Search Results (225)

Autonomous navigation in unstructured off-road environments presents fundamental challenges due to terrain heterogeneity, the absence of structured road markings, and the necessity for real-time traversability reasoning from raw sensory observations. We present TerrainFormer, a hierarchical framework that integrates a world model for terrain dynamics prediction with a temporal decision transformer for action selection. Our methodology employs a two-phase training paradigm: (1) self-supervised world model pretraining on LiDAR point clouds to learn terrain representations encompassing traversability, elevation, and semantic segmentation; (2) behavioral cloning of the decision transformer conditioned on frozen world model features with temporally derived goal directions. The world model processes raw 3D LiDAR point clouds through a PointPillars encoder for real-time bird’s-eye-view (BEV) projection, followed by a Vision Transformer backbone that produces latent terrain representations. A principal contribution is our cross-dataset generalization paradigm: the world model is trained on separate datasets while the decision transformer is trained on separate sequences, ensuring zero data overlap between training phases. We introduce automatic goal direction computation from vehicle pose trajectories, enabling the model to learn directionally conditioned navigation policies. To address the class imbalance inherent in off-road driving data, we employ focal loss with inverse-frequency class weighting and action-chunk supervision. Experimental evaluation on the RELLIS-3D dataset achieves 87.31% test accuracy with 0.7948 macro F1 across all 12 action classes. The world model’s predicted future frames produce only a 0.79% accuracy drop versus ground-truth observations, with 98.82% action agreement, demonstrating effective cross-dataset generalization for real-time off-road navigation. Full article

Inflammatory bowel disease (IBD; Crohn’s disease and ulcerative colitis) arises from convergent dysfunction of the epithelial barrier, mucosal immunity, and gut microbiome on a background of genetic susceptibility and environmental exposures. Diet is among the most modifiable of these exposures, yet much of the diet–microbiome research in IBD remains descriptive and poorly aligned with the molecular pathways linking food to mucosal effects. This comprehensive review reframes the field around functional dysbiosis, in which altered microbial metabolic capacity (rather than taxonomic shifts alone) drives disease-relevant biology. We trace how dietary substrates and additives are converted by gut microbes into bioactive metabolites (short-chain fatty acids, secondary bile acids, tryptophan-derived indoles, sulfur compounds, and polyphenol-derived molecules) and map these to host receptors and signaling pathways governing barrier function, mucus and antimicrobial peptide production, and Treg/Th17 balance. Defined dietary therapies (exclusive enteral nutrition, the Crohn’s disease exclusion diet plus partial enteral nutrition, and Mediterranean-style patterns) are reinterpreted as interventions that reshape microbial metabolic output, and candidate biomarkers for microbiome-informed precision nutrition are evaluated. Microbiota-derived metabolites provide the molecular interface between diet and mucosal immunity in IBD; personalized dietary algorithms remain a research goal, not a validated clinical tool, and diet is best framed as adjunctive to pharmacotherapy and dietitian care. Full article

Patients confined to bed for extended periods must frequently change sleeping posture to prevent pressure ulcers, which are difficult and undesirable to treat. In this study, three IMU sensors were placed on 108 bedridden patients to collect data for five different postures, resulting in 1,800,000 data points per sensor. These were converted into Eulerx, Eulery, and Eulerz values. The goal was to detect the sleep posture using a single IMU sensor. Four cases were defined: Case 1 used only IMU1, Case 2 only IMU2, Case 3 only IMU3, and Case 4 combined all three. Euler signals were converted into RGB images, framing the problem as an image classification task. A total of 2000 images were used, with 400 for training and 100 for testing in each case. A U-Net model was applied, achieving high IoU scores: 98.00%, 99.56%, 99.72%, and 98.20% respectively. Accuracy scores were 98.98%, 99.78%, 99.86%, and 99.09%, confirming U-Net’s effectiveness. Full article

Background/Objectives: Egocentric and allocentric spatial transformations are central to spatial cognition, yet it is unknown whether they rely on the same neural mechanisms. The goal of this study was to examine whether egocentric transformations engage the neural processes associated with mental rotation in visual–spatial working memory. Methods: High-density EEG was recorded while participants performed two matched pointing-direction tasks, in which they indicated the direction toward a target location, while instructed to use either allocentric array rotation or egocentric perspective-taking. Response times and accuracy were recorded, and event-related potential (ERP) responses were analyzed as a function of rotation angle (100° vs. 160°) and differences between front and back pointing directions. Results: Response times increased with rotation angle in both tasks, whereas a front–back asymmetry in accuracy was observed only in perspective-taking. Both tasks showed rotation-related ERP modulation, but the timing and spatial distribution of these effects differed across tasks. In the array-rotation task, rotation-related ERP effects were observed over right-parieto–occipital regions at 460–510 ms. In the perspective-taking task, the ERP effects were observed over left-central regions at 400–470 ms and 520–610 ms. ERP differences between front and back directions were robust and widespread in the egocentric condition but limited in the allocentric condition. Conclusions: Perspective-taking does not show the posterior rotation-related ERP effect associated with mental rotation of object representations in visual–spatial working memory. Instead, it appears to reflect updating of the observer-centered reference frame, consistent with simulated self-motion processes involving vestibular and proprioceptive signals. Full article

The accelerated advancement of artificial intelligence has triggered new discussions concerning the link between technological progress and the distribution of income. This study frames China’s National New Generation Artificial Intelligence Innovation and Development Pilot Zone (AIIDPZ) policy as a quasi-natural experiment, enabling us to identify the causal effect of AI promotion strategies on the urban–rural income inequality. Drawing on panel data from 257 Chinese cities over the period 2012–2023, we estimate the impacts using a multi-period difference-in-differences (DID) approach. The results demonstrate that the pilot zone policy significantly lowers the urban–rural income inequality index, by roughly 8.41%. The mechanism analysis reveals two primary pathways. First, the policy stimulates innovation in agricultural science and technology, which in turn boosts rural productivity. Second, it deepens the attention that the government directs toward artificial intelligence, contributing to a more balanced allocation of technological dividends between urban and rural areas. Heterogeneity tests further indicate that the inequality-reducing effects are especially notable in eastern regions, as well as in cities characterized by well-developed digital infrastructure and relatively weaker endowments of human capital. By offering empirical insight into how developing countries can reconcile distributional equity with the application of artificial intelligence, this study contributes to advancing the Sustainable Development Goals (SDGs). Full article

Public administration research provides structured explanations of collaborative governance. PPP scholarship, however, has largely emphasized macro governance frameworks, leaving micro-level collaborative drivers between internal partners underexplored. Additionally, internal transparency has seldom received attention as a governance outcome of collaboration. Building upon collaborative governance theories, this study conceptualizes collaboration in PPPs through four focal collaborative elements (FCEs): organizational capacity asymmetries, commitment to process, effective communication, and trust building. A survey instrument was used to collect experts’ opinions regarding the impact of PPP-specific characteristics, as practical mechanisms, on collaboration. The results show strong endorsement of mechanisms related to post-procurement capacity asymmetries, role/authority shifts, contractual complexity, and lifecycle discontinuities (staff changes and phase transitions). Such PPP characteristics undermine communication and information continuity. Trust building appeared to have an ambivalent role shaped by long-term incentives alongside goal drift and contractual rigidity. This study identifies the most salient mechanisms framing collaborative elements in PPP and translates them into governance implications for sustained collaboration and strengthened internal transparency across PPPs’ lifecycle. Limitations and future avenues for research based upon these findings are presented. Full article

Edible insects are recognised as a sustainable, high-protein food source, yet consumption in Western diets remains limited due to cultural barriers and concerns about taste, appearance, and safety. This study explored the factors affecting the acceptance of familiar products where insects have been added as ingredients, and how purchase intent is influenced by label information. During sensory evaluation, 59 participants tested pasta-only and pasta-with-sauce samples that were presented with and without insects (controls). Results showed no significant differences in preference between insect and control samples (pasta only: p = 0.150; pasta with sauce: p = 0.193). Open-ended feedback highlighted flavour, texture, and familiarity as key drivers. Label design strongly shaped purchase intent, with participants preferring labels that combined clear allergen and ingredient information with credible nutrition and eco-certification logos. Benefit-focused price framing (protein and sustainability) significantly increased willingness to pay (p < 0.001), while prior insect consumption, age and gender had no effect. Overall, the findings show that adding insects into a well-known ready-meal format, supported by transparent labelling and benefit-based communication, has the potential to improve acceptance. This approach highlights a practical way to bring insect proteins into mainstream food systems while contributing to nutrition and sustainability goals. Full article

Background/Objectives: Acute pancreatitis in pregnancy and the early postpartum period (APIP) is an uncommon but potentially life-threatening condition associated with significant maternal morbidity. Physiological adaptations of pregnancy, recent obstetric surgery, and overlapping postoperative symptoms frequently obscure early diagnosis and complicate perioperative and critical care management. This review provides a clinically oriented, anaesthesiology-focused overview of APIP, integrating current evidence with perioperative decision-making, pain management strategies, and intensive care considerations relevant to obstetric practice. Methods: A narrative, clinically structured review of the literature was performed focusing on epidemiology, aetiology, diagnosis, severity stratification, and management of APIP. Anaesthesiology- and ICU-specific aspects are synthesised into a pragmatic management framework. Results: Gallstone disease and hypertriglyceridaemia remain the predominant causes of APIP, with most cases occurring in the third trimester or early postpartum period. Diagnosis relies on pancreatic enzyme elevation and pregnancy-adapted imaging strategies. Early goal-directed fluid resuscitation, effective multimodal analgesia, and timely initiation of enteral nutrition are key determinants of outcome. Therapeutic ERCP and laparoscopic cholecystectomy can be safely performed during pregnancy when clinically indicated and may reduce recurrence in biliary pancreatitis. Neuraxial analgesia provides effective, opioid-sparing pain control and may improve respiratory mechanics and haemodynamic stability. Persistent organ failure remains the strongest predictor of adverse outcome and should prompt early intensive care admission. Conclusions: APIP requires early recognition and severity-adapted, multidisciplinary management. Anaesthesiology-led strategies play a central role in optimising analgesia, haemodynamic stability, and timely escalation of care. Framing APIP within a perioperative and critical care context may improve maternal outcomes in this vulnerable patient population. Full article

Background: Endometriosis is a major cause of female infertility. It significantly impacts oocyte quality and embryonic development. The condition’s pathophysiological mechanisms are multifactorial. However, they are believed to be reflected in the biochemical composition of follicular fluid (FF). FF is the immediate microenvironment of the developing oocyte hence its relevance. Conventional analytical methods provide only a limited view of this complex biofluid. This underlies the need for holistic profiling techniques. Objective: This narrative review synthesizes current knowledge on the potential of Fourier-Transform Infrared (FTIR) and Raman spectroscopy. The two are scrutinized as label-free, non-destructive tools for analyzing FF in the context of endometriosis. As such, the aim is to bridge the understanding of the disease’s impact on the follicular niche with the analytical power of these spectroscopic techniques, ultimately highlighting a critical research gap, while critically evaluating the translational pathway required to bring these techniques from research laboratories into routine clinical IVF practice. This includes assessment of practical feasibility, cost-effectiveness, turnaround time, standardization requirements, and comparison with existing clinical biomarkers. Methods: We outline the fundamental principles of FTIR and Raman spectroscopy and their complementary strengths. The review then consolidates evidence from proteomic and metabolomic studies demonstrating FF alterations in endometriosis. We also showcase the successful application of vibrational spectroscopy in other reproductive diagnostics. This synthesis is vital to identifying a specific unmet need in the field. Conclusions: Despite the known importance of FF and the proven capability of FTIR and Raman spectroscopy in related areas, there is a striking lack of studies applying these techniques directly to the FF of women with endometriosis. This review concludes by framing this void as a pivotal research opportunity. In doing so, it presents a direct rationale and methodological framework for a future study designed to characterize the unique spectral fingerprints of endometriosis in FF, with the goal of uncovering novel biomarkers and pathophysiological insights. Full article

This paper examines students’ perceptions of factors influencing normative support for the integration of AI Chatbots in universities, providing an empirical basis for developing institutional policies and implementation strategies in higher education. Framed within the sustainability perspective, the study examines how ethical, cognitive, and perceptual factors shape the long-term adoption of AI technologies in academic environments. Our study employs a structural model comprising 10 constructs, 46 items, and 9 hypotheses, tested on a sample of 408 economics students from Timisoara. The research identifies AI literacy as the most influential factor in the formal integration of these technologies in universities. The following factors have a direct impact: teacher perception, student perception, and cognitive risks (reliance on AI Chatbots and avoidance of intellectual effort). Use for personalized learning is a factor with a significant direct effect on positive perceptions and intentions to use AI Chatbots among students. Academic integrity risks, as well as limitations on accuracy and reliability, have no significant impact. AI Chatbots represent an essential opportunity to transform higher education. However, their positive impact is realized only through responsible formal integration, grounded in ethical policies, adequate digital education, and the adaptation of pedagogical practices. Universities must regard AI as a strategic ally for teachers and students, while keeping human interaction, critical thinking, and academic integrity at the centre of the educational process. The study argues that students’ perceptions are that universities must approach AI Integration as a strategic component of sustainable educational ecosystems, aligning innovation with long-term academic integrity and the objectives of sustainable development, particularly Sustainable Development Goal 4 (Quality Education). Full article

As debates intensify over establishing culture as a standalone Sustainable Development Goal (SDG) beyond 2030, this paper studies the policy implications of such a shift and its consequences for the future of global development frameworks. While acknowledging growing calls for a standalone cultural SDG—often framed as SDG18—this study cautions that isolating culture as a separate goal risks reinforcing sectoral silos and undermining its crosscutting relevance in sustainable development. Instead, the paper argues that cultural sustainability is more effectively advanced through systematic mainstreaming across the existing SDGs, ensuring balanced integration alongside economic, environmental, and social dimensions. Using qualitative and quantitative content analysis supported by NVivo, the research examines how culture is represented in SDG implementation reports, policy briefs, and Voluntary National Reviews (VNRs). The findings reveal persistent patterns of marginalization, thematic narrowness, and regional inconsistency in the treatment of culture, indicating structural limitations in SDG implementation rather than a lack of cultural relevance. This reinforces the fact that culture needs to be more visible within the SDG framework; however, the question remains: how? By comparing the two dominant policy trajectories—advocacy for a standalone cultural SDG and the mainstreaming of culture across the existing SDGs—this paper identifies pathways and a set of policy-oriented recommendations to strengthen cultural integration without further fragmenting the sustainability agenda. Full article

Bone metastases represent a major cause of morbidity in advanced cancers, yet the neural regulation of metastatic growth within bone remains largely unexplored. The skeletal system is richly innervated by sensory and sympathetic nerve fibers that influence bone remodeling, hematopoiesis, and immune surveillance. Emerging evidence suggests that disseminated tumor cells exploit these neural circuits to create a growth-permissive microenvironment. Tumor-secreted neurotrophic factors can induce nerve sprouting, while sympathetic activation via β-adrenergic receptors promotes osteoclastogenesis, immunosuppression, and tumor proliferation. Neuropeptides such as substance P and calcitonin gene-related peptide exert dual effects on bone cells and infiltrating immune populations, further shaping the metastatic niche. The interplay between neural signals, osteolytic activity, and immune modulation positions the neuro–bone axis as a critical but underappreciated driver of metastatic progression. In this review, we synthesize current evidence on the anatomy and function of bone innervation, tumor-induced neural remodeling, and neuro–immune–osteoclast interactions. We highlight preclinical and clinical data supporting neuromodulatory strategies, including β-blockers, neurotrophin inhibitors, and targeted nerve ablation, as potential adjuncts to standard bone metastasis therapies. Finally, we identify key knowledge gaps, including the need for spatial and functional mapping of nerve–tumor interfaces and for integrating neuroimaging into bone metastasis detection. By framing the neuro–bone axis as a therapeutic target, we aim to catalyze interdisciplinary research that bridges oncology, neuroscience, and bone biology, with the goal of disrupting neural support for metastatic growth Full article

The use of a corrugated steel plate shear wall (CSPSW) lateral load-bearing system in a steel moment frame (SMF) significantly increases the system’s energy absorption and stiffness. However, the design of CSPSWs involves many parameters and details that greatly increase the complexity of the structure’s response. This study aims to evaluate the effectiveness of the geometric parameters of this system using modern optimization algorithms and an alternative mathematical technique, Response Surface Methodology (RSM). Five geometric parameters, namely crest width (a), diagonal section width (b), corrugation depth (c), sheet thickness (t), and aspect ratio of plate dimension (d), were analyzed to improve the performance of CSPSWs. Design of experiments (DOE) was performed using Design-Expert software, and the required response surface methodology models were designed based on the dimensions of the five variables. Structure weight per meter reduction was set as the optimization goal of the problem. The problem constraints were also defined based on an increase in load-bearing capacity and a reduction in the equivalent plastic strain (PEEQ) percentage in three safety levels 80%, 85% and 90%. Subsequently, the alternative equations developed by RSM to define the objective function and nonlinear constraints were also optimized using modern algorithms in MATLAB 2015. Results revealed a coefficient of determination (R²) of 0.9995 between the experimental and numerical findings and a 1% error between the values obtained from the optimization and reanalysis of the finite elements. Also, they showed an increase in the frame’s lateral load-bearing capacity with the CSPSW, along with a reduction in weight. Full article

Modern interaction with smart devices is hindered by the “Midas Touch” problem, where sensors frequently misinterpret incidental physical movements as intentional commands due to a lack of human context. This research addresses this conflict by introducing the Multimodal Haptic Informatics (MHI) index within a novel Scene–Action–Trigger (SAT) framework. The goal is to contextualize mechanical movements as human intent by integrating physical, spatial, and cognitive data locally at the edge. The methodology employs an “Action-as-primary indexing” mechanism where the Action channel (IMU) serves as a temporal anchor t, triggering high-resolution Scene (computer vision) and Trigger (audio) processing only during critical haptic events. Validated through a complex origami crane task generating 29,408 data frames, the framework utilizes a three-stage informatics derivation process: single-modal scoring, score weighting, and hand state mapping. Results demonstrate that applying an adaptive “Speedometer” logic successfully reclassifies the “Transitional State”. While this state constitutes over half of the behavioral dataset (54.76% on average), it is effectively disambiguated into meaningful intent using a self-trained local Large Language Model (LLM) for semantic verification. Furthermore, the event-driven sampling of 93 keyframes reduces the processing overhead by 99.68% compared to linear annotation. This study contributes a low-latency, privacy-preserving “Protocol of Assent” that maintains user agency by providing intelligent system suggestions based on confirmed haptic intensity. Full article

This study builds on the concept of loss tolerance by introducing investment grip, a behavioral interpretation that captures investors’ commitment to long-term objectives under adverse market conditions. While loss tolerance traditionally measures the maximum financial loss an investor can withstand, investment grip focuses on the behavioral and psychological dimensions of maintaining long-term investment objectives when facing short-term setbacks, thus providing a more behaviorally grounded and operationalizable approach for evaluating client risk profiles. The investment grip framework integrates insights from self-control theory, emotional regulation research, and goal-commitment models. Using data from 92,792 Japanese retail investors in the 2025 “Survey on Life and Money,” we examine how gain-framed and loss-framed messages are associated with investment grip, controlling for digital financial literacy and demographic, socioeconomic, and psychological factors. Our findings reveal that loss framing is robustly associated with stronger investment grip, whereas gain framing demonstrates no statistically meaningful effect. These findings offer new insights into Japanese household financial behavior, explaining why conservative savings patterns persist despite the availability of better investment alternatives. The results underscore the role of information framing in shaping household investment behavior, with implications for investor protection and financial communication policy. Full article