Understanding the scale-dependent mechanisms linking landscape patterns to ecosystem services is crucial for sustainable land management, especially in fragmented hilly regions. This study, conducted in the hilly areas of southern China, aimed to quantitatively unravel these mechanisms at an optimal spatial scale. We first identified 14,400km2 as the scale where landscape metrics stabilized. Using Spatial Error Models (SEM) to control for spatial autocorrelation, we analysed the distinct effects of landscape configuration on key ecosystem services. At the class level, forest aggregation was a consistent positive driver for multiple services; for example, it maintained a stable, significant positive relationship with carbon sequestration across all study years (P < 0.01). Conversely, farmland edge (total edge) significantly promoted nutrient export (P < 0.001), highlighting a functional contrast with natural landscapes. At the landscape level, total edge exhibited a consistent positive effect on several ecosystem services (P < 0.001), whereas increased landscape evenness was a primary inhibitory factor, showing a significant negative correlation with habitat quality (P < 0.001) and a strengthening negative effect on nutrient retention over time (P < 0.01). These findings provide a scale-specific, quantitative foundation for spatial planning, underscoring the necessity of maintaining forest connectivity and strategically managing agricultural-natural land interfaces to enhance ecosystem services bundles in heterogeneous landscapes.

Combining biomarkers and anthropometric indicators is a common way to improve predictive efficacy. Yet the effect of the C-reactive protein-triglycerides-glucose index (CTI) and its derivatives on stroke is unknown. This study aims to explore their association with stroke and compare their predictive value. A total of 10,070 participants from the China Health and Retirement Longitudinal Study (CHARLS) were included. Covariate selection was performed using the Boruta algorithm and complementary methods. The predictive performance of various indicators was compared via metrics including area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to determine the optimal predictive indicator. Subsequently, Cox proportional hazards models, trajectory pattern analysis, restricted cubic spline (RCS) analysis, Kaplan-Meier curves were used to investigate its association with stroke. From 2011 to 2020, 950 participants (9.43%) experienced an incident stroke during follow-up. CTI derivatives outperformed standalone CTI in prediction, with CTI-waist-to-height ratio (CTI-WHtR) exhibiting the strongest association with stroke risk. In the fully adjusted model, each one-unit increase in CTI-WHtR linked to a 73% higher risk of stroke [odds ratio (OR) = 1.73, 95% confidence interval (CI) 1.45-2.07], and participants in the highest quartile of CTI-WHtR had more than double the risk compared with those in the lowest quartile (OR = 2.20, 95% CI 1.71-2.83). There were three distinct trajectories of CTI-WHtR over time. Compared with Cluster 1 (low value rising), Cluster 2 (stable high value) was associated with a 69% higher risk of stroke (OR = 1.69, 95% CI 1.34-2.13), and Cluster 3 (moderate value rising) with a 26% higher risk (OR = 1.26, 95% CI 1.06-1.52). A clear dose-response relationship was observed between CTI-WHtR and stroke risk, with risk increasing sharply when CTI-WHtR exceeded 2.52. The consistent positive linear association between CTI-WHtR and stroke risk highlights its potential utility as a clinical and public health indicator. Monitoring and maintaining optimal CTI-WHtR levels may aid in identification of individuals at elevated stroke risk. Graphical Abstract.

The rapid emergence of antibiotic-resistant bacteria demands the development of efficient antimicrobial agents. Here, single ZnO, CuO, and Ag nanoparticles (NPs) and copper/silver-doped nanocomposites (NCs) with high porosity were prepared employing bottom-up combustion synthesis techniques. The better optoelectrical and charge transfer characteristics of modified NCs have been confirmed from the UV-vis-DRS, PL, and CV analysis. The inclusion of copper in the ZnO lattice causes a shift towards a high angle in the XRD pattern analysis. However, silver forms a separate crystal or aggregate with ZnO (ZnO/Ag) and enhances the charge transfer process through the interface. The XRD and HRTEM image analysis verified the development of Cu-ZnO/Ag/CuO NCs. The antibacterial activity was optimized by leveraging the synergistic effects of Ag, CuO, and ZnO and assessing the influence of calcination temperature. The bacterial deactivation ability of HSs NCs is significantly higher than that of bare ZnO, confirming the existence of a synergistic effect. The maximum zone of inhibition is found to be 22mm on S. pyogenes bacteria. Here, the developed Cu-ZnO/Ag/CuO heterostructures (HSs) have been found to be a promising material for antibacterial activities. Thus, the synthesized materials have excellent future outlooks in large-scale real-life biomedical applications.

Hyperactivity is frequently observed in individuals with autism spectrum disorder (ASD) and significantly affects various aspects of life. This underscores the critical need for effective intervention methods tailored to the needs of individuals with ASD. Non-human primate models offer a promising avenue for elucidating the intricate interplay between ASD characteristics and developing individualized therapeutic strategies. This study examined the activity levels and behavioral dynamics in a prenatal valproic acid-induced (VPA) common marmoset model of ASD using ultraminiature data loggers, employing a more detailed approach to behavioral pattern analysis than is traditionally utilized. Although the overall activity levels showed no significant differences, the VPA group exhibited increased activity during specific hours, which is consistent with human ASD studies. Sample Entropy, a statistical measure used to quantify the regularity and unpredictability of time-series data, was higher during daytime in the VPA group, indicating reduced regularity in activity patterns akin to impulsive behavior in ASD. Subtle patterns that were not discernible through simple group comparisons were identified, highlighting the potential of this method as a valuable tool for the behavioral analysis of human ASD. Associations between erratic activity patterns, brief resting intervals, and elevated cortisol levels were observed, all of which correspond to stress phenotypes in individuals with ASD. The findings revealed variations in activity among the adult VPA groups, potentially linked to stress responses. Additionally, VPA juvenile marmosets showed increased locomotor activity in the social interaction test, complementing the adult behavioral findings and suggesting age-dependent manifestations of hyperactivity in this model. This non-human primate model effectively replicates real-world scenarios encountered by individuals with ASD exhibiting hyperactivity, thus holding significant implications for the advancement of personalized therapeutic strategies.

Cognitive fatigue has emerged as a critical concern in educational settings that require sustained mental effort, particularly in Islamic boarding schools implementing dual-curriculum systems. Santri are required to balance intensive Qur’anic memorization with formal general education, creating substantial cognitive demands that may affect learning effectiveness and mental well-being. This study aims to examine the level of cognitive fatigue among santri and to identify key contributing factors within a dual-curriculum pesantren context. A quantitative descriptive design was employed involving 120 students aged 13–18 at Darul Iman Islamic Boarding School, North Lombok, Indonesia. Data were collected using the Pediatric Cognitive Fatigue Scale (PCFS), supported by classroom observations and analysis of study duration, sleep patterns, and memorization load. The findings indicate that most students experience moderate to high levels of cognitive fatigue. Fatigue levels were strongly associated with prolonged daily study time exceeding ten hours, reduced sleep duration, and high Qur’anic memorization intensity, while gender and age were not significant predictors. These results highlight the cumulative cognitive risks of extended academic engagement without adequate rest. This study contributes to the limited empirical literature on student cognitive fatigue in religious education environments. The findings imply the need for pesantren administrators and policymakers to redesign learning schedules by incorporating structured rest periods, balanced memorization targets, and sleep protection strategies to promote healthier and more sustainable learning environments for adolescents in dual-curriculum Islamic boarding schools.

As the core technology of the new energy revolution, lithium-ion batteries have broad development prospects and significant strategic importance. With continuous improvements in energy density, enhanced safety, and breakthroughs in fast-charging technology, lithium-ion batteries will play a more substantial role in fields such as new energy vehicles and energy storage. Nevertheless, the development of the lithium-ion battery industry still faces safety issues related to thermal runaway risks. The intense exothermic reactions during thermal runaway can release flammable gases, potentially leading to uncontrolled combustion or explosions, thereby posing major safety threats. This paper reviews the analysis of gas composition and patterns during lithium-ion battery thermal runaway under different conditions, as well as research on gas explosion characteristics. It introduces advanced methods for gas detection and suppression during thermal runaway and summarizes studies on the chemical kinetic mechanisms and predictive models of gas generation during thermal runaway. These studies provide a scientific basis for improving the reliability of renewable energy storage systems and formulating and refining battery safety standards.

Against the backdrop of rapid urbanization and land development, the degradation of regional ecosystem services and the intensification of ecological risks have become prominent challenges. This study takes the Pinglu Canal Economic Belt—a region characterized by the triple pressures of “large-scale engineering disturbance, karst ecological vulnerability, and port economic agglomeration”—as a case study. Based on remote sensing image data from 2000 to 2020, a landscape ecological risk index was constructed, and regional landscape ecological risk levels were assessed using ArcGIS spatial analysis tools. On this basis, ecological sources were identified by combining the InVEST model with morphological spatial pattern analysis (MSPA),and an ecological resistance surface was constructed by integrating factors such as land use type, elevation, slope, distance to roads, distance to water bodies, and NDVI. Furthermore, the circuit theory method was applied to identify ecological corridors, ecological pinch points, and barrier points, ultimately constructing the ecological security pattern of the Pinglu Canal Economic Belt. The main findings are as follows: (1) Ecological risks were primarily at low to medium levels, with high-risk areas concentrated in the southern coastal region. Over the past two decades, an overall optimization trend was observed, shifting from high risk to lower risk levels. (2) A total of 15 ecological sources (total area 1313.71 km2), 31 ecological corridors (total length 1632.42 km), 39 ecological pinch points, and 15 ecological barrier points were identified, clarifying the key spatial components of the ecological network. (3) Based on spatial analysis results, a zoning governance plan encompassing “ecological protected areas, improvement areas, restoration areas, and critical areas” along with targeted strategies was proposed, providing a scientific basis for ecological risk management and pattern optimization in the Pinglu Canal Economic Belt.

Background/Objectives: Penile squamous cell carcinoma (PSCC) is a rare malignancy with poor prognosis in advanced and recurrent disease, and therapeutic options remain limited. Increasing evidence suggests that the tumor immune microenvironment (TIME), including immune cell composition and spatial organization, plays a critical role in tumor progression and survival outcomes. This study aimed to characterize immune cell density and geospatial clustering patterns within the TIME of PSCC and to evaluate their associations with clinical outcomes. Methods: Multiplex immunofluorescence (mIF) was performed on tumor samples from 57 patients with PSCC using a panel of immune markers to identify lymphoid and myeloid cell populations. Immune cell densities were quantified within tumoral and stromal compartments. Spatial relationships among immune cells and between immune cells and tumor cells were analyzed using point pattern analysis. Survival outcomes, including overall survival (OS), recurrence-free survival (RFS), and cancer-specific survival (CSS), were assessed using Kaplan–Meier methods and Cox proportional hazards models, with analyses stratified by nodal and human papillomavirus (HPV) status. Results: Higher intratumoral and stromal densities of pro-immunogenic M1 macrophages were associated with improved OS. Increased densities of CD3+CD4+ helper T cells in both compartments were also associated with favorable survival outcomes. In contrast, close clustering of pro-tumorigenic M2 macrophages with tumor cells and with one another was associated with worse OS, RFS, and CSS. Bivariate clustering of helper T cells with tumor cells was associated with improved OS, including among patients with node-positive disease. Survival outcomes did not differ significantly by HPV status in patients with high helper T cell clustering. Conclusions: Immune cell density and spatial organization within the TIME are associated with survival outcomes in PSCC. Favorable patterns involving helper T cells and M1 macrophages correlate with improved survival, whereas clustering of M2 macrophages is associated with poorer outcomes, supporting the relevance of spatial immune profiling in this disease.

From rest to focus: pharmacological modulation of the relationship between resting state dorsal attention network dynamics and task-based brain activation.

The rise of e-commerce has led to a notable escalation in product return rates, presenting a substantial difficulty in the administration of fulfillment centers. This study is to examine the impact of consumer purchasing behavior analysis and the classification of product return causes on return rates at IKEA Indonesia fulfillment centers. A quantitative methodology was employed by gathering data via a questionnaire administered to 150 respondents who had engaged in purchases and product returns within the past six months. Data analysis was performed with SmartPLS by evaluating the measurement model (outer model) and the structural model (inner model). The findings indicated that both independent variables have a positive and significant influence on product return rates. The path coefficient for Consumer Purchasing Behavior Analysis (X1) is 0.574 (T-Statistics 13.299; P-Values 0.000), whereas the path coefficient for Product Return Reason Categorization (X2) is 0.456 (T-Statistics 10.989; P-Values 0.000). Both variables concurrently account for 92.7% of the variance in product return rates (R-Square 0.927), indicating a model with exceptionally robust predictive capability. This discovery underscores the significance of an integrative strategy that combines the analysis of customer behavior patterns with the categorization of product return causes in developing data-driven return management strategies. This study offers theoretical advancements in the supply chain management literature, particularly regarding reverse logistics and consumer behavior analytics, alongside practical implications for IKEA Indonesia in formulating policies aimed at decreasing product return rates by enhancing the accuracy of product information, quality control, and logistics processes.

Father-child interactions in autism: A multivariate analysis of behavioral patterns in Italian dyads.

The histologic diagnosis of some cases of bovine dermatitis can be challenging. We investigated the predominant histologic patterns of dermatitis in cattle, to propose histologic pattern analysis as a diagnostic approach. Sixty-two cases of bovine dermatitis with confirmed etiologic diagnoses were selected in a 20-year retrospective study. The cases included 13 different primary and secondary diseases, ranging from infectious (48/62, 77%) to toxic/irritant-associated diseases (14/62, 23%). The cutaneous lesions were histologically classified into 11 dermatitis patterns, adapted from those described for small animals. Nodular to diffuse dermatitis (22/62, 34%), perivascular dermatitis (14/62, 23%), necrotizing dermatitis (11/62, 18%), and intraepidermal pustular dermatitis (10/62, 16%) were the most common patterns, followed by panniculitis (3/62, 5%); vasculitis (1/62, 2%); and perifolliculitis, folliculitis, or furunculosis (1/62, 2%). The nodular to diffuse, perivascular, necrotizing, and intraepidermal pustular dermatitis patterns included diseases with different etiologies, while the remaining patterns covered a smaller number of distinct cutaneous diseases in each classification. Our results highlighted the histologic analysis as an efficient tool for directing diagnoses, representing a starting point for the application of this technique in large animal dermatology.

This study aimed to evaluate the effect of different periods of exposure to the intracanal medication Bio-C Temp (Angelus) on the chemical composition and fracture resistance of root dentin. Sixty bovine roots with similar anatomical characteristics were selected and evenly distributed into five groups (n = 12) according to the time of exposure to the intracanal medication Bio-C Temp (Angelus): control (without medication), 7days, 14days, 30days, and 90days. After each experimental period, the medication was removed, and the roots were embedded in cylindrical acrylic molds for fracture resistance testing and fracture pattern analysis. In addition, dentin blocks were obtained from unused root segments, subjected to the same experimental protocols (n = 6), and analyzed for chemical composition and topography using SEM/EDS. One-way ANOVA, Tukey's post hoc, and Fisher's exact tests were performed (α = 5%). The control group exhibited higher fracture resistance than the 90-day group (p < 0.05), while no differences were observed among the other groups or in the distribution of fracture patterns (p > 0.05). EDS analysis revealed alterations in the elemental composition of dentin in the control group compared with all other groups, with a more pronounced decrease in inorganic components observed in the 90-day group (p < 0.05). SEM images demonstrated dentin erosion and the presence of residual medication in all groups. In conclusion, Bio-C Temp (Angelus) induces dentin chemical changes even after short exposure; however, a significant reduction in fracture resistance appears only after prolonged exposure.

Objective: to identify key patterns of calcification in explanted bioprosthetic heart valves (BHVs) using cluster analysis of computed tomography-derived graphical data. Materials and methods. The study included 11 UniLine BHVs that were routinely explanted during reoperations for structural valve dysfunction. Computed tomography was used to obtain DICOM images of each sample, followed by generation of maximum intensity projections and segmentation of the valves into individual leaflets (n = 33). The images were pre-processed using binary thresholding to differentiate calcified regions from non-calcified biological tissue. Cluster analysis was performed using various algorithms: Gaussian mixture models, Ordering Points To Identify the Clustering Structure (OPTICS), k-means clustering, agglomerative (hierarchical) clustering, and spectral clustering. A basic quantitative method assessing the proportion of pixels corresponding to calcified areas was used for comparison. The performance of clustering algorithms was evaluated using the silhouette score. The presence of calcium deposits in the valves and the accuracy of binary thresholding were further verified histologically by alizarin red S staining of valve cryosections. Results. Data preprocessing based on image binarization yielded a maximum silhouette score of 0.55. Among the clustering algorithms, the highest silhouette scores were achieved with the agglomerative (0.55) and k-means (0.54) methods; however, both demonstrated substantial data imbalance, with up to 85% of samples grouped within a single cluster, limiting their practical applicability. The most balanced clustering was achieved using spectral clustering (silhouette score 0.45) and the basic quantitative approach (0.44). Both methods identified three distinct patterns of bioprosthetic valve leaflet calcification: (1) non-calcified leaflets, (2) partial calcification, and (3) total calcification. Conclusion. Three key calcification patterns were identified in explanted BHVs – absence of calcium, partial calcification, and total calcification. Spectral clustering and the basic quantitative method demonstrated the most balanced results, while other algorithms showed pronounced cluster imbalance. Heat map analysis revealed that in partial calcification, mineral deposition typically begins in the commissural and dome regions of the leaflets, near the free edge, and in total calcification, extends across the entire dome and leaflet base.

Spatiotemporal variability, source apportionment, and ecological risk assessment of heavy metals in sediments: A case study of the Panzhihua reach (Wudongde reservoir tail).

Suicide attempt history, childhood trauma, and functional brain network alterations in major depressive disorder: a resting-state functional connectivity-based multivariate pattern analysis.

Functional connectivity-based searchlight multivariate pattern analysis for discriminating Parkinson's disease patients and predicting clinical variables.

Purpose Innovation serves as the impetus in organizing tech startups. This study aims to explore how founders articulate and frame the concept of innovation from the founding stories they tell of their tech startups. From the versions of innovation presented through narratives, the study looks at how innovation subsequently influences and structures the tech startup organization. Design/methodology/approach Hinging on the premise that “organization is structured like a narrative” (Cooren, 2000, p. 58), founding stories of ten Filipino tech startup organizations were sourced and analyzed to understand how innovation is characterized, structured and materialized in narratives. The founding stories gathered from the participants underwent thematic analysis (for patterns of meaning and narrative typologies) and structural analysis (on the form that the story takes as well as its common elements) following Greimassian narrative theory (Greimas, 1971, 1987). Findings Eight themes surfaced from the constructed data, typifying different stories of and around innovation, including “the call to venture,” “old ways in new things” and “weathering the storm.” The properties of tech startup innovation derived from the motifs and the resulting metanarrative as well as the materializing of innovation in various narrative encounters told of a process, implying that innovation is constituted in communication. The study highlights that the tech startup organization itself is fashioned by articulations generated by innovation and is thereby accomplished in communication. Originality/value Current literature maintains a persistent ambiguity of defining innovation as well as a limited exploration of how narratives actively shape its materialization. The study contributes to theory by training focus on the mobilizing capacity of innovation, diverging from conventional transmission and diffusion models of innovation. From the context of tech startups as the organization of innovation, the study theorizes on the communicative constitution of innovation.

Building an ecological safety pattern is conducive to coordinating the contradictions between the two types of ecological processes of protection and development and promoting the ecological protection and restoration of land and space. Taking Henan Province as the research area， based on the results of morphological spatial pattern analysis （MSPA）， the landscape connectivity of the core area plaque was evaluated to extract the ecological source， construct the ecological resistance surface through the comprehensive index method， and modify it with the help of night light data. Circuit theory was used to extract Henan's ecological corridors， ecological pinch sites， and ecological obstacle sites； identify the key restoration areas in Henan Province； and formulate corresponding restoration strategies. The results showed that： ① There were a total of 64 important ecological sources in Henan Province， with a total of 22 615.77 km2， mainly distributed in the western region and the northern and southern provincial boundaries. ② There were a total of 120 major ecological corridors in Henan Province， with an average length of 13.29 km. The ecological obstacle areas in Henan Province were mainly distributed in Zhengzhou City， Pingdingshan City， and Nanyang City. ③ The ecological safety pattern of "three areas in one belt-four corridors-two groups-multi sites" has been established， and optimization suggestions have been put forward for different regions， which can provide references for the policy formulation of relevant government departments and promote sustainable development in the region.

Maintaining and manipulating sequential information in working memory is crucial for complex cognitive functions, such as language processing and action planning. While prior research has extensively characterized the neural substrates of passive sequence maintenance, the mechanisms underlying dynamic sequence manipulation remain poorly understood. This fMRI study employed univariate analyses, multivariate pattern analysis, and functional connectivity methods to dissociate neural mechanisms supporting active sequence reorganization from passive maintenance. Thirty-one healthy adults performed a digit-ordering task with two conditions: pure recall (maintaining preordered sequences) and reorder & recall (dynamically organizing randomized sequences). Univariate analyses revealed that manipulation, compared with maintenance, robustly activated a frontoparietal network (FPN) and deactivated the default mode network (DMN). Multivariate pattern analysis further demonstrated that manipulation-specific neural representations were decodable within frontoparietal regions, indicating their role in encoding the transformation of information. Critically, functional connectivity analysis revealed a dynamic network reconfiguration during manipulation, characterized by strengthened intra-network connectivity within the FPN and significant decoupling between the FPN and DMN. Within this reorganized architecture, the anterior cingulate cortex emerged as an integrative hub within the FPN, while the middle frontal gyrus mediated the interaction between the FPN and DMN. These findings provide a comprehensive, multilevel account of working memory manipulation, highlighting that it relies not merely on localized activation but on a large-scale, demand-driven reconfiguration of brain networks, involving a precise balance of network segregation and integration orchestrated by key cortical hubs.