Search Results (10,396)

Potato nitrogen (N) demand varies with developmental stage rather than remaining uniformly high throughout the season. This review re-examines the “nitrate-first, ammonium-later” strategy by separating total N amount, N-supply timing, N form, and soil N transformation. Current evidence suggests that nitrate is better aligned with pre-tuber initiation because it supports stolon development and tuber set under non-excessive N supply, whereas ammonium-containing nutrition may benefit tuber bulking only when NH₄⁺ persists in the root zone and soil chemical constraints are controlled. Field responses attributed to N form are often shaped by crop N status, genotype × environment × management interactions, nitrification–denitrification dynamics, water regime, soil texture, fertilizer placement, and cultivar. We therefore interpret the strategy as a conditional, stage-oriented framework rather than a universal fertilizer prescription. Integrating NNI-/CNDC-based diagnosis, root-zone monitoring, enhanced-efficiency fertilizers, and soil-process evidence can improve synchronization between N supply and potato demand, supporting yield formation, N-use efficiency, and reduced environmental risk. Full article

With the high penetration of distributed photovoltaic and storage systems, active distribution grids are prone to experiencing “active power surplus and reactive power shortage” during the evening peak, leading to voltage sags at the network end. Although electric vehicle (EV) grid-connected inverters possess four-quadrant reactive power regulation capabilities without causing the additional chemical cyclic aging of the battery cells, existing dispatch systems often treat them as unconditional response resources, overlooking users’ actual willingness to cede control and the associated strategic interactions. To address this, this paper proposes a “grid-load” coordinated reactive power optimization strategy that accounts for EV users’ willingness to respond: a Logit model incorporating price incentives, initial energy consumption, and parking duration is constructed based on discrete choice theory. By combining a truncated normal distribution with the Monte Carlo method to eliminate micro-sampling errors, a model of the expected reactive power capacity of charging stations under dynamic incentives is established; considering the physical constraints of SVCs and EVs, a scalarized single-objective optimization model is constructed with grid loss-equivalent costs, ancillary service costs, and voltage deviation as objectives, and solved using an improved particle swarm optimization algorithm with linearly decreasing weights. Simulations on a modified 33-node IEEE system incorporating storage indicate that this strategy can assign optimal compensation prices to each node based on the spatial value of reactive power. Compared to traditional single-voltage regulation and fixed subsidies, it not only stabilizes the grid-wide voltage within a safe range but also avoids overcompensation, achieving global optimization of both power quality and economic efficiency. Full article

The growth of the global population has led to increased demand for agricultural products, resulting in greater agricultural waste production. One sustainable response to this challenge is using agricultural waste as raw material in building materials. This study examines the potential for partial replacement of natural aggregates in concrete with agricultural waste from typical Mediterranean fruits: sour cherry pits, grape seeds, ground olive pits, and carob seeds. To evaluate the effect of treatment on the behavior of agro-waste aggregates, ground olive pits were used untreated, treated with ash water, or treated with seawater. Carob seed concrete deteriorated during water curing due to seed swelling and tannin-related degradation, revealing its unsuitability without prior stabilization. Partial replacement of natural aggregates with agricultural waste resulted in decreased density, ultrasonic pulse velocity (UPV), dynamic elastic modulus, compressive strength, and thermal conductivity, while increasing saturated water absorption. Treatment with ash water on ground olive pits improved the interfacial transition zone (ITZ), resulting in 29% increase in compressive strength relative to untreated ground olive pits. Concrete with ash water treated ground olive pits demonstrated the highest practical potential among all tested agro-waste concretes. Full article

Cellulose nanocrystals (CNCs) are abundant, renewable, biodegradable, non-toxic, and cost-effective nanomaterials with exceptional properties, making them highly appealing for nanocomposite material fabrication. Recognized for their sustainability, CNCs are emerging as promising substrates for the fabrication of functional, stimuli-responsive nanomaterials. This review highlights nanocomposites comprising magnetic nanoparticles with various forms of cellulose-based materials, with a primary focus on magnetic cellulose nanocrystal (MCNC) composites, yielding materials capable of controlled, on-demand responses to external magnetic fields. The magnetic properties of these nanocomposites can be precisely tuned by adjusting the magnetic nanoparticle content on CNC surfaces. At the nanoscale, magnetic CNCs exhibit remarkable properties, including facile and rapid magnetic separation, which holds great potential for numerous applications. This review examines the latest synthesis and modification methods for CNCs functionalized with various magnetic nanoparticles, as well as their applications in the biological, packaging, environmental, and biomedical fields. Full article

Sports-related injuries involving muscle, tendon, cartilage, ligament, and bone remain challenging because of their heterogeneous mechanisms, high functional demands, and need for timely diagnosis, targeted repair, and rehabilitation monitoring. Musculoskeletal ultrasound (MSKUS) provides real-time, portable, radiation-free, and repeatable evaluation of injured tissues, including lesion location, structural continuity, vascular response, stiffness changes, and healing progression. Protein-based hydrogels, owing to their biocompatibility, tunable mechanics, extracellular matrix-like microenvironments, and capacity for localized bioactive delivery, offer promising platforms for tissue repair and functional recovery. This review summarizes major sports injuries, discusses the diagnostic and monitoring value of MSKUS, and analyzes protein-based hydrogels according to tissue-specific repair requirements. Particular attention is given to the connection between imaging assessment and hydrogel therapy, including ultrasound-guided delivery, lesion localization, post-treatment monitoring of hydrogel retention or degradation, and evaluation of therapeutic response. By linking MSKUS-based lesion assessment with hydrogel selection, image-guided delivery, post-intervention monitoring, and rehabilitation-oriented decision-making, this review outlines a coordinated framework for precise diagnosis and localized biomaterial-assisted repair in sports injury management. Full article

The deployment of Deep Learning (DL) for anomaly detection in Industrial IoT (IIoT) is critically hampered by the non-stationary nature of industrial data streams and the lack of forensic-grade explainability. This systematic review synthesizes 48 peer-reviewed studies (2021–2025) to quantify the performance collapse of static models under concept drift and to establish operational criteria distinguishing post hoc feature attribution (Type A XAI) from forensic root-cause diagnosis (Type B XAI). Our analysis reveals three critical findings: (1) static DL models suffer a 15–22% F1-score degradation across wastewater, manufacturing, and energy sectors when deployed in non-stationary environments, rendering them operationally non-viable without continuous adaptation; (2) the current literature remains saturated with Type A explainability (80% of corpus through 2023), creating a Forensic Gap where operators receive statistical correlations but lack actionable maintenance directives; and (3) emerging 2024–2025 research marks a paradigm shift toward Type B methodologies, yet no unified framework bridges real-time detection with deep causal reasoning. To address these gaps, we contribute the following: (1) a validated operational taxonomy (Cohen’s $\kappa =0.84$) with reproducible five-criterion rubric enabling forensic XAI classification; (2) the first quantitative synthesis of drift penalties in industrial deployments; and (3) a three-tier Edge-Cloud Forensic XAI architecture that achieves 70% communication payload reduction via compressed latent vectors while integrating tnGAN-based data imputation (handling 20–30% missing data) and physics-guided causal reasoning engines. Our framework decouples millisecond-level edge detection from 1–3 s cloud-based forensic diagnosis, ensuring both operational responsiveness and actionable industrial insight. We conclude that the future of safety-critical IIoT demands “Forensic-by-Design” architectures leveraging machine unlearning for drift adaptation and LLM-based natural language interfaces for operator-facing explanations, positioning Industry 5.0 to bridge the gap between algorithmic detection and human-centered decision support. Full article

Background/Objectives: Inborn errors of immunity (IEI) are rare and complex pediatric disorders that create significant information gaps for families and non-specialist healthcare professionals. Large language models (LLMs) such as ChatGPT are increasingly used as on-demand health information resources; however, evidence on their performance in rare pediatric diseases remains limited. This study aimed to evaluate the reliability, quality, readability, understandability, reproducibility, and safety-related concerns of ChatGPT-4o responses to frequently searched questions about pediatric IEI posed by healthcare professionals and patients/caregivers. Methods: This cross-sectional evaluation used the publicly accessible ChatGPT-4o interface to generate responses to 20 frequently searched questions about pediatric IEI, equally distributed between healthcare professional (n = 10) and patient/caregiver queries (n = 10). Three pediatric allergy-immunology specialists independently evaluated response quality using the modified DISCERN (mDISCERN) and Global Quality Scale (GQS) tools, supplemented by a structured expert-based assessment of misinformation, safety-related concerns, suspected factual issues, missing disclaimers, and clinically meaningful inter-iteration inconsistency. Text readability was assessed using four validated indices (ARI, FRES, FKGL, GFR), comprehensibility using the Patient Education Materials Assessment Tool (PEMAT), and reproducibility using natural language processing methods. Results: ChatGPT-4o demonstrated strong overall performance, with median mDISCERN and GQS scores of 4 (IQR: 3–5) for both query types. Readability scores substantially exceeded recommended thresholds, with FKGL scores of 12.96 ± 0.69 and 10.83 ± 0.67 for professional and patient/caregiver queries, respectively. Mean PEMAT understandability scores were 71.80 ± 5.75% for professional queries and 80.80 ± 4.73% for patient/caregiver queries (p = 0.001). Reproducibility was high, with semantic similarity rates of 86.10 ± 3.84% and 87.30 ± 3.68%, respectively. Suspected factual issues were identified in 4 of 20 responses (20%), safety-related concerns in 3 (15%), clinically meaningful inter-iteration inconsistencies in 3 (15%), and missing medical disclaimers in all 20 responses (100%). Conclusions: ChatGPT-4o showed strong performance across validated quality metrics for pediatric IEI information support; however, its high reading level, universal absence of medical disclaimers, and occasional clinically meaningful inconsistencies limit its suitability as a standalone source for clinically sensitive guidance. These findings underscore the need for AI-driven patient education tools with improved readability, adaptive complexity adjustment, and safety-oriented communication. Full article

The goal of this Special Issue was to collect the latest research results on the topics of (1) the physiological response of fish to various stressful situations and nutritional changes, (2) the replacement of fish meal and fish oil with sustainable, alternative protein and lipid sources in fish feeds, and (3) supplementing fish feeds with various additives in order to enhance the immune response and increase the stress and disease resistance of fish reared in intensive systems. These topics are very important for the development of a more effective and sustainable intensive aquaculture, as fish farming systems are becoming more intensive and industrialized, which results in a more stressful environment for farmed fish. Another important challenge is providing enough high-quality fish feed to fulfill the increasing demand of intensive aquaculture. There are 14 original research articles published in this Special Issue. The authors come from a wide array of countries, and they worked with a wide variety of freshwater and marine fish species, which are important for intensive aquaculture. These articles represent only a modest contribution to the overall literature of stress and nutritional physiology of farmed fish. However, each of these papers contain interesting new information regarding the solution of the two major problems of intensifying aquaculture: environmental stresses and nutrition management. Full article

Potentiostats are essential to electrochemical sensing, enabling precise control of electrode potentials and measurement of current responses. As demand grows for portable, wearable, and point-of-care systems, potentiostat design has evolved from benchtop instruments to compact, low-power, and wirelessly connected platforms. This review provides a comprehensive, system-level perspective on modern potentiostat architectures, covering operational principles, analog front-end design, signal generation and acquisition, communication protocols, and software integration. Unlike prior reviews that treat these aspects independently, this work integrates electrochemical theory with electronic design and data communication frameworks. Key components, including operational amplifiers, transimpedance amplifiers, DAC/ADC subsystems, and microcontroller-based control, are examined alongside communication protocols such as SPI, I²C, Bluetooth Low Energy, Wi-Fi, and NFC. Critical challenges related to miniaturization, noise, power constraints, and reproducibility are analyzed using representative platforms. This review highlights the transition of potentiostats into integrated, intelligent, and connected sensing systems, and outlines design considerations for scalable electrochemical applications in clinical, environmental, and industrial domains. Full article

Landslides cause significant casualties and economic losses worldwide each year, creating an urgent demand for rapid and reliable volume estimation during emergency response. Conventional approaches often involve trade-offs among accuracy, efficiency, and data availability, particularly when pre-event topographic data are unavailable. This study proposes a novel GIS-based method for rapid landslide volume estimation through sliding surface reconstruction. By integrating open-source geospatial data (post-landslide Digital Elevation Model and landslide boundary KML) with spline interpolation and spatial analysis, the method reconstructs the subsurface sliding surface and calculates volume by comparing this surface with the post-landslide DEM. Applied to the 2019 Shuicheng landslide (Guizhou Province, China), the method yielded a volume estimate of 1.58 × 10⁶ m³, which deviates by only ~5% from official survey data. The entire workflow can be completed within approximately one hour, demonstrating high efficiency, low operational cost, and acceptable accuracy for rapid post-disaster assessment during the critical “golden 72 h”. Full article

Background/Objectives: Soccer involves high physiological demands that induce neuromuscular fatigue, muscle damage, inflammation, and oxidative stress, impairing recovery between training sessions and competitions. Polyphenols have been proposed as a nutritional strategy to modulate these responses; however, evidence in soccer players is limited and heterogeneous. This systematic review aimed to synthesize the evidence on the effects of polyphenol supplementation on post-exercise recovery in adult male soccer players. Methods: A systematic review was conducted following PRISMA guidelines, with a protocol registered in the Open Science Framework. Randomized controlled trials (RCTs) evaluating polyphenol supplementation versus placebo on post-exercise recovery in adult soccer players were included. Searches were performed in PubMed, Scopus, Web of Science, and the Cochrane Library up to April 2026. Risk of bias was assessed using RoB 2, and certainty of evidence using GRADE. Due to heterogeneity, a qualitative synthesis was conducted. Results: Eight RCTs were included. Interventions involved tart cherry juice, pomegranate juice, beetroot juice, curcumin, and tea extracts. Evidence was inconsistent for biomarkers of muscle damage, inflammation, and oxidative stress, with most studies reporting no significant differences versus placebo. In contrast, beneficial trends for perceptual outcomes, particularly reduced muscle soreness and improved subjective well-being, were mainly observed in studies using tart cherry juice, beetroot juice, and curcumin. Evidence for oxidative stress and functional recovery was limited and heterogeneous. Certainty of evidence was low for most outcomes and very low for oxidative stress and functional recovery. Conclusions: Polyphenol supplementation, particularly tart cherry juice, beetroot juice, and curcumin, may improve perceptual recovery in adult male soccer players, particularly by reducing muscle soreness and enhancing subjective well-being. However, evidence on physiological biomarkers and functional recovery remains inconsistent and of low certainty. Further well-designed RCTs are required to establish robust recommendations in competitive soccer. Full article

Wind energy is one of the clean and sustainable energy sources that can be used to meet global energy demand. However, although wind turbines are used to harness energy in coastal and offshore areas, the extreme environmental conditions make it difficult to utilize these structures optimally and also negatively impact their safety. Therefore, in this study, the yaw angles of the National Renewable Energy Laboratory (NREL) 5 MW wind turbine mounted on a monopile platform were controlled using a Long Short-Term Memory (LSTM) artificial intelligence (AI) architecture to optimize power output and ensure structural stability against dynamic responses under irregular wave and Izmir–Samos tsunami conditions. First, the İzmir–Samos tsunami, the NREL 5 MW wind turbine mounted on a monopile platform, the analytical methods employed, the LSTM architecture, and the parameters used in the study were described. The results of the wind direction time series prediction and the aerodynamic, hydrodynamic, and structural responses of the LSTM-based yaw angle control strategy on the wind turbines were investigated and discussed. According to the results, the increase in aerodynamic power achieved using the LSTM-based strategy was approximately $5.18\%$ under a scenario with constant wind speed and variable wind direction in two different sea conditions and $5.29\%$ under conditions of irregular waves with fully variable wind speed and direction. In addition, more stable responses were observed for most of the parameters examined. The primary goal of this study is to serve as a reference for researchers working on AI-optimized power output and response analysis resulting from varying the yaw angles of wind turbines. Full article

Rising global demand for safe, high-quality foods has accelerated the development of rapid, sensitive, and cost-effective analytical technologies for detecting harmful substances and quality markers. Electrochemical sensors have emerged as promising tools for food safety monitoring due to their high sensitivity, fast response, portability, and affordability compared with conventional laboratory methods. This review highlights recent advances in nanostructured electrochemical sensors for detecting key food analytes, including antioxidants, mycotoxins, allergens, and flavor compounds in diverse food matrices. It examines advanced nanomaterials such as metal oxides, MXenes, doped carbon nitrides, and noble metal-decorated graphene, which enhance sensor performance through improved surface area, conductivity, and electrocatalytic activity. Integrated with screen-printed or glassy carbon electrodes, these materials achieve ultra-low detection limits, wide linear ranges, and strong selectivity in complex food systems. The review also explores next-generation applications such as NFC-enabled smart packaging for continuous, non-invasive monitoring across the supply chain. Emerging trends in miniaturization, multiplex sensing, and artificial intelligence are discussed, along with key challenges in translating laboratory innovations into practical commercial solutions for global food safety. Full article

The global demand for sustainable protein sources has led to increased interest in macroalgae, particularly red seaweed, due to their rich nutritional content and bioactive compounds, which translates into a wide range of biotechnological applications. This study compares the biochemical profiles, specifically pigments and proteins, as well as antioxidant activity, of four red seaweed species, namely Nitophyllum punctatum, Chondria coerulescens, Plocamium cartilagineum and Sphaerococcus coronopifolius. The aim was to compare wild and cultivated biomasses to identify optimal cultivation strategies for maximizing their value. The results show that culture conditions have a significant impact on pigment and protein content, as well as antioxidant potential, for all species. While all cultured species showed increased protein content, specific responses in pigment production and antioxidant activity were clearly species-dependent. These results highlight the specific culture conditions required to produce pigments or antioxidant activities on a species-by-species basis. As these four red seaweed species remain relatively underexplored, further targeted research is required to refine cultivation methods and enhance our understanding of their biotechnological value. Full article

Starches from various botanical sources are extensively utilized across food applications due to their functional and technological properties. However, native starches exhibit limitations under processing conditions involving heat, pH shifts, or mechanical stress, which restrict their application. In response, the demand for “clean-label” products has driven interest in sustainable and non-chemical modification strategies. This review aims to provide a critical overview of the effects of unconventional technologies—including ozone, ultrasound, high-pressure processing, high-pressure homogenization, pulsed electric fields, and cold plasma—on starch granule structure and the resulting pasting properties. A bibliometric analysis based on 1679 documents from Scopus and Web of Science^® highlighted a lack of previous studies integrating quantitative trends with in-depth technical discussion. The selected technologies demonstrate potential to enhance starch functionality through distinct modification mechanisms, although their effects are highly dependent on starch source, structure, and processing parameters. Despite promising advances, most applications remain restricted to laboratory scale, and further research is required to optimize conditions and promote industrial feasibility. Full article