Search Results (36,873)

Polymers and their composites have introduced significant advancements in engineering and technology. The primary advantages of polymeric materials include their lightweight nature, ease of manufacturing, anti-corrosion properties, reduced power consumption during assembly and integration, as well as enhanced stiffness, durability, and fatigue resistance. Polymer coatings with conductive polymers allow efficient charge transfer and make electrodes more flexible, helping them better match the mechanical properties of soft tissues. In addition, polymer coatings can protect electrodes from corrosion, reduce biofouling, and provide sites for attaching biomolecules, making them essential for reliable and long-term bioelectrode and biosensor performance. Polymer coatings for electrochemical bioelectrodes play a crucial role in enhancing sensor performance and stability in biological environments as they improve the interaction between electronic devices and biological tissues. These coatings enhance biocompatibility by reducing inflammation and tissue damage while also lowering electrode impedance to improve signal quality. The present review focuses on the most recent developments in polymer coatings for electrochemical biosensors and respective applications. The manuscript provides an overview of polymer materials, emerging strategies, coating approaches, and the resulting enhancements in bioelectrochemical applications. Full article

This study aimed to explore the effect of doubled CO₂ concentration (d[CO₂]) on the modulation of root morphological structure, leaf potassium (K)/sodium (Na) ratio, and nutrient stoichiometry, as well as water use efficiency (WUE) of a C₄ maize (Zea mays L.) in response to soil drought and salinity. C₄ maize was grown in two atmospheric CO₂ concentrations of 400 and 800 ppm (a[CO₂] and d[CO₂]), subjected to two soil water regimes (well-watered and drought stress) and two soil salinity levels (0 and 100 mM NaCl pot⁻¹ (non-salt and salt stress)). The results indicated that soil drought increased maize root tissue density and specific root length. Both d[CO₂] and salt stress reduced leaf phosphorus (P) and K concentrations; conversely, drought stress enhanced leaf nitrogen (N) and K concentrations. The lower specific leaf area, but greater specific leaf N and N/K under soil drought, was amplified by salt stress. In contrast, d[CO₂] promoted leaf carbon (C)/N and C/K. Notably, d[CO₂] combined with soil drought enhanced leaf K/Na under salt stress. Moreover, d[CO₂] ameliorated the adverse impacts of soil drought and salinity on root morphology in terms of enlarged root length and root surface area, contributing to superior leaf C, N, and K use efficiency and consequently improved C₄ maize plant dry mass and WUE. These findings would provide essential knowledge to elevate salt tolerance and achieve optimal nutrient homeostasis and WUE in C₄ maize, adapting to future drier and more saline soils under a CO₂-enriched scenario. Full article

This protocol details an optimized step-by-step procedure for performing the Seahorse XF Cell Mito Stress Test on human umbilical vein endothelial cells (HUVECs) using the Agilent Seahorse XF Pro Analyzer. Designed to address practical challenges often overlooked in standard manuals, the method preserves the native adherent state of HUVECs—a key in vitro model in vascular aging (VA) research—enabling real-time, label-free measurement of mitochondrial respiration and glycolytic function without cell detachment. The workflow is presented chronologically, covering instrument preparation, cell seeding, compound loading, assay execution, and post-assay normalization, with integrated notes and troubleshooting tips refined through hands-on experience based on the official manuals. This protocol aims to set up a detailed, rearranged standard workflow to improve experimental efficiency, reduce operator error, and support reproducible and well-organized metabolic profiling of HUVECs in aging and cardiovascular studies. Full article

This paper proposes an efficient and automated smart healthcare communication framework that integrates a two-level filtering scheme with a multi-objective Genetic Algorithm (GA) to enhance the reliability, timeliness, and energy efficiency of Internet of Medical Things (IoMT) systems. In the first stage, physiological signals collected from heterogeneous sensors (e.g., blood pressure, glucose level, ECG, patient movement, and ambient temperature) were pre-processed using an adaptive least-mean-square (LMS) filter to suppress noise and motion artifacts, thereby improving signal quality prior to analysis. In the second stage, a GA-based optimization engine selects optimal routing paths and transmission parameters by jointly considering end-to-end delay, Signal-to-Noise Ratio (SNR), energy consumption, and packet loss ratio (PLR). The two-level filtering strategy, i.e., LMS, ensures that only denoised and high-priority records are forwarded for more processing, enabling timely delivery for supporting the downstream clinical network by optimizing the communication. The proposed mechanism is evaluated via extensive simulations involving 30–100 devices and multiple generations and is benchmarked against two existing smart healthcare schemes. The results demonstrate that the integrated GA and filtering approach significantly reduces end-to-end delay by 10%, as well as communication latency and energy consumption, while improving the packet delivery ratio by approximately 15%, as well as throughput, SNR, and overall Quality of Service (QoS) by up to 98%. These findings indicate that the proposed framework provides a scalable and intelligent communication backbone for early disease detection, continuous monitoring, and timely intervention in smart healthcare environments. Full article

High-quality, well-structured trip chain data are essential for analyzing the daily activity patterns, travel behaviors, and logistical decisions of commercial vehicles, as well as for supporting sustainability-oriented freight management and low-carbon urban logistics. This study introduces a novel methodology for analyzing truck travel patterns using extensive GPS data, focusing on identifying freight trip chains and enhancing urban freight systems. A road-constrained clustering approach was developed to accurately identify vehicle stops and truck stop locations, addressing limitations in previous studies that struggled with misclassification. A trip chain reconstruction methodology was formulated, key characteristics were extracted and clustering techniques were applied to categorize trucks based on their travel behavior. A case study in Chongqing demonstrates that the proposed method outperforms traditional clustering algorithms, reducing misclassification rates in stop location identification. The findings reveal consistent trip chain patterns and distinct travel behaviors within truck groups. This research presents a data-driven framework that provides a foundation for optimizing logistics, fleet management, and low-carbon freight system planning. By enhancing the accuracy of trip chain analysis, this methodology contributes to the design of energy-efficient and sustainable urban freight systems, helping reduce emissions and foster eco-friendly logistics solutions. Full article

Drought poses a major challenge for global agriculture, demanding strategies that improve crop resilience while safeguarding water and nutrient resources. Plant growth-promoting rhizobacteria (PGPR)-based biostimulants offer a sustainable approach to enhance resource-use efficiency under water-limited conditions. This study evaluated two commercial PGPR biostimulants applied to maize (Zea mays L.) and tomato (Solanum lycopersicum L.) seedlings grown under well-watered (80% field capacity) and water-stressed (40% field capacity) conditions. Both products improved plant growth and physiological performance, although responses were crop-specific. Inoculated tomato seedlings accumulated up to 35% more shoot biomass under optimal watering (1.6 g in non-inoculated seedlings compared with 2.5 g in inoculated seedlings), whereas maize maintained biomass production under drought, consistent with its higher intrinsic water-use efficiency, showing increases of approximately 50% (well-watered: 0.5 g versus 0.8 g; water-stressed: 0.3 g versus 0.7 g in non-inoculated and inoculated seedlings, respectively). Biostimulant application enhanced the acquisition and internal utilization of essential mineral resources, increasing leaf concentrations of (i) the macronutrients P (up to 300%), K (up to 70%), Mg (up to 220%), and Ca (up to 85%), and (ii) the micronutrients B (up to 400%), Fe (up to 260%), Mn (up to 240%), and Zn (up to 180%). Maximum nutrient increases were consistently observed in water-stressed maize seedlings inoculated with biostimulant 2. Antioxidant activities, particularly ascorbate peroxidase and catalase, increased by 20–40%, indicating more effective mitigation of oxidative stress. Principal component analysis revealed coordinated adjustments among growth, nutrient-use efficiency, and physiological traits in inoculated plants. Overall, PGPR-based biostimulants improved early drought tolerance and resource-use efficiency, supporting their potential as sustainable tools for climate-resilient agriculture. Field-scale studies remain necessary to confirm long-term agronomic benefits. Full article

Residues generated during fruit processing constitute an abundant and underutilized biomass rich in bioactive compounds, pigments, structural polysaccharides, lipids, and fermentable carbohydrates. Although their potential for biorefinery applications is widely recognized, existing studies are often fragmented, focusing on isolated products, which limits a comprehensive understanding of integrated valorization strategies. To address this gap, this study presents an integrative review supported by bibliometric analysis to identify global research trends, dominant technological pathways, and key challenges associated with the use of fruit residues in biorefineries. The review covers technologies for extracting phenolic compounds, essential oils, pigments, and structural fibers, as well as lipid recovery, enzyme production, and biochemical routes for bioethanol, biohydrogen, and biogas generation. The review reveals that emerging technologies, such as pressurized fluid extraction, microwave-assisted extraction, and ultrasound-assisted extraction, enable efficient recovery of antioxidant compounds, high-purity pectin, and fermentable sugars, particularly when applied in sequential and integrated processing schemes. Bioethanol production is the most extensively investigated route, with yields strongly dependent on biomass composition and pretreatment strategies, identifying banana, cashew, apple, mango, coconut, and palm residues as promising feedstocks. In addition, biohydrogen production via dark fermentation and anaerobic digestion for biogas generation shows high technical feasibility, especially when integrated with upstream extraction steps. Overall, integrated valorization of fruit residues emerges as a key strategy to enhance economic performance and environmental sustainability in agro-industrial systems. Full article

Gaming Disorder (GD) is becoming more widely acknowledged as a behavioral addiction characterized by impaired control and functional impairment. While resting-state impairments are well understood, the neurophysiological dynamics during active gameplay remain underexplored. This study identified task-based occipital EEG biomarkers of GD and assessed their diagnostic utility. Occipital EEG (O1/O2) data from 30 participants (15 with GD, 15 controls) collected during active mobile gaming were used in this study. Spectral, temporal, and nonlinear complexity features were extracted. Feature relevance was ranked using Random Forest, and classification performance was evaluated using Leave-One-Subject-Out (LOSO) cross-validation to ensure subject-independent generalization across five models (Random Forest, KNN, SVM, Decision Tree, ANN). The GD group exhibited paradoxical “spectral slowing” during gameplay, characterized by increased Delta/Theta power and decreased Beta activity relative to controls. Beta variability was identified as a key biomarker, reflecting altered attentional stability, while elevated Alpha power suggested potential neural habituation or sensory gating. The Decision Tree classifier emerged as the most robust model, achieving a classification accuracy of 80.0%. Results suggest distinct neurophysiological patterns in GD, where increased low-frequency power may reflect automatized processing or “Neural Efficiency” despite active task engagement. These findings highlight the potential of occipital biomarkers as accessible and objective screening metrics for Gaming Disorder. Full article

To address the technical bottlenecks commonly encountered with real-time quantitative PCR instruments, such as insufficient ramp rates and uneven chamber temperature distribution, this study proposes an innovative design scheme for a temperature control system that incorporates key hot air circulation and temperature field regulation technologies. By combining the PCR instruments’ working principles and structural characteristics, the failure mechanisms associated with the temperature control system are systematically analyzed, and a reliability-oriented thermodynamic analysis model is constructed to clarify the functional positioning of core components and to systematically test the airflow uniformity, temperature dynamics, and nucleic acid amplification efficiency. An integrated fixture for airflow rectifier and cruciform frames is designed, which enables precise quantitative characterization of the system temperature uniformity, ramp rates, and amplification efficiency on a multi-condition comparison platform. Through modeling analysis combined with experimental validation, the thermal performance differences among various heating chamber structures are compared, leading to a multidimensional optimization of the temperature control system. The test results demonstrate outstanding core performance metrics for the optimized system: the up ramp reaches 7.5 ± 0.1 °C/s, the down ramp reaches 13.5 ± 0.1 °C/s, and the steady-state temperature deviation is only ±0.1 °C. The total duration for 35 PCR cycles is recorded at 16.3 ± 0.6 min, with a nucleic acid amplification efficiency of 98.9 ± 0.2%. The core performance metrics comprehensively surpass those of mainstream global counterparts. The developed temperature control system is well-suited for practical applications such as rapid detection, providing critical technological support for the iterative upgrade of nucleic acid amplification techniques while laying a solid foundation for the engineering development of high-performance PCR instruments. Full article

The high organizational complexity of the Global Coffee Supply Chain (GCSC) poses significant challenges in terms of governance and sustainability, such as asymmetric access to information, deforestation, loss of biodiversity, and overproduction, as well as high price volatility and social issues such as workers’ rights and the unequal distribution of value along the supply chain. In this context, therefore, the coffee sector could benefit from the adoption of advanced traceability systems such as blockchain, whose implications in the GCSC remain poorly systematized in the literature. Therefore, this research presented a systematic literature review on the application of BC in the GCSC to analyze its efficiency, traceability, and sustainability implications, as well as identifying the main factors that hinder its full implementation. The review included 42 peer-reviewed studies indexed in Scopus, and the results showed that, in terms of efficiency, BC adoption can help improve coordination and reduce information asymmetries along the supply chain, but only in specific contexts, as they depend largely on organizational and infrastructural conditions, rather than on the technical characteristics of the technology. With regard to sustainability, the results sometimes appear contradictory, reflecting profound differences in context. The review highlighted that the main obstacles to the effective adoption of BC in the GCSC stem from a combination of constraints, including centralized governance structures, power asymmetries in data management, infrastructure deficiencies in production contexts, and digital exclusion dynamics. Overall, the study highlighted that BC in the coffee sector cannot be considered a stand-alone solution but should be interpreted as a socio-technical infrastructure whose effectiveness depends on many interconnected factors. Full article

Inorganic arsenic species, As(V) and As(III), present significant toxicity and carcinogenic risks in water, making their effective removal critical for global water safety. This study introduces Fe-Ti-Mn/chitosan composite xerogel beads (FTMO/chitosan) designed to overcome the limitations of conventional single-component adsorbents, particularly for simultaneous removal of As(V) and As(III), and to address solid–liquid separation challenges common with powdered adsorbents. The xerogel beads feature a rough, porous surface composed of agglomerated nanoparticles. Batch tests demonstrated that the Freundlich model provided a better fit for the adsorption process, with max uptake capacities of 22.6 mg/g and 16.2 mg/g for As(III) and As(V) at 25 °C, respectively, outperforming most reported adsorbents. Adsorption kinetics were fast, reaching equilibrium within 24 h and fitting well with a pseudo-second-order kinetic model. The adsorption efficiency was strongly influenced by solution pH and the existence of minor coexisting anions. Mechanistically, As(V) removal occurred via inner-sphere surface complexation through the substitution of surface hydroxyl groups, whereas As(III) removal involved a coupled oxidation-adsorption process: MnO₂ oxidized As(III) to As(V), which was then adsorbed onto the material surface. Furthermore, the adsorbent confirmed excellent regeneration capacity and operational stability, illuminating its promising potential for frequent utilization in water treatment and environmental remediation applications. Full article

Staged multi-cluster fracturing in horizontal wells is a key technology for efficiently developing unconventional oil and gas reservoirs. Extreme Limited-Entry Fracturing (ELF) and Temporary Plugging Fracturing (TPF) are effective techniques to enhance the uniformity of fracture stimulation within a stage. However, in fractured reservoirs, the propagation morphology of multiple intra-stage fractures and fluid distribution patterns becomes significantly more complex under the influence of ELF and TPF. This complexity results in a lack of theoretical guidance for optimizing field operational parameters. This study establishes a competitive propagation model for multiple hydraulic fractures (HFs) within a stage under ELF and TPF conditions in fractured reservoirs based on the Displacement Discontinuity Method (DDM) and fluid mechanics theory. The accuracy of the model was verified by comparing it with laboratory experimental results and existing numerical simulation results. Using this model, the influence of ELF and TPF on intra-stage fracture propagation morphology and fluid partitioning was investigated. Results demonstrate that extremely limited-entry perforation and ball-sealer diversion effectively mitigate the additional flow resistance induced by both the stress shadow effect and the connection of natural fractures (NFs), thereby mitigating uneven fluid distribution and imbalanced fracture propagation among clusters. ELF artificially creates extremely high perforation friction by drastically reducing the number of perforations or the perforation diameter, thereby forcing the fracturing fluid to enter multiple perforation clusters relatively uniformly. Compared to the unlimited-entry scheme (16 perforations/cluster), the limited-entry scheme (5 perforations/cluster) yielded a 37.84% improvement in fluid distribution uniformity and reduced the coefficient of variation (CV) for fracture length and fluid intake by 54.28% and 44.16%, respectively. The essence of the TPF is non-uniform perforation distribution, which enables the perforation clusters with large fluid intake to obtain more temporary plugging balls (TPBs), so that their perforation friction can be increased and their fluid intake can be reduced, thereby diverting the fluid to the perforation clusters with small fluid intake. Deploying TPBs (50% of total perforations) at the mid-stage of fracturing (50% time) increased fluid distribution uniformity by 37.86% and reduced the CV of fracture length and fluid intake by 72.54% and 58.39%, respectively. This study provides methodological and modeling foundations for systematic optimization of balanced stimulation parameters in fractured reservoirs. Full article

The relevance of this study is determined by the need for new technological solutions to enhance the productivity of wells producing heavy and highly viscous crude oil. The work investigates multicomponent Al–Ga–In–Sn alloys as reactive systems capable of generating heat and hydrogen upon contact with water. The focus is placed on optimizing melting parameters and assessing how alloy composition and structural features affect reactivity. Phase composition was analyzed by X-ray diffraction, microstructure by SEM-EDX, and elemental composition by XRF. The results show that the hydrogen generation rate and heat release depend on melting temperature, holding time, and ratios of activating metals, as well as the physicochemical properties of the formation water, particularly salinity and pH. Reaction enthalpy and conversion efficiency were quantified. The highest hydrogen output and thermal effect were observed for the following compositions—90 wt.% Al, 5 wt.% Ga, 2.5 wt.% In, 2.5 wt.% Sn; and 85 wt.% Al, 5 wt.% Ga, 5 wt.% In, 5 wt.% Sn (825 °C, 30 min). Rapid heat and gas release is attributed to the eutectic structure and micro-galvanic interaction, which eliminate the induction period. These findings demonstrate the potential of such alloys for in situ heating, enhanced oil recovery, and autonomous hydrogen-energy applications. Full article

The accumulation of municipal sewage sludge is a worldwide problem, although when properly treated, it can be utilized for various purposes in industry and agriculture. Due to its high nutrient content, one of its possible uses is the application as fertilizer on agricultural or degraded lands with the purpose of non-food plant production. In the present study, the sustainability of dehydrated sewage sludge application was tested in Szarvasi-1 energy grass (Thinopyrum obtusiflorum cv. Szarvasi-1) plantations, with special focus on the turnover of nutrients and trace elements in two experiments conducted outdoors between 2016 and 2019. Experiment 1 was conducted in 1 m³ containers, and the treatment was started on two-year old plants in 0, 15, 22.5, and 30 Mg ha⁻¹ doses per year applied in two or three portions to reveal the upper limit of sludge application. Experiment 2 was conducted in 100 m² field quadrates with 0, 7.5, 15, and 22.5 Mg ha⁻¹ doses per year applied once a year, which is in the range of the currently permitted application dose in Hungary. Soil, sludge, and plant samples, as well as physiological data, were collected. Aboveground biomass yield was measured 2–3 times per year. Increasing doses of sewage sludge significantly increased the yield compared to the controls, but the increment between the second and third doses was small. Chlorophyll content (SPAD values) increased tendentiously and partly significantly. The maximal quantum efficiency of PSII and the stomatal conductance was not improved compared to the control, whereas the relative water content of the plants was increased in Experiment 1 but not in Experiment 2 compared to the control. Malondialdehyde concentration was increased by the largest dose in Experiment 1. The concentration of macroelements, Ca, Mg, N, and S, increased in the aboveground biomass with increasing doses of sewage sludge, but even after three years, the cumulative amount removed with the harvested biomass was much smaller than the amount remaining in the soil. The total amount of K in the harvested biomass exceeded that introduced to the soil by the treatments. Micro- and trace-element concentrations did not show increasing tendency in the biomass, suggesting a slower uptake and removal rate than macroelements. The results point to the necessity to assess the real nutrient requirement and trace-element uptake by the plants as compared to the sewage sludge treatment to avoid their uncontrolled accumulation in the soil and ensure a sustainable fertilization of the plantations. Full article

The probability integral method is the primary technique for predicting mining-induced subsidence in China, and its predictive accuracy strongly depends on the precision of the model parameters. To improve the accuracy and stability of parameter inversion and to overcome the convergence randomness of the Genetic Algorithm (GA) in global search, as well as the tendency of the BFGS quasi-Newton method (BFGS) to converge to local optima in non-convex optimization problems, a hybrid GA–BFGS optimization algorithm is proposed for inverting the parameters of the probability integral model. This hybrid approach combines the global exploration capability of GA with the fast local refinement of BFGS, resulting in a more efficient and robust parameter optimization process. Simulation results under ideal conditions without model error demonstrate that the proposed GA–BFGS algorithm outperforms pattern search (PS), GA, and BFGS in terms of inversion accuracy, convergence stability, and robustness to noise and outliers. In engineering applications, the inversion accuracy is reduced compared with simulation experiments, which can be attributed to complex geological conditions and inherent model uncertainties. Therefore, further improvements in subsidence prediction accuracy require not only refined inversion algorithms but also the development of more accurate prediction models that explicitly account for site-specific geological and mining conditions. Full article