy and weak environmental perception capability, which have become critical bottlenecks for field application. As an emerging technology in the mining field, digital twin enables high-precision virtual-real mapping and on-site operation guidance, providing a novel solution to the above problems. To realize autonomous navigation and digital twin visualization of the CMRR, this paper first carries out targeted hardware retrofits on the CMRR platform, upgrades environmental perception, communication transmission and motion control modules, and lays a solid hardware foundation for subsequent algorithm design and system implementation. Aiming at the complex post-disaster underground environment, a digital twin-integrated CMRR system is constructed. For intelligent autonomous navigation, this study investigates a 3D point cloud-based autonomous navigation framework and proposes a slope-fitting method as well as a maximum arrival probability obstacle avoidance method based on Bézier curve trajectories. For environmental visualization, a digital twin interactive interface is built to monitor gas and other environmental parameters in real time, and accurately reconstruct underground roadway structures based on point cloud data. This design not only ensures the robot's autonomous obstacle avoidance but also helps rescuers grasp underground conditions in advance. Field tests in a simulated post-disaster mine with complex terrain show that the system can stably complete autonomous navigation tasks, maintain stable motion control under dynamic interference, and provide accurate and reliable environmental data for rescue decisions, verifying its feasibility and effectiveness in harsh mine rescue scenarios.
Background/Objectives: University life is often accompanied by unhealthy lifestyle behaviors, reduced physical activity, lower fitness levels, and a high prevalence of mental health symptoms. Daily step count has emerged as a practical indicator of habitual physical activity; however, evidence on its association with cardiorespiratory fitness and symptoms of depression, anxiety, and stress in university students remains limited. Therefore, this study examined the association of daily step count with cardiorespiratory fitness and symptoms of depression, anxiety, and stress in university students. Methods: This cross-sectional association study included a convenience sample of 120 students aged 18 to 25 years from a single university. Daily step count was assessed over seven consecutive days using a Xiaomi Mi Band 9. Cardiorespiratory fitness was evaluated with the 20 m shuttle run test, and symptoms of depression, anxiety, and stress were measured using the Depression, Anxiety and Stress Scale-21 Items (DASS-21). Partial correlations, ANCOVA, MANCOVA, binary logistic regression, and restricted cubic spline models were performed after adjustment for sex, age, and socioeconomic status. Results: Higher daily step count was associated with greater cardiorespiratory fitness and with lower symptoms of depression, anxiety, and stress, although the associations with mental health symptoms were weak and not uniform across outcomes. Restricted cubic spline models showed inverse non-linear associations for mental health symptoms, with steeper inverse gradients at lower step-count levels and a tendency to level off at higher volumes, approximately around 9000 steps/day. For cardiorespiratory fitness, the association was positive across the step-count range. Step counts around 7500 steps/day were associated with lower odds of elevated symptoms of depression, anxiety, and stress. Conclusions: A higher daily step count was associated with more favorable mental health symptom profiles and greater cardiorespiratory fitness in this sample of university students.
Public health organizations in Canada play a central role in chronic disease prevention (CDP) but face persistent challenges, including system restructuring, persistent underfunding and shifting policy priorities. The growing complexity of these issues warrants qualitative insight to complement quantitative reports capturing CDP organizations' perspectives. The Public Health Organizational Capacity Study (PHORCAST) is a repeat Canada-wide census of public health organizations engaged in primary CDP at national, provincial, territorial and regional population levels. In 2023, senior managers and staff with in-depth knowledge of their organizations' CDP activities completed a questionnaire that requested optional comments via an open-ended question. The responses were analyzed using qualitative descriptive methods and inductive content analysis to identify and organize recurring issues. Theme frequencies are reported descriptively to indicate prominence across organizations and not to quantify meaning. Across the 55 organizations, 125 coded references to barriers to CDP were synthesized into five key themes: organizational capacity and program delivery challenges (n = 38), including chronic underfunding, workforce shortages and limited infrastructure; COVID-19 pandemic disruptions causing staff redeployment and prolonged service interruptions (n = 30); policy and systemic barriers (n = 28), including political interference and poor interjurisdictional coordination; fragile partnerships and the need for stronger intersectoral collaboration (n = 16); and difficulties engaging diverse communities, digital access issues and lack of culturally responsive programming (n = 13). CDP efforts in Canada are constrained by structural, operational and contextual barriers. Addressing these challenges requires sustained investment, coherent policies and stronger cross-sector partnerships. Alors que les organismes de santé publique au Canada jouent un rôle central dans la prévention des maladies chroniques, ils sont confrontés à des défis persistants, notamment à la restructuration des systèmes, à un sous-financement chronique et à des changements de priorités en matière de politique. La complexité croissante de ces enjeux justifie l’apport de données qualitatives en complément des rapports quantitatifs, qui présentent le point de vue des organismes de prévention des maladies chroniques. L’étude sur les capacités organisationnelles de santé publique (PHORCAST) est un recensement itératif à l’échelle du Canada des organismes de santé publique mobilisés dans la prévention primaire des maladies chroniques à l’échelle de la population régionale, territoriale, provinciale et nationale. En 2023, les gestionnaires principaux et le personnel ayant une connaissance approfondie des activités de prévention des maladies chroniques de leur organisme ont répondu à un questionnaire suscitant des commentaires facultatifs par l’entremise d’une question ouverte. Les réponses ont été analysées à l’aide de méthodes qualitatives descriptives et d’une analyse inductive du contenu afin d’identifier et d’organiser les enjeux récurrents. Les fréquences des thèmes sont présentées de manière descriptive afin d’indiquer leur importance au sein des organismes et non pour quantifier leur signification. Portant sur 55 organismes, 125 références codées aux obstacles à la prévention des maladies chroniques ont été synthétisées autour de 5 thèmes clés : les défis liés aux capacités organisationnelles et à la mise en oeuvre des programmes (n = 38), notamment le sous-financement chronique, la pénurie de main-d’oeuvre et des infrastructures limitées; les perturbations causées par la pandémie de COVID-19, qui ont entraîné un redéploiement du personnel et des interruptions de service prolongées (n = 30); les obstacles politiques et systémiques (n = 28), notamment l’ingérence politique et la mauvaise coordination entre administrations; les partenariats fragiles et la nécessité d’une collaboration intersectorielle plus forte (n = 16) et enfin les difficultés à mobiliser des collectivités diverses, les problèmes d’accès au numérique et le manque de programmes adaptés culturellement (n = 13). Les efforts en matière de prévention des maladies chroniques au Canada sont limités par des obstacles structurels, opérationnels et contextuels. Pour relever ces défis, il faut des investissements soutenus, des politiques cohérentes et des partenariats intersectoriels plus solides. Chronic underfunding and workforce shortages are major barriers to primary chronic disease prevention (CDP) across Canada. Policy fragmentation, political interference and weak interjurisdictional coordination continue to undermine long-term CDP capacity. The COVID-19 pandemic intensified existing challenges through staff redeployment and disruptions to CDP programs. Reaching diverse communities is hindered by digital inequities and a lack of culturally responsive approaches. Partnerships are essential but remain fragile, which emphasizes the need for more stable, crosssector collaboration frameworks. Le sous-financement chronique et la pénurie de main-d’oeuvre sont des obstacles majeurs à la prévention primaire des maladies chroniques à l’échelle du Canada. La fragmentation des politiques, l’ingérence politique et la faible coordination entre administrations continuent d’affaiblir les capacités en matière de prévention des maladies chroniques à long terme. La pandémie de COVID-19 a entraîné l’intensification des défis déjà présents en raison du redéploiement du personnel et des perturbations des programmes de prévention des maladies chroniques. Les inégalités numériques et le manque d’approches adaptées culturellement empêchent d’atteindre les collectivités dans leur ensemble. Les partenariats sont essentiels, mais demeurent fragiles, ce qui fait ressortir le besoin de mettre en place des cadres de collaboration intersectoriels plus stables.
In this work, we employ first-principles density functional theory (DFT) calculations to systematically investigate the interfacial electronic properties and contact behavior of a Dirac-metallic Dirac-FeB2/MoS2 van der Waals (vdW) heterostructure. The Dirac-FeB2/MoS2 system is found to be energetically, mechanically, thermally, and dynamically stable, indicating its potential experimental feasibility. Notably, the heterostructure forms an n-type Schottky contact with an ultralow electron barrier height of 0.125 eV and a low tunneling resistance of 1.82 × 10-9 Ω cm2. This superior contact performance is attributed to the delocalized Dirac electrons and the weak Fermi-level pinning at the interface, providing key insight into the role of Dirac metals in contact engineering. Furthermore, the Schottky barrier can be effectively tuned by an external electric field, enabling a reversible transition from Schottky to ohmic contact. These findings highlight the promise of Dirac metallic FeB2 as an efficient electrode material and offer practical guidance for the design of high-performance 2D nanoelectronic and optoelectronic devices with reduced contact resistance.
Postoperative delirium (POD) is a common and severe complication in older surgical patients. Although systemic inflammation and frailty are established risk factors, the predictive value of the lymphocyte-to-monocyte ratio (LMR) across different frailty strata remains unclear. This study aimed to evaluate the association between preoperative LMR and POD and to determine whether this relationship varies according to frailty status. We performed a retrospective analysis of prospectively collected data from a multicenter cohort of 6,475 patients aged ≥65 years undergoing elective non-cardiac, non-neurosurgical surgery in China. Preoperative LMR was calculated from preoperative blood tests. Logistic regression and restricted cubic spline (RCS) analyses were used to assess the association between preoperative LMR and POD, with further stratified analyses performed across different frailty groups. Among 6,475 patients, 789 (12.2%) developed POD. After adjustment for potential confounders, higher LMR was independently associated with a lower risk of POD (per 1-unit increase: OR 0.94, 95% CI 0.90-0.98, P = 0.009). A significant inverse dose-response relationship was observed. Compared with the lowest quartile (Q1), the adjusted ORs (95% CIs) for Q2-Q4 were 0.73 (0.59-0.90), 0.69 (0.56-0.86), and 0.68 (0.54-0.85), respectively. Stratified analyses revealed distinct patterns across frailty status: a significant nonlinear association was observed only in pre-frail patients (Q4 vs. Q1: adjusted OR 0.69, 95% CI 0.50-0.95; P for nonlinearity = 0.003). In contrast, the association in frail individuals was weaker and primarily linear, while no significant association was observed in robust patients. Preoperative LMR is independently associated with POD in older surgical patients. Its predictive value varies across frailty strata, with the association most evident among pre-frail individuals.
Background/Objectives: Identifying the factor most strongly associated with patients' quality of life (QoL) is crucial for establishing treatment goals focused on improved recovery. This study aimed to determine whether sociodemographic factors, negative, or depressive symptoms have the strongest association with QoL. Methods: Inpatients diagnosed with schizophrenia were recruited. We collected data on sociodemographic factors, asked patients to rate their well-being on a subjective well-being scale, and evaluated their psychopathology using observer-rated psychometric scales (Positive and Negative Symptoms Scale (PANSS), Brief Negative Symptoms Scale (BNSS), and Calgary Depression Scale for Schizophrenia (CDSS) as well as self-rated scales (Self-evaluation Negative Symptoms Scale (SNS). QoL was evaluated using Short-Form 36 (SF-36). Patients were also divided into primary, prominent, and predominant negative symptom groups. We conducted correlation and linear regression analyses to identify which factors were most strongly associated with QoL. Results: In this study, 323 participants were included. The CDSS total score showed the strongest correlation with QoL scores, followed by negative symptoms assessed with the SNS. Positive and negative symptoms, assessed using either the PANSS or the BNSS, showed weak or insignificant correlations with QoL. Among sociodemographic factors, the subjective well-being score, previous history of hospitalization, or suicide attempts had the strongest correlation with QoL. CDSS scores were the variable with the strongest independent association with QoL in regression analysis. Conclusions: Depressive symptom severity showed the strongest and most consistent association with QoL across both correlation and multivariable analyses. These findings are hypothesis-generating and require longitudinal confirmation.
Flunarizine is a calcium channel blocker widely used in neurological disorders; however, its low aqueous solubility may influence formulation stability and drug dispersion in polymer-based systems. The present study aimed to evaluate the compatibility of flunarizine with selected excipients and to investigate its incorporation into polymeric hydrogel matrices. Binary mixtures of flunarizine with excipients such as hydroxypropyl-β-cyclodextrin, polyethylene glycol (PEG 6000), Tween 20, gelatin, and citric acid were prepared and characterized using Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG/DTG), and high-performance liquid chromatography (HPLC). The FTIR spectra of the analyzed samples do not reveal the appearance of new absorption bands that may indicate chemical interactions; instead, minor spectral variations were observed due to weak intermolecular interactions within the polymer network. Thermal analysis revealed decomposition patterns consistent with those of the individual components, suggesting the absence of significant incompatibilities. A validated RP-HPLC method enabled sensitive and reliable quantification of flunarizine in the analyzed systems, with a limit of detection (LOD) of 0.05 µg/mL and a limit of quantitation (LOQ) of 0.16 µg/mL. Accuracy testing showed average recovery rates of 100% across 80-120% spiking levels. Overall, the results support the compatibility of flunarizine with the investigated excipients and the suitability of the studied hydrogels as potential drug delivery matrices.
To address the limitations of existing vehicle trajectory prediction methods, including insufficient modeling of dynamic inter-vehicle interactions, weak temporal continuity of complex driving intentions such as lane-changing, and high uncertainty in future trajectory prediction, this paper proposes a vehicle trajectory prediction method that integrates Dynamic Graph Neural Networks (DyGNN) with Transformer. Specifically, a time-varying interaction graph is constructed to model the dynamically evolving topological interaction relationships among vehicles, while a Transformer encoder is employed to extract temporal dependency features from historical trajectory sequences. In this way, the joint representation of spatial interaction information and temporal evolution information is achieved, thereby improving the accuracy and continuity of driving intention recognition in complex traffic scenarios. On this basis, driving intention is further introduced into the trajectory prediction process as a prior constraint, which effectively reduces the uncertainty of future trajectory prediction. Comparative experiments on real-world traffic datasets demonstrate that the proposed method maintains low prediction errors across different prediction horizons, showing good effectiveness and robustness.