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Digital twin (DT) technology is a key element of Industry 4.0. Despite its rapid development, current research is mainly focused on industrial optimisation and machine-level monitoring. However, its implementation in the educational process lags significantly behind practice. Moreover, existing DT implementations in education often emphasise visualisation or simulation, while neglecting synchronisation and verification of functional equivalence between the physical and virtual systems. This study presents the design, development and experimental verification of a digital twin of a laboratory material handling system. The virtual model created in Tecnomatix Plant Simulation is connected to the physical system controlled by a Siemens PLC SIMATIC S7-1200 and equipped with industrial sensors and an HMI interface. Real-time bidirectional communication is established via the OPC UA protocol using KEPServerEX, ensuring synchronisation between the physical and virtual systems. Experiments confirmed the functional synchronisation of both systems. Additionally, the study presents that DT technology can be adapted for educational purposes and implemented in engineering education. Full article

Papaya (Carica papaya L.) is a widely cultivated tropical and subtropical fruit crop valued for its rich nutritional content, diverse food industry applications, and the medicinal use of papain. However, bitterness in papaya fruit, particularly in fibrous strands, negatively affects fruit quality and consumer acceptance; therefore, the development of papaya cultivars with stable and desirable quality is of great importance. To identify the bitter compounds in papaya fruit fibrous strands and elucidate the molecular mechanisms underlying their biosynthesis, we performed transcriptomic and metabolomic analyses of fibrous strands from two papaya cultivars at three developmental stages. We identified carpaine, dehydrocarpaine II, and their derivative alkaloids. Furthermore, we identified two key regulatory genes, CpNAC82 and CpHD-Zip ANT2, associated with alkaloid biosynthesis. Finally, using single-nucleus RNA sequencing technology, we constructed a comprehensive gene expression atlas of papaya fibrous strands and stems, successfully identifying multiple cell types, including epidermal cells, guard cells, parenchyma cells, and phloem cells. Epidermal and phloem cells serve as the primary sites of alkaloid metabolism in papaya. These findings provide new insights into the molecular mechanisms of bitterness in papaya’s fibrous strands and yield genomic resources for improving fruit quality in papaya. Full article

Computational thinking (CT) has become a cross-curriculum priority in many educational jurisdictions, yet a growing body of research reports uneven integration in initial teacher education (ITE), limited preservice teacher confidence, and persistent misconceptions that equate CT with coding. Concurrently, generative artificial intelligence (GenAI) has rapidly entered university programmes, offering new possibilities for modelling problem-solving, generating multiple representations, and supporting iterative design. However, while constructs such as self-efficacy, cognitive load, and affect are well established in educational psychology, their specific application to the intersection of CT and GenAI in teacher education remains under-theorised: existing research has not systematically examined how these psychological dimensions interact when preservice teachers learn CT through GenAI-mediated tasks. This thematic literature review synthesises 54 sources across three intersecting domains: CT frameworks and their pedagogical implications, CT integration in preservice teacher preparation, and GenAI in teacher education and learning design. Drawing on Bandura’s social cognitive theory, cognitive load theory, and research on technology-related affect, the review foregrounds the affective, cognitive, and cultural dimensions of preservice teachers’ engagement with CT and GenAI. The review proposes the GenAI-Enabled Computational Thinking for Preservice Teachers (GECT-P) model, which integrates CT dimensions with GenAI-supported learning cycles, psychological mediators, and teacher education outcomes. The model positions prompting as an epistemic and pedagogical practice that can make CT visible, supports cycles of decomposition, abstraction, pattern recognition, and algorithmic design, and embeds critical AI literacy, ethics, affective scaffolding, and classroom enactment. Design principles and practical pathways are offered for teacher educators seeking to prepare graduates who can develop CT with and beyond GenAI across diverse curriculum areas. Full article

Owing to topographical constraints, rural domestic sewage management in karst areas faces unique challenges (scattered pollution sources, fragile hydrogeology, and inadequate infrastructure), but research on decentralized treatment technologies and their microbial mechanisms in this area remains scarce. This study aimed to evaluate the efficiency of a physicobiological process (pre-treatment + BAF) for decentralized rural sewage treatment in karst areas and clarify the relationship between microbial community composition and treatment efficiency under different scales. Annual analyses of influent/effluent pollutants and 16S rRNA gene sequencing were conducted for BAF systems of varying scales. The average removal rates of COD, TN, NH₃-N, and TP were 65.35–79.25%, 32.09–66.66%, 49.50–75.42%, and 44.92–67.69%, respectively. Treatment efficiency varied significantly with scale, being higher in larger systems (p < 0.001). All scales shared a core microbial community (dominated by Proteobacteria, Bacteroidetes, and Chlorobi), but the relative abundance of core taxa decreased with decreasing scale. Nitrification and denitrification were positively associated with NH₃-N and TN removal, respectively. Smaller treatment units were more prone to miscellaneous bacteria proliferation, potentially reducing treatment stability. This study fills the research gap of decentralized BAF application in rural karst areas and provides a scientific basis for the scale optimization of rural wastewater treatment facilities. Full article

Seamless Copper Tube Manufacturing (SCTM) is a multi-stage manufacturing chain, typically comprising billet casting, hot extrusion, cold drawing or pilgering, intermediate annealing, and finishing operations. Despite the fact that quality control (QC) practices are implemented at individual stages, many product deviations originated from cumulative thermomechanical and metallurgical interactions across multiple processes. Thus, although the current stage-wise QC schema ensures compliance with quality standards, it’s questionable whether it can identify root causes or implement proactive QC at the production level. This study presents a narrative review of QC approaches in SCTM, examining the production chain across key quality domains, including billet integrity, extrusion tooling condition, dimensional control, surface and internal defect detection, annealing atmosphere monitoring, and inner-surface cleanliness. The industrial practices are critically compared with research approaches in numerical modelling, advanced sensing technologies, and data-driven monitoring methods. Results confirmed that dimensional instability, defect formation, surface contamination, and microstructural variation in the tube are influenced by interactions among factors such as billet quality, thermomechanical conditions during extrusion and drawing, annealing conditions, tooling conditions, lubrication regimes, and handling between processing steps. Their analysis indicated that the main limitation of current QC frameworks is not the lack of monitoring or modelling technologies but the limited integration of process data across the manufacturing chain. Full article

Against the backdrop of a technological revolution centered on green and low-carbon development, the deep integration of digitalization and greening has become a core engine for high-quality progress. Moving beyond linear perspectives of environmental governance, this study constructs tripartite evolutionary game models to dissect the strategic interactions among government, enterprises, and consumers. Focusing on the institutional context of e-commerce, we examine how platform-enabled transparency mechanisms (e.g., blockchain traceability and carbon labeling) shape these interactions through key parameters: greenwashing detection (θ), premium loss coefficient (η), and information screening cost (C_D). The analysis reveals that the long-term trajectory is fundamentally determined by the intrinsic economic viability of corporate transformation. Government intervention acts as an equilibrium selector, influencing the speed of convergence, while product value (consumer utility and premium) and platform transparency determine the sustainability of the equilibrium. Critically, the tripartite model shows that the optimal outcome—full enterprise transformation and consumer adoption—can be achieved without sustained government intervention when product fundamentals are sufficiently attractive. This demonstrates the potential for market self-regulation to sustain digital–green synergy. The study makes three contributions: it captures the full tripartite feedback loop, reveals the saturation effect of policy intensity, and embeds platform transparency mechanisms into an evolutionary framework. The findings reframe the government’s role as a temporary enabler and position e-commerce platforms as key governance intermediaries, offering a theoretical basis for adaptive governance strategies in digital commerce. Full article

Labor shortages and the need for increased productivity have accelerated the development of robotic harvesting systems for greenhouse crops; however, reliable operation under fruit occlusion and clustered arrangements remains a major challenge, particularly due to the limited integration between perception and motion planning modules. The paper presents the design and experimental validation of an autonomous robotic system for greenhouse tomato harvesting. The proposed platform integrates a rail-guided mobile base, a six-degrees-of-freedom robotic manipulator, and an adaptive end effector with a hybrid vision framework that combines convolutional neural networks and watershed-based segmentation to enable robust fruit detection and localization under occluded conditions. The proposed approach enables improved separation of overlapping fruits and provides accurate spatial localization through stereo vision combined with IMU-assisted camera-to-robot coordinate transformation. An occlusion-aware trajectory planning strategy was developed to generate collision-free manipulation paths in the presence of leaves and stems, enhancing harvesting safety and reliability. The system was trained and evaluated using a dataset of real greenhouse images supplemented with synthetic data augmentation. Experimental trials conducted under practical greenhouse conditions demonstrated a fruit detection precision of 96.9%, recall of 93.5%, and mean Intersection-over-Union of 79.2%. The robotic platform achieved an overall harvesting success rate of 78.5%, reaching 85% for unobstructed fruits, with an average cycle time of 15 s per fruit in direct harvesting scenarios. The rail-guided mobility significantly improved positioning stability and repeatability during manipulation compared with fully mobile platforms. The results confirm that integrating hybrid perception with occlusion-aware motion planning can substantially improve the functionality of robotic harvesting systems in protected cultivation environments. The proposed solution contributes to the advancement of automation technologies for greenhouse vegetable production and supports the transition toward more sustainable and labor-efficient agricultural practices. Full article

This study investigated the microbiological composition and antimicrobial resistance (AMR) profiles of artisanal goat and sheep milk cheeses produced in Poland. Ten raw milk cheeses (five each from goat and sheep milk) were analyzed using a combined approach involving culture-dependent enumeration, 16S rRNA gene sequencing, and antibiotic susceptibility testing. Microbial counts revealed substantial variability among the samples, with lactic acid bacteria (LAB) dominating the microbiota. Taxonomic analysis confirmed the predominance of Lactococcus, Streptococcus, and lactobacilli, although marked intra-group heterogeneity was observed. Multivariate analyses indicated that sample-specific factors had a greater influence on microbiome composition than milk origin. Among 170 isolates, 28.7% were classified as multidrug-resistant (MDR), being most prevalent in Enterobacterales (100%) and Enterococcus spp. (73%), whereas LAB exhibited low resistance levels (16.2%). Resistance was most frequently associated with aminoglycosides and β-lactams. The resistance results were interpreted according to CLSI guidelines. These findings demonstrate that artisanal cheeses harbor complex, dynamic microbial ecosystems that may serve as reservoirs of antimicrobial resistance. The results highlight that environmental and technological factors, rather than milk source alone, are key drivers of both microbiome structure and resistance distribution, underscoring the need for targeted AMR monitoring in traditional dairy products. Full article

To address the difficulty of directionally cutting thick, hard key strata in gob-side entry retaining using conventional blasting or hydraulic fracturing, this paper proposes a high-pressure water-jet slotting-induced pre-cracked weakening belt (PCWB) roof-cutting technology. Several finite-length PCWBs are arranged within the key stratum and designed to coalesce into a plane, inducing through-going roof failure along a pre-determined path. A fixed–fixed key strata beam model combined with linear elastic fracture mechanics shows that the double-belt configuration forces the bending moment and shear force to concentrate in a thin rock bridge, where bending and shear stresses are amplified by about 1.5–2.8 times and 1.2–1.7 times, respectively, for 2–4 m thick key strata, providing a mechanical basis for preferential tensile–shear failure. Two-dimensional RFPA2D simulations reveal “width-dominated, length-assisted” control of cutting performance and identify an optimal weakening belt geometry of about 400 mm in width and 200 mm in length. Three-dimensional numerical modeling of parallel slot pairs indicates that intra-pair spacing of about 40 mm produces a continuous, directional weakening belt, whereas smaller or larger spacing causes, respectively, destructive interference or loss of connectivity. High-pressure water-jet tests (320 MPa, 0.33 mm nozzle, 1.30 mm/s traverse speed) on limestone blocks confirm that single slots can penetrate the full thickness and that cracks from adjacent slots coalesce through the rock bridge, forming a wide, straight fracture band. Field application in the Dongjiang Mine (3.5 m limestone key stratum, ~400 m depth) shows that the first weighting is advanced from the 7th to the 3rd day, peak support resistance is reduced from 8.8 to 7.4 MPa, and periodic weighting becomes more frequent and smoother. The PCWB technology is therefore suitable for panels with 2–4 m thick hard key strata at similar depths, offering precise key stratum severance, active stress relief, and safe, controllable construction. Full article

Children with Autism Spectrum Disorder (ASD) frequently exhibit marked impairments in nonverbal communication, particularly in eye contact, which serves as a foundational element for social interaction and relational development. This study evaluated the effectiveness of an early intervention program utilizing interactive games supported by Augmented Reality (AR) technology to enhance eye contact behaviors, specifically initiation and maintenance, in children with autism. Using a multiple baseline across participants single-case experimental design, four boys (aged 5–7 years) diagnosed with ASD participated in an 8-week intervention at a specialized center in Saudi Arabia. The intervention featured tablet-based, gamified AR tasks incorporating real-time visual feedback, graduated difficulty levels, and reinforcement mechanisms designed to elicit social gaze and sustained eye contact. Eye contact duration and frequency were measured during structured social interactions via systematic direct observation. The results demonstrated significant improvements across all participants, with the mean duration of eye contact increasing from a baseline of 2.0 s to 5.8 s post-intervention. Visual analysis revealed robust treatment effects, further supported by substantial Tau-U effect sizes (range = 0.89–0.96; M = 0.93). Follow-up data collected three weeks post-intervention confirmed the maintenance of gains for three of the four participants. These findings suggest that AR-based interventions provide an effective and culturally responsive approach for enhancing specific nonverbal communication behaviors among children with autism in Middle Eastern contexts. Implications for clinical practice and directions for future research are discussed. Full article

The growing interest in the role of the gut microbiome in athletic performance has led to the application of various sequencing technologies in this field. This review critically examines the sequencing methodologies used in microbiome studies on physical performance and sport, comparing their advantages, limitations, and applicability. In particular, the focus is on 16S metabarcoding and shotgun metagenomics, evaluating how these methodological approaches influence the interpretation of results in sports contexts. Close attention is directed toward technical challenges, methodological biases, and future perspectives, including emerging technologies and multi-omics approaches. This review aims to bridge the gap between methodological rigor and sports-specific applicability, providing evidence-based methodological guidance to support researchers in designing robust athlete microbiome studies and translating sequencing-derived findings into concrete applications for performance and sports health. Full article

Given that approximately 70% of traffic accidents are attributable to driver-related factors, it is necessary for vehicles to incorporate technologies that reduce risk through preventive actions derived from traffic-scene analysis. Interpreting the driving environment is non-trivial and is commonly decomposed into sub-tasks; among them, traffic light perception is critical due to its role in regulating vehicular flow. This paper evaluates five YOLO CNN families (YOLOv8–YOLOv12) on two tasks: (i) traffic light detection and (ii) traffic light state recognition (green, yellow, red). The evaluation uses a hybrid dataset comprising the public LISA traffic light dataset and a custom dataset with images from Mexico City captured under diverse lighting conditions—a relevant setting given the city’s high traffic intensity. The results show mAP@0.50 = 94.4–96.3% for traffic light detection and mAP@0.50 = 99.3–99.4% for traffic light state recognition, indicating that modern YOLO variants provide highly reliable performance for both tasks under natural illumination variability. Full article

High-fidelity haptic interfaces are widely assumed to enhance virtual reality (VR) training; however, they can trigger a “fidelity paradox” where hardware complexity paradoxically degrades usability. Grounded in Task-Technology Fit (TTF) theory and Hassenzahl’s pragmatic-hedonic quality framework, this study investigates the mechanisms underlying this paradox through a within-subject experiment ($N=70$) in a VR cooking simulation comparing three interface paradigms: VR controllers (VRC), hand tracking (HT), and haptic gloves (HG). Results confirmed that HG’s low task-technology fit—manifested as tracking errors, physical resistance, and increased operational overhead—generated significantly higher extraneous cognitive load (H1) and degraded interaction satisfaction (H2) despite its superior intended sensory resolution. Critically, in the HG condition, pragmatic quality (technical reliability) was identified as the dominant driver of satisfaction, while hedonic quality additions (thermal feedback) did not show a significant independent contribution to satisfaction in the HG condition. Perceived training effectiveness remained above the neutral threshold across all conditions (H3), indicating that content-level TTF is preserved independently of interface-level TTF mismatch. These findings suggest that VR interface design should prioritize “functional sufficiency”—ensuring tools serve as transparent, seamless extensions of the user—over the blind pursuit of sensory maximization. Full article

Polyolefin bonding technologies with metal foils are extensively employed in various sectors, particularly in automotive, electronics, and aerospace industries. This research examined the innovative electromagnetic joining of polyolefins to aluminum by evaluating the behavior of hot-melt adhesives derived from polyolefins containing metallic particles. The study aimed at establishing the specific absorption rate (SAR, expressed in W/kg) via electromagnetic simulation using CST Studio Suite software. It was observed that, regardless of particle size, Al was the most efficient particle, while the distribution of particles has a negligible impact on Total SAR values. The most significant beneficial effect of the inserts on the absorption capacity of the hot-melt material is primarily observed with a particle size of 1 μm. When connecting polyolefins to aluminum, the power loss density and SAR values exceed those for bonding polyolefins to polyolefins by at least 10 times, owing to aluminum’s conductive properties, which influence the absorption of additional energy in the hot melt mass, likely due to the Salisbury screen effect generated by the bonding arrangement. For hot melts made from polyethylene, a higher frequency of 5.8 GHz is suggested, which is a newly approved frequency used in advanced industrial applications. This positively impacts the effectiveness and viability of the bonding process of polyolefins to aluminum, resulting in reduced exposure times and/or decreased microwave exposure power. It was observed that the hot melts derived from HDPE and PP yielded greater SAR values. Conversely, the SAR values increase when aluminum is attached to HDPE. As a result, the strongest bond of polyolefins to Al occurs when connecting HDPE to Al using HDPE-based hot melts. The proposed simulation methodology may offer considerable improvement in evaluating the efficacy of bonding technology for dissimilar materials subjected to electromagnetic energy Full article

Currently, the resource wastage and safety hazards caused by fruit and vegetable spoilage are becoming increasingly prominent. Developing green, efficient, and non-toxic novel preservation materials has emerged as a hot spot in fruit and vegetable research. Based on this, this study utilized pomegranate peel as a raw material to prepare spherical multifunctional carbon dots (P-CDs) with an average particle size of 1.98 ± 0.58 nm through a one-step hydrothermal reaction. Subsequently, P-CDs were co-incorporated with L-cysteine (L-Cys) into a polyvinyl alcohol (PVA) and chitosan (CS) matrix to construct a novel composite coating material with combined antibacterial, antioxidant, and preservation functions. Experimental results demonstrate that P-CDs exhibit outstanding antioxidant activity and antibacterial performance. Compared to PVA/CS film, the P-CDs/L-Cys/PVA/CS film exhibited a 6.55 MPa increase in tensile strength and significantly enhanced thermal stability. Furthermore, the incorporation of P-CDs and L-Cys markedly boosted the PVA/CS film’s antioxidant activity (97% for ABTS; 85.69% for DPPH), antibacterial performance, and ultraviolet (UV) shielding capability. Coating cherry tomatoes with the P-CDs/L-cysteine/PVA/CS composite extended their shelf life by 6 days. This composite coating material exhibits preliminary biocompatibility and eco-friendly properties, aligning with green sustainable development needs and offering a novel potential solution for food preservation technology, while its practical applicability to food safety requires further comprehensive verification. Full article