Search Results (69,439)

Medicinal plants are important sources of secondary metabolites (SMs), but their production is constrained by resource shortages, low cultivation efficiency, and continuous cropping obstacles. As the “second genome” of host plants, the plant microbiome is deeply involved in plant growth and development, stress adaptation, and the accumulation of bioactive compounds, providing new pathways for the sustainable utilization of traditional Chinese medicine resources. This review summarizes the mechanisms by which the plant microbiome regulates biomass formation and SM accumulation in medicinal plants. Microorganisms can promote plant nutrient acquisition, enhance resistance to biotic and abiotic stresses, and regulate root architecture and hormonal signaling. Meanwhile, microorganisms can also participate in the remodeling of secondary metabolic networks in medicinal plants through elicitor- and effector protein-mediated signal transduction, regulation of metabolic gene expression, redistribution of photosynthetic carbon sources and metabolic precursors, and their own biosynthetic capacities. From the perspective of co-evolution, plants and their microbiomes constitute symbiotic systems formed through long-term interactions. Plants can selectively recruit specific microbial taxa through root exudates, SMs, and signaling molecules, whereas microorganisms influence plant adaptability and medicinal material quality through colonization, metabolic feedback, and horizontal gene transfer. This review proposes that a synergistic regulatory pattern of “close phylogenetic relatedness-similar secretions-similar microbial communities” may exist between medicinal plants and microorganisms. This pattern suggests that closely related medicinal plants may share similar core microbial taxa, which may help reveal the intrinsic mechanisms underlying specific microbial recruitment and the quality formation of geo-authentic medicinal materials. Furthermore, the design of synthetic microbial communities (SynComs) can be achieved based on the identification of shared functional genes and the screening of indigenous core functional strains. Full article

Organic pollutant degradation demands photocatalysts that couple efficient charge separation with strong redox capability. Direct Z-scheme heterojunction architectures fulfill these requirements and are consequently considered promising candidates. However, the rational design of such systems continues to present a major obstacle. Herein, a CdSe/amorphous MoSe_x (CdSe/a-MoSe_x) direct Z-scheme heterojunction was successfully synthesized via a simple solid-state grinding and low-temperature hydrothermal method. Within 120 min under visible-light irradiation, methylene blue (MB, 40 mg/L) was degraded to 97.3% efficiency by the CdSe/a-MoSe_x heterojunction, whose photocatalytic activity markedly exceeded that of pristine CdSe and a-MoSe_x. Intimate interfacial contact between CdSe and a-MoSe_x enables photogenerated carriers to separate and migrate more efficiently, underpinning the observed performance enhancement. Moreover, the suitable band alignment derived from valence-band (VB) XPS and Mott-Schottky measurements supports the formation of a direct Z-scheme charge-transfer pathway. The Z-scheme mechanism effectively inhibits electron-hole recombination while maintaining the robust oxidation and reduction capabilities of the photogenerated carriers. This study offers a straightforward approach for fabricating CdSe/a-MoSe_x direct Z-scheme heterojunctions for the efficient photocatalytic degradation of organic pollutants. Full article

Efficient thermal management is critical for proton exchange membrane fuel cells (PEMFCs). This study develops a bio-inspired active liquid cooling architecture to overcome the limitations of conventional flow channels, where convective heat transfer augmentation significantly increases pressure drop. The proposed configuration adheres to constructal theory and Murray’s law. A three-dimensional conjugate heat transfer model was formulated to evaluate the thermo-hydrodynamic performance against parallel and serpentine flow channels. Under identical conditions, the proposed configuration exhibits superior thermal uniformity and hydrodynamic behavior, alongside minimized parasitic pumping power. At an inlet Reynolds number (Re) of 400, this configuration stabilizes the average bipolar plate temperature at 349.63 K. It reduces the index of uniform temperature (IUT) to 1.49 K, representing a 52.8% thermal uniformity improvement over the parallel flow channel. Furthermore, at an inlet Re of 600, the overall pressure drop is restricted to 68.44 Pa, reducing the single-plate parasitic pumping power to 1.27 × 10⁻⁴ W, which represents reductions of 93.5% and 12.5% relative to the serpentine and parallel flow channels, respectively. This study provides an alternative architectural scheme for the design of active liquid cooling flow channels in PEMFCs. Full article

This study examined total phenolic release and mass transfer during sequential pyruvic acid (PA) pretreatment and sodium hydroxide (NaOH) extraction of bamboo leaves. A 4 × 4 design comprised PA concentrations of 7.0, 8.0, 9.0, and 10.0% and NaOH concentrations of 3.0, 4.0, 5.0, and 6.0%. Kinetic curves from 40 to 120 min showed rapid release followed by a gradual approach to equilibrium. Normalized conversion F(t) was used to evaluate release progression, and two consistent fitting windows were applied for parameter estimation. The LDF model described the 40, 60, and 80 min data and provided k_f, while the Crank spherical diffusion model described the 80, 100, and 120 min data and provided D_eff. These overlapping windows represent different portions of the same continuous extraction process rather than physically separate stages. Model comparison and predictive validation supported the framework. The characteristic time ratio τ_m/τ_d exceeded 2 under all tested conditions, indicating that external liquid film transfer contributed the greater relative resistance. The condition of 8.0% PA and 5.0% NaOH provided the most balanced performance, yielding 18.55 ± 0.26 mg GAE/g, equivalent to 94.4% of the maximum. These results provide a practical basis for rate control analysis and condition selection. Full article

Developing electrocatalysts with high stability under industrial current densities is crucial for practical water electrolysis toward green hydrogen production yet remains a formidable challenge. Here, Fe₄₀Ni₃₈Mo₄B₁₈ amorphous alloy ribbons are fabricated via a scalable single-roller melt-spinning method and used as self-supported oxygen evolution electrodes. The as-prepared amorphous alloy sustains continuous operation at 500 mA cm^–2 for 730 h before noticeable deactivation. Mechanistic investigations reveal that under high-current anodic conditions, surface reconstruction accompanied by Fe dissolution leads to the formation and accumulation of a Fe-depleted, Ni-rich (oxy)hydroxide passivation layer, resulting in reduced Ni–Fe synergistic sites and limited charge transfer. Based on this understanding, a rapid regeneration strategy is developed to remove the inactive surface layer and induce structural reconfiguration. The regenerated electrode exhibits reduced overpotential at 10 mA cm^–2 (from 304 to 243 mV) and sustains an additional 710 h of operation at 500 mA cm^–2 at a lower applied potential. These results indicate that catalyst deactivation and regeneration are governed by surface chemical evolution and provide insight into extending catalyst lifetime under practical operating conditions. Full article

Biochar (BC) is widely utilised to enhance methane production from the anaerobic digestion (AD) process due to its physicochemical properties. This study investigates the influence of biochar pretreatment on its behaviour and performance in AD systems. Pre-treated biochar derived from different feedstocks via slow pyrolysis was applied in Biochemical Methane Potential (BMP) tests at a dosage of 0.25% (w/v), and its impact on both the methane yield and digestion kinetics during cellulose degradation was evaluated. Pre-treatment was performed via steam autoclaving, serving as both a sterilisation and surface-modification step aimed at improving the physicochemical characteristics of biochar, particularly its capacity for microbial immobilisation. The results demonstrated that the effect of autoclave pretreatment on methane production was strongly feedstock-dependent. Autoclaved rice husk biochar (AC-RH550) markedly inhibited methane production, whereas autoclaved softwood biochar (AC-SW550) exhibited the best performance among all biochars tested, achieving the highest methane yield of 382.2 (mL CH₄ g⁻¹ VS), corresponding to an increase of 18.3% compared to non-pretreated SW550 and 9.2% relative to the control. This improvement is attributed to the modifications in biochar surface properties, promoting improved microbial activity and biofilm formation potentially improving direct interspecies electron transfer (DIET). Additionally, biochar may act as a buffering agent and provide adsorption sites for inhibitory intermediates such as VFA. Cell immobilisation experiments further confirmed that autoclaving enhanced biochar porosity and hydrophilicity, encouraging better colonisation and biofilm formation. Scanning electron microscopy (SEM) and microbial analyses verified increased cell attachment on pretreated biochars. Overall, these findings highlight the critical role of pretreatment in optimising biochar functionality for anaerobic digestion applications and cell immobilisation. Full article

Rural communities shrink when residents leave, farmland and housing are underused, and local economic and service functions weaken. This study examines where this process occurred in 545 townships in the Yunnan section of the Jinsha River Basin and which local conditions were most closely associated with it in 2000, 2010, and 2020. We combined population, land, and economic indicators with spatial analysis and an ensemble machine-learning model designed to explain how each factor contributed to prediction. Rural shrinkage was widespread in 2000, eased substantially by 2010, and became spatially polarized again by 2020. Spatial clustering weakened and then strengthened across the three years. Coordination among population, land, and economic subsystems improved overall but remained uneven. Public-service accessibility was most prominent in the 2000 model, whereas vegetation conditions and distance to the provincial capital were more prominent in 2020. The results identify priority locations for monitoring, clarify how environmental, accessibility, and service conditions combine in different places, and provide a transferable framework for diagnosing rural shrinkage while separating robust spatial evidence from policy options that still require local testing. Full article

Waste-derived fertilising materials, including sewage sludge, compost, digestate, food-waste-derived products and commercial organic or organo-mineral fertilisers, return nutrients to farmland but can also transfer microplastics to agricultural soil. This critical review examines their occurrence across these streams, analytical constraints, fate after application and the EU regulatory framework. Reported abundances span orders of magnitude and cannot be pooled because extraction, polymer identification and reporting are not harmonised, while particle-counting and mass-based methods measure different quantities. Field evidence indicates topsoil retention and accumulation after repeated application, whereas crop transfer and field-scale ecological effects remain poorly quantified. Regulation (EU) 2019/1009 sets no microplastic-specific product limit. For compost qualifying as CMC 3 and digestate other than fresh crop digestate qualifying as CMC 5, it controls plastic impurities above 2 mm by mass, while smaller particles remain outside that criterion. Waste-derived fertilisers can therefore form a recurrent, incompletely regulated pathway for microplastic transfer to soil. Controlled studies demonstrate hazard potential for selected particles and exposure conditions, but the magnitude and likelihood of effects under field conditions remain uncertain. The immediate priority is harmonised monitoring and reporting of the sub-2 mm fraction, including a stated lower size limit, polymer-confirmed particle counts and minimum QA/QC. Full article

This paper introduces Steady State, a noncommercial, physical, two-player educational board game designed to model behavioral processes involved in time management from a behavior-analytic perspective. Although time management has been widely discussed in psychological and educational contexts, operationalized models are still needed to examine task allocation, postponement, and self-management under controlled conditions. The game models self-management under limited resources by arranging explicit response-consequence relations involving energy and stress tokens, task demands, reinforcement contingent on task completion, and weekly differential reinforcement for balanced engagement across domains. It also embeds self-monitoring prompts. A demonstrative pilot using an alternating treatments design (12 sessions with one dyad) compared the full contingency-based game (Condition A) with a procedural comparison condition in which the main response-consequence relations were minimized and stochastic outcomes were emphasized (Condition B). Embedded performance indices, including task postponements, energy remaining at the end of the session, stress accumulation, and planning time, varied more clearly with individual strategy in Condition A, whereas patterns in Condition B were more strongly constrained by stochastic outcomes. We discuss limitations and priorities for more controlled replication. The pilot was designed not to test educational effectiveness or transfer to everyday time management, but to determine whether the game generates measurable and behaviorally interpretable in-game variability. Full article

Standalone use of EAHEs for room cooling is a passive and nature-based alternative to air conditioning technology that can be used to mitigate the increase in electricity and GWP-refrigerant consumption associated with cooling in buildings. EAHEs replacing air conditioning is documented in the technical and research literature. However, for office-room cooling, EAHEs are mostly employed as a support to air conditioning systems for precooling outdoor air. The larger cooling loads and the stricter design conditions commonly used in the sizing of office rooms prevent the most commonly investigated EAHE typologies from operating effectively in standalone cooling mode. To assess the feasibility of alternative typologies, such as large-diameter EAHEs, tools that are capable of modeling the complexity of the coupled heat and moisture transfer between air and soil are particularly valuable. For detailed assessments, researchers typically turn to advanced commercial tools; however, developments in free and open-source scientific programming languages that combine symbolic computation packages with efficient numerical solvers of partial differential equations allow analyses at reduced cost that are comparable to those from commercial tools. This paper shows how one such programming language can be used to study the coupled heat and moisture transfer problem in EAHEs. Starting from the symbolic form of the mathematical problem, the numerical implementation is described and validated with monitoring data from an existing large-diameter EAHE. Using the validated computational model, the paper proceeds to study the sensitivity of load removal in EAHEs operating in standalone and precooling cooling modes, highlighting fundamental differences between both operating modes, identifying the most relevant design parameters and providing guidance on the conditions under which an EAHE enables self-sufficient cooling of office buildings. The results show how, for a hot and dry climate, standalone EAHEs with large diameters (∼1 m), buried at depths larger than 3 m, allow the removal of up to 20 kWh/m² of room sensible cooling loads, a level that is consistent with the cooling demand of low-energy office buildings. Full article

Background: Returning home after neurological hospitalization, rehabilitation, or specialist care transfers responsibility to patients, caregivers, and community services. We mapped mechanisms and gaps across dementia/Alzheimer’s disease and related dementias (ADRD), Parkinson’s disease (PD), multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS). Methods: Following JBI guidance and PRISMA-ScR, eligibility was derived using population–concept–context. We included empirical reports involving adults with a target condition, a post-discharge, return-home, rehabilitation, telehealth, caregiver, treatment, respiratory, or palliative continuity component, and post-transition patient, caregiver, service, safety, rehabilitation, equity, or implementation outcomes. Five databases were searched through to 11 May 2026. Two reviewers independently screened records; charting and classification were verified by R.S.C., A.C., and A.Q. Results: Of 24,417 records, 69 reports were included: Dementia/ADRD, 28; PD, 10; MS, 9; and ALS, 22. Eighteen were core transition reports (26.1%), 14 return-home/community re-entry reports (20.3%), 16 adjacent continuity reports (23.2%), and 21 companion/secondary reports (30.4%). Dementia/ADRD provided discharge-anchored evidence; PD and MS mapped functional carry-over; ALS mapped adjacent respiratory, telehealth, and palliative continuity. Conclusions: The main contribution is an operational cross-disease framework separating direct discharge, return-home, adjacent-continuity, and companion evidence while linking mechanisms to disease-specific pathways. This framework maps disease-specific functions, not comparative effectiveness. The proposed frameworks are author-derived and hypothesis-generating. Future studies should use explicit anchors, standardized outcomes, longer follow-up, and equity-sensitive implementation measures addressing caregiver workload, digital access, feasibility, and sustainability. They inform testable, context-sensitive intervention designs for future neurological transition-care research and practice. Full article

This article presents an Artificial Intelligence and Internet of Things (AI–IoT/AIoT) decision-making framework for smart water management and sustainable aquaponic systems. The framework connects sensors, IoT telemetry, machine learning algorithms, and real-time monitoring of key water quality parameters, with the aim of early detection of deviations, operational decision support, and risk reduction in system management. A special contribution of the paper is that water is viewed simultaneously as a limiting resource, a biological factor and an operational cost. The proposed framework defines the structure of a decision support system, including monitoring of temperature, pH value, dissolved oxygen, ammonia/ammonium, EC/TDS value, water flow, feeding regime, and basic biological indicators. In the methodological sense, the paper presents a conceptual-methodological framework based on publicly available data, scenario estimates, and a clearly defined protocol for future pilot validation of high-frequency operational data. In addition to the technical architecture, the framework includes elements of responsible application of AIoT systems: data quality control, sensor deviation and drift detection, model explainability through XAI/SHAP, data transfer security, and the possibility of human confirmation before risky interventions. The economic part of the paper shows ROI/NPV as a scenario estimate, based on explicit assumptions about costs, resource consumption and possible operational savings, and not as a confirmed financial result. The framework is aligned with the principles of the circular bioeconomy, as it links the monitoring of water quality, the reduction in nutrient losses, the reuse of resources, and better planning of interventions in aquaculture and aquaponics. The results indicate the potential of AIoT approaches to improve monitoring, transparency and operational decision-making, while the actual effects on productivity, water consumption, food consumption, energy, and economic sustainability must be confirmed in a pilot phase. Full article

Corrosion, salt deposition, and biofouling critically impair flow assurance and mechanical integrity in oil and gas production systems, resulting in escalating operating costs and environmental burdens. This study presents a screening-level multi-criteria decision-making framework grounded in petroleum engineering practice. Unlike conventional MCDA approaches that require extensive laboratory testing for each asset, our model enables the rapid assessment of inhibitor transferability between technologically similar fields using normalized field parameters and actual procurement data. The model integrates a correlation analysis of the key field parameters of temperature, acid gas content, salt concentration, flow velocity, and water cut with a weighted effectiveness coefficient. A dataset of operational records was coupled with factual procurement prices from 2020 to 2025 to simultaneously optimize inhibitor type and dosing. The novelty lies in the multiplicative weighting scheme and the concept of critical deviation thresholds, which allow engineers to identify cost-saving opportunities without compromising the 90% protection target. Application of the model presented in this article allows a reduction in annual chemical-related operational expenditures. The proposed methodology provides petroleum engineers with a robust, data-driven screening tool to design cost-effective chemical treatment strategies that maintain corrosion protection and reduce environmental load, thereby advancing oil field chemistry technology and supporting efficient oil and gas field development. Full article

Cross-dataset pothole segmentation is difficult because illumination, camera characteristics, asphalt texture, and boundary quality vary between training and deployment environments. This study proposes PotholeBAF-Net, an EfficientNet-B3 encoder–decoder network comprising a Low-Rank Transformer Bridge, a Boundary-Aware Fusion (BAF) decoder, and a lightweight Boundary Refinement Head. The bridge uses standard multi-head attention whose pre-softmax per-head affinity matrix is rank-bounded by the query/key dimension; BAF then regulates each encoder skip using a learned soft boundary prior, channel–spatial attention, and spatial–channel gated interpolation with decoder semantics. The model was trained and validated on the Large Public Dataset and evaluated without target-domain training or calibration on the independently collected 188-image Collected Taiz Dataset. Across three independent seeds, PotholeBAF-Net obtained external-test precision of $0.8562\pm 0.1040$, recall of $0.4854\pm 0.0716$, F1/Dice of $0.6196\pm 0.0395$, IoU of $0.4164\pm 0.0365$, and MCC of $0.5802\pm 0.0198$. Removing the boundary prior, Transformer bridge, or refinement head reduced mean IoU by 0.0763, 0.0685, and 0.0675, respectively. The network contains 12.463 M parameters and requires 4.779 GMACs. These findings support controlled skip transfer as a useful design for target-free pothole segmentation, while the remaining seed variability and recall-dominated failures show that shadows, weak boundaries, and visually ambiguous pavement remain unresolved challenges. Full article

The chronic overuse of antibiotics has accelerated the emergence of antibiotic-resistant bacteria, creating a global public health crisis as conventional therapies fail against multidrug-resistant pathogens spreading through water and food chains. Cadmium sulfide (CdS) has been established as an important visible-light-driven photocatalyst for antibacterial applications. This brief review systematically examines the structure–property relationships governing CdS-based antibacterial materials, including crystallographic polymorphs (cubic sphalerite and hexagonal wurtzite), morphological diversity from quantum dots to hierarchical architectures, and synthesis methodologies that critically influence particle size, crystallinity, and surface chemistry. The mechanisms of antibacterial action are elucidated, encompassing photocatalytic reactive oxygen species (ROS) generation, controlled Cd²⁺ ion release, and membrane disruption. A detailed tabulated analysis is presented across three material classes: pristine CdS, binary composites, and ternary Z-scheme heterostructures. Density functional theory (DFT) calculations and molecular docking simulations provide atomic-level insights into charge transfer dynamics and enzyme inhibition mechanisms. Finally, critical challenges, photocorrosion, toxicity, biocompatibility concerns, and scalability limitations are addressed. This review bridges fundamental materials science with antimicrobial applications to guide rational design of next-generation CdS-based antibacterial materials. Full article