Search Results (4,984)

(1) Background: The escalating crisis of multidrug-resistant (MDR) bacteria presents a formidable threat to global public health, necessitating the urgent development of alternative antimicrobial strategies. Nanoparticles (NPs) have emerged as a promising frontier in this effort, leveraging their unique physicochemical properties and multi-modal mechanisms of action to combat bacterial infections. This systematic review aims to comprehensively evaluate the current body of evidence on the dynamic interplay between nanoparticles and bacterial resistance. (2) Methods: A comprehensive search of electronic databases, including PubMed, Scopus, and Web of Science, was performed using a combination of keywords and Medical Subject Headings (MeSH) terms to identify relevant primary research articles. Eligibility criteria focused on studies evaluating the antimicrobial effects of nanoparticles on MDR bacterial strains, reporting on mechanisms of action, efficacy, or resistance development. (3) Results: The synthesis of findings revealed that nanoparticles exert their antimicrobial effects through multiple pathways, including the generation of reactive oxygen species (ROS), direct disruption of bacterial membranes, and the release of toxic ions. However, the analysis also confirmed that bacteria have evolved sophisticated defense mechanisms against nanoparticles, including surface modifications that prevent adhesion, upregulation of efflux pumps, and chemical neutralization of toxic ions. (4) Conclusions: Nanoparticles represent a potent and versatile tool in the global effort to combat antimicrobial resistance. Their long-term efficacy is not guaranteed, as bacteria have shown a remarkable capacity for adaptation. The future of this field lies in the development of rationally designed nanoparticle systems that not only possess intrinsic antimicrobial activity but also actively disarm bacterial resistance mechanisms. This includes the strategic use of synergistic combinations with conventional antibiotics and the exploration of resistance-agnostic approaches like nanotoxoid vaccines. Full article

Background: Children with autism spectrum disorder (ASD) frequently show postural abnormalities and elevated muscle tone, which can hinder participation in education and rehabilitation. Evidence on the immediate physiological effects of standardized multisensory environments is limited. Objective: To evaluate feasibility, safety and short-term physiological/postural responses to an automated multisensory smart relaxation system in children with severe ASD. Methods: In a single-session pilot across three sites, 30 children (27 boys; 6–16 years) underwent pre–post postural observation and bilateral surface EMG of the upper trapezius, biceps brachii and rectus abdominis. The system delivered parameterized sound, vibration, and mild heat. EMG was normalized to a quiet-sitting baseline. Results: The intervention was well tolerated with no adverse events. Most children sat independently (25/30; 80%) and a majority stood up unaided after the session (24/30; 76.9%). Postural profiles reflected common ASD features (neutral trunk 76%, forward head 52%, rounded/protracted shoulders 46%), while limb behavior was predominantly calm (73%). Normalized EMG amplitudes were low, with no significant pre–post changes and no meaningful left–right asymmetries (all p > 0.05; Cohen’s d < 0.20), indicating physiological calmness rather than tonic co-contraction. Conclusions: A single session with a smart multisensory relaxation system was safe, feasible, and physiologically calming for children with severe ASD, without increasing postural or muscular tension. The platform’s standardization and objective monitoring support its potential as a short-term calming adjunct before therapy or classroom tasks. Larger, gender-balanced, multi-session trials with behavioral outcomes are warranted. Full article

The large-scale integration of renewable energy sources introduces significant uncertainty into modern power systems, posing new challenges for reliable and economical operation. Effective scheduling therefore requires accurate monitoring of uncertainty and efficient handling of nonlinear system dynamics. This paper proposes an optimization-based scheduling method that combines sensor-informed monitoring of photovoltaic (PV) uncertainty with advanced processing of nonlinear hydropower characteristics. A detailed hydropower model is incorporated into the framework to represent water balance, reservoir dynamics, and head–discharge–power relationships with improved accuracy. Nonlinear constraints and uncertainty are addressed through a unified approximation scheme that ensures computational tractability. Case studies on the modified IEEE−39 system show that the proposed method achieves effective multi-source coordination, reduces operating costs by up to 2.9%, and enhances renewable energy utilization across different uncertainty levels and PV penetration scenarios. Full article

Background and Objectives: Infantile colic affects 15–40% of infants ≤ 5 months, burdening families and health systems. While the effects of intrapartum oxytocin on neonatal outcomes have been widely investigated, its potential link with infantile colic remains poorly understood. We evaluated whether synthetic oxytocin is associated with infantile colic during the first five months of life and explored neonatal head circumference, feeding type and epidural anesthesia as additional factors. Materials and Methods: Prospective 1:1 matched case–control study in three Spanish pediatric outpatient clinics. Parents of 76 term infants aged 0–5 months (38 cases, 38 controls) completed face-to-face structured interviews documenting synthetic oxytocin and epidural use, infant anthropometry and feeding pattern. Infantile colic was diagnosed by Rome IV criteria. Associations were estimated with conditional logistic regression, producing adjusted odds ratios and 95% confidence intervals. Results: Synthetic oxytocin was used in 57.9% of deliveries and epidural anesthesia in 81.6 %. Synthetic oxytocin showed no association with infantile colic (aOR 1.24; 95% CI 0.50–3.09). Epidural strongly predicted synthetic oxytocin exposure (aOR 4.55; 95% CI 1.28–16.20) but had no independent link to infantile colic. Infants with colic had a smaller mean head circumference at birth, although this difference did not remain significant after adjusting for gestational age, likely reflecting limited sample size. Synthetic oxytocin was not associated with breastfeeding status. Conclusions: In this cohort, intrapartum synthetic oxytocin was not related to infantile colic or to feeding difficulties. Smaller head circumference among colic cases may warrant further investigation as a potential risk marker. The high co-use of synthetic oxytocin and epidural underscores the need for larger longitudinal studies to clarify their peripartum–neonatal interactions. Full article

The field of underwater robotics is experiencing rapid growth, wherein accurate object detection constitutes a fundamental component. Given the prevalence of false alarms and omission errors caused by intricate subaquatic conditions and substantial image noise, this study introduces an enhanced detection framework that combines the YOLOv8 architecture with multimodal visual fusion methodology. To solve the problem of degraded detection performance of the model in complex environments like those with low illumination, features from Visible Light Image are fused with the Thermal Distribution Features exhibited by Infrared Image, thereby yielding more comprehensive image information. Furthermore, to precisely focus on crucial target regions and information, a Multi-Scale Cross-Axis Attention Mechanism (MSCA) is introduced, which significantly enhances Detection Accuracy. Finally, to meet the lightweight requirement of the model, an Efficient Shared Convolution Head (ESC_Head) is designed. The experimental findings reveal that the YOLOv8-FUSED framework attains a mean average precision (mAP) of 82.1%, marking an 8.7% enhancement compared to the baseline YOLOv8 architecture. The proposed approach also exhibits superior detection capabilities relative to existing techniques while simultaneously satisfying the critical requirement for real-time underwater object detection. Moreover, the proposed system successfully meets the essential criteria for real-time detection of underwater objects. Full article

Hydroxytyrosol (HXT), a phenolic compound from olive, shows great potential as a neuroprotective agent and a translational target for claim-ready nutrition and food products. Human studies increasingly report benefits for vascular function, inflammatory tone, and early cognitive/psychomotor outcomes, consistent with engagement of redox and signalling pathways (Keap1–Nrf2–ARE, PI3K/Akt–ERK, and AMPK–SIRT1–PGC-1α). HXT is rapidly absorbed and likely reaches the brain, acting on endothelial and microglial targets. On the neurovascular axis, it reduces oxidative stress, preserves nitric-oxide bioavailability, lower inflammatory markers, and favourable intrinsic connectivity. For product development, bitterness from oleuropein-rich inputs can be mitigated by hydrolysis, followed by structure-guided delivery to balance sensory quality with exposure. Viable formats include cyclodextrin inclusion, microencapsulation, and (micro)emulsions in lipid matrices, plus stability engineering for aqueous systems (acidification, chelation, low-oxygen handling, or barrier packaging). Matrix effects are consequential; some proteins and fibers may decrease HXT bioaccessibility, whereas lipid phases and microstructured carriers often enhance it. Clinically, recommended doses are ~7–15 mg/day chronically and ~30–60 mg acutely. As conclusions of this review, future work should prioritize harmonized pharmacokinetics–pharmacodynamics readouts, cognition anchored to a compact neurovascular/blood–brain barrier biomarker core, and head-to-head comparisons of manufacturable delivery formats. Full article

This research tackles the intricate machining properties of cylindrical aspheric surfaces with a versatile adaption approach utilizing a robotic arm and a compact tool head, incorporating trajectory optimization. A three-step integrated error compensation framework was established as the core to address spatial inaccuracies in robotic systems, incorporating coordinate measuring machine (CMM)-based cylindrical generatrix offset correction, laser tracker-assisted progressive coordinate calibration, and contour profiler-driven feedback compensation. Complemented by a curvature-driven trajectory design, the method ensures uniform polishing coverage for non-uniform curvature surfaces. Experimental validation on S-TiH53 glass cylindrical aspheric components demonstrated a surface profile accuracy of peak-to-valley (PV) value ≤ 2 μm, meeting stringent requirements for high-power laser applications. This systematic approach enhances both efficiency and accuracy in robotic polishing, offering a viable solution for high-end optical manufacturing. Full article

Background and Clinical Significance: Adverse reactions to metal debris (ARMD) are a rare but increasingly recognized complication following total hip arthroplasty (THA), with some studies suggesting upwards of 5% of metal-on-metal (MoM) and 3% of metal-on-polyethylene (MoP) prostheses being attributed to this. Historically, metallosis due to MoM implant design was the primary cause of ARMD. However, ARMD can also arise in metal-on-polyethylene (MoP) prostheses due to trunnionosis, which involves wear and corrosion at the modular femoral head–neck interface. Clinically, ARMD can resemble periprosthetic joint infection (PJI), complicating both diagnosis and management. Case Presentation: We present the case of a 40-year-old female with a history of systemic degenerative joint disease with bilateral MoP THAs who developed progressive pain and swelling in the upper left thigh, in which the prosthesis was first put in 22 years prior. The patient presented initially in a vascular surgery department for an infected iliopsoas cyst communicating with the hip where she had received surgery 2 years prior. The symptomatology reoccurred, and imaging revealed a large mass near the prosthesis and elevated inflammatory markers. Intraoperatively, a large volume of sero-purulent fluid was encountered, prompting a diagnostic workup for PJI. All cultures returned negative, and histopathology revealed macrophage-dominant infiltration with metallic debris, consistent with ARMD. After infection was definitively excluded, a revision THA was performed with an exchange of all modular components. The patient recovered without complications, and at six months follow-up, she demonstrated stable implant positioning, restored function, and no recurrence of symptoms. Conclusions: This case highlights the diagnostic complexity of PJI in joint arthroplasty and reveals the importance of a protocol-driven approach to exclude it prior to surgical revision. As the incidence of trunnion-related failure becomes more recognized in the literature, clinicians must consider ARMD in the differential diagnosis of late THA complications. Appropriate diagnosis is essential for guiding treatment and avoiding unnecessary complications, morbidity, and treatment related side-effects. Full article

This study seeks to determine the efficacy of a novel, virtual reality (VR)-based sensorimotor assessment tool, VIST Neuro-ID, in comparison to the gold standard. This was achieved through computing common postural sway metrics, as well as comparing these metrics across population groups including sex and age (50–60 vs. 61–75). Sensorimotor assessments were conducted within the VIST Neuro-ID VR software while participants stood on a force plate. A proxy for center-of-pressure measurement was developed using the six-degree-of-freedom data collected from the head-mounted display used with the VR system. Moderate-to-high (r = 0.542–0.906) Pearson’s correlations were found between VIST Neuro-ID and the force plate for all eight postural sway metrics that were computed. Both systems detected significant differences (p < 0.05) across age groups for all metrics, except for two-dimensional path length from the force plate. Several significant differences were found across sexes, including AP and resultant sway velocity from the force plate, and resultant and AP root-mean-square from the HTC Vive Pro Eye. This indicates potential for VR to be used to collect vital postural sway metrics needed for assessing patient function, while also highlighting potential to identify balance patterns related to aging. Full article

With the rapid advancement in autonomous driving technology, vehicle object detection has become a crucial component of perception systems, where accuracy and inference speed directly influence driving safety. To address the limitations of existing lightweight detection models in small-object perception and deployment efficiency, this study proposes an enhanced YOLOv8n-based framework, termed YOLOv8n-ALM. The proposed model integrates Mixed Local Channel Attention (MLCA), a Task-Aligned Dynamic Detection Head (TADDH), and Layer-Adaptive Magnitude-based Pruning (LAMP). Specifically, MLCA enhances the representation of salient regions, TADDH aligns classification and regression tasks while leveraging DCNv2 for improved spatial adaptability, and LAMP compresses the network to accelerate inference. Experiments conducted on the KITTI dataset demonstrate that YOLOv8n-ALM improves mAP@0.5 by 2.2% and precision by 5.8%, while reducing parameters by 65.33% and computational load by 29.63%. These results underscore the proposed method’s capability to achieve real-time, compact, and accurate vehicle detection, demonstrating strong potential for deployment in intelligent vehicles and embedded systems. Full article

The liquid reservoir is a critical component of the automotive air conditioning system, while weld seams on its surface may exhibit different types of defects with various shapes and scales, meaning traditional detection methods struggle to detect them effectively. In this article, we propose a YOLOv8s-based algorithm to detect liquid reservoir weld defects. In order to improve feature fusion within the neck and enhance the model’s capacity to detect defects showing substantial size variations, the neck is optimized through the integration of the improved Reparameterized Generalized Feature Pyramid Network (RepGFPN) and the addition of a small-object detection head. To further improve the capacity of identifying complex defects, the Spatial Pyramid Pooling Fast (SPPF) module in YOLOv8s is substituted with Focal Modulation Networks (FocalNets). Additionally, the Cascaded Group Attention (CGA) mechanism is incorporated into the improved neck to minimize the propagation of redundant feature information. Experimental results indicate that the improved YOLOv8s achieves a 6.3% improvement in mAP@0.5 and a 4.3% improvement in mAP@0.5:0.95 compared to the original model. The AP value for detecting craters, porosity, undercuts, and lack of fusion defects improves by 3.9%, 13.5%, 5.0%, and 2.5%, respectively. We conducted comparative experiments against other state-of-the-art models on the liquid reservoir weld dataset and the steel pipe weld defect dataset, and the results show that our model has outstanding detection performance. Full article

This research analyzes the energy balance of the purification water pumping system at the La Presa drinking water purification plant (DWPP) in Manises (Valencia) and evaluates alternatives to improve its energy efficiency. These alternatives include the construction of a storage tank at an elevation of 75 m between La Presa Plant and Valencia city, allowing the lower area of the city to be supplied independently from the upper zone. This configuration will adapt to the pressure levels of the whole city and control the residence time in the tanks, thereby improving both energy and quality parameters in the whole network. Hydraulic simulations were conducted in EPANET using models representing the system from the La Presa gallery to the delivery points under various demand scenarios and operational criteria. Three alternatives for feeding the new tank are studied: using additional pumps; using turbines; and a combination of both. From the data obtained in the simulations (flows and heads), the net energy consumed was calculated, and the average water residence time in the tanks was simulated as an indicator of water quality, using certain theoretical criteria. The results indicate that all alternatives represent a significant energy saving and maintain water quality at any moment. The best solution is proposed, which involves combining pumps and turbines and minimizing residence time in the tanks. In this case, a saving of 42.26% of energy is achieved when compared with the actual situation, with an average residence time in the tanks of less than 50 h. The combination of both restrictions of quality and energy savings represents a novelty in the management of future decisions for purification plants supplying real networks. Full article

This paper presents a mobile application designed to support emergency operators during indoor missions, where Global Positioning System (GPS) often fails. The system combines a wearable waist-mounted Inertial Measurement Unit (IMU) with a network of pre-installed Radio Frequency Identification (RFID) tags, enabling robust, real-time geo-referenced tracking of both personnel and critical Points of Interest (PoIs), such as resources and threats. Development was guided by interviews and surveys with emergency professionals, ensuring the tool addresses real operational needs. Key features include dynamic updates of operator positions and nearby hazards, enabled by an Indoor Positioning System (IPS) that fuses IMU and RFID data to improve accuracy in position and heading estimation. The application also offers a user-friendly Human–Environment Interface (HEI) displaying information on a spatially referenced map. By merging advanced technology with expert feedback, this system enhances safety and coordination in critical scenarios, offering a promising solution for indoor navigation and Situational Awareness (SA) in emergency response. Full article

Financial sustainability in higher education is increasingly fragile due to policy shifts, rising costs, and funding volatility. Legacy early-warning systems based on static thresholds or rules struggle to adapt to these dynamics and often overlook fairness and interpretability—two essentials in public-sector governance. We propose a university financial risk early-warning framework that couples a causal-attention Transformer with Multi-Objective Bayesian Optimization (MBO). The optimizer searches a constrained Pareto frontier to jointly improve predictive accuracy (AUC↑), fairness (demographic parity gap, DP_Gap↓), and computational efficiency (time↓). A sparse kernel surrogate (SKO) accelerates convergence in high-dimensional tuning; a dual-head output (risk probability and health score) and SHAP-based attribution enhance transparency and regulatory alignment. On multi-year, multi-institution data, the approach surpasses mainstream baselines in AUC, reduces DP_Gap, and yields expert-consistent explanations. Methodologically, the design aligns with LLM-style time-series forecasting by exploiting causal masking and long-range dependencies while providing governance-oriented explainability. The framework delivers earlier, data-driven signals of financial stress, supporting proactive resource allocation, funding restructuring, and long-term planning in higher education finance. Full article

This paper presents a comprehensive review that provides an in-depth examination of humanoid heads, focusing on their mechanics, perception systems, computational frameworks, and human–robot interaction interfaces. The integration of these elements is crucial for developing advanced human–robot interfaces that enhance user interaction and experience. Key topics include the principles of context, functionality, and appearance that guide the design of humanoid heads. This review delves into the different aspects of human–robot interaction, emphasizing the role of artificial intelligence and large language models in improving these interactions. Technical challenges such as the uncanny valley phenomenon, facial expression synthesis, and multi-sensory integration are further explored. This paper identifies future research directions and underscores the importance of interdisciplinary collaboration in overcoming current limitations and advancing the field of humanoid head technology. Full article