Search Results (1,193)

Salinity and drought are major abiotic stresses responsible for substantial losses in global agricultural productivity, particularly in arid and semi-arid regions. Although Bacillus spp. are widely studied as plant growth-promoting rhizobacteria (PGPR) capable of enhancing plant tolerance to abiotic stress, the extent to which this research has addressed combined salinity and drought stress remains underexplored. This study conducted a bibliometric analysis of scientific output and experimental evidence available in the Scopus-indexed literature published between 2016 and 2024 on Bacillus spp. as PGPR under combined salinity and drought stress conditions. A total of 479 documents were analyzed using the Bibliometrix R package v. 5.4.1 in R v. 4.5.3 and VOSviewer v. 1.6.20, applying Bradford’s and Lotka’s laws, keyword co-occurrence analysis, and citation analysis. Scientific output exhibited a compound annual growth rate of 24.5%, reaching 103 publications in 2024. China, India, and Pakistan were the leading contributors. Among the 495 eligible studies, only 2 studies identified through the primary Scopus search experimentally evaluated Bacillus spp. as PGPR under combined salinity and drought stress conditions. A third study was identified through a complementary external search, revealing a critical gap in experimental in vivo evidence under combined stress conditions. Addressing this gap is essential for advancing effective bioinoculant development for sustainable agriculture under combined abiotic stresses. Full article

The accumulation and persistence of plastic waste have made microbial plastic biodegradation an important topic in pollution control, environmental remediation, and sustainable materials management. This study combines a mini-review with bibliometric analysis to link mechanistic understanding with global research trends in microbial plastic biodegradation from 2000 to 2025. The mini-review summarizes polymer weathering and fragmentation, microbial colonization and biofilm formation, extracellular depolymerization or oxidative chain cleavage, uptake and intracellular catabolism of plastic-derived intermediates, physiological regulation, ecological interactions, and potential applications in bioremediation and upcycling. Bibliographic records were retrieved from the Web of Science Core Collection and analyzed using bibliometrix, VOSviewer, CiteSpace, and SCImago Graphica. A total of 2959 publications were identified. Publication output increased markedly, especially after 2018, reaching 617 publications in 2025; cumulative citations reached 31,373. China, India, and the United States were the leading contributors. Journal and keyword analyses showed strong links among environmental science, polymer science, microbiology, biotechnology, and engineering. Highly cited publications mainly focused on plastic biodegradability, biodegradable polymers, engineered PET depolymerization, polyethylene degradation, and microbial or enzymatic degradation mechanisms. Keyword evolution revealed a shift from material-oriented topics, including polymer blends, poly(vinyl alcohol), polyesters, morphology, mechanical properties, composites, and polyhydroxyalkanoates, toward degrading enzymes, cutinase-like enzymes, plastic-degrading strains, microbial colonization, fungi, and marine environmental degradation. Overall, microbial plastic biodegradation has evolved from material-centered biodegradability evaluation toward a mechanism-oriented and environment-oriented interdisciplinary field. Full article

Mitigating population exposure to fine particulate matter (PM_2.5) is a core prerequisite for advancing Sustainable Development Goal 11.6.2 and global urban sustainability. This study integrated 0.1° × 0.1° gridded PM_2.5 reanalysis data, WorldPop high-resolution population datasets, and official SDG 11.6.2 scoring records spanning 2000–2019, and adopted multi-scale spatial statistics and population-weighted exposure models to systematically explore the spatiotemporal differentiation of global PM_2.5 concentrations and associated population exposure risks, as well as their coupling relationship with SDG 11.6.2 implementation progress. This study employs ArcGIS 10.6 software to harmonize the spatial scales of multi-source heterogeneous data through spatial statistics and resampling methods, and applies the SDSN (Sustainable Development Solutions Network) standardized scoring framework to quantify long-term progress across regions in meeting urban air quality targets. The results reveal significant latitudinal spatial heterogeneity in global PM_2.5 concentrations, with values ranging from 0.95 to 262.15 μg/m³; severe pollution hotspots exceeding 35 μg/m³ were agglomerated across Asia, Africa and South America, while Canada, Greenland, the Tibetan Plateau and eastern Russia maintained ultra-low PM_2.5 levels below 5 μg/m³. Global SDG 11.6.2 standardized scores rose steadily from 71.05 in 2000 to 76.64 in 2019, with Asia and Africa achieving the most remarkable score growth despite low initial baselines. Regional gaps in target realization remained stark: North America, Oceania and Northern Europe basically met the PM_2.5 sustainability standards, whereas densely populated regions of Asia and Africa faced critical governance challenges. Among nine typical countries, only China and India recorded population-weighted PM_2.5 concentrations above 25 μg/m³ in 2019; China’s air pollution control policies delivered continuous emission reductions after 2013, while India sustained extremely high exposure risks. From 2010 to 2019, the global range of urban population-weighted PM_2.5 concentrations narrowed, yet Afghanistan, Tajikistan and North Korea remained the most severely exposed nations. This study verifies the severe cross-regional inequity of PM_2.5 exposure risks under the SDG framework, and provides multi-scale empirical evidence for differentiated air quality governance and international collaborative interventions to accelerate the delivery of the 2030 sustainable development agenda. Full article

Natural, synthetic, and modified zeolites are widely recognized as versatile materials for environmental remediation due to their high capacity for cation-exchange, adjustable pore structure, and strong chemical stability. These properties enable their effective application in removing diverse contaminants, including heavy metals, ammonium ions, dyes, and various organic pollutants, making them highly relevant in water, wastewater, and soil treatment systems. However, although research in this field has expanded considerably, the overall global development patterns and knowledge structure of zeolite-related studies have not been thoroughly quantified. This study conducts a bibliometric assessment of global research on zeolite applications in water, wastewater, and soil remediation covering the period from 2010 to 2024, using a dataset of 203 peer-reviewed Scopus-indexed publications. The analysis was carried out using VOSviewer to examine publication trends, leading authors, productive countries and institutions, as well as thematic clusters and emerging research directions. The findings indicate a consistent increase in scientific output over the study period, with China, India, Malaysia, and the United States emerging as the most influential contributors in terms of both publication volume and citation impact. Key journals publishing in this area include the Journal of Hazardous Materials, Chemosphere, and Science of the Total Environment. Keyword co-occurrence mapping reveals dominant research themes such as adsorption processes, ion exchange mechanisms, heavy metal remediation, nanostructured materials, and advanced oxidation technologies, highlighting a clear shift toward integrated and hybrid remediation approaches. Overall, the results emphasize the growing significance of modified and composite zeolite materials in enhancing pollutant removal efficiency and supporting sustainable environmental management. This bibliometric evaluation provides a structured overview of the research landscape and offers insights into future directions for zeolite-based remediation technologies. Full article

Accurate and scalable estimation of rock shear strength parameters is essential for remote-sensing-supported geological hazard assessment, slope stability evaluation, and engineering geological mapping. However, determining cohesion and internal friction angle requires multiple triaxial tests under different confining pressures, which are time-consuming, costly, and difficult to apply widely. To support remote-sensing-oriented geoscience and civil engineering applications, this study develops a hybrid machine learning framework for estimating cohesion and internal friction angle from geophysical and mechanical indicators. A cross-source database was compiled from published rock records collected from the Jinchuan mining area in China and the Luhri area in India. After completeness screening and unit harmonization, 213 mixed-lithology cases were retained for modeling, with P-wave velocity, density, uniaxial compressive strength, and tensile strength used as input variables. An Equilibrium Optimizer was coupled with a multilayer perceptron to optimize the network weights and biases, and model performance was evaluated using five-fold cross-validation, independent testing, repeated runs, and comparisons with conventional MLP and several typical machine learning models. The proposed EO–MLP model achieved high prediction accuracy, with test-set coefficient of determination values of 0.946 for internal friction angle and 0.983 for cohesion and corresponding RMSE values of 1.072 and 0.671, respectively. Robust scaler normalization produced the best performance among the three tested normalization strategies. SHapley Additive exPlanations analysis indicated that density was the dominant predictor of cohesion, whereas uniaxial compressive strength and P-wave velocity made the largest contributions to internal friction angle prediction. The proposed framework provides an indirect data-driven tool for estimating shear strength parameters and can complement engineering-geological investigation and rock engineering design. Full article

Medicinal plants constitute an essential component of global biodiversity and have long served as a primary source of traditional and modern therapeutic agents. Forest ecosystems harbor a significant proportion of medicinal plant diversity, providing habitats for numerous species with recognized pharmacological value. However, increasing anthropogenic pressures, including habitat destruction, overexploitation, land-use change, forest fragmentation, and climate change, have contributed to the decline of many medicinal plant populations worldwide. Consequently, a growing number of medicinal forest species are now classified as endangered, threatened, vulnerable, or protected under national and international conservation frameworks. This review synthesizes current scientific knowledge on endangered and protected medicinal plants found in forest ecosystems. A mixed-methods approach combining bibliometric assessment and qualitative literature analysis was employed to evaluate publication trends, geographical distribution, research hotspots, ecological characteristics, genetic resources, pharmacological properties, and conservation strategies related to threatened medicinal forest species. The review identified 77 medicinal plant species of conservation concern distributed across diverse forest regions worldwide, with the highest research activity originating from Asia, particularly India and China. The findings highlight the ecological importance and therapeutic potential of these species while emphasizing the critical threats posed by habitat degradation, unsustainable harvesting, and climate change. Advances in habitat suitability modeling, molecular genetics, ex situ propagation, and conservation planning have improved opportunities for species protection; however, significant knowledge gaps remain regarding population dynamics, long-term conservation effectiveness, and sustainable utilization. Strengthening integrated conservation approaches that combine habitat protection, sustainable management, scientific research, and traditional ecological knowledge is essential for safeguarding endangered medicinal forest plants and ensuring their continued contribution to biodiversity conservation, healthcare, and future drug discovery. Full article

Synthetic nitrogen fertilizer underpins global cereal production, yet a substantial share of applied nitrogen escapes to the atmosphere as nitrous oxide, ammonia, and nitrogen oxides, with significant consequences for climate, air quality, ecosystems, and soil health. Despite extensive research on nitrogen losses and mitigation options, no synthesis has traced the historical intensification of cereal nitrogen use, current emission patterns, and the technological and policy responses to these losses as a single connected trajectory. This review provides that integrated synthesis. This review adopts a gloom-to-glory framing to trace nitrogen fertilizer use in cereal systems from its Green Revolution origins through current emission trends to the technological and policy responses now being deployed, treating these as a single continuous narrative rather than separate bodies of literature. Global nitrogen application in maize, wheat, and rice rose roughly tenfold between 1961 and 2010, and more than half of applied nitrogen across this period was never recovered in harvested grain. This unrecovered fraction partitions across mechanistically distinct loss pathways, i.e., nitrous oxide from soil nitrification and denitrification, ammonia from urea hydrolysis and volatilization, and indirect losses from residual soil nitrate, each carrying separate climate, air quality, and ecosystem consequences. Enhanced-efficiency fertilizers, precision nitrogen management, renewable hydrogen-based ammonia synthesis, and biologically mediated approaches such as nitrification inhibition each demonstrate mitigation potential without compromising yield, though field-scale evidence for the biological route remains limited. Regional case studies from China, India, and the European Union show that national policy has altered nitrogen use trajectories without closing the gap to demonstrated best-practice potential, for reasons specific to each jurisdiction’s regulatory design, price structure, and institutional capacity. The review concludes that the principal barriers to realising cereal production’s glory pathway are no longer primarily mechanistic but lie in measurement coverage, technology transfer to smallholder and developing-region producers, and the economic architecture needed to scale proven mitigation measures across cereal-growing regions. Full article

While green bonds are increasingly used to channel capital towards environmentally responsible projects, their effectiveness depends not only on market growth, but also on the credibility of the institutional frameworks that support the green label. Through focused bibliometric positioning, scoping synthesis and comparative document analysis, the paper examines how seven major green-bond frameworks organise credibility: the EU European Green Bond Standard, the ICMA Green Bond Principles, the Japan Green Bond Guidelines, the ASEAN Green Bond Standards, China’s catalogue-plus-principles framework, India’s Sovereign Green Bond Framework and China’s Sovereign Green Bond Framework 2025. The findings show that frameworks converge in product grammar, including project selection, management of proceeds, reporting and external review, but diverge substantially in credibility architecture, especially regarding external review, supervision, refinancing governance and environmental additionality. Current frameworks generally make green-bond labels more transparent, comparable and verifiable, but not necessarily more additional in environmental terms. Important challenges therefore remain: fragmented standards, greenwashing risks, information asymmetries, weak impact-reporting comparability and limited safeguards against refinancing existing assets. The paper argues that the contribution of green bonds to the green transition depends on how credibility is institutionally organised. Full article

Nano-priming has emerged as a novel technology for improving seed germination, vigour, and stress tolerance, and enhancing nutrient uptake in cereal grains, especially rice and wheat. This study presents a bibliometric analysis of 6302 publications obtained by a Boolean search query from the Scopus database, executed in November 2025. The dataset was further refined by using strict inclusion–exclusion criteria and mapped for the intellectual, geographic, and collaborative structure of the research on the topic under study at the global level. Country-level research productivity, subject-area distribution, annual publication trajectories, source-level publication patterns, and co-authorship networks are part of this study. The analysis revealed a highly skewed global publication distribution dominated by China, India, and Pakistan, which are major global hubs for nanotechnology-assisted seed treatment research, on the nano-priming of seeds. Agricultural sciences, environmental sciences, materials science, and nanotechnology emerged as dominant interdisciplinary contributors to nano-priming research. Annual publication trends continue to show an exponential rise since 2013, driven by growing interests in nanotechnology-enabled crop improvement. Co-authorship analysis revealed dense collaborative clusters centred in South and East Asia, interconnected through key bridging authors. The bibliometric evaluation, together with evidence-based synthesis of experimental studies, highlighted zinc oxide, titanium dioxide, silver, iron oxide, chitosan, and carbon-based nanomaterials as the main hotspots driving physiological enhancement in rice and wheat through enzymatic activation, nutrient uptake, and stress-resilience pathways. Nanotechnology-based seed treatments in rice and wheat offer a promising and sustainable approach to enhance crop productivity, stress tolerance, nutrient-use efficiency, and global food security under changing environmental conditions. Full article

Precision agriculture (PA) has emerged as a transformative approach for improving agricultural productivity, resource-use efficiency, and environmental sustainability through the integration of digital technologies, including Global Positioning Systems (GPSs), Geographic Information Systems (GISs), remote sensing, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), and autonomous systems. Although previous reviews have primarily emphasized technological innovation, adoption trends, or environmental outcomes, they have provided limited synthesis of the economic mechanisms linking technology adoption, resource allocation, production efficiency, investment performance, and long-term sustainability. A structured narrative–systematic review was conducted using peer-reviewed research retrieved from Scopus, Web of Science, and Google Scholar, covering studies published between 2004 and 2026. An integrated analytical framework combining technology adoption theory, resource economics, and production-efficiency models was employed to explain how digital technologies generate economic value while identifying methodological limitations, geographical bias, unresolved research questions, and future research priorities. The review demonstrates that GPS-guided machinery, variable-rate technologies, smart irrigation systems, AI-driven decision-support tools, and integrated digital platforms improve water- and nutrient-use efficiency, labor productivity, production efficiency, and farm profitability. However, economic performance remains highly context-dependent, varying according to farm size, crop type, climatic conditions, institutional support, digital infrastructure, resource scarcity, and policy environments. Methodological inconsistencies in return on investment (ROI), net present value (NPV), lifecycle costing, ecosystem-service valuation, and environmental externality assessment reduce comparability among studies and complicate evidence-based policymaking. The review further identifies a pronounced geographical concentration of evidence in North America, Europe, and Australia, with comparatively limited understanding of PA economics in China, India, Brazil, Sub-Saharan Africa, and Southeast Asia. Persistent challenges include high capital costs, unequal access among smallholder farmers, data governance concerns, interoperability limitations, uncertainty in long-term investment performance, and limited integration of agricultural insurance, climate-risk management, and digital finance. By integrating economic theory, methodological comparison, geographical analysis, sustainability valuation, and policy perspectives within a unified conceptual framework, this review highlights the need for standardized economic evaluation methodologies, broader geographical representation, and interdisciplinary research to support evidence-based policy and the sustainable digital transformation of global agriculture. Full article

Background: Finite element analysis (FEA) has become a cornerstone of dental biomechanics, supporting the simulation of stress, strain, and displacement in biological structures and biomaterials. Methods: This combined bibliometric and narrative review examines the development, geographic and disciplinary distribution, and methodological state of FEA-based dental research by analysing 3379 publications indexed in Scopus between 1969 and 2024. Results: The dataset shows continued exponential growth in annual output, particularly after 2000, with China, the United States, and India as the leading contributors. Journal articles account for the bulk of the literature, and implant dentistry remains the most prominent focus area. The 100 most-cited works concentrate on implant biomechanics, prosthodontics, and scaffold design, while interdisciplinary contributions linking FEA to regenerative biomaterials, orthodontics, and endodontics are increasing. Conclusions: FEA in dentistry is a mature but still rapidly expanding field. Persistent methodological gaps remain, including the routine use of isotropic and linear-elastic bone, idealised osseointegration, static loading, limited patient-specific variability, and scarce in vivo validation. Future work should converge on patient-specific multiscale models, fatigue and contact-aware formulations, standardised validation pipelines, and the integration of artificial intelligence into both pre-processing (mesh generation, parameter identification) and post-processing (surrogate models, outcome prediction). The wider relevance of FEA across orthopaedic, thoracic, and reconstructive biomechanics confirms its role as a unifying computational tool for clinical translation. Full article

Thailand’s ceramic manufacturing tradition possesses a long and distinguished history, reflecting the nation’s rich cultural heritage, artistic excellence, and capacity for technological adaptation. Traditional Thai ceramics extend beyond their functional purposes, serving as important expressions of indigenous knowledge, craftsmanship, social values, and religious beliefs that have been transmitted across generations. While preserving their distinctive Thai characteristics, these ceramic traditions have continuously evolved through cultural exchanges with neighboring civilizations, particularly China and India, as well as later influences from the West. Among the various decorative techniques employed in Thai ceramics, stamping and hand-painted ornamentation are recognized as two of the most significant methods, contributing to the aesthetic and cultural value of ceramic works. These techniques enable ceramic products to embody both artistic expression and practical functionality by harmoniously integrating aesthetic design with reliable craftsmanship. In contemporary manufacturing environments, traditional stamping and painting methods are increasingly integrated with semi-automated processes and advanced ceramic machinery to enhance production efficiency while preserving cultural authenticity. This study proposes an Internet of Things (IoT)-based control system for ceramic stamping and painting machines, designed to support remote operation, real-time monitoring, and performance evaluation, with particular attention given to response time and error characteristics. By incorporating sensors, controllers, and networked communication technologies into ceramic manufacturing equipment, the proposed system establishes a meaningful connection between intelligent automation and traditional artistic practices. Full article

This study examines the association between the fossil fuel share in electricity generation, energy-related climate change mitigation technologies, and CO₂ emissions in four selected major emitting economies—China, the United States, India, and Russia—over the period 1990–2023. Using an extended STIRPAT framework, the analysis considers both consumption-based and territorial CO₂ emissions per capita to distinguish between demand- and production-side perspectives on environmental responsibility. The fossil fuel electricity variable is measured as the combined share of electricity generated from coal, oil, and gas in total electricity generation and is further disaggregated into coal-, oil-, and gas-based shares. Energy-related technological innovation is proxied by the share of climate change mitigation technologies related to energy generation, transmission, or distribution among environment-related technologies. The baseline ECM and Driscoll–Kraay fixed-effects estimates indicate that the aggregate fossil fuel share in electricity generation is positively associated with both emissions measures, while the technology variable is negatively associated with emissions. However, the FMOLS estimates are less consistent, suggesting that long-run coefficients are sensitive to estimator choice. Country-level disaggregated estimates reveal substantial heterogeneity across fuels and countries, with coal-based electricity generation showing the most consistent positive association with emissions in China, India, and the United States. The findings suggest that electricity sector decarbonization in major emitters should prioritize coal substitution, renewable-energy deployment, grid modernization, and targeted energy-technology innovation, while climate responsibility assessments should consider both territorial and consumption-based emissions. Full article

Plant cell, tissue, and organ cultures are increasingly used as controlled platforms for producing pharmaceutically important specialized metabolites. Their productivity can be improved through elicitors, plant biostimulant-like substances, microbial inputs, and nano-enabled delivery systems. However, the regulatory interpretation of these inputs is not determined only by their biological mechanism. It also depends on product composition, formulation, intended use, exposure scenario, and label claim. This review analyzes how elicitors, plant biostimulants, biofertilizer- and bioinput-related concepts, and nano-enabled inputs are positioned within selected regulatory frameworks in the European Union, United States, Canada, Brazil, India, China, and Mexico. The analysis shows that current frameworks increasingly emphasize product identity, efficacy substantiation, safety evidence, and labeling, but they remain fragmented for multifunctional materials that may simultaneously affect nutrient-related processes, abiotic stress tolerance, defense signaling, growth regulation, and specialized metabolism. Nano-enabled and encapsulated formulations create additional challenges because they can modify uptake, persistence, bioavailability, release behavior, residue profiles, and non-target exposure compared with conventional formulations. A clearer distinction is therefore needed between contained biotechnological use in plant biofactories and open-environment agricultural applications. Future regulatory development should move toward formulation-level assessment, claim-specific evidence, nanospecific characterization, traceability, and harmonized terminology to support innovation while ensuring safety, reproducibility, and regulatory clarity. Full article

Machine learning has created new opportunities for gas adsorption research using nanoporous materials, but the field’s evolution remains insufficiently quantified. This study retrieved literature from the Web of Science Core Collection for 2010–2026 and retained 730 valid records from 1581 initial publications after screening. VOSviewer, CiteSpace, and R were used to analyze publication growth, collaboration networks, journal sources, and thematic evolution. Results show that annual output remained generally below 20 before 2019, then increased rapidly and reached approximately 280 publications in 2025, indicating accelerated integration of machine learning with adsorption simulation, material screening, and performance evaluation. The source distribution broadened from a limited set of chemistry and engineering journals to diverse venues, with recent high publication weights in Chemical Engineering Journal, Separation and Purification Technology, ACS Applied Materials & Interfaces, Microporous and Mesoporous Materials, and Journal of Materials Chemistry A. Collaboration analysis identified 10 compact author clusters, including groups associated with Randall Q. Snurr, Seda Keskin, Zhiwei Qiao, Qingyuan Yang, and Chongli Zhong, whereas the weak bridging links among clusters indicate that cross-community collaboration remains limited. Country and institutional analyses show that China, the United States, Canada, Iran, India, South Korea, and the United Kingdom are leading contributors, with Guangzhou University, Koç University, Northwestern University, the Chinese Academy of Sciences, Beijing University of Chemical Technology, and the United States Department of Energy occupying prominent positions. Keyword evolution reveals a shift from adsorption behavior and porous adsorbents toward data-guided material selection, high-throughput screening, deep learning, Bayesian optimization, and performance optimization, offering guidance for data-driven adsorbent discovery. Full article