Search Results (189)

Binary metallic nickel–copper nanocatalysts were anchored onto a polyvinylidene fluoride-co-hexafluoropropylene membrane [NiCu/PVdF–HFP] using the electrospinning technique, followed by the chemical reduction of the relevant precursor salts by introducing sodium borohydride to the synthesis mixture. A series of varied Ni:Cu weight % proportions was developed in order to optimize the electroactivity of this binary nanocomposite towards the investigated oxidation process. A number of physicochemical tools were used to ascertain the morphology and chemical structure of the formed metallic species on polymeric films. Cyclic voltammetric studies revealed a satisfactory performance of altered NiCu/PVdF–HFP membranes in alkaline solution. Ethylene glycol molecules were successfully electro-oxidized at their surfaces, showing the highest current intensity [564.88 μA cm⁻²] at the one with Ni:Cu weight ratios of 5:5. The dependence of these metallic membranes’ behavior on the added alcohol concentration to the reaction electrolyte and the adjusted scan rate during the electrochemical measurement was carefully investigated. One hundred repeated scans did not significantly deteriorate the NiCu/PVdF–HFP nanostructures’ durability. Decay percentages of 76.90–87.95% were monitored at their surfaces, supporting the stabilized performance for prolonged periods. A much-decreased R_ct value was estimated at Ni₅Cu₅/PVdF–HFP [392.6 Ohm cm²] as a consequence of the feasibility of the electron transfer step for the electro-catalyzing oxidation process of alcohol molecules. These enhanced study results will hopefully motivate the interested workers to explore the behavior of many binary and ternary combinations of metallic nanomaterials after their deposition onto convenient polymeric films for vital electrochemical reactions. Full article

Indoor positioning remains a recurrent and significant challenge in research. Unlike outdoor environments, where the Global Positioning System (GPS) provides reliable location information, indoor scenarios lack direct line-of-sight to satellites or cellular towers, rendering GPS inoperative and requiring alternative positioning techniques. Despite numerous approaches, indoor contexts with resource limitations, energy constraints, or physical restrictions continue to suffer from unreliable localization. Many existing methods employ a fixed number of reference anchors, which sets a hard balance between localization accuracy and energy consumption, forcing designers to choose between precise location data and battery life. As a response to this challenge, this paper proposes an energy-aware indoor positioning strategy based on Mobile Ad Hoc Networks (MANETs). The core principle is a self-adaptive control loop that continuously monitors the network’s positioning accuracy. Based on this real-time feedback, the system dynamically adjusts the number of active anchors, increasing them only when accuracy degrades and reducing them to save energy once stability is achieved. The method dynamically estimates relative coordinates by analyzing node encounters and contact durations, from which relative distances are inferred. Generalized Multidimensional Scaling (GMDS) is applied to construct a relative spatial map of the network, which is then transformed into absolute coordinates using reference nodes, known as anchors. The proposal is evaluated in a realistic simulated indoor MANET, assessing positioning accuracy, adaptation dynamics, anchor sensitivity, and energy usage. Results show that the adaptive mechanism achieves higher accuracy than fixed-anchor configurations in most cases, while significantly reducing the average number of required anchors and their associated energy footprint. This makes it suitable for infrastructure-poor, resource-constrained indoor environments where both accuracy and energy efficiency are critical. Full article

Edible hydrogels are the central material class in 3D food printing because they reconcile two competing needs: (i) low resistance to flow under nozzle shear and (ii) fast recovery of elastic structure after deposition to preserve geometry. This review consolidates the recent years of progress on hydrogel formulations—gelatin, alginate, pectin, carrageenan, agar, starch-based gels, gellan, and cellulose derivatives, xanthan/konjac blends, protein–polysaccharide composites, and emulsion gels alongside a critical analysis of printing technologies relevant to food: extrusion, inkjet, binder jetting, and laser-based approaches. For each material, this review connects gelation triggers and compositional variables to rheology signatures that govern printability and then maps these to process windows and post-processing routes. This review consolidates a decision-oriented workflow for edible-hydrogel printability that links formulation variables, process parameters, and geometric fidelity through standardized test constructs (single line, bridge, thin wall) and rheology-anchored gates (e.g., yield stress and recovery). Building on these elements, a “printability map/window” is formalized to position inks within actionable operating regions, enabling recipe screening and process transfer. Compared with prior reviews, the emphasis is on decisions: what to measure, how to interpret it, and how to adjust inks and post-set enablers to meet target fidelity and texture. Reporting minima and a stability checklist are identified to close the loop from design to shelf. Full article

A common misconception is that behavioral economics rejects microeconomics. This entry explains how behavioral economics, despite challenging core assumptions of rationality, remains fundamentally aligned with the structure of microeconomics. Anchored in the insight that rational market outcomes can emerge even when individual behavior is non-rational, it revisits the explanatory role of constraints in economic theory. Rather than displacing microeconomics, behavioral economics extends it by incorporating bounded rationality while preserving key structural principles. Central to this integration is Say’s law, the macro-level notion that production generates income and thus the capacity for demand. This connection makes microeconomic constraints reflect deeper macroeconomic principles. Even when market behavior is distorted by correlated cognitive biases and their associated positive feedback dynamics—such as herding or bubbles—the fundamental identity that supply generates the income necessary for demand remains intact, provided that adjustments occur over the long run. The analysis also considers how behavioral deviations affect aggregate outcomes. Ultimately, this entry shows that behavioral economics is not a departure from microeconomics but its natural extension: by embedding bounded rationality within the framework of economic constraints, it preserves the structural coherence of microeconomics while adding psychological depth. Full article

As the world increasingly gravitates towards green, environmentally friendly and low-carbon lifestyles, wind power has become one of the most technologically established renewable energy sources. However, with the continuous increase in their output power and height, wind turbine towers are subjected to higher-intensity alternating wind loads. This makes critical components more prone to fatigue failure, potentially leading to major accidents such as tower buckling or turbine collapse. High-strength bolts play a vital role in supporting towers but are susceptible to fatigue crack initiation under long-term cyclic loading, necessitating regular inspection. Types of wind turbine bolts mainly include high-strength bolts, stainless steel bolts, anchor bolts, titanium alloy bolts, and adjustable bolts. These bolts are distributed across different parts of the turbine and perform distinct functions. Among them, high-strength bolts in the tower are particularly critical for structural support, demanding prioritized periodic inspection. Compared to destructive offline inspection methods requiring bolt disassembly, non-destructive testing (NDT) has emerged as a trend in defect detection technologies. Therefore, this review comprehensively examines various types of NDT techniques for wind turbine towers’ high-strength bolts, including disassembly inspection techniques (magnetic particle inspection, penetration inspection, intelligent torque inspection, etc.) and non-disassembly inspection techniques (ultrasonic inspection, radiographic inspection, infrared thermographic inspection, etc.). For each technique, we analyze the fundamental principles, technical characteristics, and limitations, while emphasizing the interconnections between the methodologies. Finally, we discuss potential future research directions for bolt defect NDT technologies. Full article

Background: Less invasive surfactant administration (LISA) can reduce exposure to mechanical ventilation in preterm infants, but factors associated with LISA failure in routine practice remain uncertain, particularly outside Europe. Methods: We performed a single-center retrospective cohort at King Abdulaziz Medical City, Riyadh (June 2023–June 2025). Inborn preterm infants at 26–34 weeks of gestation who received LISA as first-line surfactant therapy were included. The primary outcome was LISA failure, defined as intubation within 72 h for apnea, escalating oxygen requirement, or respiratory acidosis. Secondary outcomes included intraventricular hemorrhage (IVH), NICU length of stay, and other major morbidities. Multivariable logistic regression (gestational age as the anchor variable with a limited number of additional covariates) was used to identify predictors of failure and of IVH. Kaplan–Meier methods (log-rank test) were used to compare time to NICU discharge. Results: Forty-one infants were included (median gestational age: 30 weeks; median birth weight: 1300 g). LISA failure occurred in 39% of the cohort. Compared with infants with successful LISA, those who failed were more premature (median GA: 28 vs. 29 weeks; p = 0.009), had lower birth weight (1100 g vs. 1270 g; p = 0.011), higher IVH rates (38% vs. 8%; p = 0.020), and longer NICU stay (60 vs. 40 days; p = 0.041). Lower gestational age was the only independent factors associated with LISA failure (adjusted OR 1.44; 95% CI: 1.07–1.95; p = 0.018). LISA failure was independently associated with IVH (adjusted OR 10.08; 95% CI: 1.29–78.50; p = 0.027). Kaplan–Meier analysis showed significantly prolonged NICU stay among infants with LISA failure (p = 0.011). Conclusions: LISA is feasible in a high-acuity Middle Eastern NICU. However, failure—closely linked to lower gestational age—is associated with IVH and prolonged hospitalization. Careful patient selection and procedural planning are essential to optimize outcomes. Full article

Background/Objectives: Miscarriage (spontaneous abortion) can precipitate post-traumatic stress disorder (PTSD). In Peru, post-loss mental healthcare is limited. We aimed to identify factors associated with PTSD symptoms persisting ≥ 3 months among women who experienced miscarriage and were treated in the emergency department (ED) of a national hospital in Lima, 2021–2023. Methods: We conducted a cross-sectional analytical study of 214 women with spontaneous abortion seen in the ED (January 2021–December 2023). PTSD symptoms were measured with the PTSD Checklist for DSM-5 (PCL-5), anchored to the miscarriage index; sociodemographic and gyneco-obstetric variables were obtained with a validated questionnaire. Multivariable Poisson regression with robust variance estimated the adjusted prevalence ratios (aPRs). Results: Probable PTSD (PCL-5 ≥ 33) was present in 52.8% of participants. Independent correlates included previous miscarriage (aPR 1.75; 95% CI 1.35–2.25), ≥2 pre-gestational medical visits (aPR 1.66; 95% CI 1.21–2.27), and one (aPR 1.36; 95% CI 1.00–1.84) or multiple comorbidities (aPR 1.61; 95% CI 1.12–2.30). No other sociodemographic or obstetric variables were significantly associated. Conclusions: More than half of women assessed ≥ 3 months after miscarriage screened positive for probable PTSD. Previous pregnancy loss increased pre-gestational healthcare contact, and medical comorbidities were associated with higher prevalence. Integrating routine mental health screening and trauma-informed support within ED and reproductive health services could improve detection and care for this population. To our knowledge, this is the first ED-based study in Peru to examine factors associated with post-loss probable PTSD (PCL-5 ≥ 33) after miscarriage. Full article

Background/Objectives: Long-term obesity management consistently fails due to two major barriers: poor adherence, exacerbated by ultra-processed foods with addictive potential, and post-weight loss metabolic adaptation that reduces energy expenditure by approximately 500 kcal/day. Current paradigms—static diets and GLP-1 receptor agonists—address these barriers only partially. The objectives of this thesis-driven review are: (1) to conduct a focused evidence-mapping of Ketogenic–Mediterranean Diet (KMD) protocols; (2) to analyze why existing protocols have not explicitly countered metabolic adaptation; and (3) to present the Adaptive Ketogenic–Mediterranean Protocol (AKMP). Methods: Hybrid methodology—an argumentative narrative review anchored by a structured evidence-mapping search (PRISMA-style flow for transparency). Results: We identified 29 studies implementing KMD protocols with significant weight loss and superior adherence. However, none of the published protocols explicitly implement anti-adaptive strategies, despite an estimated ketogenic metabolic advantage (≈100–300 kcal/day), context-dependent and more consistently observed in longer trials and during weight-maintenance settings. Conclusions: Unlike GLP-1 receptor agonists—which primarily suppress appetite, require ongoing pharmacotherapy, and do not directly mitigate the decline in energy expenditure—the AKMP couples a Mediterranean foundation for adherence with a ketogenic metabolic advantage and a biomarker-guided adjustment system explicitly designed to counter metabolic adaptation, aiming to improve the durability of weight loss and patient self-management. As a theoretical construct, the AKMP requires confirmation in prospective, controlled studies; accordingly, we outline a pragmatic 24-week pilot design in “Pragmatic Pilot Trial to Validate the AKMP–Incretin Sequencing”. Full article

High-pier partially cable-stayed bridges, with their significant pier heights and relatively low structural stiffness and stability, experience pronounced vehicle–bridge coupling effects during vehicle transit, influencing their dynamic response and safety. This study developed a co-simulation analysis program using easy language and ANSYS to investigate the dynamic behavior of a prestressed concrete five-tower partially cable-stayed bridge under vehicle–bridge interaction, considering factors such as vehicle speed, bridge deck grade, and cable force. The research findings indicate that a reduction in bridge deck grade leads to increases in peak dynamic responses and impact factors, with the dynamic amplification factor showing a deteriorating trend across all cross-sections. Structural responses fluctuate with vehicle speed and exhibit sensitivity to speed variations, with the maximum response observed at a speed of 80 km/h. Adjusting cable forces can reduce the impact factor: a 5% change in cable tension causes the mid-span impact factor to drop sharply from 0.38 to 0.04, a substantial decrease of 89.5%. The structural system can exert an impact on the impact factor by as much as several times: while the dynamic displacement and bending moment of the fixed system are smaller than those of the continuous beam system, its impact factor is as high as 4.22 times that of the continuous beam system. Additionally, dynamic responses are closely related to the position of the fixed bearing, with responses near the fixed bearing being reduced. Notably, the maximum impact factors of critical sections all exceed the 0.05 limit specified in the code for this type of bridge, with values of 0.54 at the mid-span, 0.91 at the pier top, and 0.43 at the tower top anchor zone. This indicates that the provisions regarding dynamic amplification factors in the current code are inappropriate for such bridges. The difference in impact factors between bridge components can reach 2.12 times, this indicates that specific impact factors should be assigned to individual components to achieve an optimal balance between safety and economic performance. Full article

We previously developed SA-conf, a method designed to quantify backbone structural variability in protein targets. This approach is based on the HMM-SA structural alphabet, which enables efficient and rapid comparison of local backbone conformations across multiple structures of a given target. In this study, SA-conf (version for python2.7) was applied to a dataset of 130 crystallographic chains of Bcl-xL, a protein involved in promoting cell survival. SA-conf quantified and mapped backbone structural variability, revealing the protein’s capacity for conformational rearrangement. Our results showed that while most mutations had minimal impact on backbone conformation, some were associated with long-range structural effects. By jointly analyzing residue flexibility and backbone rearrangements across apo and holo structures, SA-conf identified key regions where the backbone undergoes structural adjustments upon ligand binding. Notably, the $\alpha 2$–$\alpha 3$ region was shown to be a hotspot of structural plasticity, exhibiting ligand-specific conformational signatures. Furthermore, SA-conf enabled the construction of a structural map of the binding site, distinguishing a conserved anchoring core from flexible peripheral regions that contribute to ligand specificity. Overall, this study highlights SA-conf’s capacity to detect conformational changes in protein backbones upon ligand binding and to uncover structural determinants of selective ligand recognition. Full article

UAV small target detection in urban security, disaster monitoring, agricultural inspection, and other fields faces the challenge of increasing accuracy and real-time requirements. However, existing detection algorithms still have weak small target representation ability, extensive computational resource overhead, and poor deployment adaptability. Therefore, this paper proposes a lightweight algorithm, I-YOLOv11n, based on YOLOv11n, which is systematically improved in terms of both feature enhancement and structure compression. The RFCBAMConv module that combines deformable convolution and channel–spatial attention is designed to adjust the receptive field and strengthen the edge features dynamically. The multiscale pyramid of STCMSP context and the lightweight Transformer–DyHead hybrid detection head are designed by combining the multiscale hole feature pyramid (DFPC), which realizes the cross-scale semantic modeling and adaptive focusing of the target area. A collaborative lightweight strategy is proposed. Firstly, the semantic discrimination ability of the teacher model for small targets is transferred to guide and protect the subsequent compression process by integrating the mixed knowledge distillation of response alignment, feature imitation, and structure maintenance. Secondly, the LAMP–Taylor channel pruning mechanism is used to compress the model redundancy, mainly to protect the key channels sensitive to shallow small targets. Finally, K-means++ anchor frame optimization based on IoU distance is implemented to adapt the feature structure retained after pruning and the scale distribution of small targets of UAV. While significantly reducing the model size (parameter 3.87 M, calculation 14.7 GFLOPs), the detection accuracy of small targets is effectively maintained and improved. Experiments on VisDrone, AI-TOD, and SODA-A datasets show that the mAP@0.5 and mAP@0.5:0.95 of I-YOLOv11n are 7.1% and 4.9% higher than the benchmark model YOLOv11 n, respectively, while maintaining real-time processing capabilities, verifying its comprehensive advantages in accuracy, light weight, and deployment. Full article

Traditional unmanned aerial vehicle (UAV) detection and tracking methods have long faced the twin challenges of high cost and poor efficiency. In real-world battlefield environments with complex backgrounds, occlusions, and varying speeds, existing techniques struggle to track small UAVs accurately and stably. To tackle these issues, this paper presents an enhanced YOLOv8N-Drone-based algorithm for improved target tracking of small UAVs. Firstly, a novel module named C2f-DSFEM (Depthwise-Separable and Sobel Feature Enhancement Module) is designed, integrating Sobel convolution with depthwise separable convolution across layers. Edge detail extraction and multi-scale feature representation are synchronized through a bidirectional feature enhancement mechanism, and the discriminability of target features in complex backgrounds is thus significantly enhanced. For the feature confusion problem, the improved lightweight Context Anchored Attention (CAA) mechanism is integrated into the Neck network, which effectively improves the system’s adaptability to complex scenes. By employing a position-aware weight allocation strategy, this approach enables adaptive suppression of background interference and precise focus on the target region, thereby improving localization accuracy. At the level of loss function optimization, the traditional classification loss is replaced by the focal loss (Focal Loss). This mechanism effectively suppresses the contribution of easy-to-classify samples through a dynamic weight adjustment strategy, while significantly increasing the priority of difficult samples in the training process. The class imbalance that exists between the positive and negative samples is then significantly mitigated. Experimental results show the enhanced YOLOv8 boosts mean average precision (Map@0.5) by 12.3%, hitting 99.2%. In terms of tracking performance, the proposed YOLOv8 N-Drone algorithm achieves a 19.2% improvement in Multiple Object Tracking Accuracy (MOTA) under complex multi-scenario conditions. Additionally, the IDF1 score increases by 6.8%, and the number of ID switches is reduced by 85.2%, indicating significant improvements in both accuracy and stability of UAV tracking. Compared to other mainstream algorithms, the proposed improved method demonstrates significant advantages in tracking performance, offering a more effective and reliable solution for small-target tracking tasks in UAV applications. Full article

The methanol oxidation reaction (MOR) of direct methanol fuel cells (DMFCs) is limited by the slow kinetic process and high reaction energy barrier, significantly restricting the commercial application of DMFCs. Therefore, developing MOR catalysts with high activity and stability is very important. In this paper, oxygen-functionalised activated carbon (FAC) with controllable oxygen-containing functional groups was prepared by adjusting the volume ratio of H₂SO₃/HNO₃ mixed acid, and Pd/AC and Pd/FAC catalysts were synthesised via the hydrazine hydrate reduction method. A series of characterisation techniques and electrochemical performance tests were used to study the catalyst. The results showed that when V(H₂SO₃):V(HNO₃) = 2:3, more defects were generated on the surface of the AC, and more oxygen-containing functional groups represented by C=O and C–OH were attached to the surface of the support, which increased the anchor sites of Pd and improved the dispersion of Pd nanoparticles (Pd NPs) on the support. At the same time, the mass–specific activity of Pd/FAC for MOR was 2320 mA·mg_Pd, which is 1.5 times that of Pd/AC, and the stability was also improved to a certain extent. In situ infrared spectroscopy further confirmed that oxygen functionalisation treatment promoted the formation and transformation of *COOH intermediates, accelerated the transformation of CO_L into CO_B, reduced the poisoning of CO_ads species adsorbed to the catalyst, optimised the reaction path and improved the catalytic kinetic performance. Full article

Assessing sustainability in urban projects became a key priority in the face of growing urban complexity. Therefore, how can global sustainability indicators be effectively adapted to assess urban projects at local scales? The paper proposes a framework for integrating sustainability into the decision-making process, aligning urban governance with the 2030 Agenda at the district and building levels. Governments’ growing demand for reliable monitoring, reporting, and evaluation systems underscores the urgency of data-driven tools to guide and adjust policies. In this context, indicators are essential instruments, making sustainability measurable and transparent. Anchored in the global framework of the 17 Sustainable Development Goals (SDGs), the paper focuses on SDG 11, integrating strategic targets with operational metrics from Sustainable Assessment Tools (SATs). The research adopts a multi-method approach, combining inductive analysis—guided by the PRISMA methodology for systematic reviews—with deductive analysis based on surveys. This study represents the theoretical foundation of the GLOSSA project (GLOcal knowledge-System for the Sustainable Assessment of urban projects), aiming to provide a set of indicators for measuring and evaluating sustainable urban transformation projects. This paper highlights the need to integrate sustainability into urban decision-making, providing an operational framework for sustainable urban governance. Full article

The COVID-19 pandemic has resulted in countless losses around the world, profoundly affecting the lives of many people, especially those who faced the death of family members, bringing several negative repercussions to these families and constraining the experience of grief. This study aimed to understand the experience of loss and grief among bereaved individuals who lost family members during the COVID-19 pandemic. This qualitative study was guided by Charmaz’s constructivist grounded theory as a methodological framework. The study adhered to the Criteria for REporting Qualitative research (COREQ) checklist. Data collection took place between May and November 2023 through telephone interviews that were audio-recorded and later transcribed in full. The purposive sample consisted of 21 bereaved family members who had lost their loved ones during the COVID-19 pandemic. Participants were mainly female (n = 16) with a mean age of 55.5 (SD = 16.2). The loss of their family members occurred 12 to 24 months before data collection. The following central phenomenon was identified through the analytical process: “Family experience of loss and grief: between the unspoken goodbye and post-loss adjustment”. This was anchored in the following three categories: (1) Anguish and fear of the unknown; (2) Death by COVID-19—communication of death and lack of goodbyes; and (3) (Re)construction of meaning—support networks and the grieving process. Our findings recommend that policymakers allocate additional resources to grief support services to better prepare for future pandemic events. Furthermore, it is necessary to invest in the implementation of relevant training programs for healthcare professionals, with a family centered approach. Full article