Search Results (2,081)

To address the issue of excessive chemical fertilizer use in agricultural production, this study conducted a pot experiment with four treatments: CK (no fertilization), T1 (the application of potassium magnesium sulfate fertilizer), T2 (the application of slow-release fertilizer equal to T1), and T3 (the application of slow-release fertilizer with the same fertility as T1). The effects of these treatments on garlic seedling yield, growth quality, chlorophyll content, photosynthetic characteristics, and the soil environment were investigated to evaluate the feasibility of replacing conventional fertilizers with slow-release formulations. The results showed that compared with CK, all three fertilized treatments (T1, T2, and T3) significantly increased the plant heights and stem diameters of the garlic sprouts (p < 0.05). Plant height increased by 14.85%, 17.81%, and 27.75%, while stem diameter increased by 9.36%, 8.83%, and 13.96%, respectively. Additionally, the chlorophyll content increased by 4.34%, 7.22%, and 8.05% across T1, T2, and T3, respectively. Among the treatments, T3 exhibited the best overall growth performance. Compared with those in the CK group, the contents of soluble sugars, soluble proteins, free amino acids, vitamin C, and allicin increased by 64.74%, 112.17%, 126.82%, 36.15%, and 45.43%, respectively. Furthermore, soil organic matter, available potassium, magnesium, and phosphorus increased by 109.02%, 886.25%, 91.65%, and 103.14%, respectively. The principal component analysis indicated that soil pH and exchangeable magnesium were representative indicators reflecting the differences in the soil’s chemical properties under different fertilization treatments. Compared with the CK group, the metal contents in the T1 group slightly increased, while those in T2 and T3 generally decreased, suggesting that the application of slow-release fertilizer exerts a certain remediation effect on soils contaminated with heavy metals. This may be attributed to the chemical precipitation and ion exchange capacities of phosphogypsum, as well as the high adsorption and cation exchange capacity of bentonite, which help reduce the leaching of soil metal ions. In summary, slow-release fertilizers not only promote garlic sprout growth but also enhance soil quality by regulating its chemical properties. Full article

Cybersecurity represents a critical challenge for data-sharing platforms involving multiple stakeholders, particularly within complex and decentralized systems such as livestock supply chain networks. These systems demand novel approaches, robust security protocols, and advanced data management strategies to address key challenges such as data consistency, transparency, ownership, controlled access or exposure, and privacy-preserving analytics for value-added services. In this paper, we introduced the Framework for Framework for Livestock Empowerment and Decentralized Secure Data eXchange (FLEX), as a comprehensive solution grounded on five core design principles: (i) enhanced security and privacy, (ii) human-centric approach, (iii) decentralized and trusted infrastructure, (iv) system resilience, and (v) seamless collaboration across the supply chain. FLEX integrates interdisciplinary innovations, leveraging decentralized infrastructure-based protocols to ensure trust, traceability, and integrity. It employs secure data-sharing protocols and cryptographic techniques to enable controlled information exchange with authorized entities. Additionally, the use of data anonymization techniques ensures privacy. FLEX is designed and implemented using a microservices architecture and edge computing to support modularity and scalable deployment. These components collectively serve as a foundational pillar of the development of a digital product passport. The FLEX architecture adopts a layered design and incorporates robust security controls to mitigate threats identified using the STRIDE threat modeling framework. The evaluation results demonstrate the framework’s effectiveness in countering well-known cyberattacks while fulfilling its intended objectives. The performance evaluation of the implementation further validates its feasibility and stability, particularly as the volume of evidence associated with animal identities increases. All the infrastructure components, along with detailed deployment instructions, are publicly available as open-source libraries on GitHub, promoting transparency and community-driven development for wider public benefit. Full article

The spatial distribution of ephemeral and perennial dryland plant species is increasingly modified and restricted by ever-changing climates and development expansion. At the interface of biodiversity conservation and developmental planning in desert landscapes is the growing need for adaptable tools in identifying and monitoring these ecologically fragile plant assemblages, habitats, and, often, heritage sites. This study evaluates usage of Sentinel-2 time series composite imagery to discriminate vegetation assemblages in a hyper-arid landscape. Spatial predictor spaces were compared to classify different vegetation communities: spectral components (PCs), vegetation indices (VIs), and their combination. Further, the uncertainty in discriminating field-verified vegetation assemblages is assessed using Shannon entropy and intensity analysis. Lastly, the intensity analysis helped to decipher and quantify class transitions between maps from different spatial predictors. We mapped plant assemblages in 2022 from combined PCs and VIs at an overall accuracy of 82.71% (95% CI: 81.08, 84.28). A high overall accuracy did not directly translate to high class prediction probabilities. Prediction by spectral components, with comparably lower accuracy (80.32, 95% CI: 78.60, 81.96), showed lower class uncertainty. Class disagreement or transition between classification models was mainly contributed by class exchange (a component of spatial allocation) and less so from quantity disagreement. Different artefacts of vegetation classes are associated with the predictor space—spectral components versus vegetation indices. This study contributes insights into using feature extraction (VIs) versus feature selection (PCs) for pixel-based classification of plant assemblages. Emphasising the ecologically sensitive vegetation in desert landscapes, the study contributes uncertainty considerations in translating optical satellite imagery to vegetation maps of arid landscapes. These are perceived to inform and support vegetation map creation and interpretation for operational management and conservation of plant biodiversity and habitats in such landscapes. Full article

Underground brine as a liquid mineral resource available for development and utilization has attracted widespread attention. However, how the mining process affects the hydrochemical characteristics and evolution of underground brine has yet to be fully understood. Herein, 207 underground brine samples were collected from the Luobei mining area of the Lop Nur region during pre-exploitation (2006), exploitation (2019), and late exploitation (2023) to explore the dynamic change characteristics and evolution mechanisms of the underground brine hydrochemistry using the combination of statistical analysis, spatial interpolation, correlation analysis, and ion ratio analysis. The results indicated that Na⁺ and Cl⁻ were the dominant ionic components in the brine, and their concentrations remained relatively stable throughout the mining process. However, the content of Mg²⁺ increased gradually during the mining process (increased by 45.08% in the middle stage and 3.09% in the later stage). The elevation in Mg²⁺ concentration during the mining process could be attributed to the dissolution of Mg-bearing minerals, reverse cation exchange, and mixed recharge. This research furnishes a scientific foundation for a more in-depth comprehension of the disturbance mechanism of brine-mining activities on the groundwater chemical system in the mining area and for the sustainable exploitation of brine resources. Full article

Chemically demethoxylated and Ca-cross-linked orange-peel waste was engineered as a biosorbent for Mn(II) removal from water. A three-factor Box–Behnken design (biosorbent dose 3–10 g L⁻¹, initial Mn²⁺ 100–300 mg L⁻¹, contact time 3–8 h; pH 5.5 ± 0.1, 25 °C) required only 16 runs to locate the optimum (10 g L⁻¹, 100 mg L⁻¹, 8 h), at which the material removed 94.8% ± 0.3% manganese removal under the optimized conditions (10 g L⁻¹, 100 mg L⁻¹, 8 h, pH 5.5) of dissolved manganese and reached a Langmuir capacity of 29.7 mg g⁻¹. Equilibrium data fitted the Freundlich (R² = 0.968) and Sips (R² = 0.969) models best, indicating a heterogeneous surface, whereas kinetic screening confirmed equilibrium within 6 h. FTIR and SEM–EDX verified abundant surface –COO⁻/–OH groups and showed Mn deposits that partially replaced residual Ca, supporting an ion-exchange component in the uptake mechanism. A preliminary cost analysis (<USD 10 kg⁻¹) and > 90% regeneration efficiency over three cycles highlight the economic and environmental promise of this modified agro-waste for polishing Mn-laden effluents. Full article

Proton Exchange Membrane Fuel Cells (PEMFCs) are seen as an alternative for heavy-duty transportation electrification. Powered by a green hydrogen source, they can provide high efficiency and low carbon emissions compared to traditional fuels. However, to be competitive, these systems require high reliability when operated in real-life conditions, as well as safe and efficient operating management. In order to achieve these goals, the X-in-the-loop (also called model-based design) methodology is well suited. It has been largely adopted for PEMFC system development and optimisation, as they are complex multi-component systems. In this paper, a systematic analysis of the scientific literature is conducted to review the methodology implementation for the design and improvement of the PEMFC systems. It exposes a precise definition of each development step in the methodology. The analysis shows that it can be employed in different ways, depending on the subsystems considered and the objectives sought. Finally, gaps in the literature and technical challenges for fuel cell systems that should be addressed are identified. Full article

In placental mammals, the co-option of vertebrate orthologous ATP1B4 genes has profoundly altered the properties of the encoded BetaM proteins, which function as bona fide β-subunits of Na,K-ATPases in lower vertebrates. Eutherian BetaM acquired an extended Glu-rich N-terminal domain resulting in the complete loss of its ancestral function and became a skeletal and cardiac muscle-specific component of the inner nuclear membrane. BetaM is expressed at the highest level during perinatal development and is implicated in gene regulation. Here we report the long-term consequences of Atp1b4 ablation on metabolic parameters in adult mice. Male BetaM-deficient (Atp1b4−/Y) mice have remarkably lower body weight and adiposity than their wild-type littermates, despite higher food intake. Indirect calorimetry shows higher energy expenditure (heat production and oxygen consumption) with a greater spontaneous locomotor activity in Atp1b4−/Y males. Their lower respiratory exchange ratio suggests a greater reliance on fat metabolism compared to their wild-type counterparts. Consistently, Atp1b4−/Y KO mice exhibit enhanced β-oxidation in skeletal muscle, along with improved glucose and insulin tolerance. These robust metabolic changes induced by Atp1b4 disruption demonstrate that eutherian BetaM plays an important role in regulating adult mouse metabolism. This demonstrates that bypassing the co-option of Atp1b4 potentially reduces susceptibility to obesity. Thus, Atp1b4 ablation leading to the loss of evolutionarily acquired BetaM functions serves as a model for a potential alternative pathway in mammalian evolution. Full article

The Wyrtki Jet (WJ), a pivotal surface circulation system in the equatorial Indian Ocean, exerts significant regulatory control over regional climate dynamics through its intense eastward transport characteristics, which modulate water mass exchange, thermohaline balance, and cross-basin energy transfer. To address the scarcity of in situ observational data, this study developed a satellite remote sensing-driven multi-parameter coupled model and reconstructed the WJ’s seasonal variations using the XGBoost machine learning algorithm. The results revealed that wind stress components, sea surface temperature, and wind stress curl serve as the primary drivers of its seasonal dynamics. The XGBoost model demonstrated superior performance in reconstructing WJ’s seasonal variations, achieving coefficients of determination (R²) exceeding 0.97 across all seasons and maintaining root mean square errors (RMSE) below 0.2 m/s across all seasons. The reconstructed currents exhibited strong consistency with the Ocean Surface Current Analysis Real-time (OSCAR) dataset, showing errors below 0.05 m/s in spring and autumn and under 0.1 m/s in summer and winter. The proposed multi-feature integrated modeling framework delivers a high spatiotemporal resolution analytical tool for tropical Indian Ocean circulation dynamics research, while simultaneously establishing critical data infrastructure to decode monsoon current coupling mechanisms, advancing early warning systems for extreme climatic events, and optimizing regional marine resource governance. Full article

Image dehazing technology is a crucial component in the fields of intelligent transportation and autonomous driving. However, most existing dehazing algorithms only process images in the spatial domain, failing to fully exploit the rich information in the frequency domain, which leads to residual haze in the images. To address this issue, we propose a novel Frequency-domain Information Guided Symmetric Dual-branch Dehazing Network (FIGD-Net), which utilizes the spatial branch to extract local haze features and the frequency branch to capture the global haze distribution, thereby guiding the feature learning process in the spatial branch. The FIGD-Net mainly consists of three key modules: the Frequency Detail Extraction Module (FDEM), the Dual-Domain Multi-scale Feature Extraction Module (DMFEM), and the Dual-Domain Guidance Module (DGM). First, the FDEM employs the Discrete Cosine Transform (DCT) to convert the spatial domain into the frequency domain. It then selectively extracts high-frequency and low-frequency features based on predefined proportions. The high-frequency features, which contain haze-related information, are correlated with the overall characteristics of the low-frequency features to enhance the representation of haze attributes. Next, the DMFEM utilizes stacked residual blocks and gradient feature flows to capture local detail features. Specifically, frequency-guided weights are applied to adjust the focus of feature channels, thereby improving the module’s ability to capture multi-scale features and distinguish haze features. Finally, the DGM adjusts channel weights guided by frequency information. This smooths out redundant signals and enables cross-branch information exchange, which helps to restore the original image colors. Extensive experiments demonstrate that the proposed FIGD-Net achieves superior dehazing performance on multiple synthetic and real-world datasets. Full article

Hydrogen production through electrolysis of water can achieve efficient, stable and diversified utilization of renewable energy. To this end, a hybrid electrolyzer system for hydrogen production based on bi-layer optimization is constructed. Firstly, the wind and photovoltaic power is decomposed into high-frequency and low-frequency components by an adaptive wavelet packet. The low-frequency power is allocated to the alkaline electrolyzers (AWE) to ensure its stability, and the high-frequency power is allocated to the proton exchange membrane electrolyzers (PEM) with a faster response characteristic, thereby improving the energy utilization rate. This paper proposes a bi-layer optimization model, in which the upper-layer objective is to minimize the cost of mixed hydrogen production, and the lower-layer optimization objective is to maximize the utilization rate of renewable energy. The differential evolution algorithm optimizes the upper-layer objective, with results sent to the lower layer. Then, the YALMIP toolbox is used to solve the lower-layer objective. Through case analysis, the optimal proportion of AWE and PEM hydrogen electrolyzers obtained by this optimization method is 89.5 and 10.5, respectively. Compared with a single type of electrolyzer, the method proposed in this paper effectively improves the energy utilization efficiency and reduces the cost of hydrogen production. Full article

This paper aims to enhance operational efficiency in the labor-intensive production of composite wind turbine blades, which are critical components of renewable energy systems. The study was conducted at a wind energy facility in Türkiye, integrating the Single-Minute Exchange of Die (SMED) methodology with a Multi-Mode Resource-Constrained Project Scheduling Problem (MRCPSP) model to reduce production cycle time and optimize labor utilization. An operational time analysis was used to identify and classify non-value-adding activities. SMED principles were then adapted to the fixed-position manufacturing environment, enabling the conversion of internal setup activities into external ones and facilitating task parallelization. These improvements significantly increased productivity and labor efficiency. Subsequently, a scheduling model was developed to optimize the sequence of operations while accounting for activity precedence and resource constraints. As a result, the proposed approach reduced cycle time by 28.6% and increased average labor utilization from 68% to 87%. Scenario analyses confirmed the robustness of the model under varying levels of workforce availability. The findings demonstrate that integrating lean manufacturing techniques with optimization-based scheduling can yield substantial efficiency gains without requiring major capital investment. Moreover, the proposed approach offers practical insights into workforce planning and production scheduling in renewable energy manufacturing environments. Full article

Through the use of heterogeneous catalysts, catalytic ozone oxidation technology, an effective and eco-friendly advanced oxidation process (AOP), facilitates the breakdown of ozone into reactive oxygen species (like ·OH) and greatly increases the mineralization efficiency of pollutants. This study examines the development of heterogeneous ozone catalysts through a critical evaluation of the five primary preparation techniques: ion exchange, sol–gel, coprecipitation, impregnation, and hydrothermal synthesis. Each preparation method’s inherent qualities, benefits, drawbacks, and performance variations are methodically investigated, with an emphasis on how they affect the breakdown of different resistant organic compounds. Even though heterogeneous catalysts are more stable and reusable than homogeneous catalysts, they continue to face issues like active component leaching, restricted mass transfer, and ambiguous mechanisms. In order to determine the key paths for catalyst selection in catalytic ozone treatment going forward, the main goal of this review is to provide an overview of the accomplishments in the field of the heterogeneous ozone catalyst treatment of wastewater that is difficult to degrade. Full article

Stream metabolism is traditionally defined as the combined metabolism of all aerobic organisms in a stream. Its component processes of oxygenic photosynthesis and aerobic respiration create and consume dissolved oxygen (DO) and therefore can be measured using time series of DO concentration, solar radiation, and water temperature, in conjunction with a model of DO dynamics that includes photosynthesis, respiration, and oxygen exchange with the atmosphere. A complication is that stream communities typically exhibit pronounced longitudinal heterogeneity in habitat type (e.g., shaded versus unshaded reaches) and species composition and abundance. The influence of a given stream reach and associated community on DO concentration propagates downstream with the current, gradually being replaced, over a transition zone, by the influence of the next downstream reach. Knowing the approximate length of this transition zone is important when estimating stream metabolism with one-station DO monitoring, since it indicates which stream reach and associated community the metabolism estimates apply to. We propose new methods for estimating the transition-zone length and for estimating the proportions of DO at a given location in a stream reach that entered the reach from upstream, from photosynthesis within the reach, and from atmospheric uptake within the reach. We also propose methods for estimating the residence-time distribution of DO present at a given stream location, and the corresponding distribution of upstream distances at which the DO entered the stream. Both distributions are approximately exponential. Thus, habitat immediately upstream of the sonde has the greatest influence on metabolism estimates with one-station monitoring, and it is therefore important to place the sonde so this habitat is representative of the study reach. Full article

The MENA region, with its high solar potential and increasing investments in renewable energy, is transitioning away from fossil fuels toward more sustainable energy systems. To fully benefit from this transition and address issues such as intermittency and energy storage, “green” hydrogen is emerging as a key parameter. When produced using simple and cost-effective technologies like linear Fresnel reflector (LFR), it offers a practical solution. Therefore, assessing the potential of hydrogen production from LFR technology is essential to support the development of the energy sector and promote local industrial growth. This study investigates “green” hydrogen production using a 50 MW concentrated solar power (CSP) system based on LFR technology, where the CSP system generates electricity to power a proton exchange membrane electrolyzer for hydrogen production for three locations, including Ain Beni Mathar in Morocco, Assiout in Egypt, and Tabuk in Saudi Arabia. The results show that Tabuk achieved the highest annual hydrogen production (45.02 kg/kWe), followed by Assiout (38.72 kg/kWe) and Ain Beni Mathar (32.42 kg/kWe), with corresponding levelized costs of hydrogen (LCOH₂) of 6.47 USD/kg, 6.84 USD/kg, and 7.35 USD/kg, respectively. In addition, several sensitivity analyses were conducted addressing the impact of thermal energy storage (TES) on the hydrogen production and costs, the effect of reduced investment costs resulting from the local manufacturing of LFR components, and the futuristic assumption of the electrolyzer cost drop. The integration of TES enhanced hydrogen output and reduced LCOH₂ by up to 9%. Additionally, a future PEM electrolyzer costs projected for 2030 showed that LCOH₂ could decrease by up to 1.3 USD/kg depending on site conditions. These findings demonstrate that combining TES with cost optimization strategies can significantly improve both technical performance and economic feasibility in the MENA region. Full article

Plant growth-promoting rhizobacteria (PGPR) have significant potential for enhancing soil quality and plant growth; however, their agricultural application is limited by challenges such as immobilization and desiccation vulnerability. Background: This study addressed PGPR solid formulation by applying JetCutter-assisted immobilization technology to PGPR strains isolated from the rhizosphere of hazelnut (Corylus avellana). Methods: Four immobilized PGPR strains were evaluated under controlled greenhouse conditions: Serratia proteamaculans, Pseudomonas mohnii, Pseudomonas baetica, and Bacillus safensis. Their effects on root development, gas exchange parameters, dissolved organic carbon (DOC), and soil enzymatic activities (phosphatase, urease, protease, and β-glucosidase) were assessed. Principal component analysis (PCA) was used to identify the top-performing strain. Results: Treatment with encapsulated bacteria resulted in a 27% increase in DOC compared to controls (p < 0.05), while phosphatase and urease activities increased by 35% and 28%, respectively. Root length and volume improved by 18% and 22%, respectively, with PCA identifying P. baetica as the most effective strain. Conclusions: Immobilized Gram-negative PGPR strains enhanced root development and soil biochemical activity in hazelnuts, whereas B. safensis enhanced photosynthesis but had minimal impact on soil properties. These results highlight functional differences and support the use of PGPR immobilization to promote early plant establishment. Full article