Search Results (16,328)

Non-grain production of cultivated land has increasingly affected regional food security and the stability of agricultural ecosystems. In traditional rice-producing regions, changes associated with non-rice cultivation, fallow land, rice-fishery integrated farming, and intensive agricultural management are reshaping the spatial structure of paddy landscapes. To identify the long-term spatiotemporal evolution of paddy systems, this study investigated Northern Jiangxi, China, using Landsat surface reflectance imagery from 2000, 2005, 2010, 2015, and 2020 on the Google Earth Engine (GEE) platform. The Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) were used to construct a phenology-based Flooding Frequency (FF) indicator. Based on the annual frequency with which pixels satisfied the condition LSWI > EVI, cultivated land was classified into three categories: non-flooded cropland, standard rice paddy, and high-frequency flooded cropland. In this study, non-flooded cropland was used as an indicator of potential non-rice cultivation rather than as direct evidence of confirmed non-grain production. Landscape metrics, transition matrices, gravity center migration, standard deviation ellipses, and geographically weighted regression (GWR) were then used to examine paddy landscape dynamics, fragmentation patterns, and county-level spatial associations with socioeconomic factors. The results suggest that the paddy system in Northern Jiangxi experienced marked stage-based fluctuations between 2000 and 2020. Standard rice paddy recovered during 2005–2010, whereas non-flooded cropland expanded considerably during 2010–2015, accompanied by intensified paddy landscape fragmentation. Non-flooded cropland was mainly distributed around urban fringes, transport corridors, and some hilly margins. Standard rice paddy was concentrated in traditional grain-producing areas, including the Poyang Lake Plain and the Gan-Fu Plain. High-frequency flooded cropland was primarily located in low-lying lake areas, where its dynamics were likely associated with rice-fishery integrated farming, continuous irrigation, and hydrological fluctuations. Landscape metrics showed that the largest patch index and mean patch size of standard rice paddy declined after 2010, indicating reduced spatial continuity of core paddy fields. The GWR analysis provided auxiliary evidence that total population, per capita gross domestic product (GDP), and urbanization rate were spatially associated with changes in non-flooded cropland at the county level; however, the results should be interpreted as exploratory associations rather than causal mechanisms. Overall, paddy landscape change in Northern Jiangxi was expressed not only through changes in cultivated land area, but also through the reorganization of paddy function, spatial continuity, and land-use intensity. Future cropland protection should therefore move beyond area-based control toward integrated management of quantity, quality, function, and spatial configuration. Future research should further verify these findings using dynamic cropland boundaries, higher-resolution imagery, and more detailed socioeconomic data. Full article

The deep decarbonization of high-emission chemical industries requires green hydrogen–ammonia parks that directly integrate volatile renewable energy with continuous synthesis processes. However, high-resolution, physically consistent operational datasets covering the multi-stage evolution from grid-connected economic dispatch to off-grid resilient islanded operation remain scarce. This paper presents a comprehensive, multi-scenario operational dataset for a green-power, directly connected hydrogen–ammonia chemical park in Jilin, Northern China. Derived from 24 typical meteorological scenarios, the dataset covers grid-connected mode with five daily ammonia production targets (72–36 tons/day) and off-grid mode with dynamic yield maximization under a 195 MWh battery energy storage system. Hourly records are provided for renewable generation, electrolyzer and synthesis unit power consumption, grid exchange, battery state-of-charge, and waste heat recovery. All operational states are strictly validated against physical constraints—equipment load limits, energy conservation laws, thermodynamic recovery bounds, and state-of-charge limits—ensuring engineering feasibility. The dataset is publicly available in CSV format and serves as a benchmark for capacity planning, energy management system development, and flexible production strategy validation. Full article

Biodiesel production offers a promising route towards the achievement of net-zero emissions by 2050. However, current reliance on unsustainable feedstocks and inefficient processes hampers its commercial viability. This study investigates the transesterification of waste cooking oil (WCO) with methanol in a continuous microreactor (1 mm internal diameter) and systematically compares pseudo-homogeneous and biphasic second-order kinetic models for describing the reaction. The biphasic model provided the highest predictive accuracy by explicitly accounting for interfacial mass transfer and phase interactions, whereas the pseudo-homogeneous model offered a simpler formulation with comparable overall statistical performance when model complexity was considered. The activation energy estimated using the biphasic model was 15.61 kJ mol⁻¹, which is lower than values typically reported for homogeneous base-catalysed systems, which is consistent with the enhanced mass-transfer characteristics of the microreactor. Thermodynamic activation parameters were also determined, resulting in an activation enthalpy of 12.93 kJ mol⁻¹, an activation entropy of −272.3 J mol⁻¹ K⁻¹ and an activation free energy of 94.08 kJ mol⁻¹, indicating an energetic barrier to the formation of the activated complex and a more ordered transition state than the reactants. The results demonstrate that explicit treatment of phase interactions improves kinetic prediction while providing practical guidance for selecting kinetic models according to the intended engineering application. These findings support the use of intensified microreactor systems and physically representative kinetic models for the design and scale-up of sustainable biodiesel production processes. Full article

Fused deposition modeling (FDM) of polylactic acid (PLA) is widely used, yet most parameter studies tune one mechanical property at a time and leave the conflicts between properties unresolved. This work treats three responses of FDM PLA together: ultimate tensile strength, flexural strength, and Shore D hardness. A Taguchi L9 orthogonal array varied infill density, raster angle, and layer thickness; signal-to-noise ratios and analysis of variance ranked the factors, linear regression linked the parameters to each response, and the NSGA-II algorithm mapped the trade-off surface between them. Layer thickness proved the leading factor for tensile and flexural strength, while hardness answered mainly to infill density; raster angle stayed weak for every response. The Pareto front showed that low infill favors tensile strength while high infill favors flexural strength and hardness, all at the finest layer setting, and these trends were converted into parameter guidelines for tensile-led, flexure-led, and balanced parts. The statistical limits of the screening design are stated openly, the flexural and hardness campaigns are flagged as provisional, and a replicated, standard-compliant confirmation study is set out as the next step. Full article

To address the separated organization of structural and attribute information in three-dimensional geological modeling for coal mine production, this study presents a three-dimensional geological structure–property coupled modeling method implemented through an integrated voxel-based workflow. A regular voxel model is used as a unified spatial carrier to organize stratigraphic structures, coal seams, boundaries, reserve parameters, and gas content attributes within the same spatial framework. Structural information is first identified under surface and boundary constraints, and attribute values are then assigned within structurally constrained voxel domains. Using production data from the Hemei No. 3 Mine, the method was applied at both mine and working-face scales to evaluate its implementation, engineering consistency, sensitivity, and uncertainty. The results show that the proposed method can jointly represent the coal seam geometry and gas content distribution and can support spatial query and reserve updating. At the mine scale, the voxel-based reserve estimate for the No. 2-1 coal seam differed from the traditional geological block estimate by 1.67%. At the working-face scale, as an engineering consistency check, the relative difference between the voxel-based estimate and the engineering reference estimate decreased from 31% to 8.4% after additional borehole constraints were incorporated. Additional validation and sensitivity tests yielded quantified errors for gas content and working-face coal-seam geometry estimation. The results further show that reserve estimates are affected by voxel resolution and apparent density assumptions, whereas the spatial distribution of gas content estimates is affected by the tested IDW parameters. Therefore, the proposed method provides a practical application-oriented modeling and updating method under the data conditions of the case study, while broader transferability requires further independent validation and more systematic uncertainty analysis. Full article

Poly[(R)-3-hydroxybutyrate] [P(3HB)] is a biological polyester synthesized by microorganisms and can be used as a biodegradable plastic. The higher the molecular weight of P(3HB), the stronger it can be processed into films and fibers. Therefore, high-molecular-weight P(3HB) can be used as high-performance plastics for engineering and specialty applications. The P(3HB) biosynthetic operon consists of three genes, canonically arranged as phaC-phaA-phaB (phaCAB). This study specifically rearranges the phaCAB operon to the phaBCA order to investigate P(3HB) production and its molecular weight from glucose and/or xylose, which can be derived from wood hydrolysates, using Escherichia coli XL1-Blue as a host. By rearranging the gene order to phaBCA, the expression balance of PHA synthase (PhaC, encoded by phaC) and 3HB monomer-supplying enzymes (PhaA and PhaB, encoded by phaA and phaB, respectively) changed, enabling the host to produce P(3HB) with a higher molecular weight than that with the canonical operon. This effect was significant when xylose was used as the carbon source or when a nutritionally rich medium was used. However, the amount of P(3HB) produced by the phaCAB-expressing strain was consistently better than that by the phaBCA-expressing strain. This study establishes that high-molecular-weight P(3HB) can be produced through an integrated approach of operon engineering and wood-derived sugar bioprocessing, offering a sustainable production route for high-performance biodegradable plastics from non-food biomass. Full article

Coal gangue, a major by-product of coal mining, has long posed significant environmental and resource management challenges. With increasing global emphasis on energy transition and environmental sustainability, the comprehensive utilization of coal gangue has emerged as a critical research and policy priority. This review systematically examines the sources, characteristics, environmental impacts, and integrated utilization pathways of coal gangue. First, the formation mechanisms, mineralogical composition, and physicochemical properties of coal gangue are summarized, with particular attention to hazardous constituents and associated environmental risks, including soil and groundwater contamination, atmospheric pollution, and ecological degradation. Subsequently, current technological approaches for coal gangue management and comprehensive utilization are evaluated, including subsidence areas reclamation and underground backfilling, applications in construction materials and energy conversion, extraction of valuable chemical elements and functional materials, ecological soil engineering, and carbon sequestration. The potential contributions of these pathways to waste reduction, resource efficiency, and low-carbon development are critically discussed. Finally, key environmental, technological, and socio-economic considerations influencing sustainable coal gangue utilization are emphasized. This review provides a comprehensive synthesis of existing knowledge and identifies future research directions aimed at advancing environmentally sound, economically viable, and large-scale utilization strategies. The findings are intended to support researchers, policymakers, and industry stakeholders in promoting circular resource systems and sustainable development. Full article

Background: Live biotherapeutic products (LBPs) require robust genetic stability and effective biocontainment to support safe clinical translation and regulatory acceptance. Aim: This study presents a single-step chromosomal engineering strategy that integrates auxotrophy-mediated biocontainment with therapeutic gene insertion to support regulatory-oriented live biotherapeutic chassis design. Methods: A no-SCAR genome-editing approach combining CRISPR/Cas9 and λ-Red recombineering was used to generate an Escherichia coli MG1655 ΔilvC::hlyA strain by replacing ilvC with the hlyA gene encoding listeriolysin O. Chromosomal and episomal expression systems were compared for auxotrophy, growth, haemolytic activity, plasmid stability, and intracellular DNA delivery to RAW 264.7 macrophages. Results: Auxotrophy was successfully established and restored by branched-chain amino acid supplementation. Chromosomal integration preserved haemolytic activity and bacterial growth while improving long-term genetic stability and plasmid maintenance compared with episomal expression. Both systems supported intracellular DNA delivery, whereas the chromosomal construct showed improved host-cell preservation under higher bacterial challenge. Conclusions: This proof-of-concept study supports the feasibility of using a single-step chromosomal engineering strategy to combine intrinsic biocontainment with therapeutic-gene integration in an engineered bacterial chassis. Full article

Plant-derived extracellular vesicles (PDEVs) have emerged as promising natural nanocarriers for biomedical applications owing to their distinctive ability to facilitate intercellular communication and transport bioactive molecules. In this review, we employ bibliometric analysis to identify research hotspots and trends, providing a comprehensive overview of these core themes. The bibliometric results reveal a sustained increase in annual publications in this field, with keyword analysis identifying drug delivery, cross-kingdom regulation, immunomodulation, engineering modification, and gut microbiota as five major research themes. The focus of research has evolved from early basic biological characteristics into engineered smart delivery platforms, with the application areas expanding from intestinal inflammation to neurological, metabolic, dermatological, and oncological diseases. This review systematically examines the core directions in this field. It compares the strengths and limitations of mainstream isolation methods and highlights the value of multi-omics integration, covering the molecular mechanisms of ferroptosis and gut microbiota regulation by PDEVs along with engineering strategies such as drug loading, surface modification, and membrane fusion. It also discusses the latest progress in frontier therapeutic applications of PDEVs, including cancer, inflammatory diseases, tissue regeneration and aesthetics, and neurological disorders. Finally, this review summarizes the key challenges confronting the field, including the lack of standardized protocols, production bottlenecks, and engineering obstacles. It also delineates future directions, including establishing international standardization definitions, advancing multi-omics and AI-driven mechanistic elucidation, developing scalable and efficient purification technologies, and executing systematic preclinical safety and pharmacokinetic evaluations to facilitate clinical translation. Full article

Thermal spray coatings have also been adopted as a solution strategy to increase the service life and improve the performance of designed engineered electrochemical energy devices, especially batteries and solid oxide cells. These systems share common attributes of challenges in interfacial stability, degradation in microstructure, and transport limitations in extreme operating conditions. This review revolves around the significance of microstructural coating, that is, distribution of porosity, phase composition, splat bonding, and interface quality in regulating the electrochemical performance. High-entropy alloys, functional graded material, and nanostructured feedstock are also mentioned in the context of how they can be utilized to modify coating properties and make the device more reliable. The processing environments and microstructure development relative to major performance indices, such as ionic/ electronic conductivity, corrosion behavior, and stability, are critically examined. Furthermore, the trade-off between the energy consumed during the synthesis of the powders and the efficiency of deposition of the coating is discussed to give information on sustainable production. Other new approaches involving the use of computational models and artificial intelligence to maximize the processes are also discussed in this review. Generally, this paper creates a process–structure–performance system for the rational development of thermal spray coatings in the next generation of electrochemical-based energy systems. Full article

Remaining useful life (RUL) prediction is critical for improving reliability and supporting predictive maintenance in aero-engine systems. However, existing methods have limitations in jointly modeling the spatial correlations between multi-sensor signals and the temporal evolution characteristics of the degradation process. Hence, this study develops a knowledge-enhanced spatiotemporal framework for system-level aero-engine RUL prediction. Firstly, a graph based on the Pearson correlation coefficient (PCC) is constructed from monitoring data to capture data-driven dependencies among sensors. Afterwards, a thermodynamic-cycle-mechanism prior is incorporated into the PCC-based graph through the Hadamard product, forming a knowledge-enhanced graph that emphasizes physically meaningful sensor relationships. Subsequently, an enhanced graph attention module is designed to extract discriminative spatial representations from the knowledge-enhanced graph. Furthermore, relational representations between adjacent time steps are constructed to capture implicit temporal correlations and local degradation dynamics. Finally, a dual-stream GRU with an attention mechanism is employed to model the fused feature stream and relational feature stream for RUL prediction. Experiments on the CMAPSS and N-CMAPSS datasets demonstrate that the proposed method achieves competitive and overall superior performance compared with nine state-of-the-art methods. KESTF achieves the best average RMSE/Score of 12.83/580 on CMAPSS and 5.94/3468 on N-CMAPSS, validating its effectiveness and robustness. Full article

This study examined awareness, perceived benefits and risks, adoption barriers and future adoption potential for Augmented Wood among construction professionals in South East Nigeria. A quantitative dominant convergent mixed methods design combined a survey of 254 registered architects and engineers with 24 semi-structured interviews. Survey data were analyzed using descriptive statistics, one-sample t-tests, and ordinal logistic regression with 95% confidence intervals reported for all effect sizes. Interview data were analyzed thematically using Cohen’s kappa (κ = 0.81) for inter-rater reliability and integrated with the quantitative findings. Professional awareness was low, with an overall mean of 2.45 on a five-point scale. A one-sample test confirmed that awareness was significantly below the moderate benchmark of 3.00, t(253) = −9.04, p < 0.001, Cohen’s d = −0.57 (95% CI: −0.69, −0.45). Product unavailability, the absence of a regulatory framework and high procurement cost were the most severe barriers, with mean scores of 4.28, 4.17 and 4.11 respectively. Ordinal logistic regression revealed that architects showed greater willingness than engineers to recommend the material to clients (OR = 0.618, 95% CI: 0.444–0.861, p = 0.004), after controlling for years of experience and state of practice, although both groups reported strong readiness for training. Interview accounts explained the conditional nature of this interest, especially the need for local testing, demonstration projects, standards and accessible supply. The findings provide an evidence base for professional education, pilot projects, product certification and policy development in Nigeria and comparable markets. Full article

Robotic systems for search-and-rescue operations require robust, non-line-of-sight victim detection in order to locate trapped individuals behind obstacles with high precision. This paper presents a robotic victim-localization system based on a convolutional neural network—vision transformer (CNN-ViT) architecture trained on an open-source radar dataset for through-wall presence detection. In addition to binary presence detection, the proposed approach uses attention information from the transformer layers to estimate the region of the radar signal most relevant to the victim location. The model is deployed on a robotic platform and tested in an additional realistic environment, where classification and distance-estimation outputs are fused into a heatmap-style spatial representation. This enables the system to localize the estimated victim position on the map generated by the robot. To enhance robustness, the system is evaluated using both a leave-one-subject-out (LOSO) protocol on the original open-source radar dataset and additional experimental sessions collected with the robotic platform. On the original dataset, the model achieved victim-detection F1 scores of 82–96% and distance-estimation MAE of 0.25–0.65 m relative to the robot. On newly collected, previously unseen data, it achieved F1 scores of 72–92% and an MAE of 0.16–0.78 m on correctly classified present samples. The complete pipeline was further deployed on a mobile robot in an environment different from the one used to collect the original dataset, illustrating the potential of the proposed system for practical search-and-rescue scenarios. Full article

Permeability stress sensitivity influences productivity evaluation and stimulation design in tight sandstone reservoirs. Lithic-rich tight sandstone cores from the Baijiantan Formation in the Junggar Basin were investigated using X-ray diffraction and staged effective-stress permeability tests at 25 °C. The plastic mineral index (PM), defined as the summed whole-rock contents of clay minerals, calcite, siderite, and pyrite, was used to classify the samples. Weakly plastic samples S1–S4 had PM values of 28.2–33.5% (PM < 35%), whereas strongly plastic samples S5–S7 had PM values of 37.9–48.3% (PM ≥ 35%); 35% was adopted as a dataset-specific engineering threshold. A complete coupled elastoplastic damage model was developed by incorporating plastic damage and elastic-modulus degradation into the traditional exponential model. The sum of squared errors (SSE) between the measured and predicted normalized permeability values was used to assess model fit; lower SSE values indicate better agreement. Weakly plastic samples were described by the traditional exponential model, with SSE values ranging from 6.0 × 10⁻⁵ to 1.39 × 10⁻³. Strongly plastic samples exhibited pronounced nonlinear permeability decline at effective-stress increments of 10–20 MPa. Across the full 0–20 MPa dataset, the coupled model yielded SSE values ranging from 0.00309 to 0.00498 and lower prediction errors than the traditional exponential model. Sensitivity analysis showed that initial fracture compressibility dominated the overall decline, whereas characteristic plastic strain and damage evolution rate mainly controlled nonlinear decline at effective-stress increments of 10–20 MPa. These results show that mineralogical plasticity classification can guide permeability-model selection for tight sandstones. Full article

Background: Plant synthetic biology reprograms metabolic networks for the sustainable production of high-value compounds. Recent computational advances incorporate machine learning to accelerate the design-build-test-learn (DBTL) cycle, enabling more predictable and scalable engineering in photoautotrophic chassis. However, the translation of AI-generated designs into stable plant phenotypes remains constrained by incomplete plant-specific training datasets, tissue heterogeneity, and limited in vivo validation. Scope: This review examines the convergence of machine learning methods with plant metabolic engineering across four spatial engineering levels: subcellular compartmentalization, cell/tissue/organ-specific control, developmental or inducible regulation, and genome-level organization. Spatial omics is considered a cross-cutting validation layer, and the evidence supporting each technology is classified as plant-demonstrated, non-plant proof-of-concept, or prospective. Conclusions: Integrating predictive machine learning with spatial engineering offers promising strategies to design complex biosynthetic pathways. Hybrid approaches, combining constraint-based metabolic models with generative algorithms, reduce trial-and-error in crop engineering. Future plant synthetic biology is likely to rely increasingly on automated and data-rich workflows to support more predictable plant bioproduction. Full article