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Intelligent Disassembly System for PCB Components Integrating Multimodal Large Language Model and Multi-Agent Framework
No full textThe escalating volume of waste electrical and electronic equipment (WEEE) poses a significant global environmental challenge. The disassembly of printed circuit boards (PCBs), a critical step for resource recovery, remains inefficient due to limitations in the adaptability and dexterity of existing automated systems. This paper proposes an intelligent disassembly system for PCB components that integrates a multimodal large language model (MLLM) with a multi-agent framework. The MLLM serves as the system’s cognitive core, enabling high-level visual-language understanding and task planning by converting images into semantic descriptions and generating disassembly strategies. A state-of-the-art object detection algorithm (YOLOv13) is incorporated to provide fine-grained component localization. This high-level intelligence is seamlessly connected to low-level execution through a multi-agent framework that orchestrates collaborative dual robotic arms. One arm controls a heater for precise solder melting, while the other performs fine “probing-grasping” actions guided by real-time force feedback. Experiments were conducted on 30 decommissioned smart electricity meter PCBs, evaluating the system on recognition rate, capture rate, melting rate, and time consumption for seven component types. Results demonstrate that the system achieved a 100% melting rate across all components and high recognition rates (90–100%), validating its strengths in perception and thermal control. However, the capture rate varied significantly, highlighting the grasping of small, low-profile components as the primary bottleneck. This research presents a significant step towards autonomous, non-destructive e-waste recycling by effectively combining high-level cognitive intelligence with low-level robotic control, while also clearly identifying key areas for future improvement
How Extended Reality Is Shaping Smart Cities: A Systematic Literature Review
No full textXR technologies enhance the sustainable development of urban areas by merging digital and physical worlds. In smart city contexts, XR has been applied in miscellaneous ways, from supporting urban planning and design through immersive visualization, to improving traffic and navigation services via real-time overlays, and to enhancing public safety and emergency response through simulation and situational support. However, the literature does not clearly categorize XR application domains in smart cities, interaction methods, and types of sensory feedback. This study presents an SLR reported in accordance with the PRISMA 2020 guidelines. We included 92 studies published between 2009 and 2024, proposing a classification of application domains, interaction modalities, and sensory feedback. We searched Scopus, Web of Science, and IEEE Xplore using predefined search terms and eligibility criteria. This review offers a comprehensive overview of nearly 20 years of XR research in smart cities, highlighting established practices and guiding future application development and research directions
Carbon Filters Modified with Synthesized TiO2, Fe3O4 and CaO via Mechanical Milling for Methylene Blue Adsorption
No full textAlthough carbon filters (CF) can exhibit limited adsorption/selectivity for certain emerging pollutants and operating conditions, incorporating carbon–metal-oxide composites provides a platform to study how surface chemistry, charge distribution and oxide dispersion influence adsorption behavior. This study investigates the incorporation of metal oxides (Fe3O4, TiO2 and CaO) into a commercial carbon filter via mechanical milling, focusing on fundamental changes in surface properties and methylene blue (MB) adsorption mechanisms. The synthesized oxides were characterized by X-ray diffraction and scanning electron microscopy, confirming crystalline structures with crystalline sizes between 11 and 23 nm. Composite filters with varying oxide contents (10–30 wt%) were evaluated for point of zero charge (PZC), surface charge distribution and methylene blue (MB) adsorption. The kinetic experiments were adjusted to pseudo-second order (PSO). Although the maximum adsorption capacity (2.75 mg·g−1 for CaO-modified filters) is lower than commercially activated carbons, this work clarifies how oxide type and dispersion control adsorption performance and interaction mechanisms. Langmuir and Freundlich models revealed monolayer adsorption with favorable dye-surface interactions. These models provide key insights into the role of oxide type and pH in the dye removal process
Comparable Effectiveness of Novel and Commercial Saliva Substitute Gels in Dental Patients Experiencing Xerostomia: A Randomized, Double-Blind Crossover Trial
No full textSaliva substitutes are the standard treatment for dry mouth. This study aimed to evaluate the clinical effectiveness of a novel artificial saliva gel (RSU gel) compared with a commercial product (GC Dry Mouth Gel®). A randomized, double-blind, two-phase crossover clinical trial was conducted with 37 participants with xerostomia. In the short-term phase, oral wetness, xerostomia scores, and clinical score of oral dryness (CSOD) were assessed up to 60 min after a single gel application. In the short-term repeated-use phase, each gel was applied 4 times daily for 14 days, separated by a 14-day washout period. The same parameters, including patient satisfaction and adverse events, were re-evaluated. Data were analyzed using generalized linear mixed models and generalized estimating equations. Both the RSU and GC Dry Mouth Gel® significantly improved oral wetness immediately after a single application. No significant difference was observed for the RSU gel relative to the GC Dry Mouth Gel® for oral wetness (OR = 1.01, 95% CI 0.98, 1.04, p = 0.248), xerostomia score (OR = 1.10, 95% CI 0.42, 2.88, p = 0.661), or CSOD (OR = 0.95, 95% CI 0.58, 1.55, p = 0.765) at 60 min. After 14 days of use, oral wetness increased significantly in both groups (2.94%, 95% CI 0.30%, 5.76%, p = 0.030) and did not differ significantly between the two products (p = 0.110). The xerostomia scores and CSOD also significantly improved, independent of product type (OR = 7.21, 95% CI 2.56, 20.34, p < 0.001, and OR = 2.82, 95% CI 1.50, 5.32, p = 0.001, respectively). The participants reported high satisfaction and acceptable taste, and no adverse effects were detected in those using the RSU gel throughout the study. Its lower cost and local availability make it a practical option for xerostomia management, particularly in populations with limited access to commercial saliva substitutes
Self-Construal as a Predictor of Antagonistic Personality Traits
No full textSelf-construal refers to how individuals perceive themselves relative to others and includes dimensions of independence and interdependence. To understand antagonistic personality traits of Machiavellianism, psychopathy, narcissism, and sadism, we investigate how these four traits (the Antagonistic or Dark Tetrad) are predicted by independent and interdependent self-construal using self-report measures from 861 Canadian university students. Direct entry linear regression found that after accounting for age and gender, each antagonistic trait was significantly predicted by independent and interdependent self-construal. As the pattern of regression weights differ for self-construal dimensions, we conclude that self-construal differentially predicts the Antagonistic Tetrad. These results add to work examining how self-construal is related to the Antagonistic Triad by the addition of sadism and investigating the predictive ability of self-construal
An Improved NSGA-II–TOPSIS Integrated Framework for Multi-Objective Optimization of Electric Vehicle Charging Station Siting
No full textThe rapid growth of electric vehicle (EV) adoption poses significant challenges for the rational planning of charging infrastructure, where economic efficiency and service quality are inherently conflicting. To support scientific decision-making in charging station siting, this study proposes an integrated multi-objective optimization and decision-support framework that combines an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) with an entropy-weighted TOPSIS method. A bi-objective siting model is developed to simultaneously minimize total operator costs and maximize user satisfaction. User satisfaction is explicitly characterized by a nonlinear charging distance perception function and a queuing-theoretic waiting time model, enabling a more realistic representation of user service experience. To enhance convergence performance and solution diversity, the NSGA-II algorithm is improved through variable-wise random chaotic initialization, opposition-based learning, and adaptive crossover and mutation operators. The resulting Pareto-optimal solutions are further evaluated using an improved entropy-weighted TOPSIS approach to objectively identify representative compromise solutions. Simulation results demonstrate that the proposed framework achieves superior performance compared with the standard NSGA-II algorithm in terms of operating cost reduction, user satisfaction improvement, and multi-objective indicators, including hypervolume, inverted generational distance, and solution diversity. The findings confirm that the proposed NSGA-II–TOPSIS framework provides an effective, robust, and interpretable decision-support tool for EV charging station planning under conflicting objectives
Emerging Oncogenic and Immunoregulatory Roles of BST2 in Human Cancers
No full textBST2 has emerged as a multifunctional molecule that bridges antiviral defense, membrane architecture, and tumor immunity. Originally characterized as an interferon-inducible restriction factor that tethers virions to the plasma membrane, BST2 is now recognized as an oncogenic driver and immunoregulatory hub in diverse malignancies. In cancer, BST2 expression is frequently upregulated through promoter hypomethylation and transcriptional activation. Functionally, BST2 promotes proliferation, epithelial–mesenchymal transition, anoikis resistance, and chemoresistance, whereas its loss sensitizes tumor cells to proteotoxic and metabolic stresses. Beyond tumor cells, BST2 modulates the tumor microenvironment by promoting M2 macrophage infiltration, dendritic cell exhaustion, and natural killer (NK)-cell resistance, thereby contributing to immune evasion. Elevated BST2 expression correlates with poor prognosis in glioblastoma, breast, nasopharyngeal, and pancreatic cancers, and it serves as a circulating biomarker within small extracellular vesicles. In conclusion, BST2 is a dual-function molecule that integrates oncogenic signaling and immune regulation, making it an attractive diagnostic and therapeutic target for hematological and solid tumors
Polydopamine-Coated Surfaces Promote Adhesion, Migration, Proliferation, Chemoresistance, Stemness, and Epithelial–Mesenchymal Transition of Human Prostate Cancer Cell Lines In Vitro via Integrin α2β1–FAK–JNK Signaling
No full textPolydopamine (PDA) surface coatings are widely used in biomedical engineering to enhance cell–substrate interactions; however, their effects on cancer-cell behavior remain unclear. In this study, we investigated how PDA-coated two-dimensional (2D) culture surfaces influence oncogenic traits of human prostate cancer (PC) cells in vitro. Using LNCaP, DU145, and PC3 cell lines, we found that PDA-coated substrates markedly increased the adhesion, migration, invasion, proliferation, and colony formation in a dose- and time-dependent manner. PDA exposure also induced epithelial–mesenchymal transition (EMT), upregulated cancer stem cell markers (CD44, CD117, CD133, Sox2, Oct4, and Nanog), and elevated expression of metastasis- and chemoresistance-associated molecules (MMP-2, MMP-9, MDR1, and MRP1). Mechanistically, PDA coatings enhanced integrin α2β1-associated cell adhesion, accompanied by increased focal adhesion kinase (FAK) phosphorylation and downstream activation of JNK signaling. Pharmacological inhibition of integrin α2β1 (BTT-3033), FAK (PF573228) and JNK (SP600125) effectively abrogated PDA-induced malignant phenotypes and restored chemosensitivity to cabazitaxel, cisplatin, docetaxel, curcumin, and enzalutamide. Collectively, these findings identify PDA-coated surfaces as a simple, efficient, and reductionist in vitro platform for studying adhesion-mediated signaling and phenotypic plasticity in PC cells, while acknowledging that further validation in three-dimensional (3D) and patient-derived models will be required to establish in vivo relevance
Unveiling the Genomic Landscape of Yan Goose (Anser cygnoides): Insights into Population History and Selection Signatures for Growth and Adaptation
No full textThe Yan goose (YE, Anser cygnoides) is a valuable indigenous poultry genetic resource, renowned for its superior meat quality and environmental adaptability. Despite its economic importance, the genetic basis underlying these adaptive traits remains unclear. In this study, we employed whole-genome resequencing (WGS) to perform high-throughput sequencing on a conserved population of 15 samples. Bioinformatic analyses were conducted to systematically evaluate the population’s genetic structure, and a genome-wide scan for selection signals related to economically significant traits was performed using the integrated haplotype score (iHS) method. An average of 4.43 million high-quality SNPs were identified, which were predominantly located in intergenic and intronic regions. Population structure analysis revealed a close genetic relationship within the conserved population of YE, with no significant lineage stratification observed. Pairwise sequentially Markovian coalescent (PSMC) analysis indicated that the YE underwent a severe genetic bottleneck during the Last Glacial Maximum (LGM), followed by gradual population recovery in the early Neolithic period. Genome-wide selection signal scanning identified multiple genomic regions under strong selection, annotating key genes associated with growth and development (e.g., GHRL, AKT1, and MAPK3), lipid deposition (e.g., PLPP4, SAMD8, and LPIN1), and disease resistance and stress resilience (e.g., TP53, STAT3). Functional enrichment analysis revealed significant enrichment of these genes in pathways related to glycerophospholipid metabolism (p < 0.01), purine metabolism (p < 0.01), and immune response (p < 0.01). This study not only provides a theoretical foundation for the scientific conservation of the YE germplasm resources but also offers valuable genomic resources for identifying functional genes underlying important economic traits and advancing molecular breeding strategies
Influence of the Synergistic System of Carbon-Based Fillers with Melamine Polyphosphate on the Thermal Properties and Fire Hazard of Flexible Polyurethane Foams
No full textIn the article we investigated the effectiveness of a synergistic system designed to reduce the fire hazard of flexible polyurethane (PUR) foams. The examined system consisted of a carbon-based filler graphene (G), carbon nanotubes (CNTs), or expanded graphite (EG) combined with melamine polyphosphate (MPP). The investigated polyurethane foams (PUR) were synthesized at room temperature via a polycondensation reaction between a polyol and an isocyanate, with an OH: NCO molar ratio of 2:1. Both the carbon fillers and melamine polyphosphate were homogeneously dispersed within the polyol component. Thermogravimetric analysis (TGA), cone calorimetry, and microcalorimetry were used to evaluate the influence of the fillers on the thermal stability and flammability of the PUR foams. The toxicity of the gaseous products was assessed using a coupled TG-gas analysis system, while the optical density of the evolved gases was determined using a Smoke Density Chamber (SDC). The obtained results demonstrated that the applied synergistic carbon-phosphorus filler system significantly reduced the fire hazard of the tested PUR foams. In particular, the EG5-MPP system enabled the formation of self-extinguishing materials