Search Results (6,777)

Maintaining consistent part quality remains a critical challenge in industrial additive manufacturing, particularly in laser-based powder bed fusion of polymers (PBF-LB/P), where crystallization-driven thermal instabilities, governed by isothermal crystallization within a narrow sintering window, precipitate defects such as curling, warping, and delamination. In contrast to metal-based systems dominated by melt-pool hydrodynamics, polymer PBF-LB/P requires monitoring strategies capable of resolving subtle spatio-temporal thermal deviations under realistic industrial operating conditions. Although machine learning, particularly convolutional neural networks (CNNs), has demonstrated efficacy in defect detection, a structured evaluation of heterogeneous modeling paradigms and their deployment feasibility in polymer PBF-LB/P remains limited. This study presents a systematic cross-paradigm assessment of unsupervised anomaly detection (autoencoders and generative adversarial networks), supervised CNN classifiers (VGG-16, ResNet50, and Xception), hybrid CNN-LSTM architectures, and physics-informed neural networks (PINNs) using 76,450 synchronized thermal and RGB images acquired from a commercial industrial system operating under closed control constraints. CNN-based models enable frame- and sequence-level defect classification, whereas the PINN component complements detection by providing physically consistent thermal-field regression. The results reveal quantifiable trade-offs between detection performance, temporal robustness, physical consistency, and algorithmic complexity. Pre-trained CNNs achieve up to 99.09% frame-level accuracy but impose a substantial computational burden for edge deployment. The PINN model attains an RMSE of approximately 27 K under quasi-isothermal process conditions, supporting trend-level thermal monitoring. A lightweight hybrid CNN achieves 99.7% validation accuracy with 1860 parameters and a CPU-benchmarked forward-pass inference time of 1.6 ms (excluding sensor acquisition latency). Collectively, this study establishes a rigorously benchmarked, scalable, and resource-efficient deep-learning framework tailored to crystallization-dominated polymer PBF-LB/P, providing a technically grounded basis for real-time industrial quality monitoring. Full article

Linear integrators are traditionally used in motion control systems to compensate for static effects and suppress low-frequency disturbances. However, their use is inevitably accompanied by phase delays that limit the performance and robustness of control systems, especially in conditions of parametric uncertainty. In this regard, nonlinear integrators have been considered for several decades as a promising alternative that can weaken phase constraints and improve the quality of transients. In this paper, the concept of nonlinear integrators is reinterpreted in the context of self-organizing motion control of precision stages. In contrast to traditional approaches focused primarily on frequency analysis and the method of describing the function, a method is proposed for the synthesis of a self-organizing control system for nonlinear SISO objects based on catastrophe theory, namely in the class of elliptical dynamics with the property of structural stability. The control action is formed in such a way that transitions between stable modes occur due to bifurcation-conditioned self-organization, without using external switching logic. To ensure strict analytical guarantees of stability, the Lyapunov gradient-velocity vector function method is used, which guarantees aperiodic robust stability, suppression of oscillatory and chaotic modes, as well as monotonic convergence of trajectories under conditions of parameter uncertainty. The parameters of the nonlinear integrator are adapted using Self-Organizing Maps (SOM), while any parameter changes are allowed only within the regions that meet the conditions of Lyapunov stability. This approach ensures the alignment of analytical and data-oriented methods without violating the structural stability of the system. The results of numerical experiments demonstrate the superiority of the proposed method in comparison with classical linear and adaptive regulators in problems of controlling the movement of stages, especially near bifurcation boundaries and with significant parametric uncertainty. The results obtained confirm that the integration of nonlinear integrators with catastrophe theory and self-organization mechanisms forms a promising basis for the creation of robust and high-precision motion control systems of a new generation. Full article

Welding copper (Cu) and aluminum (Al) is highly demanded for lightweight and cost-effective manufacturing. However, it faces significant challenges. First, substantial differences in physical properties may lead to high residual stresses and distortion. Second, brittle intermetallic compounds (IMCs) readily form at the interface, severely compromising the joint’s mechanical properties and electrical conductivity. Third, the native oxide film on Al impedes effective wetting and bonding. Therefore, effective control over the interfacial microstructure of the welded joint is essential. This review provides a critical analysis and comparison of several typical welding techniques, including laser welding (LW), friction stir welding (FSW), ultrasonic welding (UW), brazing and soldering, and welding–brazing. These analyses focus on their process characteristics, joint microstructures, and corresponding formation mechanisms. Furthermore, this review synthesizes key strategies for enhancing joint quality, including process parameter optimization, introduction of functional interlayers, and external assistance, aimed at optimizing joint microstructure and minimizing defects. Based on the analysis, this work provides comparative insights into process selection and microstructure control, and highlights future directions: advancing novel methods such as magnetic pulse welding and transient liquid phase bonding; developing intelligent real-time process control to suppress brittle IMCs and associated defects; promoting sustainable practices and establishing standardized performance evaluation; and systematically investigating long-term reliability to support the industrial application of robust Cu/Al joints. Full article

With the increasing popularity of photovoltaic (PV) equipment in residential and commercial buildings, there is a pressing need for systems that maximize energy efficiency and self-consumption. This paper introduces an integrated management framework for retrofitting existing infrastructures, enabling high photovoltaic (PV) self-consumption in residential buildings through a rule-based control strategy. The framework supports three service classes—defined by user-level Quality of Service (QoS) parameters—and monitors battery voltage along with grid power exchange to coordinate heat pumps, batteries, and hot water cylinders. Experimental deployment in a residential testbed achieved up to 89% PV self-consumption while keeping daily grid usage below 0.5 kWh. Ablation experiments on battery size further demonstrated the approach’s robustness to reduced storage capacities. The use of Commercial-Off-The-Shelf (COTS) components underscores the minimal intrusiveness of this solution, highlighting its potential for seamlessly integrating diverse, vendor-specific equipment into a coordinated control system. Full article

The optimization of agrochemical spraying can be approached by increasing the efficiency of product distribution, which improves application quality and the biological effectiveness of the treatment. This study presents the development and evaluation of four distinct control strategies to adjust the hydraulic system of a new small, low-cost, electric, vertical variable-rate sprayer based on variations in travel speed, aiming to maintain a constant spray volume during operation and, thereby, increase distribution efficiency. The evaluated algorithms were developed from a mathematical model of the prototype’s hydraulic system obtained from experimental data and using the system identification tool in MATLAB software version 2021. Two open-loop algorithms (linear regression and Fuzzy) and two closed-loop algorithms (Integral and Fuzzy-PD with output integration) were developed. The evaluation was conducted through simulations, using a normalized speed data series provided by the United States Environmental Protection Agency. Performance evaluation results determined that the Fuzzy-PD algorithm with output integration showed the best performance (ISE = 0.21 × 10⁻⁵), followed by the linear regression algorithm (ISE = 3.38 × 10⁻⁵). The results demonstrated that, compared to applications based on fixed rates defined by nominal parameters, the developed sprayer showed potential to improve the uniformity of spray distribution in the field. Full article

Postharvest fruit losses significantly impact producers and distributors. Although synthetic preservatives mitigate these losses, consumer safety concerns and regulatory restrictions drive interest in alternative approaches. Propolis, rich in polyphenols, exhibits antioxidant and antimicrobial activities, making it a promising natural strategy to preserve fruit quality. This study aimed to evaluate the effects of the pre- and postharvest applications of Portuguese propolis extracts on the preservation of postharvest quality of ‘Rocha’ pear, an exclusively Portuguese variety of major economic importance. Treatments were applied by spraying the fruits one month before and at harvest. After five months of cold storage, the main quality parameters, phenolic content, antioxidant capacity, physiological disorders, and microbial contamination were assessed. The results showed that the application of propolis extract, either 30 days before or immediately after harvest, reduces the total microbiological load on the fruit’s epidermis (~1-log to 2-log reduction, after treatment). Moreover, the treatment enhanced the preservation of key quality attributes, including a reduction in water loss of up to 44%, a 13–33% decrease in firmness loss relative to the control, and a lower incidence of physiological disorders during postharvest storage. Furthermore, the application of propolis can enhance the production of fruits with higher levels of bioactive compounds, while also adding value to a bee product that is often underappreciated by most beekeepers. Full article

The current investigation examined the effect of inclusion of Black soldier fly (Hermetia illucens; BSF) dry larvae in hens’ diet on egg quality and hen performance. A total of 260 brown egg-laying hens (RIR × RIW) were divided into four groups (65 hens/group; 5 pens/group) and fed with control and experimental diets (inclusion rates 3%, 6%, 9%). Although the four-week feeding period did not influence production parameters, yolk color responded positively to the test diets, showing a linear increase with the percentage of BSF inclusion rate (p < 0.001). This was reaffirmed by the increased levels of yolk carotenoids (astaxanthin and β-carotene) and α-tocopherol, with notable differences in 6% and 9% BSF-fed groups (p ≤ 0.003). Lipids are an important factor in carotenoid absorption and assimilation, and the combination of fat content and carotenoids in BSF suggests the potential of this system for egg enrichment. Along with the increased antioxidant levels, a novel finding is the positive correlation between BSF inclusion rates and hens’ egg yolk levels of C:15 and C:17 fatty acids, key players in the core mechanisms of cell health and longevity. Altogether, the results provide evidence of the potential of BSF for enrichment of eggs with carotenoids and vitamins with strong antioxidant activity, which would have a positive effect on human health. Full article

Background/Objectives: Stroke frequently leads to balance deficits. Vestibular physical therapy (VPT) may enhance postural control through neuroplastic mechanisms. Virtual reality (VR) can provide ecologically valid environments for rehabilitation, increasing patient engagement. Methods: In this randomized feasibility study, nine individuals with chronic stroke were randomized to either a Real visuo–vestibular rehabilitation group (n = 6) or a Sham VR group (n = 3) to explore the feasibility of the protocol and randomization procedures rather than to compare clinical efficacy. Both groups were trained in immersive VR environments for 12 sessions. The Real group experienced visuo–vestibular stimuli requiring sensorimotor integration; the Sham group trained in the same environments without such stimuli. Feasibility was assessed through attendance, participation (Pittsburgh Rehabilitation Participation Scale, PRPS), and user satisfaction (USEQ). Safety and acceptability were monitored through adverse event reporting. Secondary exploratory outcomes included measures of balance—the Mini Balance Evaluation Systems Test (MiniBESTest), the Berg Balance Scale (BBS), and the Performance-Oriented Mobility Assessment (POMA)—as well as functional independence (Barthel Index), health-related quality of life (Stroke-Specific Quality of Life Scale, SSQoL), and a set of spatiotemporal and gait quality parameters derived from inertial measurement unit (IMU) data collected during the 10-Meter Walk Test and the Figure of 8 Walk Test. Results: All participants completed the protocol without adverse events. Participation, as measured by the PRPS, remained consistently high across sessions (mean ≥5.7/6), while USEQ scores indicated excellent user satisfaction (mean ≥28/30). Exploratory analyses revealed improvements in MiniBESTest and BBS scores for the Real group. Instrumental measures derived from IMUs demonstrated improvements across groups. Conclusions: Exploratory outcomes suggested positive trends in balance improvements, and the integration of clinical scales with wearable sensors proved feasible and informative. Full article

The one-dimensional Bin Packing Problem (1D-BPP) is a well-known NP-hard grouping problem characterized by high structural complexity and broad practical relevance. Among the metaheuristic approaches proposed for this problem, the Grouping Genetic Algorithm with Controlled Gene Transmission (GGA-CGT) has shown remarkable performance. In this work, an Adaptive Grouping Genetic Algorithm with Controlled Gene Transmission based on Fullness and Item Strategies (AGGA-CGT-FIS) is presented. This approach extends the original GGA-CGT by integrating domain-guided crossover mechanisms and adaptive parameter control schemes. The proposed algorithm incorporates a novel gene-level crossover operator, termed Fullness–Items Gene-Level Crossover 1 (FI-GLX-1). This operator exploits structural information from the solutions through Fullness- and Item-based ordering and transmission strategies. In addition, adaptive control schemes are introduced for key evolutionary parameters associated with crossover and mutation. These mechanisms allow the algorithm to dynamically adjust its behavior according to feedback extracted from the search process, resulting in a fully adaptive variant of the GGA-CGT. The effectiveness of AGGA-CGT-FIS is evaluated using two benchmark sets for the 1D-BPP: the classic and the BPP$v_u\_c$ instances. The proposed approach is compared against the baseline GGA-CGT using the original Gene-Level Crossover (GLX) operator. Experimental results show improvements in solution quality and convergence behavior, supported by statistical analyses that confirm the significance of the observed performance differences. Full article

To evaluate the runoff pollution characteristics of roofs in an arid region, this study focused on Yinchuan City, China. It analyzed the runoff properties of various roof materials, including tile, asphalt, and color steel plate. Five rainfall events were monitored during 2024, with samples collected manually at roof pipe outlets and analyzed for suspended solids (SS), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (NH₃-N). The results indicated that the concentration of pollutants in runoff from these roofs decreased as rainfall duration increased. The event mean concentration (EMC) of TN and COD in runoff from all three roof materials exceeded the Class V surface water quality standards in China. The first flush of pollutants in roof runoff followed a descending order: SS > COD > TP > TN > NH₃-N. Cluster analysis of three rainfall parameters—dry period, precipitation, and rainfall intensity—revealed that dry period exerted the strongest influence on runoff quality, indicating that the overall quality of roof runoff was primarily influenced by the cumulative effects of atmospheric deposition, with rainwater scouring being the secondary factor. These findings provide critical insights for designing stormwater management strategies and rainwater harvesting systems in arid and semi-arid cities, emphasizing the need to prioritize first-flush control and consider local climatic conditions. Full article

Nickel-titanium (NiTi) alloys are attractive for functional and biomedical applications due to their shape memory effect, superelasticity, and favorable corrosion resistance and biocompatibility. In this work, the influence of strut size on the compressive response of laser-based powder bed fusion (PBF-LB/M) fabricated NiTi ortho-octahedral porous scaffolds was systematically investigated using combined experiments and finite element simulations. Four scaffold designs with identical unit-cell size (2 mm) but different strut sizes (280, 320, 360, and 400 μm) were fabricated, and their forming quality and deformation behaviors were examined. The as-built scaffolds exhibited high geometric fidelity to the CAD models and stable manufacturability across the investigated parameter range. Quasi-static compression tests revealed a typical three-stage response (linear-elastic regime, plateau/collapse regime, and densification), with both elastic modulus and compressive strength increasing markedly with strut size. Specifically, the modulus increased from 1.17 to 4.28 GPa and the compressive strength increased from 155 to 564 MPa as the strut size increased from 280 to 400 μm. A pronounced oscillatory plateau was observed for the 280 μm scaffolds, indicating progressive layer-by-layer collapse, whereas larger struts promoted a shear-band-dominated failure mode characterized by an approximately 45° fracture zone. Explicit quasi-static simulations reproduced the experimentally observed collapse sequence and demonstrated that stress preferentially concentrates at nodal junctions, with load transfer dominated by struts aligned with the loading direction. The agreement between experiments and simulations confirms the predictive capability of the proposed modeling framework and provides mechanistic insights into geometry-controlled failure. These findings establish a structure-property-failure relationship for PBF-LB/M-fabricated NiTi octahedral scaffolds and offer practical guidance for tailoring stiffness, strength, and collapse mode through strut-size design. Full article

The control of cladding layer morphology is crucial in laser cladding technology. However, traditional process parameter-based regulation suffers from parameter coupling issues, and previous nanosecond laser pretreatment is prone to causing uneven substrate morphology due to significant thermal effects. This study proposes a novel substrate pretreatment method using femtosecond laser etching, employing 45 steel as the substrate and Ni45 powder as the cladding material to investigate its regulatory effect on cladding layer morphology. The results show that femtosecond laser etching enables a good linear correlation between substrate roughness and laser power, forming uniform grid-like microgrooves without the spherical remelted structures observed in nanosecond laser treatment, thus achieving superior regulatory stability. With the increase in substrate roughness, the contact angle and dilution rate of the cladding layer decrease, while the cladding height and width increase, with the optimal cladding quality obtained in the roughness range of 4~7 μm. This study reveals the intrinsic mechanism by which femtosecond laser regulates molten pool behavior through mechanical anchoring and groove guiding effects, providing a more stable technical pathway for the preparation of high-quality cladding coatings. Full article

The global polymer waste burden has catalyzed a shift from linear “production–use–disposal” systems to circular models that prioritize recycling, reuse, and value retention. This article proposes an integrated, technology-ready roadmap for mechanical recycling and reuse of commodity and bio-based polymers via filament re-extrusion and Additive Manufacturing (AM). Building upon recent findings on performance envelopes of virgin vs. recycled Polylactic Acid (PLA) filaments processed by Fused Deposition Modeling (FDM), process parameter sensitivities (layer height, infill density) and their statistical optimization, and functional reinforcement routes (aluminum: Al, alumina: Al₂O₃, titanium: Ti, and Nano Boron Nitride: nano-BN), we articulate (1) a process–structure–property (PSP) mapping; (2) a low-defect, low-energy filament re-extrusion protocol; and (3) a graded-value strategy for upcycling mixed polymer streams. Across case analyses, we show that recycled PLA can achieve near-parity with virgin PLA when extrusion quality and printing parameters are controlled, and that ceramic/metal nanofillers enable thermal management and biocompatibility benefits crucial for durable reuse scenarios. Full article

The delicate fruits of highbush blueberry are exposed to factors causing mechanical damage and yield losses during cultivation, harvesting, and postharvest handling. Foliar stimulation with silicon-based formulations may improve fruit firmness and postharvest quality, thereby increasing the market value of the produce. This study evaluated the effect of foliar silicon fertilisation on highbush blueberry fruit quality in terms of changes in mechanical properties, taking into account the applied spraying technique. The experiments were conducted using standard flat-fan and air-induction nozzles at different spraying speeds and varying spray liquid pressures. Treatment quality was assessed based on the degree of spray deposition, determined through analysis of silicon content in leaves and fruits. Instrumental compression and fruit detachment tests were performed to determine safe ranges of pressures and forces from the perspective of harvest quality. The results showed that the loads exerted by the picker’s hand during manual harvesting of the cultivar ‘Patriot’ remain within safe limits but are close to the critical threshold of fruit mechanical resistance (2 N). The greatest increases in destructive force and fruit firmness were obtained with the use of standard XR nozzles, reaching 3.19–3.34 N (up to 19%) and 2.03–2.21 N (up to 10%), respectively, compared with the control treatment. These findings provide practical guidance for optimising foliar silicon applications and spray parameters in highbush blueberry cultivation to improve fruit mechanical resistance and reduce the risk of harvest and postharvest damage. Full article

A thunderstorm is a weather system that can trigger severe natural disasters, characterized by sudden onset, short duration, and significant damage. Accurate forecasting of thunderstorms has long been a challenging task. Data-driven artificial intelligence (AI) technologies have provided new solutions, yet AI-driven thunderstorm forecasting still lacks high-quality thunderstorm training datasets. Leveraging lightning data from the China Meteorological Administration’s Advanced Direction and Time-of-Arrival Detecting (ADTD) network and the three-dimensional Very Low Frequency/Low Frequency (VLF/LF) lightning location data of the Institute of Electrical Engineering, Chinese Academy of Sciences, we have constructed an AI training dataset for thunderstorms over China (AITDTS) through four sequential procedures: rigorous data quality control, multi-source integration, thunderstorm-prone area labeling, and feature extraction. The AITDTS encompasses 85,071 thunderstorm events and 3,973,171 corresponding gridded samples at 10 min temporal resolution and 1 km × 1 km spatial resolution across China during 2016–2023. Each sample includes location labels, 38 radar-derived physical parameters with a 10-min temporal resolution and 62 environmental parameters with an hourly temporal resolution. We further quantified predictor information gain for thunderstorm forecasting: radar echo top/base heights, composite reflectivity, vertical integrated liquid water content and reflectivity at 10 km showed high information gain. Atmospheric instability, dynamic uplifting, moisture conditions and vertical wind shear at 1 km exhibited moderate information gain. The AITDTS can be directly applied to training and evaluation of AI-driven forecasting models, offering critical data for thunderstorm nowcasting. Full article