Search Results (1,117)

The co-contamination of aquatic environments by antibiotic residues and organic dyes poses a serious threat to ecological security and human health, underscoring the urgent need for high-efficiency, recyclable, and environmentally benign adsorbents. Chitosan, a naturally occurring alkaline polysaccharide rich in reactive functional groups, has attracted considerable attention in water treatment applications. Nevertheless, its practical use is often constrained by intrinsic limitations, including poor stability in acidic media, inadequate mechanical strength, and difficulties in solid–liquid separation. Chitosan-based hydrogels, featuring unique three-dimensional cross-linked networks, high porosity, and strong hydrophilicity, provide efficient mass-transfer pathways for macromolecular contaminants and thus offer a promising strategy to overcome the shortcomings of pristine chitosan. This review comprehensively summarizes recent advances in chitosan-based hydrogel adsorbents, with a focus on elucidating the critical structure–performance relationships that link molecular/structural design to adsorption efficacy. First, fabrication strategies are systematically reviewed, ranging from molecular-level modifications (e.g., grafting, chemical cross-linking, and interpenetrating polymer networks) to macroscopic structural engineering approaches (e.g., mechanically reinforced, magnetic, and stimuli-responsive hydrogels). Subsequently, adsorption behaviors toward representative classes of antibiotics, including tetracyclines, fluoroquinolones, and sulfonamides, are critically examined, with emphasis on the underlying mechanisms such as electrostatic interactions, hydrogen bonding, π–π stacking, and pore-filling effects. In addition, the removal performance of chitosan-based hydrogels for organic dyes with varying charge characteristics is summarized, together with an analysis of how environmental factors (e.g., pH and ionic strength) influence adsorption kinetics and thermodynamics. Finally, key challenges related to mechanical robustness, selective adsorption, and recyclability are discussed, and future perspectives are proposed for the development of multifunctional, synergistic, and intelligent, environmentally responsive chitosan-based hydrogel materials. This review aims to provide systematic insights and guidance for the rational design of advanced hydrogel adsorbents for the treatment of complex wastewater. Full article

Algal cultivation has attracted significant attention due to CO₂ biocapture and potential for biofuel generation. Enormous generation of waste polymer often poses an environmental problem due to non-biodegradability. This study comprehensively analyses the thermal degradation characteristics of blue–green alga, Leptolyngbya subtilis JUCHE1 (LS) and waste textile polyester (WTP) and their mixtures (LS1P3 (1:3); LS1P1 (1:1); LS3P1 (3:1)) during co-pyrolysis. The interaction between LS and WTP during co-pyrolysis has been assessed through the verification of synergism using different blending ratio and through the comparison of the corresponding values of the Comprehensive Pyrolysis Index (CPI). The composite, LS1P3, exhibited the highest synergism and the maximum value of CPI. Isoconversional models (FWO, Starink, Bosewell and Tang) have been used to predict the activation energies (E_a). Thermodynamic parameters, namely, heat of reaction (ΔH), Gibbs free energy change (ΔG) and entropy change (ΔS), have also been determined for all. The average value of E_a for LS1P3 is also the lowest (96.015 kJ/mol) among all composites. The Master plot method identifies that there is a shift of reaction mechanism from phase boundary type (R2 and R3) for LS and WTP to a P2-type acceleratory reaction rate mechanism for LS1P3. The lowest average value of ΔH and the highest values of ΔG and ΔS for LS1P3 co-pyrolysis also support the least consumption of energy and the highest favorability under present conditions. The product yield distribution of co-pyrolysis in the isothermally operated conditions (450 °C) also establishes the superiority of LS1P3. Yields of pyro-oil and pyro-gas are the highest among all composites. The study ensures the future application prospects of co-pyrolysis of LS and WTP as a means for generation of energy resources (pyro-oil and pyro-gas) and chemicals (pyro-char). Full article

This review examines the state-of-the-art in catalytic oxidative dehydrogenation of propane and butane to olefins under oxygen-free gas-phase conditions (FOx–PCODH and FOx–BCODH). First, it is compared with traditional methods for C₃–C₄ olefin production, using reaction enthalpies as an indicator of the process energy required. The role of catalyst oxygen species, including lattice and chemisorbed oxygen, is discussed in relation to olefin formation under oxygen-free gas-phase operation. This is followed by a review of V₂O₅-based catalysts, with particular emphasis on co-catalysts and catalyst supports. The performance of V₂O₅-based catalysts for FOx–PCODH is assessed using overall olefin formation rates. Special attention is given to catalyst performance in the mini-fluidized CREC Riser Simulator, which exhibit the highest overall olefin formation rates. These studies are also valuable to shed light into the FOx–PCODH reaction mechanism and to determine paraffin conversion, olefin selectivity, oxygen availability, and coke formation. This data can be used to determine FOx–PCODH kinetic parameters by assessing the effects of temperature, contact time, paraffin partial pressure, and catalyst-to-feedstock ratio. Finally, this review analyzes Barracuda-based numerical simulations of a large-scale downer reactor using statistically derived kinetic parameters. These simulations are employed to confirm the viability of the FOx–PCODH process at an industrial scale. Full article

Photobiomodulation (PBM) has gained increasing attention in tissue engineering and cell biology, yet reproducible in vitro studies remain limited by the availability of standardized irradiation platforms. This study presents the design, construction, and technical validation of Ce3Light, a modular LED-based irradiation system developed for controlled photobiomodulation experiments under standard cell culture conditions. The platform was fabricated using additive manufacturing (PA12) and incorporates interchangeable LED modules, integrated monitoring of illuminance and temperature, and compatibility with conventional CO₂ incubators. To demonstrate its applicability for in vitro research, the system was evaluated using MRC-5 fibroblasts exposed to four wavelengths (460, 530, 660, and 800 nm). Cellular responses were assessed by measuring intracellular glutathione levels and dehydrogenase activity. The experiments confirmed that the platform enabled stable and reproducible irradiation while detecting wavelength-dependent cellular responses consistent with previous reports in the literature. These findings primarily validate the functionality and suitability of Ce3Light as an experimental platform rather than establish new biological mechanisms. The developed system provides a versatile, reproducible, and adaptable tool for future photobiomodulation studies requiring precise control of irradiation conditions. Full article

Digital dependence and substance use may co-occur in post-digital cohorts when platform design, peer norms, stress exposure, and individual vulnerabilities converge to reinforce dysregulated patterns of reward seeking, self-regulation failure, and affective coping. This Entry defines their co-occurrence as a multidetermined phenomenon in which digital environments, including algorithmic feeds, notifications, social comparison, and variable rewards, interact with developmental vulnerabilities such as identity formation, impulsivity, reward sensitivity, and emotional dysregulation. Psychiatric comorbidities, particularly depression, anxiety, Attention-Deficit/Hyperactivity Disorder, and personality pathology, may increase susceptibility, while socioeconomic disadvantage and unequal access to care can intensify harm. Current evidence suggests that problematic digital use and substance use are more strongly related to functional impairment, coping motives, peer norms, and contextual stressors than to screen time alone. This Entry therefore organizes the available evidence around structural determinants, individual mechanisms, mental-health mediators, and prevention strategies, with emphasis on proportionate regulation, digital literacy, culturally adapted interventions, and integrated clinical pathways. Full article

Gamification increasingly influences learning experiences, cognitive engagement, and behavioral performance in digital learning, cognitive training, and health intervention contexts. However, the mechanisms underlying cognitive factors, along with related research hotspots and evolutionary trends, have not been adequately synthesized. Using the Web of Science Core Collection, this study analyzes 813 publications on gamification and cognitive factors published between 2012 and 2024. Using a bibliometric method, CiteSpace was utilized to analyze publication trends, collaborations, keyword co-occurrence, cluster structures, burst terms, cited references, and knowledge-map visualizations. The cluster analysis produced 10 interrelated themes: “flipped classroom,” “active learning,” “continuance intention,” “dementia,” “executive function,” “cognitive control training,” “computational thinking,” “cognitive training,” “cognitive load” and “user experience”. Potential future directions suggested by the bibliometric patterns include: (1) expanding gamification across educational contexts; (2) refining gamification theory models that focus on cognitive processes by examining user experience and cognitive load as potential mechanisms that link gamification design features to outcomes such as motivation, self-efficacy, task performance, and continuance intention; (3) promoting applications in cognitive training, cognitive impairment intervention, and digital health; (4) optimizing experimental design, data collection, interdisciplinary collaboration, and personalized design; and (5) clarifying how gamification shapes cognitive processes such as attention allocation, cognitive load regulation, problem solving, executive function, and computational thinking. This study does not aim to establish causal effects; rather, it uses bibliometric evidence to reveal the developmental trajectory, thematic structure, and emerging directions of research on gamification and cognitive factors. Full article

Catalytic oxidation is one of the most effective technologies for controlling atmospheric pollutants like carbon monoxide (CO), volatile organic compounds (VOCs), and diesel soot. Catalyst performance is governed by the interplay between reaction mechanisms, physicochemical properties, and catalyst architecture. This review provides a comprehensive overview of the fundamental oxidation pathways, including Langmuir–Hinshelwood, Eley–Rideal, and Mars–van Krevelen mechanisms, highlighting their relationship with oxygen mobility, oxygen vacancies, redox behavior, and metal–support interactions. The catalytic roles of noble metals and transition metal oxides are comparatively discussed, with emphasis on the contribution of lattice oxygen and defect chemistry to oxidation activity. The review also examines recent advances in structured catalysts designed to improve heat and mass transfer, catalyst accessibility, and practical reactor performance. Particular attention is given to biomorphic fibers, electrospun nanofibers, catalytic ceramic papers, conventional monoliths, and additively manufactured (3D-printed) monolithic structures as emerging platforms for environmental catalysis. Unlike previous reviews focused primarily on catalyst composition or individual oxidation reactions, this review integrates oxidation mechanisms, catalyst chemistry, and emerging structured catalyst architectures to provide a unified perspective on the design of efficient, durable, and scalable catalytic systems for environmental oxidation applications, while identifying key challenges and future research directions. Full article

The travel problem of visually impaired people is a worldwide issue that needs urgent attention. Although intelligent guide sticks provide obstacle detection and early warning through multi-sensor fusion and embedded algorithms, existing systems generally cannot model the temporal movement patterns of dynamic obstacles, such as pedestrians and vehicles, thereby hindering intention prediction and active obstacle avoidance. Long short-term memory (LSTM), with its gating mechanism, effectively captures long-term dependencies in trajectories and offers a promising solution. This review compares and analyzes LSTM against other mainstream temporal models under the resource constraints of intelligent guide sticks and finds that LSTM demonstrates a favorable combination in temporal modeling capability, lightweight maturity, and edge deployment feasibility. We categorize five lightweight techniques—architecture simplification, low-rank decomposition, structured pruning, quantization, and knowledge distillation—and examine their compression effectiveness, accuracy preservation, and hardware applicability across typical platforms. Furthermore, this review surveys application cases in speech guidance, trajectory prediction-based obstacle avoidance, positioning and navigation, edge computing, and Internet collaboration, exploring the diverse potential of LSTM in intelligent guide stick scenarios. The findings indicate that, after lightweight processing, LSTM models can meet the deployment requirements of resource-constrained edge devices, suggesting their potential feasibility on resource-constrained hardware platforms. However, existing applications still face challenges in balancing real-time performance and accuracy, meeting stringent resource constraints, and the absence of end-to-end validation on real intelligent guide stick prototypes. The reviewed evidence suggests that LSTM-based prediction represents a promising and practically valuable pathway for transitioning intelligent guide sticks from passive response to active prediction. Future research should prioritize real-world deployment validation, domain-specific data collection, and hardware-software co-design to realize its potential fully. Full article

Nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H₂S) were once regarded solely as toxic environmental gases. However, accumulating evidence over the past several decades has established them as the three principal endogenous gasotransmitters that regulate a wide spectrum of physiological and pathological processes. Unlike conventional signaling molecules, gasotransmitters diffuse freely across biological membranes and exert potent biological effects through receptor-independent mechanisms, including redox-sensitive post-translational modifications and modulation of heme-containing proteins. Although the individual functions of NO, CO, and H₂S have been extensively reviewed, emerging studies indicate that these gaseous mediators rarely operate in isolation. Instead, they form a highly integrated signaling network characterized by direct chemical interactions, reciprocal enzymatic regulation, and convergence upon common downstream pathways. In this mini-review, we propose the concept of a “Gasotransmitter Trio Network,” emphasizing the molecular crosstalk among NO, CO, and H₂S as a fundamental determinant of cellular homeostasis. We first summarize the biosynthetic pathways and major signaling mechanisms of the gasotransmitter trio, including S-nitrosylation, persulfidation, and heme-dependent regulation. We then discuss recent advances revealing how interactions among these gases generate novel bioactive intermediates and coordinate redox signaling. Particular attention is given to the emerging roles of gasotransmitters in regulating ferroptosis, autophagy, and mitophagy by modulating iron metabolism, lipid peroxidation, mitochondrial quality control, and antioxidant defense systems. These findings support a unified framework in which gasotransmitters function as master regulators of cellular fate under conditions of physiological and pathological stress. Finally, we highlight recent progress in stimuli-responsive donors, CO-releasing molecules (CORMs), NO-releasing materials (NORMs), H₂S donors, and advanced nanoplatforms that enable spatiotemporally controlled gas delivery. We propose that future therapeutic strategies will increasingly rely on programmable multi-gas systems that recapitulate endogenous gasotransmitter networks. Collectively, this review provides a systems-level perspective on gasotransmitter biology and outlines emerging opportunities for the development of precision gas medicine in cardiovascular, neurodegenerative, inflammatory, metabolic, and malignant diseases. Full article

The development of bioactive surgical sutures capable of delivering therapeutic agents directly at the wound site has gained increasing attention in biomedical research. Functionalized sutures may provide localized antimicrobial or anti-inflammatory activity, potentially reducing postoperative complications and promoting tissue healing. In this study, absorbable surgical sutures were impregnated with carvacrol, a natural phenolic compound with well-known antimicrobial properties, using supercritical carbon dioxide (scCO₂) technology. The impregnation process was carried out at 35 °C and 10 MPa for 120 min, allowing for the incorporation of carvacrol into the polymeric matrix of the sutures. The in vitro release behavior of the impregnated sutures was evaluated in phosphate-buffered saline (PBS, pH 7.4) at 37 °C over an 8-day period. The concentration of released compounds was determined by UV–Vis spectrophotometry using previously established calibration curves. An analysis of the experimental release data demonstrated that both carvacrol and benzydamine hydrochloride (HCl) (Tantum Verde^®) exhibited a sustained release profile throughout the incubation period. Carvacrol release increased progressively from 2.02 ± 0.15 ppm on day 1 to 7.45 ± 0.15 ppm on day 7, followed by a slight stabilization on day 8 (7.25 ± 0.31 ppm). Similarly, benzydamine HCl (Tantum Verde^®) release increased from 1.83 ± 0.11 ppm on day 1 to 3.29 ± 0.13 ppm on day 8. Release kinetics were analyzed using the Korsmeyer–Peppas model, indicating that the release mechanism was predominantly diffusion-controlled during the initial stage of the experiment. The results demonstrate that supercritical CO₂ impregnation is an effective solvent-free technique for incorporating bioactive compounds into absorbable sutures, enabling controlled release under physiological conditions. Full article

Population ageing has increased the need for safe, accessible, and sustainable exercise strategies that support functional capacity, independence, and healthy ageing. Nordic walking has been examined across physiological, functional, clinical, and health-related contexts; however, previous research syntheses have generally focused on specific intervention effects, populations, or outcome categories, leaving the relationships among these research strands insufficiently understood. This study combined CiteSpace-based bibliometric analysis with Latent Dirichlet Allocation (LDA) topic modeling to examine the knowledge structure and thematic development of Nordic walking research in ageing-related populations from 2006 to 2025. A total of 263 publications indexed in the Web of Science Core Collection were included in the final analysis. The results showed that research activity was geographically concentrated, whereas institutional connections were relatively dispersed. Co-citation patterns linked the field with exercise science, rehabilitation, gerontology, gait analysis, and clinical health research. Keyword and temporal analyses indicated that research attention expanded from the physiological and biomechanical characterization of Nordic walking toward functional rehabilitation, chronic disease-related applications, and broader health outcomes. The seven LDA-derived topics reflected health-outcome evaluation, metabolic and cardiovascular indicators, functional rehabilitation, exercise physiology, cognitive health, body composition and muscle function, and gait-related rehabilitation. Rather than representing isolated research domains, these topics reveal an interconnected knowledge structure linking exercise-related mechanisms, functional and clinical outcomes, and broader ageing-related health concerns. Future research should improve intervention reporting, adopt population-specific outcome selection, and strengthen the linkage between exercise mechanisms and functional or health-related outcomes to support more comparable and cumulative evidence. Full article

The overall influences of grazing practice on soil microbial community shifts have received considerable attention, but how dung-induced community coalescence affects soil microbial diversity, structure, interaction and the underlying assembly mechanism remains unclear. To address this, we investigated soil microbial community alterations in response to dung deposition, which included three different dung sources in a single grassland. The results indicated that dung deposition by different livestock species had varying impacts on soil microbial community diversity and structure, with cattle dung associated with the largest observed shifts in soil microbial diversity and community structure in this study. The structure of the soil microbial community was strongly associated with multiple edaphic properties (e.g., pH and nutrient content), but these correlations were reshaped by dung deposition in a dung-source-dependent manner. In addition, dung deposition consistently reduced the complexity and robustness of the co-occurrence network across different dung sources, and the strongest alterations in the network were found in shallow soils (0–20 cm). Null model analysis suggests that dung deposition improved the proportional contribution of the stochastic process in bacterial and fungal communities and conversely increased the deterministic process in the archaeal community, implying distinct assembly mechanisms of those microbial domains to the disturbance induced by dung deposition. These results highlight the source effect of dung deposition on the diversity and structure of soil microbial communities, as well as the domain-dependence of dung deposition on the assembly mechanism. The findings suggest that multispecies grazing is associated with distinct dung-induced microbial community shifts, highlighting the need for future research that explicitly incorporates dung source as a variable in grassland soil microbial assessments. Full article

Psychological stress can affect female reproductive function through behavioral, endocrine, ovarian, and oxidative mechanisms. Antioxidant supplements have therefore attracted attention for their potential to mitigate stress-related reproductive alterations. Coenzyme Q10 (CoQ10) is a lipid-soluble quinone involved in mitochondrial energy metabolism and is widely used as a dietary supplement. However, whether CoQ10 modulates female reproductive responses to repeated psychological stress remains unclear. Although water avoidance stress (WAS) is a well-established psychogenic stress model, its effects on female reproductive outcomes are still not fully defined. In this study, we examined how repeated WAS affects female reproductive outcomes and whether CoQ10 modifies these effects. Twenty-eight regularly cycling female rats were assigned to sham control, WAS, CoQ10, or WAS + CoQ10 groups. WAS was applied for 1 h/day for 10 days, and CoQ10 was administered orally at 100 mg/kg/day. Repeated WAS did not significantly alter sexual incentive motivation parameters, reproductive hormones, corticosterone, total antioxidant capacity (T-AOC), 8-hydroxy-deoxyguanosine (8-OHdG), or mast cell count under the present experimental conditions (all p > 0.05). However, WAS reduced male-directed active investigation time (p = 0.008) and male investigation preference ratio (p = 0.024), increased absolute ovarian and adrenal gland weights (p = 0.035 and p = 0.016, respectively), reduced primordial follicle number (p = 0.030), decreased germinative epithelium thickness (p = 0.017), lowered VEGF histoscore (p = 0.033) regardless of CoQ10 treatment, and reduced corpus luteum angiogenesis in animals not receiving CoQ10 (p = 0.030). CoQ10 reduced total investigation time toward the male (p = 0.032), male investigation preference ratio (p = 0.037), 17-β estradiol (E2) (p = 0.003), testosterone (p = 0.021), and germinative epithelium thickness (p < 0.001) regardless of WAS exposure. CoQ10 also decreased kisspeptin-1 levels under non-stressed conditions (p = 0.010), while increasing corpus luteum angiogenesis under stress conditions (p = 0.003). Overall, repeated WAS produced selective behavioral and ovarian alterations rather than broad reproductive dysfunction. CoQ10 was not associated with a broadly protective or uniformly beneficial profile in this model, and its endocrine, behavioral, and ovarian effects should be interpreted with caution. Full article

The outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged as one of the most significant global health crises in recent history. Coronaviruses are a diverse group of RNA viruses classified into alpha, beta, gamma, and delta genera, with SARS-CoV-2 belonging to the beta-coronavirus family. The virus exhibits high transmissibility and causes a wide spectrum of clinical manifestations ranging from mild respiratory symptoms to severe complications such as acute respiratory distress syndrome, multi-organ failure, and death, particularly among elderly and immunocompromised individuals. Structurally, SARS-CoV-2 possesses a large single-stranded RNA genome encoding major structural proteins, including spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, which play critical roles in host-cell recognition and viral infection. Understanding the molecular mechanisms of virus–host interactions, especially protein–protein interactions (PPIs), is essential for uncovering viral pathogenesis and identifying potential therapeutic targets. Traditional experimental techniques for PPI detection, such as yeast two-hybrid and affinity purification methods, are often expensive, labor-intensive, and prone to inaccuracies. Consequently, computational approaches based on machine learning (ML) and deep learning (DL) have gained significant attention for efficient and scalable PPI prediction. These methods use diverse biological information, including protein sequences, structural features, genomic data, Gene Ontology annotations, and interaction networks, to model complex biological relationships. This survey reviews computational approaches to PPI prediction, highlighting ML- and DL-based techniques, methodological advances, performance evaluation practices, and limitations that affect benchmark comparability. It also discusses biological databases and data sources commonly used in PPI studies and explicitly considers how models trained in coronavirus-centered settings may generalize to other viral families with different mechanisms of host interaction. Full article

Accurate carbon price forecasting is essential for emission trading risk management and low-carbon investment decisions. In existing decomposition-prediction frameworks, secondary decomposition targets are typically selected based on statistical complexity rather than domain-informed causality, and standard Long Short-Term Memory (LSTM)-Transformer architectures discard the cell state that encodes long-term temporal memory. These limitations are particularly pronounced where energy-driven causal structures and regime-switching volatility coexist. This study proposes Causal State-driven Network (CaStNet), an intelligent forecasting framework with two core innovations. A Policy-Causality-guided Residual Secondary Decomposition (PCRSD) module replaces entropy-based criteria with Granger causality to select intrinsic mode functions (IMFs) exhibiting significant energy-carbon causal linkages for targeted variational mode decomposition (VMD). A Cell-State-Driven Dual-function Attention (CSDA) mechanism repurposes the LSTM cell state for simultaneously injecting long-term memory into the Transformer and employing the cell-state differential velocity as a volatility proxy to adaptively regulate Top-k attention sparsity. The Artificial Lemming Algorithm (ALA) globally co-optimizes decomposition dimensions and attention boundaries. A Shapley Additive exPlanations (SHAP)–Local Interpretable Model-agnostic Explanations (LIME) interpretability analysis reveals horizon-dependent driver transitions from short-term autoregressive momentum to long-term energy fundamentals, uncovering threshold nonlinearities in energy-carbon transmission channels. Validation on the Shanghai market (2013–2025) achieves point-forecast RMSE = 0.8326 and R² = 0.9777, outperforming all twelve benchmark models. Cross-market testing on the Hubei market yields R² = 0.9487, and expanding-window five-fold cross-validation on the Shanghai dataset yields mean R² = 0.9704, jointly confirming generalization robustness. Full article