Search Results (120)

We investigate functional behavioural differentiation in genetically homogeneous animal collectives using the $ϵ$-machine and $ϵ$-transducer frameworks from symbolic dynamics. Long-term tracking of unmarked individuals in colonies of the clonally reproducing ant Pristomyrmex punctatus reveals two distinct movement modes—clustering within the group and solitary exploration outside it. Reconstructed individual $ϵ$-transducers expose a sharp asymmetry in computational structure between these modes: solitary explorers are described by a deterministic machine, whereas clustering ants require stochastic machines to capture their complex patterns of micro-movement. A population-level (universal) $ϵ$-transducer, inferred from pooled data, captures the shared behavioural repertoire across all individuals. Individual differences are parsimoniously explained as biased and partial traversals of a common state space rather than as distinct generative programs. We compare three predictive models: the $ϵ$-machine, which relies solely on an ant’s own output history; a memoryful $ϵ$-transducer, which additionally conditions on changes in the local neighbour count as social input; and a memoryless $ϵ$-transducer, which uses this social input alone. The memoryful transducer matches the $ϵ$-machine in prediction accuracy despite requiring ten times as many states, while the memoryless transducer performs substantially worse. This shows that an ant’s own behavioural history is the essential predictor of its future movement at the temporal resolution examined here. We argue, however, that this predictive redundancy does not entail the causal irrelevance of social input: the behavioural history itself accumulates the trace of past social encounters so that any role differentiation established through prior interactions is already inscribed in the output sequence that the $ϵ$-machine reads, and mode transitions—the moments at which social input most plausibly exerts causal influence—are rare events that contribute negligibly to aggregate one-step accuracy. Agent-based simulations driven by the universal $ϵ$-transducer reproduce basic motion statistics and transient aggregations but fail to generate the stable macroscopic clusters observed experimentally, pointing to the role of additional mechanisms such as longer-term memory or stigmergic coupling. Nevertheless, ants do respond to their social environment: an explorer encountering an increase in neighbours is absorbed into the cluster and ceases directed movement. Together, our results suggest a two-level organisation: within each behavioural mode, individual dynamics are self-sufficient for one-step prediction, while transitions between modes are environmentally triggered and represent switches between fundamentally different classes of dynamical organisation. Full article

The middle reaches of the Minjiang River, shaped by the Dujiangyan irrigation system, provide a typical setting for studying long-term human–water interactions. During the Little Ice Age, the water management system as a whole experienced a full cycle of recovery, expansion, and decline from 1644 to 1949 (Qing to Republican period), although subregions exhibited marked spatial heterogeneity. This heterogeneity makes the area an ideal case for comparative analysis; however, previous studies have neither quantitatively reconstructed river–canal changes nor systematically disentangled the composite natural and anthropogenic drivers across different subregions. Using archival documents, historical maps, remote sensing imagery, and water cultural heritage sites, this study reconstructs the evolution and quantifies two change types: anthropogenic construction, including new construction, reconstruction, and modification, and environmentally driven changes such as rerouting, damage, and maintenance. Correlations were analyzed among the four subregions: Inner River, Outer River, Nanhe River, and the Lower Basin to identify driving mechanisms. Results indicate that anthropogenic construction is constrained by natural conditions and driven by population growth, whereas environmentally driven changes are primarily caused by floods and worsened by canal head maintenance failure. The four spatially differentiated driving patterns are: Inner River—human-dominated intervention type; Outer River—flood stress type; Nanhe River—low-disturbance stable type; and Lower Basin—natural–human composite type. This study offers new insights into long-term human–water interactions in large irrigation districts under climate change. Full article

Background: Ventral hernias are a common complication following abdominal surgery, occurring in up to 20% of patients after midline laparotomy and as many as 43% of those who undergo orthotopic liver transplantation (OLT). These hernias pose unique challenges due to chronic immunosuppression, impaired wound healing, and the anatomic disruption caused by subcostal and “Mercedes-Benz” incisions. As survival after OLT continues to improve, the need for durable, infection-resistant abdominal wall reconstruction has become increasingly important. Methods: We performed a single-institution retrospective review of all OLT patients undergoing abdominal wall reconstruction by the senior author between June 2014 and April 2026. Our approach emphasizes component separation to reestablish myofascial continuity, biologic onlay reinforcement with human acellular dermal matrix (HADM), and multipoint fixation in a progressive tension pattern. Results: Forty patients (43 encounters) were included. Mean age was 55.7 ± 10.2 years, mean BMI was 31.2 ± 4.9 kg/m², and 60.0% were obese. The majority presented with recurrent hernias (67.4%), and 41.9% had prior mesh in situ. Component separation was performed in all cases, and intraoperative Botox in 18.6%. HADM was used in 83.7% of encounters. At a mean follow-up of 34.0 months, there was 1 hernia recurrence (2.3%). The surgical site occurrence rate was 14.0%, with seroma as the most common complication (9.3%). There were no 30-day mortalities. Conclusions: By integrating biologic and mechanical principles, this reconstructive strategy provides a durable solution for abdominal wall repair in liver transplant recipients. A 2.3% recurrence rate and 14.0% surgical site occurrence rate compare favorably to published benchmarks in the transplant population. Full article

As the complexity, scale, and nonlinearity of modern engineering optimization problems continue to increase, traditional optimization algorithms face significant challenges in achieving high solution accuracy, fast convergence, and robust performance. To address these issues, this paper proposes a Rural Tourism Migration-based Improved Equilibrium Optimizer (RTM-IEO), aiming to enhance the global search capability and adaptive balance between exploration and exploitation. Specifically, an adaptive lens imaging opposition-based learning strategy is introduced to effectively expand the search space and maintain population diversity. A dynamic elite-guided elimination mechanism is designed to strengthen exploitation capability and accelerate convergence by reconstructing inferior individuals using high-quality solutions. In addition, a multi-stage rural tourism migration strategy is developed to dynamically regulate the search behavior across different optimization phases, enabling a more flexible and efficient search process. The effectiveness of the proposed algorithm is comprehensively validated on the CEC2021 and CEC2022 benchmark suites, where RTM-IEO demonstrates superior performance in terms of convergence accuracy, convergence speed, and robustness compared with several representative state-of-the-art algorithms. The statistical superiority of the proposed method is further confirmed through Friedman mean ranking and Wilcoxon rank-sum tests. To further evaluate its practical applicability, RTM-IEO is applied to the sustainable economic dispatch problem of a microgrid integrating renewable energy sources, including wind power and photovoltaic generation, along with energy storage systems and controllable units. The optimization objective simultaneously considers economic cost minimization and sustainable operation requirements, such as improving renewable energy utilization and reducing dependence on fossil-fuel-based generation. Experimental results indicate that the proposed method achieves a significant reduction in daily operating cost (exceeding 52% compared with benchmark algorithms), while effectively promoting low-carbon energy utilization and enhancing overall system sustainability. Overall, the proposed RTM-IEO provides an efficient and reliable optimization framework for addressing complex global optimization problems, particularly in scenarios requiring a coordinated balance between economic performance and sustainable development. Full article

Anterior cruciate ligament (ACL) injuries remain a leading cause of morbidity in athletic populations, with 70–80% occurring through non-contact mechanisms driven by biomechanical risk factors including knee valgus (>10°), low knee flexion (<30°), tibial internal rotation (>20°), and loading asymmetry (>15°), yet implementation of evidence-based neuromuscular training (which reduces injury risk by 50–70%) remains limited due to barriers in identifying at-risk individuals through accessible field-based screening. This narrative review synthesizes motion analysis technologies spanning laboratory-based optical systems (marker-based), wearable inertial measurement units (IMUs), computer vision and marker-less pose estimation, force plate and pressure-sensitive insole systems, and integrated drone-based field assessment platforms to address this critical gap. We present a three-tier clinical screening framework that progresses from basic anthropometric and single-plane video analysis to multi-modal biomechanical assessment using real-time kinematic feedback. As an illustrative example of emerging field-deployable technology, an integrated drone-based motion capture and smart insole system combining 4K video capture, AI-driven 3D motion reconstruction, and plantar pressure mapping is described to demonstrate how laboratory-quality biomechanical assessment can be achieved in ecologically valid field settings. This evidence-based review addresses current gaps between laboratory research and practical field deployment, with emphasis on cost-effectiveness, accessibility, and clinical utility for ACL injury prevention in diverse sporting environments. Full article

As the primary peripheral relay station for vibrissal tactile information, the trigeminal ganglion (TG) features heterogeneous three-dimensional (3D) cytoarchitecture that eludes full characterization using conventional two-dimensional methodologies. A high-resolution 3D imaging and reconstruction pipeline is thus required to unveil TG structural organization and define the spatial framework of target-related sensory neurons. Herein, we established a fluorescence micro-optical sectioning tomography (fMOST)-based workflow for 3D cytoarchitectural mapping of TG anatomy and validated its utility for profiling the distributions of TG neurons innervating vibrissae via single-axon tracing. fMOST imaging coupled with propidium iodide (PI) staining was applied to acquire whole-head anatomical data encompassing the vibrissae and the TG at cellular resolution. Based on clearly resolved cellular morphology and the spatial distribution of neuronal somata, we delineated the soma distribution of TG neurons and revealed a spatially heterogeneous 3D organization pattern, from which we operationally defined two anatomically distinct subdomains: the neuronal soma-rich region (NSRR) and the fiber-rich region (FRR). Furthermore, with retrograde viral/genetic labeling combined with neuronal tracing, TG neurons innervating the C2, D3, and δ vibrissae were observed in both NSRR and FRR, showing partially overlapping yet spatially biased distributions consistent with previous population-level observations of vibrissa-row-dependent topography. Notably, TG neurons innervating the δ vibrissa occupied a comparatively broader spatial extent along the anteroposterior plane in our dataset. Overall, this study facilitates an in-depth mechanistic and anatomical understanding of TG cytoarchitectural organization and underlying functional mechanisms. Full article

As critical underground engineering structures, wellbores may suffer complex structural deterioration and hidden safety hazards may be encountered during drilling. Multi-source sensor monitoring data provides an effective data basis for structural health perception and early warnings for wellbore structures at risk. The inherent diversity of formation conditions and the dynamic disturbances during drilling jointly lead to the differentiated presentation of drilling loss types, among which fractured, permeable, and vuggy losses are the most typical. This paper focuses on fractured wellbore leakage, regards wellbore leakage as an important structural failure form of underground drilling engineering structures. In-depth analysis and research on the structural deterioration mechanism of wellbore leakage were conducted, and we propose a wellbore leakage prediction method based on the improved sparrow search algorithm (ISSA) optimized gradient boosting decision tree (XGBoost). First, the Sobol sequence is adopted to replace the random initialization strategy, combined with the opposition-based learning mechanism; then, an adaptive Levy flight search mechanism is introduced to dynamically adjust the population ratio of discoverers and vigilantes; finally, intelligent optimization technologies are integrated to reconstruct the position update strategies of discoverers, followers, and vigilantes, enhancing the optimization adaptability of the algorithm. Relying on multi-field sensor monitoring datasets collected from actual drilling engineering, this paper compares the proposed model with wellbore leakage prediction models built by classical machine learning algorithms, and verifies its generalization ability on different datasets. Experimental data indicate that the improved algorithm exhibits significant advantages in optimization accuracy, enabling the proposed model to achieve an AUC improvement of 4.46%, along with accuracy (95.1%), precision (94.9%), recall (94.7%), and F1-score (94.2%). On this basis, the ISSA was applied to the hyperparameter optimization of XGBoost, constructing the ISSA-XGBoost prediction model. The method has high accuracy and good generalization ability in fractured wellbore leakage prediction, and it can realize intelligent health monitoring of underground wellbore structures, including early warnings. This study provides a reliable sensing data analysis scheme and technical support for structural health monitoring and hazard prevention in drilling engineering. Full article

The diagnosis of missing seedlings in high-density drill-seeded crops is often hindered by the strong coupling between visual perception and diagnostic rules, which leads to an irreversible cascade amplification of underlying missed detection errors. To address this dilemma, this paper proposes a “Perception–Topology” collaborative decoupling framework oriented toward row structure perception. In the perception phase, a row-structure-enhanced detection model (RS-YOLO) is constructed. It integrates Space-to-Depth (SPD) conversion, a Selective Frequency-domain Aggregation Module (SFAM), and a Row-Structure Attention Mechanism (RSM) to effectively suppress tire rut interference and explicitly reinforce the spatial topological priors of crops. In the diagnostic phase, an Adaptive Intra-row Gap Analysis (AIGA) algorithm is proposed. By utilizing a dynamic median intra-plant spacing scale and core canopy geometric pruning, this algorithm fundamentally reformulates missing seedling diagnosis into a physical interruption metric of one-dimensional graph connectivity. Evaluated on a finely reconstructed UAV-based sorghum imagery dataset, RS-YOLO achieved a significant improvement of 2.7% in precision and 3.2% in recall over the baseline model, providing a structure-aligned, high-confidence input for the diagnostic process. Based on this perceptual foundation, the AIGA algorithm ultimately achieved a diagnostic precision of 96.11% and a recall of 91.48% without the need for negative sample annotations. This framework effectively severs the propagation chain of perceptual errors, providing a noise-robust and highly physically interpretable new paradigm for the automated inspection of field population structures. Full article

GDSL esterase/lipase (GELP) proteins constitute an evolutionarily conserved yet functionally diversified hydrolase family in land plants. They participate in cuticle and secondary cell wall biosynthesis, seed lipid remobilization, reproductive development, and hormone-mediated responses to biotic and abiotic stresses. Despite extensive genome-wide and comparative genomic studies that have categorized large GELPs across numerous crops and model species, only a fraction of members have been functionally characterized in plants, and their catalytic mechanisms and regulatory architectures remain poorly understood. Recent population genomics and cross-species orthogroup analyses in 46 angiosperms have uncovered substantial natural variation within GELP coding sequences and regulatory regions, providing a powerful framework to link allelic diversity to evolutionary trajectories and physiological functions. This review synthesizes current knowledge on GELP evolution, biochemical properties, and roles in development and stress adaptation, and critically evaluates how these insights can be translated into biotechnology and molecular breeding strategies. It highlights emerging resources and concepts from orthogroup-based classification and multi-species datasets that enable systematic discovery of GELP alleles affecting agronomic traits. It further outlines research exploiting GELPs in crop improvement, emphasizing the integration of reverse and forward genetics with multi-omics profiling, biochemical and structural characterization, and gene regulatory network reconstruction. Systematic assessment of the phenotypic impacts of single and combinatorial GELP perturbations on yield, quality, and stress resilience is proposed as a key step toward translating basic insights into breeding and engineering strategies. Full article

Scientifically assessing the spatiotemporal evolution of regional carbon storage is of great significance for achieving the “dual carbon” goals and optimizing territorial spatial patterns. This study integrated the PLUS and InVEST models to systematically reconstruct the spatiotemporal pattern of carbon storage in Hebei Province from 2000 to 2020, simulate its evolution trajectory under different scenarios in 2030, and identify its driving mechanisms using the GeoDetector model. The main findings are as follows: (1) From 2000 to 2020, cropland was the dominant land use type in Hebei Province, and carbon storage exhibited a spatial pattern of “high in the northwest, low in the southeast.” Carbon storage increased from 16.23 × 10⁸ t to 16.31 × 10⁸ t, with a significantly slowed growth rate after 2010. (2) Multi-scenario simulations for 2030 indicate that under the natural development and economic priority scenarios, construction land expands significantly while cropland and grassland continue to decrease. In contrast, carbon storage shows an increasing trend under the ecological protection and cropland protection scenarios. (3) Driving factor analysis reveals that the spatial differentiation of carbon storage is primarily controlled by natural factors such as slope, elevation, and NDVI, while the explanatory power of anthropogenic factors, particularly population density, has significantly increased. The interaction between NDVI and slope exhibits a synergistic enhancement effect. This study elucidates the coupling mechanisms between land use change and carbon storage under different policy orientations, providing a scientific basis for territorial spatial optimization and the formulation of differentiated carbon neutrality pathways in Hebei Province. Full article

Background: Autobiographical memory undergoes qualitative changes across the lifespan, influencing self-understanding, emotional regulation, and psychological adaptation. Research shows memory is a dynamic process, reconstructed through retrieval, narration, and social interaction. How narrative construction and empathic engagement shape memory reconsolidation and self-continuity remains insufficiently integrated. Objectives: This narrative review synthesizes theoretical, empirical, and applied findings on autobiographical memory, narrative processes, and empathy, proposing an integrative model linking memory reconsolidation, identity reconstruction, and adaptive functioning. Methods: A theory-oriented narrative review was conducted across psychology, neuroscience, gerontology, and narrative research, drawing on literature from PubMed, PsycINFO, Web of Science, Scopus, J-STAGE, and CiNii. Peer-reviewed empirical studies, systematic reviews, and theoretical papers were organized around three interrelated conceptual domains: (1) autobiographical memory and self-related processes, (2) neurobiological and emotional mechanisms relevant to memory updating and reconsolidation, and (3) narrative construction within empathically mediated social interaction contexts, with additional consideration of evidence from narrative-based and creative interventions. Results: The reviewed literature suggests that autobiographical memory functions as a plastic, socially embedded system supporting self-continuity, although the strength and consistency of evidence vary across studies and contexts. Narrativization within empathically responsive and psychologically safe contexts enhances narrative coherence, emotional integration, and perspective-taking, promoting psychological stability, although these effects are not uniformly observed across all populations and study designs. Creative narrative activities further facilitate retrieval and meaning reconstruction, extending memory updating beyond recall, while the underlying mechanisms and causal pathways remain to be fully established. Conclusions: We propose an empathy-mediated narrative reconstruction model in which creative activity, narration, empathic response, and retelling interact cyclically to support memory reconsolidation and self-narrative updating. By integrating cognitive, social, and creative dimensions, this model provides a theoretically grounded framework with implications for clinical, educational, gerontological, and creative applications. Full article

The SDGs and the New Urban Agenda both stress the importance of strengthening urban–rural linkages to promote balanced and inclusive development. Taking China as a case, this paper explores the underlying mechanisms driving the evolution of urban–rural relations. Existing studies have primarily periodized China’s urban–rural relations based on institutional changes, with limited attention to their endogenous evolutionary mechanisms. Drawing on New Institutional Economics, this study develops an “institutional–technological–cognitive” framework. It argues that China’s urban–rural relations have evolved through three stages: prior to the Reform and Opening-Up, institution-led governance resulted in urban–rural separation; in the 1980s–2010s, technological change reshaped the constraints and return structures of factor flows, resulting in urban–rural imbalance; in the 2010s–the present, early urban–rural integration was marked by tensions between cognitive reconstruction and existing institutional arrangements. Throughout the three stages, cognition has evolved from ideological cognition to opportunity-driven cognition and further to value-driven cognition, with its agency continuously strengthening and gradually becoming a key variable influencing the effectiveness of institutional operations and the pathways of technological empowerment. Accordingly, urban–rural relations should be understood not only as the outcome of factor allocation shaped by institutions and technology, but also as a dynamic structure embedded in the evolution of cognition. The advancement of urban–rural integration should place greater emphasis on people-centered cognitive transformation, rather than relying on improvements in factor mobility or population urbanization. Full article

Background/Objectives: Bud sports (somatic mutations) offer a quick way to develop new bougainvillea varieties by altering specific traits while keeping the desirable genetic background of the original cultivar. However, we still lack a comprehensive understanding of their genomic architecture and the molecular mechanisms behind their formation. This study aimed to characterize the population genomic characteristics of bud sports derived from the commercial variety Bougainvillea × buttiana ‘Miss Manila’. Methods: We employed genotyping by sequencing (GBS) on 39 accessions, including 27 bud sports and 12 conventional varieties. Population genomic analyses, such as principal component analysis (PCA), phylogenetic reconstruction, ADMIXTURE, and diversity statistics (π, He, Tajima’s D), were performed on 64,810 high-quality SNPs. Genome-wide scans for differentiation (FST) and selective sweeps (XP-CLR) were also conducted. Results: Bud sports showed significantly lower genetic diversity (π and He) than conventional varieties, which matches their clonal origin. PCA, phylogenetic, and ADMIXTURE analyses (optimal K = 4) revealed clear genetic differentiation and distinct population structures between the two groups. The bud sport population possessed fewer private alleles and a less negative Tajima’s D value. Genomic scans identified regions under selection in bud sports, with functional annotation pointed to genes involved in ubiquitin-mediated proteolysis and RNA transport. Notably, Bou_119143 (UDP-rhamnose rhamnosyltransferase 1) showed a high mutation frequency specifically in bud sports. Conclusions: We provide the first population-genomic evidence that bud sports of ‘Miss Manila’ are genetically distinct clonal lineages, shaped by somatic mutation and selection. These findings support bud sports as efficient sources for germplasm innovation. The identified genomic regions and candidate genes lay a foundation for future marker-assisted selection and molecular breeding in bougainvillea. Full article

This paper reconstructs the archive of Islamic humanism as a cultural resource for Critical Psychologists, addressing the geopolitical double-bind of the global Muslim population caught between Islamophobia and fundamentalism. This living archive spans intellectual contributions to falsafa (rationalism) and tasawwuf (mysticism), from medieval thinkers like Ibn Rushd and al-Ghazali to modern figures like Mourad Wahba and Ali Shariʿati. While primarily philosophical, these contributions offer practical implications for psychosocial liberation. Utilizing a methodology of deconstructive unsilencing, the archive is positioned as both pluriversal and metaphorical. By analyzing the ideological mechanism of virtual internment, the paper proposes a praxis of learned ignorance and decolonial resistance to subvert the panoptic look of anti-humanism through the Real Gaze of Islamic humanism. This retrieval offers a materialist praxis seeking to overturn the (post)colonial triad of fundamentalism, parasitic capitalism, and postmodernism. In sum, the article argues that a genealogical consignation of Islamic humanism facilitates a transmodernity that integrates Totality with Exteriority, effectively negating both coloniality and antimodernity. Full article

Given China’s strategic need to alleviate poverty and promote high-quality development in the Yellow River Basin, in this paper, we adopt the unique perspective of ecological migration to dynamically analyze changes in the spatial structure, spatial differentiation, trajectory, and formation mechanism of multidimensional poverty. This study finds the following: (1) In recent years, multidimensional poverty in the contiguous poverty-stricken areas represented by Liupan Mountain in Ningxia has shown a tendency to change from overall poverty to partial poverty. (2) The influence of rural per capital net income on multidimensional poverty has been gradually slowing down over time, which reflects the evolution of the concentrated contiguous poverty-stricken areas represented by the Liupan Mountain area in Ningxia from absolute poverty to relative poverty. (3) Geographical capital and economic development exert a high degree of direct impact on multidimensional poverty. However, as key carriers of spatial reconstruction, ecological migration is not a direct first-order input factor. Instead, it indirectly influences the spatial reconstruction of poverty by reshaping the distribution of population, housing, cultivated land, and infrastructure, with its effects reflected in core indicators such as per capita cultivated land and ecological vulnerability. Establishing a long-term poverty alleviation mechanism for advantageous industries, building a multidimensional education system for poverty reduction, and implementing ecological migration are important pathways to alleviate and eliminate multidimensional poverty in this region. Full article