Search Results (87)

Land degradation in drylands increasingly threatens infrastructure and the performance of renewable energy (RE) systems through coupled hydro-chemo-mechanical changes in soil fabric, density, matric suction, and pore–water chemistry. A key gap is the limited integration of unsaturated soil mechanics with practical indicator sets used in engineering screening and operations. This narrative review synthesizes evidence from targeted searches of Scopus, Web of Science, and Google Scholar. Searches are complemented by key organizational reports and standards, as well as citation tracking. Priority is given to sources that report mechanisms linked to measurable indicators, thresholds, tests, or models relevant to dryland infrastructure. The synthesis uses the soil-water characteristic curve (SWCC) and hydraulic conductivity k(θ) to connect hydraulic state to strength and deformation and couples these with chemical indices, including electrical conductivity (EC), exchangeable sodium percentage (ESP), and sodium adsorption ratio (SAR). Practical diagnostics include the dynamic cone penetrometer (DCP) and California Bearing Ratio (CBR) tests, infiltration and crust-strength tests, monitoring with unmanned aerial vehicles (UAVs), geophysics, and in situ moisture and suction sensing. The contribution is an indicator-driven, practice-oriented framework linking mechanisms, monitoring, and mitigation for photovoltaic (PV), concentrating solar power (CSP), wind, transmission, and well-pad corridors. This framework is implemented by consistently linking unsaturated soil state (SWCC, k(θ), and matric suction) to degradation processes, measurable indicator/test sets, and trigger-based interventions across the review. Full article

Effective metabolic waste clearance and maintaining ionic homeostasis are essential for the health and normal function of the central nervous system (CNS). To understand its mechanism and the role of fluid flow, we develop a multidomain electro-osmotic model of optic-nerve microcirculation (as a part of the CNS) that couples hydrostatic and osmotic fluid transport with electro-diffusive solute movement across axons, glia, the extracellular space (ECS), and arterial/venous/capillary perivascular spaces (PVS). Cerebrospinal fluid enters the optic nerve via the arterial parivascular space (PVS-A) and passes both the glial and ECS before exiting through the venous parivascular space (PVS-V). Exchanges across astrocytic endfeet are essential and they occur in two distinct and coupled paths: through AQP4 on glial membranes and gaps between glial endfeet, thus establishing a mechanistic substrate for two modes of glymphatic transport, at rest and during stimulus-evoked perturbations. Parameter sweeps show that lowering AQP4-mediated fluid permeability or PVS permeability elevates pressure, suppresses radial exchange (due mainly to hydrostatic pressure difference at the lateral surface and the center of the optic nerve), and slows clearance, effects most pronounced for solutes reliant on PVS–V export. The model reproduces baseline and stimulus-evoked flow and demonstrates that PVS-mediated export is the primary clearance route for both small and moderate solutes. Small molecules (e.g., A$\beta$) clear faster because rapid ECS diffusion broadens their distribution and enhances ECS–PVS exchange, whereas moderate species (e.g., tau monomers/oligomers) have low ECS diffusivity, depend on trans-endfoot transfer, and clear more slowly via PVS–V convection. Our framework can also be used to explain the sleep–wake effect mechanistically: enlarging ECS volume (as occurs in sleep) or permeability increases trans-interface flux and accelerates waste removal. Together, these results provide a unified physical picture of glymphatic transport in the optic nerve, yield testable predictions for how AQP4 function, PVS patency, and sleep modulate size-dependent clearance, and offer guidance for targeting impaired waste removal in neurological disease. Full article

Energy Communities have emerged as a key mechanism for promoting citizen participation in the energy transition. In Greece, recent legislation replaced the virtual net-metering scheme with a virtual net-billing framework, introducing new economic and regulatory conditions for shared renewable energy investments. This study develops an optimization tool for determining the optimal PV system size and Demand Response actions for individual EC members under this new framework. The model is constructed to align closely with the current regulatory and legal context, incorporating technical, economic, and policy-related constraints. It uses real electricity production and consumption data from existing Greek ECs, as well as 2024 Day Ahead Market prices, grid fees, and surcharges. The results emphasize the importance of customized sizing strategies and suggest that policy refinements may be needed to ensure equitable participation and maximize community-level benefits. Full article

This study aims to explore the significant factors that predicted the purchase intention (PI) of Generation Z (Gen Z) in China on photovoltaics (PV) products. The Theory of Planned Behaviour (TPB) is extended with two exogenous variables (environmental responsibility (ER) and environmental consciousness (EC)) and government support (GS) as a moderator. In the proposed model, three TPB dimensions also serve as mediators. A total of 675 valid responses from Generation Z in China were gathered via purposive sampling and analysed using partial least squares–structural equation modelling (PLS-SEM). The findings revealed that subjective norms (SN), perceived behavioural control (PBC), and EC exerted a substantial influence on PI towards PV products. In accordance with the findings, EC has an indirect effect on PI via SN and PBC. In addition, the moderation analysis revealed that GS significantly enhances the relationship between EC and PI. Several important practical implications derived from the findings of the study were discussed, and it could be a useful reference for stakeholders in framing strategies to promote the PI of PV products. This study extends the TPB model by including two possible exogenous variables and examining the moderator and mediator propositions that significantly influence the PI of PV products, based on a comprehensive literature review. The proposed model is envisaged to provide additional evidence on the topic. Full article

As energy systems transition toward high shares of variable renewable generation, local energy communities (ECs) are increasingly relevant for enabling demand-side flexibility and self-sufficiency. This shift is particularly evident in the residential sector, where the deployment of photovoltaic (PV) systems is rapidly growing. While mixed-integer linear programming (MILP) remains the standard for operational optimization and demand response in such systems, its computational burden limits scalability and responsiveness under real-time or uncertain conditions. Reinforcement learning (RL), by contrast, offers a model-free, adaptive alternative. However, its application to real-world energy system operation remains limited. This study explores the application of a Deep Q-Network (DQN) to a real residential EC, which has received limited attention in prior work. The system comprises three single-family homes sharing a centralized heating system with a thermal energy storage (TES), a PV installation, and a grid connection. We compare the performance of MILP and RL controllers across economic and environmental metrics. Relative to a reference scenario without TES, MILP and RL reduce energy costs by 10.06% and 8.78%, respectively, and both approaches yield lower total energy consumption and CO₂-equivalent emissions. Notably, the trained RL agent achieves a near-optimal outcome while requiring only 22% of the MILP’s computation time. These results demonstrate that DQNs can offer a computationally efficient and practically viable alternative to MILP for real-time control in residential energy systems. Full article

Accurate and reliable fault detection in photovoltaic (PV) systems is essential for optimizing their performance and durability. This paper introduces a novel approach for fault detection and diagnosis in large-scale PV systems, utilizing power loss analysis and predictive models based on Random Forest (RF) and K-Nearest Neighbors (KNN) algorithms. The proposed methodology establishes a predictive baseline model of the system’s healthy behavior under normal operating conditions, enabling real-time detection of deviations between expected and actual performance. Faults such as string disconnections, module short-circuits, and shading effects have been identified using two key indicators: current error (Ec) and voltage error (Ev). By focusing on power losses as a fault indicator, this method provides high-accuracy fault detection without requiring extensive labeled data, a significant advantage for large-scale PV systems where data acquisition can be challenging. Additionally, a key contribution of this work is the identification and correction of faulty sensors, specifically pyranometer misalignment, which leads to inaccurate irradiation measurements and disrupts fault diagnosis. The approach ensures reliable input data for the predictive models, where RF achieved an R² of 0.99657 for current prediction and 0.99459 for power prediction, while KNN reached an R² of 0.99674 for voltage estimation, improving both the accuracy of fault detection and the system’s overall performance. The outlined approach was experimentally validated using real-world data from a 500 kWp grid-connected PV system in Ain El Melh, Algeria. The results demonstrate that this innovative method offers an efficient, scalable solution for real-time fault detection, enhancing the reliability of large PV systems while reducing maintenance costs. Full article

The control of bacterial plant diseases is very challenging and often relies on the application of copper compounds, although the frequent emergence and spread of resistant bacterial strains compromise their efficacy. Additionally, copper-based compounds raise environmental and human health concerns, leading to their inclusion in the European Commission’s list of candidates for substitution. As a promising and sustainable alternative, we investigated the efficacy of biogenic zinc oxide nanoparticles (ZnO-NPs) in protecting tomato plants against Pseudomonas syringae pv. tomato (Pst), the causal agent of bacterial speck disease. ZnO-NPs exhibited significant in vitro antibacterial activity (EC₉₅ = 17.0 ± 1.1 ppm) against the pathogen. Furthermore, when applied to the foliage of tomato plants at 100 ppm before or following Pst inoculation, they induced significant reductions in symptom severity and bacterial growth in planta, which were comparable to those shown by plants treated with acibenzolar-S-methyl, a plant defense inducer. Gene expression assessed by qPCR revealed the involvement of the systemic acquired resistance (SAR) pathway in tomato plants treated with ZnO-NPs before inoculation, suggesting that the observed protection could be due to a priming effect. Finally, infected plants showed oxidative stress, with higher H₂O₂ and malondialdehyde (MDA) contents. ZnO-NPs reverted this effect, containing the content of the above molecules, and stimulated the production of metabolites involved in dealing with oxidative perturbations (carotenoids and phenols), while unaffecting flavonoids and anthocyanins. Full article

The Baltic countries are exploring diverse ways to achieve renewable energy objectives, with a particular emphasis on utilizing photovoltaic (PV) technologies in urban areas. Despite the northerly geographical location, PV energy has proven effective, particularly in individual households under the net metering scheme. Energy communities (EC) in urban areas have the potential to support sustainable energy transition by promoting local generation and increasing resilience. However, the broader adoption of rooftop PV systems faces numerous challenges, including technical limitations and legislative gaps. This study examines challenges encountered by community energy projects in residential apartments through a case study in the Latvian context. The paper provides a comparative analysis of PV community implementation scenarios across the three types of typical apartment buildings. The study demonstrates a number of fundamental obstacles that hamper the development of ECs in apartment buildings. The results indicate that the economic benefits of ECs largely depend on electricity market price, and that selection of optimal community design is the key aspect for minimizing investment risks amid market and legislative uncertainty. Results indicate that individual households may have limited motivation to form ECs under current policies. Finally, the insights provided help shape suggestions for future research. Full article

This study reports on the development and validation of a video-based instrument to assess early childhood education (ECE) teachers’ professional vision (PV) of language-stimulation (LS) interactions. PV refers to noticing and reasoning about key classroom interactions, a skill that can be trained and distinguishes experts from novices. The instrument targets the PV of three language-stimulation (LS) strategies: language input (LI), opportunities for language production (OLP), and feedback (FB). The instrument measures noticing through comparative judgement (CJ) and reasoning through multiple-choice items. Construct validity was assessed using the AERA framework, using three samples: a sample of professionals (n = 22), a pre-service teachers’ sample (n = 107), and a mixed sample with in- and pre-service teachers (n = 6). Reliability and validity were confirmed, with strong reliability scores for the CJ aggregated “master” rank orders (SRR: 0.827–0.866). Think-aloud procedures demonstrated that respondents’ decisions during CJ were mainly based on LS-relevant video features. Decisions unrelated to LS require further study. Multiple-choice reasoning items were developed from professionals’ open-ended feedback. Pre-service teacher reasoning scores showed no significant predictors. Using real classroom videos, this instrument provides an ecologically valid, scalable tool for assessing teachers’ professional vision of LS interactions. This validated instrument offers a foundation for professional development programs aimed at addressing the theory–practice gap in early language education. Full article

Energy communities (ECs) have emerged across the EU, with the Clean Energy Package providing the legal foundation for the establishment of energy communities. The actual transposition is up to the member states, leading to heterogeneous regulatory approaches. The national frameworks often provide financial support mechanisms like local grid tariffs, along with regulatory limitations on size and membership, which significantly influence the business case for ECs. This paper analyzes the economic feasibility of ECs under different national frameworks in Spain, Portugal, France, Italy, and Austria. Two scenarios were evaluated by means of a case study, consisting of households and two public entities. The first scenario compares national incentives under uniform conditions, while the second considers country-specific factors like PV irradiation and electricity costs. Results show that energy communities can only partially decouple electricity prices from market dynamics. The study concludes that financial incentives lead to adequate financial savings for the members in most countries; however, the level of incentive does not necessarily relate to the number of established energy communities. Electricity grid benefits could be created by promoting demand response measures in the EC. Full article

Solar hydrogen production is a promising pathway for sustainable CO₂-free hydrogen production. It is mainly classified into three systems: photovoltaic electrolysis (PV-EC), photoelectrochemical (PEC) system, and particulate photocatalytic (PC) system. However, it still has trouble in commercialization due to the limitation of performance and economic feasibility in the large-scale system. In this review, the challenges of each large-scale system are, respectively, summarized. Based on this summary, recent approaches to solving these challenges are introduced, focusing on core components, fabrication processes, and systematic designs. In addition, several demonstrations of large-scale systems under outdoor conditions and performances of upscaled systems are introduced to understand the current technical level of solar-driven hydrogen production systems for commercialization. Finally, the future outlooks and perspectives on the practical application of large-scale solar-driven hydrogen production are discussed. Full article

Pests and diseases have caused significant problems since the domestication of crops, resulting in economic loss and hunger. To overcome these problems, synthetic pesticides were developed to control pests; however, there are significant detrimental side effects of synthetic pesticides on the environment and human health. There is an urgent need to develop safer and more sustainable pesticides. Industrial hemp is a reservoir of compounds that could potentially replace some synthetic bactericides, fungicides, and insecticides. We determined the efficacy of industrial hemp extracts against Pseudomonas syringae pv. tabaci (PSTA), Pseudomonas syringae pv. tomato (PSTO), and Erwinia carotovora (EC). The study revealed a minimum inhibitory concentration (MIC) of 2.05 mg/mL and a non-inhibitory concentration (NIC) of 1.2 mg/mL for PSTA, an MIC of 5.7 mg/mL and NIC of 0.66 mg/mL for PSTO, and an MIC of 12.04 mg/mL and NIC of 5.4 mg/mL for EC. Time-kill assays indicated the regrowth of E. carotovora at 4 × MIC after 15 h and P. syringae pv. tomato at 2 × MIC after 20 h; however, P. syringae pv. tabaci had no regrowth. The susceptibility of test bacteria to hemp extract can be ordered from the most susceptible to the least susceptible, as follows: P. syringae pv. tabaci > P. syringae pv. tomato > E. carotovora. Overall, the data indicate hemp extract is a potential source of sustainable and safe biopesticides against these major plant pathogens. Full article

Energy Communities (ECs) are aggregations of users that cooperate to achieve economic benefits by sharing energy instead of operating individually in the so-called “disagreement” case. As there is no unique notion of fairness for the cost/profit allocation of ECs, this paper aims to identify an allocation method that allows for an appropriate weighting of both the interests of an EC as a whole and those of all its members. The novelty is in comparing different optimization approaches and cooperative allocation criteria, satisfying different notions of fairness, to assess which one may be best suited for an EC. Thus, a cooperative model is used to optimize the operation of an EC that includes two consumers and two solar PV prosumers. The model is solved by the “Social Welfare” approach to maximizing the total “incremental” economic benefit (i.e., cost saving and/or profit increase) and by the “Nash Bargaining” approach to simultaneously maximize the total and individual incremental economic benefits, with respect to the “disagreement” case. Since the “Social Welfare” approach could lead to an unbalanced benefit distribution, the Shapley value and Nucleolus criteria are applied to re-distribute the total incremental economic benefit, leading to higher annual cost savings for consumers with lower electricity demand. Compared to “Social Welfare” without re-distribution, the Nash Bargaining distributes 39–49% and 9–17% higher annual cost savings to consumers with lower demand and to prosumers promoting the energy sharing within the EC, respectively. However, total annual cost savings drop by a maximum of 5.5%, which is the “Price of Fairness”. Full article

Bacterial virulence plays an important role in infection. Antibacterial virulence factors are effective for preventing crop bacterial diseases. Resin acid copper salt as an effective inhibitor exhibited excellent anti-Xanthomonas oryzae pv. oryzae (Xoo) activity with an EC₅₀ of 50.0 μg mL⁻¹. Resin acid copper salt (RACS) can reduce extracellular polysaccharides’ (EPS’s) biosynthesis by down-regulating gumB relative expression. RACS can also effectively inhibit the bio-mass of Xoo biofilm. It can reduce the activity of Xoo extracellular amylase at a concentration of 100 μg mL⁻¹. Meanwhile, the results of virtual computing suggested that RACS is an enzyme inhibitor. RACS displayed good curative activity with a control effect of 38.5%. Furthermore, the result of the phytotoxicity assessment revealed that RACS exhibited slight toxicity compared with the control at a concentration of 200 μg mL⁻¹. The curative effect was increased to 45.0% using an additional antimicrobial agent like orange peel essential oil. RACS markedly inhibited bacterial pathogenicity at a concentration of 100 μg mL⁻¹ in vivo. Full article

Equus caballus papillomavirus 2 (EcPV2) is known to cause genital neoplasms in horses. However, reports on EcPV2 in Japan and Asia are limited. Herein, we present the histopathological and virological findings of the first reported case of an EcPV2-associated penile mass in Japan. The patient was a 22-year-old stallion with a history of breeding in Japan and abroad. Histopathological examination contained RNA in situ hybridization targeting the E6/E7 region and an immunohistochemical approach, and whole-genome sequencing was conducted within the viral examination. Proliferating epidermal cells were observed, and EcPV2 E6/E7 mRNA was detected within the epidermis, which was interpreted as viral papilloma. The detected EcPV2 virus was genetically close to foreign strains and different from the strain previously reported from a Japanese mare. This suggests that various types of EcPV2 might already exist among horses in Japan. Although the mass reported herein was not malignant based on histopathological findings and the absence of recurrence, its presence on the penis would be an obstacle to breeding. These results provide a better understanding of the pathogenesis and diversity of EcPV2. Full article