Search Results (6,564)

In order to reduce the risk of collapse disasters during tunnel construction in mountainous areas and to make full use of the available data, a collapse risk assessment model for highway tunnel construction was established based on the WOA–XGBOOST algorithm. Three major categories of tunnel construction risk, namely engineering geological factors, survey and design factors, and construction management factors, were selected as the first-level indicators, and 14 secondary indicators were further specified as the input variables of the collapse risk assessment model for tunnel construction. The confusion matrix and accuracy metrics were employed to evaluate the training and prediction performance of the risk assessment model on both the training set and the test set. The results show that subjective weights derived from the G1 method were integrated with objective weights generated by the WOA–XGBOOST algorithm. A game-theory-based weight integration strategy was then applied to optimize the combined weights, effectively mitigating the biases inherent in single-method weighting approaches. Risk quantification was systematically conducted using a cloud model, while spatial risk distribution patterns were visualized through graphical cloud-mapping techniques. After completion of model training, the proposed model achieved a high accuracy of over 99% on the training set and around 95% on the held-out test set based on an available dataset of 100 collapse-prone tunnel construction sections. Case-based verification further suggests that, in the studied collapse scenarios, the predicted risk levels are generally consistent with the actual engineering risks, indicating that the model is a promising tool for assisting tunnel construction risk assessment under similar conditions. The research outcomes provide an efficient and reliable approach for assessing risks in tunnel construction, thereby offering a scientific basis for engineering decision-making processes. Full article

This paper establishes a comprehensive framework for the hereditary transfer of categorical completeness and cocompleteness to categories of internal group objects in D-modules. We prove that while completeness of $\mathbf{Grp}\left(\mathbf{D}\text{-}\mathbf{Mod}\right)$ follows unconditionally from the completeness of the base category $\mathbf{D}\text{-}\mathbf{Mod}$, cocompleteness requires $\mathbf{D}\text{-}\mathbf{Mod}$ to be regular, cocomplete, and admit a free group functor left adjoint to the forgetful functor. Explicit constructions are provided for limits via componentwise operations and for colimits through coequalizers of relations induced by group axioms over free group objects. The theory reveals fundamental geometric obstructions: differentially constrained subcategories such as holonomic D-modules fail to be cocomplete due to characteristic variety constraints that prevent free group constructions. Applications demonstrate cocompleteness in topological D-module groups and D-module sheaves, while counterexamples in differential geometric groups exhibit necessary analytic constraints. Additional results include regularity inheritance under product-preserving free group functors, internal hom-object constructions in locally Cartesian closed settings yielding Tannaka-type dualities, and monadicity criteria for locally presentable base categories. This work unifies categorical algebra with differential geometric obstruction theory, resolving fundamental questions on exactness transfer while enabling new constructions in homotopical algebra and internal representation theory for D-modules. Full article

Understanding and predicting the metabolic fate of xenobiotics is essential in early drug discovery stages, as poor ADMET properties are a leading cause of new drug candidates’ failure. In silico metabolism modeling offers a way to design safer and more effective compounds. We present Meta^QM, a set of random forest classifiers enhanced with quantum chemical descriptors to predict (i) the occurrence of metabolic reactions (Metaclass^QM) and (ii) the site of metabolism (Metaspot^QM). Models were trained on the MetaQSAR database, which contains 3788 expert-curated reactions divided into 3 main categories, 21 classes, and 101 subclasses. The descriptors used to train the models included physicochemical, constitutional, and stereo-electronic features computed at two levels of theory: PM7 (MOPAC 2016) and DFT (B3LYP/6-31G(d)). For Metaclass^QM, the use of DFT descriptors led to improved classification performances by 10% at the class level and 8.6% at the subclass level, compared to PM7 descriptors. In Metaspot^QM, both descriptor sets showed similar performance in SoM prediction across different datasets. DFT descriptors enhance the classification of metabolic reactions, while simpler methods suffice for the prediction of metabolic sites. These findings support the use of quantum descriptors in metabolism modeling workflows, balancing accuracy and computational cost. Full article

Background: Antibiotic resistance is a pressing public health concern, exacerbated by the prescribing of antibiotics in primary care settings when they are not clinically indicated. Research shows that providers often feel pressured to prescribe antibiotics in response to patients’ expectations. To address this challenge, we developed a theory-informed video intervention to enhance antibiotic stewardship communication skills among current and future primary care providers, with emphasis on college health settings. The intervention consisted of five videos targeting core skills: explaining diagnosis and treatment, discussing antibiotic risks, advising on symptom management, offering patient support, and navigating visits with emerging adults. Program effectiveness was assessed immediately and three months post-intervention. Methods: Providers and medical students (N = 135) completed a three-wave study. At baseline, they reported demographics, perceived importance of the five skill sets, as well as self-efficacy, and completed closed- and open-ended skill assessment. Two weeks later, participants viewed the intervention videos, reassessed their skills, and rated their motivation to improve. Three months after video exposure, they completed the same skill assessments. Results: Participants showed improvements in all communication skills immediately post-intervention, except for supporting patients. While some skills showed sustained improvements at three months, the overall long-term effects were less pronounced. Perceived skill importance, baseline self-efficacy, and post-intervention motivation moderated these effects. Conclusions: A brief video-based intervention effectively enhanced current and future providers’ antibiotic stewardship communication skills. Sustaining these gains, however, requires ongoing reinforcement. Notably, the intervention was especially beneficial for those with low motivation and self-efficacy, key targets for such programs. Full article

Insects constitute a vital component of terrestrial ecosystems, yet their ongoing global decline underscores the urgency of identifying the factors that facilitate or hinder public engagement in their conservation. This study identifies the key psychological drivers of insect-related conservation behavior within a Romanian context, an understudied geographical and sociocultural setting. Using data collected from 346 adult respondents via an online questionnaire, the predictive performance of the Value–Belief–Norm (VBN) theory, the Theory of Planned Behavior (TPB), and an integrated VBN–TPB framework was examined through Partial Least Squares Structural Equation Modeling (PLS-SEM). The VBN model exhibited superior explanatory power relative to TPB, with biospheric values, ecological worldviews, and personal moral norms emerging as the most influential determinants of behavioral intention and self-reported action. Although participants demonstrated moderate levels of general entomological knowledge, awareness of specific insect-friendly practices was notably limited and frequently characterized by misconceptions. Perceived barriers, particularly informational deficits, time constraints, and financial considerations, exerted significant inhibitory effects on conservation engagement. The findings indicate that effective interventions must extend beyond knowledge transmission, incorporating strategies that activate moral norms, strengthen affective and identity-based motivations, and reduce structural barriers to action. Full article

Traditional degree semantics approaches have aimed to pin down the inherent class of adjectives. This paper presents a novel dynamic perspective, where the classification of an adjective is dynamic and syntactically dependent. Using measurement theory and fuzzy set analysis, the proposed framework defines dynamic patterns of adjective classes with a set of axioms and integrates these patterns with syntactic structures to explain the flexibility and constraints observed in adjectival expressions. Employing Mandarin data, the paper illustrates how different syntactic constructions select specific adjective classes, thereby affecting their distribution and interpretation. This approach not only accommodates cross-linguistic variations but also provides a more comprehensive understanding of the semantics of adjectives. Full article

The transition to sustainable food systems requires communication strategies that resonate with consumers’ values, not only technological innovation. This study examines how values-centric communication can shape German consumers’ responses to alternative proteins, focusing on insect-based snacks. A desk-based synthesis of recent studies, guided by Schwartz’s value theory, identified Tradition and Security as dominant drivers of food choice and yielded five communication requirements: Cultural familiarity, Emotional safety, Simplicity and clarity, Trust and credibility, and Routine integration. These were operationalised into communication guidelines and short on-pack claims, which were applied to a refined packaging prototype. An exploratory focus group (N = 7) then compared reactions to the original versus the refined packaging, analysed using McGuire’s communication–persuasion stages. Within this small exploratory group, participants reported that familiar formats, a reassuring tone, clear visual hierarchy, and salient trust cues made them more willing to consider trying the product, whereas information overload, claim–image incongruence, value-incongruent brand naming, and delayed recognition of insect content appeared to impede acceptance. The study contributes an integrative analytic lens combining Schwartz’s value theory with McGuire’s model and a set of testable guidelines for value-aligned food communication. Because the empirical evidence is based on a single small student focus group with fixed presentation order, bundled manipulations, and hypothetical intentions, these results are exploratory and self-reported and should be interpreted cautiously; future research should employ counterbalanced factorial designs with behavioural outcomes. Full article

As emotion becomes increasingly digitized, there is a growing risk that computational systems may overreach, shaping or managing affect in ways that undermine human autonomy. This study builds a cross-cultural dialog between Daoist affective philosophy and Western theories of emotion to address this problem. By comparing their assumptions about emotional life—what emotions are, how they should be guided, and what counts as appropriate intervention—the paper develops a set of ethical principles for the design of affective technologies. Through textual analysis and a historical–conceptual review, the study identifies three safeguards drawn from Daoist thought—minimality, autonomy, and reversibility—and translates them into practical guidance for data use, system behavior, and user interaction. A brief case from Finland’s well-being initiatives illustrates how these principles can redirect technological design toward supporting inner balance and self-directed regulation rather than external control. The paper’s contribution lies in offering a clear boundary ethics for affective computing, showing how Daoist ideas of moderation and self-cultivation can help prevent emotional alienation while still allowing technological systems to enhance human well-being. Full article

Public spaces in peri-urban towns are becoming key focal points of urban regeneration in China due to their geographic advantages, resource endowments, and diverse populations. Substantial investments have been made to improve residents’ living environments and well-being. As over-commercialized urban centers increasingly face congestion and homogenization, the distinctive landscapes and authentic everyday life of peri-urban towns are attracting growing attention from tourists. Understanding both residents’ and visitors’ perceptions of these public spaces is therefore essential for successful regeneration. This study examines Nanquan Street, which lies ina peri-urban heritage town in Wuxi, Jiangnan region, China. Drawing on user-generated content from major Chinese social media platforms (Xiaohongshu and Dianping) and field observations guided by the AEIOU framework, a three-stage grounded theory approach was employed to identify the key factors influencing user satisfaction. The analysis identified twelve sub-dimensions grouped into three overarching categories: foundational preconditions, social developmental factors, and spatial-operational factors, which collectively shape sustained satisfaction in Peri-urban heritage towns. By translating the satisfaction model into sustainable design strategies, this study proposes a set of renewal pathways applicable not only to Nanquan Street but also to similar peri-urban towns facing comparable challenges. Emphasizing multi-user experience, low-intervention strategies, and contextual adaptability, this research contributes to theoretical understandings of sustainable renewal in peri-urban towns. It provides actionable guidance for balancing everyday life, cultural heritage, and sustainable tourism development. Full article

We develop the theory of Difference Lindelöf perfect functions. Through difference covers, we provide intrinsic characterizations; prove stability under composition, subspace restriction, and suitable products; and obtain preservation theorems. Under standard separation axioms, properties such as D-countable compactness, regularity, paracompactness, and the closedness of projections transfer along D-Lindelöf perfect maps. We also connect the framework to statistics. Uses include decision regions expressed as differences of open sets and parameter screening, with visualizations of countable subcovers and their pushforwards. The results point to practical countable cores for learning and inference and suggest extensions to bitopological and fuzzy contexts. Full article

This study investigates how technostress and work intensification jointly influence employee health harm through two distinct stressor-strain pathways within Pakistan’s manufacturing sector. The proposed model specifies two mechanisms, (1) technostress induces IT strain that contributes to health harm, moderated by user satisfaction; and (2) work intensification heightens emotional exhaustion that similarly leads to health harm, moderated by perceived organizational support. Grounded in Conservation of Resources (COR) theory, the framework explains how cumulative digital and organizational demands deplete employee resources, amplifying both psychological and physical harm. A cross-sectional quantitative design was employed, utilizing a structured self-administered questionnaire administered to mid and senior-level employees across manufacturing firms. A total of 252 valid responses were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using Smart PLS 4. Results revealed that both IT strain and emotional exhaustion significantly mediated the effects of technostress and work intensification, respectively, on health harm. Moreover, user satisfaction significantly moderated the IT strain-health harm relationship, indicating that higher satisfaction with digital tools mitigates the adverse impact of technological stress. Similarly, organizational support weakened the association between emotional exhaustion and health harm, underscoring its protective role in high-pressure work settings. This study offers theoretical advancement by integrating fragmented stressor-strain models and offers practical recommendations to foster digital well-being and supportive organizational work cultures in evolving industrial contexts. Full article

The aim of this study is to investigate generalized prime hyperideals in the framework of Krasner hyperrings. To this end, new classes of hyperideals are introduced and analyzed based on multiplicatively closed properties. In particular, the concepts of s-m-hypersystems, f-hypersystems, and their associated s-prime and f-prime hyperideals are defined and examined. A subset $S\subseteq R$ of a Krasner hyperring is called an s-m-hypersystem if, for every $s\in S$, there exists a multiplicatively closed subset $S^{\ast }\subseteq S$ such that $⟨s⟩\cap S^{\ast }\ne \varnothing$. This concept extends the classical ideal of multiplicative compatibility to the setting of hyperrings. Furthermore, for each element $a\in R$, we define a hyperideal $f\left(a\right)$ satisfying the following conditions: (i) $a\in f\left(a\right)$, (ii) For any hyperideal K, if $x\in f\left(a\right)+K$, then $f\left(x\right)\subseteq f\left(a\right)+K$. Using this notion, a subset $S\subseteq R$ is defined to be an f-hypersystem if there exists a multiplicatively closed subset $S^{\ast }\subseteq S$ such that $f\left(a\right)\cap S^{\ast }\ne \varnothing$ for every $a\in S$. We provide characterizations and original examples of these hypersystems and their corresponding prime hyperideals. The relationships and distinctions between the s-m-hypersystems and f-hypersystems are also explored. Our findings offer a refined perspective on hyperideal theory and open new pathways for the algebraic analysis of hyperstructures. Full article

Objectives: This study aims to provide conceptual clarity on self-direction support in the care of vulnerable older adults, particularly those with dementia. It focuses on how self-direction is supported in meaningful daily activities and social participation. The goal is to define and operationalize the concept by identifying its key attributes, antecedents, and consequences across care contexts. Methods: A two-phase approach will be used. First, an integrative review will synthesize empirical evidence from gerontology, occupational therapy, psychology, nursing, and health ethics to examine current conceptualizations and practices. Second, a concept analysis will explore the theoretical structure of self-direction support. Findings will be synthesized into a conceptual framework. Expected outcomes: This study is expected to provide a clearer conceptual framework outlining the core components of self-direction as described in existing literature. This framework will define key attributes, identify influencing factors, and propose measurable indicators. The framework aims to guide professionals in balancing autonomy, safety, and care needs. Conclusions: As this is a study protocol, no results are presented; findings will be reported in the forthcoming review. The anticipated outcomes are expected to contribute to theory and practice by framing self-direction within social health. The framework may inform future research, policy, and intervention development to strengthen self-direction in meaningful activities and participation among vulnerable older adults. Further validation across settings and cultural contexts will be required. Full article

Studying the thermodynamic properties of soft rocks is critical for geothermal energy extraction, as it elucidates their temperature-dependent mechanical behaviors and heat transfer mechanisms, thereby optimizing reservoir stimulation, enhancing extraction efficiency, and ensuring long-term operational stability. Owing to the intricate geothermal settings and interconnected physicochemical processes, the thermodynamic properties exhibit pronounced spatial heterogeneity and interdependencies. Concurrently, constraints imposed by technical and economic limitations result in scarce practical field survey and experimental data on these properties, severely hampering comprehensive assessments of geothermal energy potential and exploitation feasibility. To evaluate the spatial variability of thermodynamic properties for heterogeneous soft rock using limited data, the thermal conductivity (TC), heat capacity (HC), and thermal diffusivity (TD) were measured. A new Copula statistical method is used to analyze thermodynamic properties under limited measurement data. Spatial variability in heterogeneous soft rocks is quantified using random field theory. The methodology’s reliability is confirmed through cross-validation against theoretical predictions, empirical measurements, and simulation outputs. The analysis framework of thermodynamic variability characteristics has been presented by stability point analysis and linear regression analysis processes. The variance reduction function, scale of fluctuation, autocorrelation distances, and autocorrelation structure of thermodynamic properties for heterogeneous soft rock are analyzed and discussed. This study can provide scientific data for thermal energy analysis and geothermal reservoir modification specifically applicable to soft rock formations with diagenetic and tectonic histories similar to those investigated in the Weishan Lake area. Full article

This systematic review and meta-analysis synthesises 88 effect sizes from 88 peer-reviewed journal articles to evaluate the association between marketing capability and firm performance. Studies were identified in Scopus and Dimensions for the period 2000–2025 and were eligible if they reported a construct identifiable as marketing capability, at least one firm performance outcome, and sufficient statistics to compute a correlation. Random-effects pooling indicates a positive and practically meaningful correlation between marketing capability and performance (r = 0.44, 95% CI [0.40, 0.48]), with a 95% prediction interval from 0.06 to 0.71, indicating that marketing capability is an important correlate of performance outcomes. Subgroup analyses show stronger correlations for reflective first-order models, weaker estimates for higher-order and formative specifications, and wider prediction intervals when confirmatory factor analysis (CFA) is reported. Contextual differences are also evident: business-to-consumer samples exhibit the largest effects, business-to-business samples moderate effects, and mixed samples smaller effects. Small-study patterns were examined with funnel plots, Egger’s test and trim-and-fill, and sensitivity analyses using Restricted Maximum Likelihood (REML), Hartung–Knapp, and multilevel models produced similar pooled estimates. Most included studies were cross-sectional, which limits causal interpretation, so the findings should be read as consistent associations rather than proven effects. Taken together, the review shows that construct design, validation practice, and market setting systematically shape both the size and spread of the marketing capability–performance association and provides benchmarks and prediction intervals that future studies can use for theory development and research design. Full article