Search Results (6,696)

Soil organic carbon (SOC) plays a critical role in the global carbon cycle and serves as a sensitive indicator of climate change impacts, with its dynamics significantly influencing regional ecological security and sustainable development. This study focuses on the Songnen Plain in Northeast China—a key black soil agricultural region increasingly affected by water erosion, primarily through surface runoff and rill formation on gently sloping cultivated land. We aim to investigate the spatiotemporal dynamics of SOC stocks across different cultivated land erosion zones under projected future climate change scenarios. To quantify current and future SOC stocks, we applied a boosted regression tree (BRT) model based on 130 topsoil samples (0–30 cm) and eight environmental variables representing topographic and climatic conditions. The model demonstrated strong predictive performance through 10-fold cross-validation, yielding high R² and Lin’s concordance correlation coefficient (LCCC) values, as well as low mean absolute error (MAE) and root mean square error (RMSE). Key drivers of SOC stock spatial variation were identified as mean annual temperature, elevation, and slope aspect. Using a space-for-time substitution approach, we projected SOC stocks under the SSP245 and SSP585 climate scenarios for the 2050s and 2090s. Results indicate a decline of 177.66 Tg C (SSP245) and 186.44 Tg C (SSP585) by the 2050s relative to 2023 levels. By the 2090s, SOC losses under SSP245 and SSP585 are projected to reach 2.84% and 1.41%, respectively, highlighting divergent carbon dynamics under varying emission pathways. Spatially, SOC stocks were predominantly located in areas of slight (67%) and light (22%) water erosion, underscoring the linkage between erosion intensity and carbon distribution. This study underscores the importance of incorporating both climate and anthropogenic influences in SOC assessments. The resulting high-resolution SOC distribution map provides a scientific basis for targeted ecological restoration, black soil conservation, and sustainable land management in the Songnen Plain, thereby supporting regional climate resilience and China’s “dual carbon” goals. These insights also contribute to global efforts in enhancing soil carbon sequestration and achieving carbon neutrality goals. Full article

The Warta River basin, Poland’s third-largest basin, is highly vulnerable to drought, which occurs in both cold and warm seasons. This study examined meteorological and hydrological droughts using daily temperature and precipitation data from 211 meteorological stations and discharge data from 15 hydrological gauges for 2000–2020. Four indicators were applied: SPI and SPEI for meteorological drought, and SRI and ThLM for hydrological drought. The analysis revealed prolonged droughts and a systematic decline in SRI values, especially from March to September. The longest event, a shallow drought, lasted 555 days between 2019 and 2020 at the Sławsk gauge. The period from 2018 to 2020 was particularly severe, with drought intensity increasing and affecting 70–80% of river flows, while events persisted longer than usual. Water withdrawals, especially for municipal use, further reduced river levels. The section between Uniejów and Oborniki, located downstream of one of Poland’s largest reservoirs, proved most vulnerable to hydrological drought. Overall, results indicate a deteriorating water situation in the Warta basin, with the most significant deficits in spring and summer. These trends pose serious challenges for water management and water supply security. An improved understanding of meteorological and hydrological droughts and their impact is essential for managing the water–food–environment–energy nexus, including restrictions on water use for domestic, economic, and agricultural purposes, as well as the functioning of aquatic ecosystems. Full article

In the era of digital intelligence, information literacy (IL) competency has become a critical indicator for measuring the comprehensive quality and sustainable development potential of university’s education. Using Yancheng Institute of Technology as a case study, this study systematically elucidates the connotation and current development status of college students’ IL within the framework of sustainable development. An evaluation index system is constructed, comprising four dimensions: information awareness and attitude, information ethics, law and security, information knowledge and skills, and information integration and innovation. The study employs the Analytic Hierarchy Process (AHP) to determine the weights of indicators at various levels and integrates the Fuzzy Comprehensive Evaluation Method (FCEM) to establish a quantitative assessment model for IL competency. Empirical research demonstrates that the proposed model effectively enables a multidimensional and quantitative evaluation of students’ IL, with results that exhibit sound scientific validity and applicability. Based on the analysis, specific strategies are proposed to enhance students’ IL from the perspectives of curriculum design, teaching models, and library services, thereby providing theoretical references and practical pathways for advancing informatization and sustainable development in higher education. Full article

The growing importance of data as a driver of the digital economy is promoting the creation of data spaces for the secure and controlled exchange of data between organizations. Data governance is emerging as an essential pillar to ensure efficient, ethical and transparent access and use of data in these ecosystems. The article reviews the state of the art to identify the specific requirements that data governance must address in data spaces and proposes a reference enterprise architecture to facilitate the design, development and implementation of a data governance system for a data space scenario. The proposed framework has already been formally defined and validated in the context of Industry 4.0, and is now adapted to the particular characteristics and needs of data spaces. This architecture focuses on key aspects of data governance in data spaces, such as new requirements, principles, organization, roles and responsibilities, and data quality, security and metadata management, as well as the data lifecycle in the data space. This research contributes to guiding data space government bodies to formalize data strategies and high-level governance principles in concrete architectural components that establish the capacities to be implemented within the data ecosystem. To support practical adoption, this work also provides clarifying examples of different blocks of architecture. Full article

Due to the important role of quantum information technology in the future development of science and technology, researchers have extensively studied the preparation, characterization, and application of quantum systems. It is of great significance to further study the universality and generalization of multi-qubit entangled states. Especially in quantum communication, the actual quantum system is always affected by various noises from the environment. Noise has a significant impact on the properties of the actual quantum system, so we study the effects of noise on a prepared two-photon four-qubit state by two methods. We experimentally simulated the most common bit-flip noise in quantum systems. The law of evolution of the fidelity of two-dimensional four-qubit states and violation of the Mermin inequality and the Ardehali inequality for LR under different levels of bit-flip noise are investigated. The experimental results show that entanglement fidelity and nonlocality can be used to judge the degree of noise interference in the quantum channel and, thus, judge the security of the quantum communication channel. This judgment is of great significance for the realization of practical long-distance multi-node quantum communication. Full article

Increasing the nutritional composition of food is a strategy to add added value to products in key agrochains, contributing to food security, and providing nutritional compounds available to improve selected nutritional deficiencies. An increased level of β-carotenes is an important contribution to reducing vitamin A deficiency. In Colombia, the Bioversity-CIAT alliance and Agrosavia evaluated eight cassava genotypes with the aim of identifying promising candidates for commercial release adapted to Caribbean region in Colombia. Experimental genotypes were established together with two checks, in six locations representing dry and humid Caribbean region. Agronomic evaluations, combined with culinary quality assessments and participatory evaluations of consumer preferences, enabled a comprehensive analysis of each genotype. The experimental genotypes exhibited different plant architecture, with some showing greater height and higher first branching than current varieties. However, excessive plant height in certain genotypes led to increased susceptibility to lodging, negatively affecting the quality of planting material. While only a few genotypes matched the check varieties in root yield (20 T/ha), several demonstrated significantly improved nutritional quality due to higher accumulation of total and β-carotenes (>8 µg/gr and >5 µg/gr, respectively) compared to current varieties (<2 µg/gr and 1.5 µg/gr, respectively). Cooking quality and consumer acceptance were key determinants in the final selection. Among the evaluated lines, genotype GM3426-5 stood out for its favorable agronomic performance, high provitamin A content, and excellent root and cooking quality. Nevertheless, further steps are required before its commercial release, as the product profile for cassava destined for human consumption must prioritize food quality and consumer preferences. Full article

Water and land resources are fundamental to agricultural production, and their spatiotemporal matching and utilization efficiency have a profound impact on agricultural sustainability and food security. Utilizing data from 25 counties in Northern Shaanxi (NS) from 2010 to 2021, this study applied the Gini coefficient, generalized matching coefficient, spatial correlation analysis, and clustering techniques to analyze the spatiotemporal matching patterns of agricultural water and land resources (AWLRs) and propose a functional zoning scheme. The results revealed significant spatial disparities in AWLR matching. The AWLR matching coefficient in NS was below the provincial average and substantially lower than the national average, indicating a generally poor level of matching. From 2010 to 2021, the Gini coefficient of AWLR decreased, reflecting an improvement from a severe mismatch to a generally balanced state. A significant positive spatial correlation was observed between AWLR matching and agricultural development levels. Counties with high AWLR matching but low agricultural development were mainly concentrated in the north, whereas southern counties exhibited both high AWLR matching and high agricultural development. The coordinated development degrees among agricultural development level, agricultural water use benefit, and cultivated land use benefit in the 25 counties were at low or relatively low levels. Furthermore, the K-Means++-AHC clustering algorithm demonstrated better applicability for functional zoning, dividing NS into four distinct agricultural zones: Zone I (good AWLR match but low agricultural development); Zone II (low utilization efficiency and AWLR match); Zone III (water scarcity and high land reclamation, sustaining high agricultural development despite poor AWLR match); and Zone IV (the core agricultural area with comprehensive advantages). The results clarify the matching degree of AWLRs and their utilization potential in NS and the zoning framework will guide targeted interventions to enhance agricultural efficiency in water-scarce regions. Full article

The COVID-19 pandemic demonstrated both the transformative capacity of vaccine innovation and the persistent inequities that accompany emergency access, underscoring the critical need for stronger collaboration between global health governance and the vaccine industry. Influenza pandemics remain inevitable threats. The continued emergence of avian influenza strains such as H5N1 reinforces the necessity of robust preparedness. This perspective examines the underutilization of private sector vaccine manufacturers in current pandemic influenza frameworks and identifies three central areas where industry participation is indispensable: predictable vaccine demand through robust seasonal influenza programs, economic incentives that de-risk investments in research and development, and diversification of vaccine platforms to expand response capacity. In addition, regionalizing manufacturing, advancing collaborative regulatory models, and negotiating export waivers are presented as potential mechanisms to strengthen equity and supply security. The review highlights demand-based tiered pricing and Advance Purchase Agreements as practical tools to align commercial incentives with public health priorities. Furthermore, it makes the case for embedding private sector representation and knowledge into top-level decision-making and preparedness planning, ensuring investment in innovation is aligned with global health objectives. Ultimately, true pandemic influenza readiness depends on building a sustained seasonal influenza market, embedding private sector engagement into governance structures, and fostering mutual trust to ensure timely access and equitable protection for populations worldwide. Full article

Shrub communities play an irreplaceable role in maintaining ecological security in the stressed habitat areas of Northwest China. In these areas, multiple types of shrublands coexist simultaneously. Their diversity levels and community assembly processes may perform different patterns along different stress gradients. This study using linear model fitting, principal component analysis, analyzed the species and phylogenetic diversity of desert, alpine, and secondary shrublands along the gradients of environmental stress factors such as topography, soil, and climate, which reflect low temperature, human disturbance, and drought stress habitats. The changing trend of the phylogenetic structure of different types of shrublands was also studied with using variance decomposition, and phylogenetic structure analysis, which reveals their diversity maintenance mechanisms along environmental stress gradients. The research shows that (1) the mean annual temperature is the main environmental factor shaping the diversity patterns and maintenance processes of shrub communities because low temperatures may lead to habitat filtering; (2) in the western Loess Plateau, the community assembly of different types of shrublands is dominated by deterministic processes, but the diversity and assembly patterns of different shrublands are inconsistent across different environmental stress gradients. Systematic research on the diversity characteristics and assembly patterns of different shrub communities is of great significance for clarifying the restoration, succession, and stability of stressed habitat areas. Full article

With the continuous growth of global communication demands, the space-ground integrated optical network (SGION), composed of the satellite optical network (SON) and terrestrial optical network (TON), has gradually become a critical component of global communication systems due to its wide coverage, low latency, and large bandwidth. However, although the high directivity of laser communication can significantly enhance the security of data transmission, it still carries the risk of being eavesdropped on during the process of service routing. To resist eavesdropping attacks during service transmission in the SGION, this paper proposes a secure routing scheme named dynamic multipath secure routing (DMSR). In DMSR, a metric called the service eavesdropping ratio (SER) is defined to quantify the service leakage severity. The objective of DMSR is to reduce each service’s SER by switching its routing path proactively. To realize DMSR, heuristic algorithms are developed to sequentially search for optimal routing paths for service path switching in the TON and SGION. Finally, simulation results demonstrate that DMSR can achieve trade-offs between secure service transmission and network performance at different levels by adjusting its system parameters. Furthermore, the DMSR scheme significantly reduces the SER compared to the baseline schemes, while introducing acceptable increases in computation overhead and service latency. Full article

Against the backdrop of expanding off-farm employment, it is of great practical significance to examine how off-farm employment affects grain production and its underlying mechanisms, in order to build a more stable and sustainable national food security system. Drawing on micro-level data from wheat-producing households in the national Rural Fixed Observation Points survey from 2004 to 2021, this study systematically investigates the impact of off-farm employment on wheat planting decisions and the channels through which it operates. The findings reveal the following: (1) Off-farm employment encourages farmers to adjust their factor input structure and crop choices, leading to an increased proportion of wheat sown area. (2) Agricultural socialized services, especially mechanized operations, enhance the feasibility of factor substitution and effectively channel off-farm income into agricultural investment. Furthermore, the number of service providers at the village level plays a significant moderating role in this process; the more adequate the service supply, the stronger the positive effect of off-farm employment on wheat cultivation. (3) The influence of off-farm employment on wheat production is more pronounced in plain regions with favorable topographic conditions and among large-scale farming households. Based on these findings, the study recommends improving the agricultural service system, promoting better coordination between off-farm employment and agricultural development, and fostering a more stable and sustainable support system for grain production. Full article

Background: Antimicrobial resistance (AMR) in Legionella pneumophila is emerging as a concern, particularly with resistance to macrolides and fluoroquinolones. Although clinically significant resistance in Legionella pneumophila remains uncommon, systematic genomic surveillance using whole-genome sequencing (WGS) is needed to anticipate treatment failure as metagenomic diagnostics move toward routine use. Objectives: We assessed the UK Health Security Agency AMR pipeline for predicting resistance in L. pneumophila by analysing 522 L. pneumophila isolates from England and Wales (2020–2023) together with nine database sequences that carry confirmed 23S rRNA mutations conferring high-level azithromycin resistance. The objective of the present study was to examine the presence of antimicrobial resistance genes (ARGs) in L. pneumophila isolates and to determine whether they exhibited phenotypic resistance through minimum inhibitory concentration (MIC) testing. Methods: Serogroups (sgs) were determined using an in-house qPCR assay, and L. pneumophila non-sg1 isolates were serogrouped using the Dresden monoclonal antibody (mAb) typing method. Sequence types were determined using the standard sequence-based typing method by Sanger sequencing. WGS reads were screened against standard AMR databases to identify resistance genes and resistance-mediating mutations. Agar dilution measured MICs for azithromycin, erythromycin, ampicillin, levofloxacin, tetracycline and spectinomycin in isolates possessing the bla_OXA-29, lpeAB or aph(9)-Ia gene. Results: AMR screening detected lpeAB, two allelic β-lactamase variants (bla_OXA-29 and bla_LoxA) and aph(9)-Ia in 165 of the 522 L. pneumophila isolates, while all high-azithromycin MIC reference sequences contained the expected 23S mutation. Only lpeAB was associated with a significant twofold elevation in macrolide MICs. Neither β-lactamase variant increased ampicillin MICs, and aph(9)-Ia carriage did not correlate with higher spectinomycin MICs. Conclusions: Advanced genomic analytics can now deliver timely therapeutic guidance, yet database-flagged genes may not translate into phenotypic resistance. Continuous pairing of curated mutation catalogues with confirmatory testing remains essential for distinguishing clinically actionable determinants such as 23S mutations and lpeAB from silent markers like bla_OXA-29 and aph (9)-Ia. Full article

Meteorological droughts have been occurring with greater frequency and intensity, impacting water security in various regions. Between 2013 and 2015, the Paraopeba River Basin in southeast Brazil experienced its most severe drought in the last 70 years, resulting in low levels in the Paraopeba system reservoirs, which supplies 53% of the Metropolitan Region of Belo Horizonte, the third largest metropolitan area in Brazil. This study evaluated the climate models’ performance from the NEX-GDDP-CMIP6 through drought indices projections, specifically the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). The results showed that seven climate models can represent the current climate in the basin. For the drought’s projection, the indices were used in two time scales (six and twelve months) for both the current climate and two future scenarios (SSP245 and SSP585). Our results highlight the intensification of droughts throughout the twenty-first century, with greater intensification in the SSP585 scenario. The SPEI indicated trends towards drier conditions, particularly under the SSP585 scenario and on the twelve-month timescale. These findings demonstrate the relevance of climate change and drought indices on the projections, supporting public policies for mitigation and adaptation, especially in strategic regions for water supply and hydro-electric generation. Full article

Background: Generating electricity from renewable sources continues to receive significant attention from both scholars and professional communities. This is mainly because traditional energy use harms public health, threatens biodiversity, and increases pollution, particularly in developing countries. Meanwhile, renewable technologies are considered one of the most effective solutions to enrich energy security for future usage with clean practices and affordable prices. However, planning such applications may become complex due to the convolution of many technical, economic, environmental, and social dimensions, particularly from a supply chain management viewpoint. Methods: The paper identifies the dimensions affecting the supply chain variables of downstream processes in renewable energy supply systems, especially for generating electricity in Egypt. Also, this paper investigates the relationships between the dimensions of renewable energy supply systems and the downstream supply chain variables that are closely related to the Egyptian energy sector. Results: The different relationships between these indicators and downstream supply chain variables are revealed. Conclusions: This study employed conceptual causality diagramming to organize these relationships harmoniously, which helps to analyze the behavior of the supply chain during the transitions to renewable energy applications and its implications, whether at the managerial or policy and procedural levels. Full article

The End–Edge–Cloud (EEC) paradigm hierarchically orchestrates Internet of Things (IoT) devices, edge nodes, and cloud, optimizing system performance for both delay-sensitive data and compute-intensive processing tasks. Securing IoT data sharing in the EEC-driven paradigm while maintaining data traceability poses critical challenges. In this paper we propose STDSM, a symmetry-enhanced secure and traceable data sharing model for the EEC-driven data sharing paradigm. STDSM enables IoT data owners to share data securely by attaching symmetric security labels (for secrecy and integrity) to their data. This mechanism symmetrically controls both data outflow and inflow. Furthermore, STDSM can also track data user identity. Subsequently, the security properties of STDSM, including data confidentiality, integrity, and identity traceability, are formally verified; the verification takes 280 ms, using a novel approach that combines High-Level Petri Net modeling with the satisfiability modulo theories library and the Z3 solver. In addition, our experimental results show that STDSM reduces time overhead by up to 15% while providing enhanced traceability. Full article