Although travel route choice analysis is abundantly conducted using statistical models, some shortcomings, such as easy neglect of nonlinear effects among factors, and subjective assumptions in modeling, are apparent. This study provides an interpretable framework based on machine learning models to better analyze the travel route decisions of intercity travelers. Four types of travel route choice behavior analysis models (i.e., extreme gradient boosting [XGBoost], Light gradient boosting machine, random forest, and the binary logit model) were conducted using travel survey data for passenger car drivers in Guangxi, China, in 2021. The model parameters showed that XGBoost achieved the highest prediction accuracy (89.8%). Based on objective data distribution, the Shapley additive explanation approach was used to explain the output of XGBoost. The results showed that vehicle types, passenger capacity, expected toll discounts, and travel frequency on freeways had nonlinear effects on travel route choice, while traditional statistical models could not identify the nonlinear effects because of the effect of data distribution. Travel route choice was affected by potential interaction effects (e.g., vehicle types and toll payers). There were differences in the contribution of the same factor (e.g., education level) to route choice for different vehicle groups. These findings help better understand the generative mechanisms of travel route choice from a more objective perspective and provide references for developing more effective strategies to alleviate intercity road congestion and improve road network capacity by guiding travelers’ route choices.

Understanding the temporal dynamics of predator-prey interactions is the basis for predicting behavioral responses to climate or other environmental changes. Bats, as generalist apex predators, can provide a holistic view on ecosystem health, because their diet integrates signals from diverse insect communities and rapidly reflects environmental change. However, most molecular diet studies lack the temporal resolution needed to infer hunting strategies and prey choice mechanisms, because guano-derived species lists cannot be meaningfully interpreted without knowing when and what potential prey were available. Previous research has typically analyzed eDNA metarcoding data or insect activity patterns separately, limiting insights into mechanisms underlying prey selection. This study combines eDNA metabarcoding of bat guano with metabarcoding of time-stamped insect samples collected using automated Malaise traps to investigate the foraging ecology of long-eared bats (Plecotus sp.). Guano-derived prey communities most closely resemble insect bulk samples captured between 22.00 and 6.00, with species-specific differences in peak foraging times and prey composition. We further detected distinct prey-selection patterns between two closely related species, Plecotus auritus and Plecotus austriacus, consistent with their individual hunting strategy. Our findings demonstrate that adding a temporal axis to molecular diet analysis enables direct inference of prey selection and foraging behavior from guano. This integrative approach advances biodiversity monitoring and offers a tool box for conservation planning under changing environmental conditions. Our findings demonstrate that adding a temporal axis to molecular diet analysis enables direct inference of prey selection and foraging behavior from guano. This integrative approach advances biodiversity monitoring and offers a tool box for conservation planning under changing environmental conditions.

Introduction. The effectiveness of strategic management is determined by the ability of the enterprise to integrate the results of strategic analysis through the formation of adaptive mechanisms of competitive behavior, which is an important element of its development in modern conditions. The purpose of the article. To justify the peculiarities of the formation of competitive management strategies of the enterprise on the basis of strategic analysis, the development of the strategic process algorithm and the interpretation of SWOT analysis as a tool for generating strategic decisions. Methods. The research uses methods of strategic analysis, logical-structural generalization, systemic approach, methods of interpretive modeling, as well as analytical tools for assessing threats to the development of the enterprise. SWOT analysis was used as a tool for building a map of strategic decisions. Results. The article summarizes the theoretical foundations of the features of the development of competitive management strategies and their formation algorithm, which includes diagnostics of the initial state, assessment of environmental factors, setting of strategic goals, scenario modeling and operational detailing of decisions. The expediency of interpreting SWOT analysis in the form of a decision map, which ensures the transformation of factor analysis into structured variants of competitive behavior, is substantiated. Conclusions. The research confirms that an effective competitive management strategy is formed on the basis of the integration of analytical tools, taking into account the systemic interaction of factors and the use of adaptive mechanisms of strategic choice through the proposed algorithm of the SWOT analysis decision map.

Transnational surrogacy involving Indonesian citizens creates complex conflicts in Private International Law (PIL) due to contradictions between the legality of the practice in the country of birth and the implicit prohibition under Indonesian law (Health Act No. 36 of 2009, Article 127 paragraph (2)). This study examines the mechanism of choice of law in PIL, as well as the determination of legal parentage and citizenship status of children born through foreign surrogacy. The analysis reveals that although PIL applies connecting factors such as lex loci celebrationis and lex patriae, the recognition of a child’s legal status in Indonesia is strictly limited by the doctrine of Public Order (Ordre Public). Surrogacy contracts are considered null and void as they violate morality and national ethics. Based on the principle that the legal mother is the woman who gives birth, Indonesian courts recognize the surrogate as the lawful mother, severing civil ties with the intended parents. Although the child may still obtain Indonesian citizenship as a form of human rights protection, this is classified as a child born out of wedlock (Article 4(g/h) of the Citizenship Law). Such classification is deemed discriminatory and contrary to the Best Interests of the Child, highlighting the urgent need for a Parentage Order mechanism to ensure legal certainty and protect fundamental child rights.

Artificial bee colony (ABC) algorithm is one representative of many wellknown swarm intelligence methods for continuous optimization problems. However, it cannot directly solve discrete optimization problems without using complex transfer functions. Furthermore, the solutions quality and deviations obtained by many famous intelligent algorithms are still to be enhanced for solving uncapacitated facility location problems (UFLP). To this end, a continuous ABC called cABC is proposed for UFLP. In cABC, a chaotic initialization technique is employed to produce a good initial population in the range of [0,1), which enables cABC to evolve in continuous space. Then, a common probability discretizing mechanism is used to convert a continuous individual to a 0-1 vector, which enables cABC to solve UFLP. In addition, for infeasible solutions, a dynamic repair strategy is presented. Next, to enhance search performance of ABC, a random guiding mechanism is proposed. Subsequently, a time varying perturbation scheme is presented to share much more information between current individual and guiding individual. Next, a modified probability choice mechanism with random character is employed before entering onlooker bees phase. Last, an opposition based learning technique is employed to improve continuous nonupdating individual at the scout bees phase. To test effectiveness of cABC, it is first compared with traditional ABC on famous CAP dataset consisting of fifteen instances. To further validate superiority of cABC, it is compared with other eleven famous approaches on CAP dataset and M* dataset with twenty instances. Experimental results show that cABC surpasses other state-of-the-art methods in terms of solution accuracy and robustness.

Тhe article presents a comprehensive analysis of neuromarketing as an innovative interdisciplinary direction that combines the tools of marketing, cognitive psychology, neurobiology and behavioral sciences for the purpose of in-depth study of the mechanisms of consumer choice. It is substantiated that in the conditions of transformation of the modern market, increasing competition and oversaturation of the information space, traditional marketing communications are gradually losing their effectiveness due to sensory fatigue and a decrease in the level of consumer trust. In this regard, the need to use approaches aimed at studying subconscious cognitive and emotional reactions that immediately precede purchasing decisions is becoming more urgent. The essence of neuromarketing as a methodological "bridge" between classical economic models and modern neuroscientific research is revealed, and its role in the formation of a new paradigm for the analysis of consumer behavior is determined. The key tools of neuromarketing research are described, in particular, methods of registering brain activity, electrodermal, cardiovascular and muscle activity, as well as eye tracking technologies that allow recording latent consumer reactions to marketing stimuli. The main principles of neuromarketing and directions of their practical application in the process of forming marketing strategies, personalizing communications and increasing advertising effectiveness are systematized. Particular attention is paid to the analysis of sensory technologies of influence, in particular color and smell, as important elements of neuromarketing practices. It is proven that aromamarketing and coloristic solutions are able to activate the emotional and motivational centers of the brain, forming a positive perception of the brand and stimulating purchasing behavior. At the same time, the need for an ethical approach and state regulation in the field of neuromarketing research is emphasized in order to protect consumer rights and ensure the responsible development of this scientific and practical field.

Municipally provided water is low-cost, considered safe in most communities, and usually fluoridated to improve oral health. Yet, many Chicago region families report relying on other water sources. We investigated if safety and quality concerns were associated with these decisions; we also investigated whether there were spatial trends related to lead risk associated with water choice preferences. We used self-reported water consumption behavior data from the Coordinated Oral Health Promotion (CO-OP) Study, a longitudinal cohort of young children and their families. Respondents' residences (N = 331) were geolocated at the census tract level. We evaluated associations between parent demographics, estimated lead risk and water preferences. Among those who "Never" gave their children tap water, we investigated demographic characteristics associated with viewing tap water as "Not safe". Sixty-five percent (n = 216) of caregivers report that their child "Never" drinks tap water. Ordinal logistic regression indicates that parents aged <30 years are more likely to respond "Never" relative to "Sometimes" or "Always" (OR = 1.89; CI = 1.04, 3.40). Among those in the "Never" category, we grouped reasons into safety concerns (n = 114), observed quality concerns (n = 48), and preference (n = 40). We found that the decision not to give children municipal water is not aligned with the estimated lead risk. Understanding water consumption choice mechanisms is important for communities seeking safe and quality drinking water.

Product competitiveness is commonly discussed through three major lenses: quality superiority, price advantage, and customer value creation. In practice, firms often rely on one dominant lens, which can distort decision-making when markets are volatile, consumer expectations are heterogeneous, and competition is increasingly shaped by service ecosystems and brand trust. This article offers a comparative analysis of quality-, price-, and value-based approaches to assessing product competitiveness and proposes a coherent evaluative framework suitable for managerial diagnostics and academic research. Using a conceptual-analytical method supported by an illustrative index-building procedure, the study clarifies the philosophical and economic assumptions embedded in each approach, identifies their measurement logics, and explains typical sources of bias. The results show that quality metrics tend to capture product integrity and compliance but may overlook perceived benefits; price metrics capture market entry and cost discipline but may misrepresent competitiveness when total cost of ownership and risk are ignored; value metrics best reflect consumer choice mechanisms yet require careful operationalization to avoid subjectivity. The discussion argues that a robust competitiveness assessment should be multi-dimensional and context-sensitive, combining objective quality evidence, relative price positioning, and value indicators tied to willingness-to-pay and experience outcomes. The article concludes with implications for product strategy, standardization, and further research on digital markets where value is increasingly co-produced through platforms and services.

Based on a social psychological perspective, this study employed a mixed-methods approach to explore the mechanisms underlying high school students' career choice under the interaction of cultural environment and social cognition. Through quantitative surveys of 1,200 high school students and in-depth interviews with 36 students, data were analyzed using structural equation modeling, multilevel linear modeling, and thematic analysis. The findings revealed that: (1) Cultural environment exerted significant direct effects on career choice, with family, school, and societal cultural environments collectively explaining 28.5%-41.3% of the variance in career choice behaviors; (2) Social cognitive variables played important mediating roles, with the total mediating effects of self-efficacy, outcome expectations, and career values accounting for 39.2%-45.8% of the total effects; (3) Cultural adaptability, cognitive flexibility, and social support demonstrated moderating, facilitating, and buffering-amplifying effects respectively in the cultural environment-cognitive process relationship; (4) The high adaptability group showed stronger cultural environmental influence effects (β=0.234), individuals with high cognitive flexibility exhibited better environmental adaptation capabilities (r=0.612), and social support demonstrated buffering effects under stressful situations (β=-0.245) while showing amplifying effects in positive environments (β=0.318). This study constructed an integrative theoretical model of cultural environment-social cognition interaction, extended the cross-cultural applicability of social cognitive theory, provided a new analytical framework for understanding adolescent career development patterns in complex cultural contexts, and offered scientific evidence for career guidance practice and educational policy formulation.

This paper examines Pune’s evolving municipal wastewater management framework as a model for sustainable urban development policy in rapidly urbanising Indian cities. Through a comprehensive analysis of infrastructure expansion, technological innovation, and regulatory frameworks, we assess the effectiveness of decentralised treatment strategies in addressing urban environmental challenges. Our study reveals that despite significant infrastructure investments totalling ₹1,173 crore under the JICA-funded Project for Pollution Abatement of River Mula-Mutha (PARMM), Pune continues to face a 503 MLD daily treatment gap, with only 49% of generated sewage receiving treatment. Using a multi-parametric policy assessment, integrating performance data from 11 sewage treatment plants, policy documents, and environmental monitoring reports, the research finds that while technological diversification demonstrates promise, persistent funding delays, land acquisition disputes, and the "subsidy barrier" in water pricing threaten environmental sustainability outcomes. The research contributes to sustainable urban development literature by demonstrating how policy integration, technology choice, institutional coordination, and financial sustainability mechanisms determine wastewater management effectiveness.

摘要： 备选是指最终被组织安排承担某项任务或角色, 但并非该任务或角色首选的员工, 近年来逐渐受到学者关注。然而现有研究却忽视了任务分配情境下备选对员工自身态度和行为的影响。本研究基于社会信息加工理论和联想命题评价理论, 采用情境实验(研究1)和三阶段问卷调查(研究2), 探讨了任务分配情境下备选对员工行为的“双刃剑”效应及边界条件。研究结果表明, 当上级发展性反馈水平高时, 备选会激发和谐型激情, 进而引发主动担责行为; 当上级发展性反馈水平低时, 备选会引起工作拖延倾向, 进而发生时间窃取行为。研究结论为大众更加客观、辩证地认识备选提供参考和借鉴。

In multi-objective particle swarm optimization (MOPSO), challenges persist, including low diversity in external archives, ambiguous individual optimal choice mechanisms, high sensitivity to parameter settings, and the arduous task of balancing global exploration and local exploitation capabilities. To address these issues, this paper introduces a novel multi-objective particle swarm optimization algorithm named HCRMOPSO. The proposed algorithm innovatively leverages hierarchical clustering based on Ward’s linkage to generate the center of mass as reference points, which are then combined with the ideal point and crowding distance. This effectively maintains the external archive, thereby resolving the diversity deficiency commonly found in traditional MOPSO archives. Additionally, HCRMOPSO fuses multiple particles to update the personal best positions. It also adaptively tunes the flight parameters according to the diversity information within each particle’s neighborhood, enhancing the algorithm’s adaptability. Notably, a new strategy is designed for two specific types of particles, further optimizing the search process. The performance of HCRMOPSO is rigorously evaluated against ten existing algorithms on 22 standard test problems. Experimental results demonstrate that HCRMOPSO outperforms its counterparts on multiple benchmarks, showcasing superior effectiveness in handling multi-objective optimization tasks.

Cognitive impulsivity has traditionally been examined by isolating single factors, such as delay, effort, or reinforcement probability. However, real-world decision-making is inherently complex, with these variables rarely acting independently. While some perspectives suggest that effort and time represent a unified construct-effort merely reflecting the time employed responding-empirical evidence suggests that they are dissociated, supported by different neuromodulation mechanisms involved in effort-based versus time-based decision making. Understanding how these variables interact is essential for elucidating the mechanisms underlying maladaptive choices in psychological disorders. This study investigated the interaction between effort and time in shaping preferences by using SHR and WKY rat strains, models for motivational-related psychopathologies. A delay-discounting task was employed, incorporating fixed-ratio schedules to manipulate effort. Each strain was divided into two groups: one had effort in the delayed option; the other had effort in the immediate option. Results showed that in both strains effort in the delayed option led to steeper discounting rates compared to effort in the immediate option, highlighting the significant role of effort in modulating impulsive behavior. No strain differences were found, which is consistent with the notion that delay and effort operate as separate cost factors influencing decision-making, mediated by specific and partially independent dopaminergic pathways. These findings contribute to a broader understanding of the neural mechanism and behavioral dynamics associated with effort and delay, offering insights into their joint influence on decision-making processes.

Intrinsic uncertainty in the reward environment requires the brain to run multiple models simultaneously to predict outcomes from preceding cues or actions. For example, reward outcomes may be linked to specific stimuli and actions, corresponding to stimulus- and action-based learning. But how does the brain arbitrate between such models? Here, we combined multiple computational approaches to quantify concurrent learning in male monkeys performing tasks with different levels of uncertainty about the model of the environment. By comparing behavior in control monkeys and monkeys with bilateral lesions to the amygdala or ventral striatum, we found evidence for adynamic, competitive interaction between stimulus-based and action-based learning, and for a distinct role of the amygdala in model arbitration.We demonstrated that the amygdala adjusts the initial balance between the two learning systems and is essential for updating arbitration according to the correct model, which in turn alters the interaction between arbitration and learning that governs the time course of learning and choice behavior. In contrast, VS lesions lead to an overall reduction in stimulus-value signals. This role of the amygdala reconciles existing contradictory observations and provides testable predictions for future studies into circuit-level mechanisms of flexible learning and choice under uncertainty.

This comparative study examines the cultural identity construction strategies in Chinese and Korean art songs of the colonial modernization period (1910-1950). In this study, the questions of how composers of the two countries worked in the circumstances of maintaining indigenous cultural identity and acceptance of western forms under the colonial and semi-colonial realities within the systematic analysis of musical works, relevant historical contexts, and cultural policies with the use of secondary data were investigated. The study reveals significant differences in colonial experiences that led to different models of cultural identity building. Korea was a direct colony of Japan (1910-1945), and the strategies of resistance it created were highly language-inclined (linguistic preservation) and hidden cultural performance. The semi-colonial situation in China made modernization-related approaches that combined Western methods with Chinese culture possible. The study uses four strategic facets: linguistic adaptation, musical indigenization, thematic choice, and dissemination mechanism. Although both countries managed to live up to the creation of the roots of modern musical identity, their various colonial backgrounds led to different models of cultural strength and adaptation, which can be used in modern debate concerning cultural globalization and retaining national identities.

Inverse option generation: Inferences about others' values based on what comes to mind.

Market design mechanisms are often required to be strategy proof, ensuring that no misreporting is profitable. This, however, may be overly restrictive: Real-world participants may be unable to engage in complex misreporting. In the context of school choice, this paper proposes that mechanisms ought to be immune only to certain “simple” misreports. While no strategy-proof mechanism Pareto improves on the deferred acceptance (DA) mechanism, we find one under our weaker requirement: Kesten's (2010) efficiency adjusted DA (EADA). By extending our criterion to also prevent simple “collective” misreports, we obtain characterizations of Kesten's mechanism. These insights contribute to practical market design. (JEL C78, D47, D82, I21)

Although information theory is widely used in neuroscience, its application has primarily been limited to the analysis of neural activity, with much less emphasis on behavioral data. This is despite the fact that the discrete nature of behavioral variables in many experimental settings—such as choice and reward outcomes—makes them particularly well-suited to information-theoretic analysis. In this study, we provide a framework for how behavioral metrics based on conditional entropy and mutual information can be used to infer an agent’s decision-making and learning strategies under uncertainty. Using simulated reinforcement-learning models as ground truth, we illustrate how information-theoretic metrics can reveal the underlying learning and choice mechanisms. Specifically, we show that these metrics can uncover (1) a positivity bias, reflected in higher learning rates for rewarded compared to unrewarded outcomes; (2) gradual, history-dependent changes in the learning rates indicative of metaplasticity; (3) adjustments in choice strategies driven by reward harvest rate; and (4) the presence of alternative learning strategies and their interaction. Overall, our study highlights how information theory can leverage the discrete, trial-by-trial structure of many cognitive tasks, with the added advantage of being parameter-free as opposed to more traditional methods such as logistic regression. Information theory thus offers a versatile framework for investigating neural and computational mechanisms of learning and choice under uncertainty—with potential for further extension.

ABSTRACT Background Over recent decades, school choice (the process by which parents select a school of their choosing for the child/children) has become a key component of education policy pursued in many countries, and a critical decision for many parents. While global scholarship has broadened understanding of how families engage with and experience school choice, less is known about how this choice operates in reciprocity with institutional practices, namely school admissions and selectivity procedures, particularly in non-Western contexts. Purpose This paper examines parents’ school choices in Iran – not in isolation, but in a reciprocal relationship with schools’ student choices. In this context, both parents and schools actively assess one another to decide whether the other is the right ‘fit’. The study posed two research questions: 1) How do parents think about and enact school choice in relation to schools’ selectivity? and 2) How do school personnel perceive and respond to parent’s affections, expectations, and preferences during the school choice process? Method Twenty-five in-depth interviews with parents and school personnel were conducted in Tehran, the capital of Iran, during autumn 2019. The data were analysed thematically, using the concepts of school cultural orders (instrumental and expressive), habitus, and distinction. Findings Parents’ school choice, as a complex social process, reciprocally influenced, and was influenced by, schools’ student choice. Through this reciprocity, parents and schools weighed one another up, expressed concerns and preferences, negotiated expectations, and sought an optimal ‘fit’; a dynamic that shaped the enrolment of the ‘right’ students, the composition of a particular student body, and the ongoing reproduction of both familial privileges and institutional culture. Conclusion These reciprocal mechanisms of school choice reveal that school choice is not merely about accessing educational resources but about securing boundary-making and distinction. Through practices of inclusion and exclusion, the interplay between parental and institutional decision making can contribute to the persistence of inequalities and the perpetuation of social reproduction and division.

In humans and other primates, food intake depends on sophisticated, individualized preferences for nutrients and oral-sensory food qualities that guide decision-making and eating behavior. The neural and behavioral mechanisms for such primate-typical food preferences remain poorly understood, despite their importance for human health and their targeting by pharmacological obesity treatments. Here, we review a series of experiments that investigated how the biologically critical properties of foods-their nutrients (sugar, fat, protein) and oral-sensory qualities (viscosity, oral sliding friction)-influence food preferences in monkeys and humans. In an economic nutrient-choice paradigm, macaques flexibly trade nutrients and oral-sensory food qualities against varying food amounts, consistent with the assignment of subjective values. Nutrient-value functions that link objective nutrient content to subjective values accurately model these preferences, predict choices across contexts, and explain individual differences. The monkeys' aggregated choice patterns resulting from their nutrient preferences lead to daily nutrient balances that deviate from dietary reference points, resembling suboptimal human eating patterns when exposed to high-calorie foods. To investigate the sensory basis underlying nutrient values, we developed novel engineering tools that quantify food textures on oral surfaces, using fresh pig tongues. Oral-texture (i.e., mouthfeel) parameters, including viscosity and sliding friction, were shown to mediate monkeys' preferences for high-fat foods. When translated to human subjects, this approach revealed a neural mechanism for preferring high-fat foods from oral texture in the orbitofrontal cortex (OFC)-a key reward system of the brain. Importantly, human OFC responses to oral sliding friction in individual subjects-measured in the MRI scanner-predicted subsequent fat intake in a naturalistic, life-like eating test. These findings suggest that a primate nutrient-reward paradigm offers a promising approach for investigating the behavioral and neural mechanisms for human-typical food reward and food choice, to advance understanding of human eating behavior, overeating, and obesity.