Search Results (29,561)

The exponential growth of genomic and proteomic data has made computational protein–protein interaction (PPI) prediction indispensable, driving the need for a comprehensive and method-aware evaluation of supervised learning approaches. PPIs are fundamental to understanding cellular processes and disease mechanisms, yet experimental identification remains slow, costly, and difficult to scale. This survey systematically investigates ten supervised learning models—Extreme Learning Machine (ELM), Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), Deep Neural Networks (DNNs), Naïve Bayes, Probabilistic Decision Tree, Support Vector Machine (SVM), Least Squares SVM (LS-SVM), K-Nearest Neighbor (KNN), and Weighted K-Nearest Neighbor (WKNN)—through a tri-layered framework that integrates Comparative Quantitative Analysis, Comparative Observational Analysis, and Experimental Evaluations. Beyond conventional accuracy summaries, this work provides critical commentary tied to real-world use, analyzing where techniques succeed or fail in practice—for instance, when instance-based methods bottleneck during inference, when kernel choices influence SVM variance, or when deep architectures trade accuracy for computational cost. The survey also offers concrete deployment guidance, such as calibration insights for WKNN versus KNN under varying feature noise or dataset curation quality, delivering operational perspectives that typical surveys omit. Comparative Quantitative Analysis consolidates metrics such as accuracy, F1-score, and computational time from the existing literature, while Comparative Observational Analysis evaluates interpretability, scalability, dataset suitability, and efficiency. Complementing these, Experimental Evaluations conducted by the authors empirically validate model performance on benchmark datasets. Together, these layers provide a unified and evidence-backed perspective on algorithmic strengths, weaknesses, and practical applicability. Findings show that GNNs and DNNs achieve the highest predictive accuracy due to their ability to capture structural and topological relationships, whereas ELM and Naïve Bayes offer superior efficiency. SVM and LS-SVM maintain robust stability under noisy conditions, and CNNs are well-suited for sequence-based prediction tasks. By combining empirical validation, critical insights, and deployment-focused recommendations, this survey delivers decision-grade guidance that bridges theoretical understanding with real-world implementation, thus clarifying the trade-offs among accuracy, efficiency, and scalability in PPI detection research. Full article

This research investigates the formation of an amorphous phase in a non-equiatomic aluminum-based alloy, Al₈₂Fe₁₂Cu₂Nb₂Co₂, synthesized via mechanical alloying. By utilizing minor additions of Nb, Co, and Cu, structural stability and “chemical complexity” effects are achieved in a matrix dominated by a single element (82% Al). Thermodynamic analysis reveals that a moderately negative mixing enthalpy (ΔHₘᵢₓ = −6.89 kJ/mol) and elevated configurational entropy (ΔSₘᵢₓ = 5.420 J/mol·K) are the primary thermodynamic drivers of amorphization, supplemented by a transitional-regime atomic size mismatch (δ = 4.82%). The evolution of the structure, morphology, and magnetic properties of mechanically alloyed amorphous Al₈₂Fe₁₂Cu₂Nb₂Co₂ as a function of milling time was systematically investigated using X-ray diffraction, scanning electron microscopy, Fourier-transform infrared spectroscopy, and a vibrating sample magnetometer. Full article

Varistors are critical overvoltage protection components in modern power electronic systems. They effectively absorb and dissipate surge energy to ensure the safe and stable operation of electrical equipment. However, surface defects can lead to substandard performance or even trigger equipment failure, compromising overall system stability. Therefore, high-precision surface defect detection is essential for quality assurance. To address these challenges, we propose a lightweight model termed Defect-Aware and Edge-Reconstruction Enhanced YOLO (DAER-YOLO) for efficient varistor inspection. First, we construct a C3k2-based defect-aware enhancement module (C3k2-iEMA). This module tackles the difficulty of extracting features from small or morphologically complex defects. By integrating multi-scale feature extraction, an attention mechanism, and efficient nonlinear mapping, it strengthens the perception of defect details. Second, to enhance the reconstruction capability for edge damage and small-object defects, we introduce the Efficient Up-Convolution Block (EUCB). This block improves multi-level feature fusion and generates clearer enhanced feature maps. Based on these improvements, DAER-YOLO outperforms the YOLOv11n baseline on a custom varistor dataset, with mAP@50 and mAP@50:95 increasing by 1.6% and 2.3%, respectively. Experimental results demonstrate that the model effectively improves detection accuracy while exhibiting significant potential for real-time industrial applications. Full article

Gravelly soil is widely used in western China but suffers from poor gradation, low water stability, and weak freeze–thaw resistance. Traditional cementitious stabilizers involve high energy and carbon emissions. To address these issues, a novel, eco-friendly gravelly soil stabilizer was prepared from waste foamed concrete (WFC) via crushing, ball milling, and high-temperature calcination. This study systematically evaluated stabilization performance and mechanisms. Results indicate that the WFC stabilizer significantly enhances soil properties. At the optimal 30% dosage, the 28-day unconfined compressive strength (UCS) reached 6.5 MPa (a 333% increase), and water stability was significantly improved. Under freeze–thaw conditions, the 30% dosage yielded a mere 2% mass loss after five cycles, with the UCS reaching 9.56 MPa (a 437% increase). Microstructural analyses (XRD, SEM) revealed that hydration generates calcium silicate hydrate (C-S-H) gel and katoite (Ca₃Al₂(SiO₄)_3−x(OH)_4x). These products effectively fill soil pores and the spaces of the particles, optimizing the microstructure. This study provides a sustainable pathway for WFC recycling and offers a relatively lower energy consumption, low-carbon and high-performance stabilizer for reinforcing gravelly soil subgrades in cold regions. Full article

Multi-unmanned aerial vehicle (UAV) platforms integrate radio-frequency (RF) sensing, datalinks, and onboard embedded compute; adversarial electronic warfare (EW) degrades these subsystems through jamming and forces decentralized control policies to act on fragmented observations—a setting aligned with intelligent electronic systems and autonomous robotics in contested spectrum. Cooperative swarms then face two compounding failure modes: loss of coherent situational awareness, and reward-driven passive survival that suppresses mission completion. Memory-based multi-agent reinforcement learning (MARL) partially addresses the first but tends to reinforce the second; dense intent shaping addresses the second but becomes unreliable when observations are incomplete. We propose CIDA (Cognitive–Intent Dual-Stream Architecture), a reinforcement learning framework that decouples belief reconstruction from tactical intent at the representation level while coupling them through a unified actor–critic update. The cognitive stream encodes a 64-step observation history with a pre-normalized Transformer to reconstruct threat belief; the intent stream supplies a hierarchical potential field (reconnaissance, threat-weighted engagement, and approach incentives). A steady-state training mechanism (dynamic reward scaling and adaptive gradient clipping) stabilizes Transformer-based on-policy learning under non-stationary multi-agent dynamics. In a complex terrain scenario with SAM, AAA, and jammer assets, CIDA reaches 96.15% task success versus 12.21% (memoryless PPO) and 25.28% (MAPPO+RNN), with ablations showing nonlinear coupling and emergent tactics such as jammer bypass and weak-sector traversal. Results are robust to a four-fold sweep of the intent-shaping weight (above 90% success). Full article

Microleakage at the implant–abutment interface represents a potential pathway for bacterial penetration and may contribute to peri-implant inflammation, marginal bone loss, and mechanical complications such as screw loosening. The increasing clinical use of compatible prosthetic abutments as cost-effective alternatives to original components has raised concerns regarding their fit, sealing capacity, and mechanical stability at this interface. The aim of this in vitro study was to evaluate differences in sealing capacity and torque loss between original and non-original abutments in a mixed internal connection implant system and to investigate the applicability of a novel quantitative approach for assessing microleakage based on a hydraulic conductance perfusion system. Nine abutments, including four multi-unit and five screw-retained cementable abutments, were connected to Straumann Bone Level implants at two tightening torques (5 N·cm and 35 N·cm). Microleakage was quantified by measuring fluid transport across the implant–abutment interface using the perfusion system, and removal torque values were recorded after testing. Non-original abutments exhibited significantly greater microleakage than original abutments at both torque levels. Microleakage increased significantly when the installation torque was reduced to 5 N·cm. At the manufacturer-recommended torque, screw-retained cementable abutments demonstrated higher microleakage than multi-unit abutments. Non-original abutments also showed significantly greater torque loss. These findings suggest that original abutments provide improved sealing capacity and mechanical stability at the implant–abutment interface, while the hydraulic conductance perfusion system represents a promising quantitative tool for investigating microleakage. Full article

PLLA-b-PEG-b-PLLA triblock copolymers are promising materials because of their highly tunable properties. However, a systematic understanding of composition–property relationships remains limited. In this study, a series of A-B-A triblock copolymers was synthesized with polyethylene glycol (PEG) as soft center (B) domains and poly(L-lactic acid) (PLLA) as hard end (A) domains via ring-opening polymerization. Copolymer composition and molecular weights were characterized by proton nuclear magnetic resonance spectroscopy (¹H NMR) and gel permeation chromatography (GPC). The thermal and mechanical properties of the copolymers were evaluated by differential scanning calorimetry (DSC) and tensile testing. We established quantitative structure–property relationships using empirical data, demonstrating that PLLA block length played a key role in modulating tensile properties, with a near-linear relationship, while PEG molecular weight critically influenced mechanical stability. An approximate minimum PLLA block length of 20 repeat units was found as a threshold required to maintain structural integrity during in vitro 24 h swelling. These findings provide insights and practical guidance for the design of triblock copolymers with tunable thermal, mechanical, and swelling properties of PLLA-b-PEG-b-PLLA triblock copolymers. Full article

This study presents the results of evaluating composites based on modified thermoplastic starch (TPS) with BWW40 and FD600/30 cellulose fibers at varying mass contents. The aim of this study was to assess the effect of filler type and quantity on mechanical properties and water absorption. Test samples were prepared using the injection molding method. It was shown that increasing fiber content led to a reduction in strength of approximately 36% for BWW40 fibers and approximately 37% for FD600/30 fibers at maximum fill. Similar results were observed for elongation at break. Young’s modulus increased by approximately 15% for BWW40 fibers and approximately 13% for FD600/30 fibers. Water absorption also increased with increasing fiber content, which is due to the hydrophilic nature of both the starch matrix and the reinforcing phase. The main conclusion drawn from the conducted research is that by properly selecting the type and content of fibers, it is possible to consciously shape the stiffness and dimensional stability of such composites while maintaining their biodegradability. The results obtained allow for a better assessment of the application potential of these materials in the context of developing sustainable material solutions. Full article

Soft spread cheese is highly perishable, and conventional packaging offers limited protection against surface spoilage. Here, we present a sustainable, multifunctional solution: edible films made from whey protein concentrate (WPC), a valuable by-product of the cheese industry, incorporated with the probiotic Lactobacillus acidophilus LA5 (LA5). The objective of this study was to evaluate these films as active coatings for soft cheese, specifically assessing their physicochemical properties, probiotic viability during storage and simulated gastric transit, and their impact on cheese microbial stability and sensory quality over 60 days. Applied as active coatings on soft cheese stored at 4 °C for 60 days, these films were evaluated for their physicochemical properties, probiotic viability, microbial stability, and sensory acceptance. The incorporation of LA5 did not significantly alter film thickness (control: 0.20 ± 0.03 mm; test: 0.18 ± 0.02 mm), moisture content (control: 33.42 ± 0.54%; test: 32.34 ± 1.28%), or water solubility (control: 21.44 ± 1.14%; test: 22.89 ± 0.75%) (p > 0.05). However, mechanical properties were markedly modified: tensile strength decreased from 35.42 ± 5.38 MPa (control) to 6.04 ± 0.55 MPa (test), while elongation at break increased from 4.87 ± 0.93% to 68.23 ± 3.46% (p < 0.05), indicating a transition from rigidity to flexibility upon probiotic incorporation. The probiotic strain exhibited exceptional resilience, retaining 100% viability during simulated gastric exposure at both day 0 and day 30 of storage. During cheese storage, LA5 counts in test film-coated samples remained above the recommended therapeutic threshold (10⁶ cfu/g), starting at 7.44 ± 0.15 log(cfu/g) on day 0 and maintaining 6.56 ± 0.20 log(cfu/g) after 60 days. Critically, yeast and mold spoilage were delayed in probiotic-coated cheese, with detectable growth appearing only at day 60 (1.64 ± 1.34 log(cfu/g)), whereas uncoated cheese showed spoilage as early as day 28 (1.33 ± 1.62 log(cfu/g)). Sensory evaluation revealed no significant differences (p > 0.05) between the coated and uncoated samples for color, appearance, texture, flavor, or overall acceptability. By valorizing a dairy by-product into an active, probiotic-loaded edible film, this approach offers a sustainable, waste-reducing strategy that enhances cheese preservation while delivering added functional value—bridging the gap between food packaging and nutrition. Sensory evaluation (n = 8, preliminary) indicated no significant differences between coated and uncoated samples, but these results require confirmation with a larger, validated panel. Full article

O3-type layered transition-metal oxides are widely regarded as promising cathode materials for sodium-ion batteries due to their intrinsically high sodium content and favorable energy density. Nevertheless, their practical rate capability is hindered by sluggish Na⁺ transport and relatively high diffusion barriers. To address this issue, elemental substitution has emerged as an effective modification strategy. In this work, fluorine (F), characterized by strong electronegativity and a small ionic radius, is introduced to partially substitute oxygen in the bulk lattice of O3-type NaNi_1/3Fe_1/3Mn_1/3O₂ (NNFM). First-principles calculations demonstrate that F incorporation leads to an expansion of the interlayer spacing along the c-axis and a weakening of Na–O interactions, both of which facilitate Na⁺ migration. Among the considered configurations, Mn-adjacent substitution exhibits the lowest formation energy, indicating enhanced thermodynamic stability. Furthermore, electronic structure analysis reveals a reduced band gap (from 0.515 eV to 0.342–0.356 eV) and strengthened O-2p/Mn-3d orbital hybridization, contributing to improved electronic conductivity. These findings provide atomistic insights into F-induced modulation mechanisms and suggest an effective pathway for optimizing Na⁺ transport in O3-type cathodes. Full article

Environmental pollution from plastics is largely driven by inadequate waste management, particularly in food packaging that relies heavily on petroleum-derived materials. This study utilized gelatin capsule waste (GCW) as a sustainable biopolymer and incorporated yellow peacock flower extract (YPE), obtained via ultrasound-assisted extraction (UAE), at various concentrations (0–2%, w/v) to develop biodegradable films with enhanced functional and antioxidant properties. The main phenolic constituents of YPE were flavonoid aglycones and their glycosylated derivatives. YPE showed total phenolic content of 98.44–129.34 mg GAE/g dry extract, with ABTS, DPPH, and FRAP antioxidant activities ranging from 5.51 to 8.11, 3.17–7.63, and 3.86–5.82 mg TE/g dry extract, respectively. Incorporation of YPE into GCW films significantly improved light barrier properties, thermal stability, mechanical strength, and antioxidant activity, along with a reduction in water vapor permeability and an increase in contact angle, indicating enhanced film hydrophobicity. All films exhibited excellent biodegradability, with complete disintegration within 15 days under soil burial conditions. Films containing 2% YPE (GF4) showed significantly higher thickness, tensile strength, and thermal stability, along with increased opacity, compared with the control (GF0), indicating a reinforcing effect. FTIR analysis revealed the interaction between protein and phenolic compounds from YPE. In a food application model, GF4 film pouches (5 × 5 cm²) effectively delayed oxidative deterioration of dried shrimp during storage at 25 ± 2 °C for 15 days. These findings highlight YPE as a promising bioactive ingredient for biodegradable active packaging and demonstrate the feasibility of GCW as a sustainable biopolymer for eco-friendly films. Full article

Spinal muscular atrophy (SMA) therapies that restore SMN expression improve survival and motor function but often fail to fully stabilize distal motor units or sustain endurance. We propose a hypothesis-driven adjunctive approach, intended to complement SMN-restoring therapies, in which localized nanotube-enabled interfaces acting at or near the distal motor unit and neuromuscular junction enhance neuromuscular transmission reliability in surviving, remodeled motor units. The model predicts a temporal cascade: improved junctional reliability and reduced activity-dependent failure, followed by consistent motor unit output across repeated activation, and ultimately, enhanced endurance and functional reserve. Phenotype-specific responsiveness identifies patients most likely to benefit, specifically those with preserved-but-limited residual motor unit substrate accompanied by measurable neuromuscular junction instability. Drawing on shared mechanisms from ALS, spinal cord injury, and other neuromuscular disorders, we discuss mechanistic, translational, safety, regulatory, and ethical considerations. This framework links objective physiological constructs to functional outcomes, offering a mechanistically grounded path for adjunctive therapy development in SMA and related conditions. Full article

This paper investigates the stability of perovskite films under bonding conditions, focusing on the impact of bonding temperature on the electrical, morphological, and elemental characteristics of perovskite solar cells (PSCs) incorporating a barium–strontium titanate (BST) barrier layer. This study aimed to elucidate the interdiffusion phenomena at interfaces and their effect on device performance. We found that increasing the bonding temperature significantly degrades PSC performance, with efficiencies dropping from 21% at 100 °C to 65% at 180 °C relative to unbonded devices. A critical bonding temperature of 150 °C was identified, which correlates with a pronounced drop in short-circuit current and a peak in series resistance, phenomena primarily attributed to severe elemental interdiffusion and defect formation at the interfaces. Morphological (SEM) and elemental (EDS) analyses confirmed the temperature-dependent nature of interdiffusion across the Au/BST/perovskite interfaces. These findings underscore the critical role of bonding temperature in triggering interfacial degradation, a factor that mediates the stability of BST-interfaced PSCs during packaging. Full article

Formaldehyde (HCHO) is a typical volatile organic compound (VOC) that poses significant risks to human health. Long-term exposure, even at low concentrations, has been associated with various malignant diseases, including nasopharyngeal, colon, and brain cancers. Common technologies for HCHO abatement include ventilation, adsorption, photocatalysis, and catalytic oxidation. Among these methods, catalytic oxidation is regarded as the most promising due to its high removal efficiency, low cost, minimal energy consumption, and no toxic by-products. In recent years, supported catalysts with excellent room-temperature activity and high dispersibility have attracted considerable attention. These catalysts can usually be divided into two categories: noble metal catalysts and non-noble metal catalysts. Zirconia (ZrO₂) has become an ideal support owing to its advantages of high specific surface area, abundant and tunable acid–base sites, and strong metal–support interaction (SMSI). Various modification strategies have been developed to improve the catalytic performance of ZrO₂-based systems, such as the construction of phase interfaces and the stabilization of single-atom species. This review summarizes the recent research progress of ZrO₂-based systems for the catalytic oxidation of formaldehyde. It provides a detailed discussion of the physicochemical properties of ZrO₂ supports and the reaction mechanisms involved, and highlights achievements in crystal phase regulation, elemental doping, metal–support interaction, and composite modification. Finally, future challenges and development directions for these catalysts are also outlined. Full article

Nanofluids have emerged as promising candidates for enhancing the dielectric and thermal performance of insulating liquids used in power transformers. While numerous studies report significant improvements in breakdown voltage (up to +10–40%) and thermal conductivity, the underlying mechanisms remain only partially understood and often contradictory, particularly with respect to long-term stability and ageing behavior. This paper presents a comprehensive and critical review of nanofluids applied to transformer insulation, adopting a system-level approach focused on the oil–paper insulation system. The analysis reveals that the reported performance strongly depends on key parameters such as nanoparticle concentration, dispersion quality, and experimental conditions, leading to significant inter-study variability. Dielectric improvements are shown to be maximized within narrow concentration ranges and may deteriorate due to nanoparticle aggregation, while thermal enhancements are often accompanied by increased viscosity, resulting in a thermo-hydraulic trade-off. Furthermore, this review highlights major contradictions in the literature, including the paradoxical relationship between electrical conductivity and dielectric strength, as well as the unclear impact of nanofluids on cellulose ageing. The findings demonstrate that performance observed at the fluid level cannot be directly extrapolated to real transformer conditions without considering the complex interactions between nanoparticles, oil, cellulose, and moisture. To address these limitations, a conceptual framework termed Nano-Modified Composite Insulation (NMCI) is proposed. This model provides a unified description of multiphase interactions and offers a basis for a more realistic evaluation of nanofluids under operational conditions. This work emphasizes the need for standardized experimental methodologies and long-term studies and provides clear research directions toward the development of reliable and industrially applicable nanofluid-based insulation systems. Full article