Search Results (39,034)

Crown gall disease (CGD), caused by Agrobacterium tumefaciens, is a common plant disease that leads to significant economic losses. Biological control is a sustainable and scalable method for managing CGD. In this study, we isolated three Bacillus strains from the rhizosphere soil of healthy cherry trees and investigated their biocontrol activities and the underlying mechanisms against CGD of cherry trees. The results demonstrate that the three Bacillus strains can effectively inhibit the growth of the pathogenic A. tumefaciens strain XYT58 in vitro under different culture conditions. The pot experiments showed that the three strains could prevent CGD in cherry seedlings. Using PCR amplification, we identified the genes responsible for the synthesis of difficidin, macrolactin, and bacilysin in the three strains. In addition, inoculation with strains WY66 and WY519 significantly enhanced the expression of JA, ET, and SA pathway-related genes in cherry plants. The presence of antibiotic synthesis-related genes in the Bacillus strains and the trigger of plant ISR may explain their ability to control CGD in cherry trees. The findings of this study provide a theoretical basis for the application and development of plant growth-promoting rhizobacteria Bacillus strains in the control of CGD. Full article

Accurate and objective regional landslide risk assessment is crucial for the precise prevention of regional disasters. This study proposes an integrated landslide risk assessment via a landslide susceptibility model based on intelligent optimization algorithms. By simulating the process of rime frost formation, it effectively selects features and assigns weights, overcoming the overfitting issue faced by XGBoost in handling high-dimensional features. By integrating the concepts of landslide susceptibility, dynamic landslide factors, and social vulnerability, an integrated landslide risk index was developed. Further investigation was conducted on how landslide susceptibility results influence risk, identifying regions with varying levels of landslide risk due to spatial heterogeneity in geological background, natural environment, and socio-economic conditions. This study’s results demonstrate that the RIME-XGBoost landslide susceptibility model exhibits superior stability and accuracy, achieving an AUC score of 0.947, which represents an improvement of 0.064 compared to the unoptimized XGBoost model, while the accuracy shows a maximum increase of 0.15 relative to other models. Additionally, an analysis using cloud theory indicates that the model’s expectation and hyper-entropy are minimized. High-risk-level areas, constituting only 1.26% of the total area, are predominantly located in densely populated, economically developed urban regions, where roads and rivers are the key influencing factors. In contrast, low-risk areas, which cover approximately 72% of the total area, are more broadly distributed. The landslide susceptibility predictions notably influence high-risk regions with concentrated populations. Full article

The improvement of energy efficiency (EE) and growing consumption of renewable energy sources (RES) in the commercial and public services sector are playing important roles in seeking to pursue sustainable development in the Baltic States and contributing to the transition to a low-carbon economy. This paper provides findings from a detailed analysis of energy intensity trends in economic sectors from 2005 to 2022 in three countries, considering the role of transformations in the energy and climate framework of the European Union (EU). Based on the Fisher Ideal Index application, the different contributions from improving EE and structural changes are revealed. The dominant role of EE improvements in energy savings is identified in Estonia and Lithuania, and structural changes are dominant in Latvia. Changes in energy-related greenhouse gas (GHG) emissions in the commercial and public services sector and the main determinants of their reduction are examined. Based on applying the Kaya identity and the logarithmic mean Divisia index (LMDI) method, decreasing energy intensity is the most important determinant in all three countries. Due to the different extents of RES deployment, their role was very important in Estonia and Latia but was less effective in Lithuania. Reduction in emission intensity has the largest impact in Latvia. The GHG emissions decreased by 34.1% in Estonia, 17.5% in Latvia, and 16.7% in Lithuania. The results confirm the need for new policies, implementation of relevant EE measures, and the growing contribution from RES in Latvia and Lithuania. Full article

The integration of distributed generation (DG) into distribution networks has significantly increased the strong coupling between power supply capacity and renewable energy acceptance capacity. Addressing this strong coupling while enhancing both capacities presents a critical challenge in modern distribution network development. This study introduces an innovative joint planning and reconstruction strategy for network and energy storage, designed to simultaneously enhance power supply capacity and renewable energy acceptance capacity. The proposed approach employs a bi-level optimization model: the upper level focuses on minimizing economic costs by determining the optimal locations and capacities of energy storage systems and the layout of network lines, while the lower level aims to maximize power supply and renewable energy acceptance capacities by optimizing line switch states. Additionally, this research quantifies the coupling relationship between these two capacities under uncertainty, providing a deeper understanding of their dynamic interaction. Advanced computational techniques, including Monte Carlo simulations and particle swarm optimization (PSO), are utilized to solve the model efficiently. Case studies demonstrate that the proposed strategy effectively enhances both power supply and renewable energy acceptance capacities. Furthermore, exploring the strong coupling relationship between these two capacities under various conditions not only optimizes the utilization of renewable energy in the power system and prevents resource waste, but also helps avoid the volatility impacts of renewable energy uncertainty on the power system in actual planning. Additionally, the network and energy storage joint planning and reconstruction strategy proposed in this study achieves cost minimization under the constraint of limited resources and simultaneously enhanced both capacities. The strategy provides feasible solutions for power grid planning in actual applications. Full article

Verticillium wilt and Fusarium wilt cause significant losses in cotton (Gossypium hirsutum) production and have a significant economic impact. This study determined the functional role of GhSTR1, a member of the ABCG subfamily of ATP-binding cassette (ABC) transporters, that mediates cotton defense responses against various plant pathogens. We identified GhSTR1 as a homolog of STR1 from Medicago truncatula and highlighted its evolutionary conservation and potential role in plant defense mechanisms. Expression profiling revealed that GhSTR1 displays tissue-specific and spatiotemporal dynamics under stress conditions caused by Verticillium dahliae and Fusarium oxysporum. Functional validation using virus-induced gene silencing (VIGS) showed that silencing GhSTR1 improved disease resistance, resulting in milder symptoms, less vascular browning, and reduced fungal growth. Furthermore, the AtSTR1 loss-of-function mutant in Arabidopsis thaliana exhibited similar resistance phenotypes, highlighting the conserved regulatory role of STR1 in pathogen defense. In addition to its role in disease resistance, the mutation of AtSTR1 in Arabidopsis also enhanced the vegetative and reproductive growth of the plant, including increased root length, rosette leaf number, and plant height without compromising drought tolerance. These findings suggest that GhSTR1 mediates a trade-off between defense and growth, offering a potential target for optimizing both traits for crop improvement. This study identifies GhSTR1 as a key regulator of plant–pathogen interactions and growth dynamics, providing a foundation for developing durable strategies to enhance cotton’s resistance and yield under biotic and abiotic stress conditions. Full article

The digital economy is a new economic form that has a significant impact on urban land green use efficiency (ULGUE). With the provincial panel data between 2013 and 2021, this paper empirically tests how the digital economy development level (DEDL) promotes the improvement of ULFUE in China. The key findings include the following: (1) There were significant spatial differences for the ULGUE and DEDL of China. For China’s ULGUE, China shows an ascent after an initial decline trend from 2013 to 2017, but a decline trend after 2017. China’s DEDL took on a rising tendency during the research period. In 2021, China’s DEDL increased by 143.8% compared with that in 2013. (2) The digital economy can obviously promote the ULGUE, but the promotion effect is affected by the urbanization level; with improvements in urbanization level, the impact of that may strengthen. (3) Technological innovation demonstrates a complete intermediary effect between the digital economy and ULGUE; the mediation transmission mechanism of technological innovation is evident. These results have been verified by robustness tests, proving their stability and reliability. The research results will provide new insights into the high-quality utilization of urban land resources. Full article

The livestock high-quality development (LHIQUD) is an important guarantee for promoting livestock modernization and sustainability. The scientific evaluation of LHIQUD and its regulations is significant to solving the key problems in livestock sustainability and promoting LHIQUD. This paper holds that LHIQUD is influenced by the cutting-edge view of economic development and ecological civilization construction, driven by innovation and the change in quality and efficiency. Its fundamental goal is to satisfy people’s growing demand for safe, high-quality agricultural products. Finally, it will realize the sharing of development achievements and enhance competitiveness of the livestock. Based on this, the study sets up an evaluation system for LHIQUD, including indicators of quality and efficiency improvement, coordination and sharing, green development, and innovative development. The entropy method, exploratory spatial data analysis, and kernel density estimation method are used to evaluate the regional LHIQUD of China from 2010 to 2019. The dynamic evolution and spatial auto-correlation analysis results show that (a) Regional LHIQUD in China has generally improved, and there is a decreasing trend from the East, Northeast, and central region to the West, with the characteristics of spatial non-equilibrium. (b) LHIQUD is positively correlated with the regional economic development. (c) The spatial auto-correlation of LHIQUD is not obvious, generally showing a weak agglomeration pattern. Provincial LHIQUD is interdependent in geographical space, with agglomeration characteristics. The findings of this study are invaluable for governments at all levels to accurately comprehend the true state of regional LHIQUD in China, thereby providing a solid foundation for formulating corresponding policies. Full article

Investments are the development core of every economic operator and the driving force for national economic development. While finding the optimal investment point is extremely difficult, every operator may seek to attain a level of fixed assets which allows them to maintain an increase in production and keep their income flowing. The difficulties in finding this optimum may lead to overinvestment. Hence, this paper estimates the parameters of the production function at various investment levels. Its purpose is to identify the relationship between the investment levels, the use of productive inputs, and growth or decline in production (output) levels. This study used microdata for 3273 Polish farms, as retrieved from the FADN (Farm Accountancy Data Network). The differences found at various farm investment levels allow for highlighting some problematic areas, e.g., in the context of excessive capital use relative to yearly increments in production values. The proposed method of analyzing overinvestment based on the production function can be extended to other countries. According to this paper, farms that invested too little or too much in relation to their production potential showed the worst economic performances, including the greatest declines in production. Full article

Plateau ecological vulnerability areas are experiencing substantial ecological challenges that threaten the integrity of ecological networks (ENs) due to irrational human activities, leading to habitat fragmentation and ecological connectivity degradation. The objectives of this study focus on understanding the structure, connectivity, and responses of ENs to construction land, crucial for maintaining ecological sustainability. Employing the circuit theory, the Minimum Cumulative Resistance (MCR) model, and complex network analysis methods, the ENs are constructed and the evolution characteristics are analyzed. The Geographically Weighted Regression (GWR) model is used to explore the correlation between construction land and ecological pinch points. The number of ecological corridors increased by 42, and the total length was reduced by 432.85 km, for a reduction of 15.25%. The proportion of highest-level ecological pinch points declined from 0.95% to 0.67%, indicating enhanced overall connectivity. Complex network analysis showed declining betweenness centrality in eight ecological sources over two periods, indicating reduced connectivity in partial northern and central regions. Correlation analysis showed the interaction of regional economic development policies and regional ecological restoration measures on the ecological networks. In areas with positive correlations, six ecological conservation areas were designated to maintain existing connectivity. In regions with negative correlations, seven ecological restoration areas were planned to improve ecological connectivity through scientific ecological restoration methods. This research provides a framework for optimizing regional ecological networks and enhancing ecological connectivity in plateau ecological vulnerability areas. It offers significant insights into the optimization of the ecological security pattern and practical guidance for policymakers and planners seeking to maintain ecological sustainability and resilience. Full article

Corporate sustainability performance becomes the central element in many current business developments: the total value of ESG investment grows, more and more clients want to invest in projects that deliver more than the pure financial return, companies are innovating and transforming their business models, and adopting the B-Corp values. Environmental and wider societal impact becomes the central focus of the businesses that want to become the force for good. This article adopts an empirical approach and builds an ESG index of corporate performance based on eight critical metrics representing the economic, social, and environmental dimensions under varying policy priorities. Furthermore, it investigates correlations between these aggregate ESG indices and share prices as well as return on investment, or ROE, of companies. The article goes on to investigate empirically the correlation between employees/turnover, diversity, CO₂ emissions, waste generation, and water use of companies and share prices and ROE metrics, respectively. The reasons for divergence between correlations of sustainability performance indicators with share prices, ROE, and profits/turnover are discussed in detail, with particular attention drawn to the reasons why diversity might matter more for the share prices than ROE and why waste generation, water use, and CO₂ emissions might still be poorly reflected in the ROE while some of these metrics have a significant connection with the profit/turnover ratio. The article will undoubtedly be of interest to ESG fund managers, investors, corporate sustainability officers, and policymakers. Full article

Carbon emissions (CE) from expanding construction land (CL), a vital territory for human production and habitation, have contributed to climate change worldwide. The Yellow River Basin (YRB), an essential economic region and energy supply base in China, is experiencing rapid urbanization, and the contradiction between economic development and ecological protection is increasingly acute. Consequently, a thorough examination of the spatial and temporal change features of carbon emissions from construction land (CECL) and its decoupling from economic growth (EG) is crucial for the maintaining development of the region. This study adopts the IPCC carbon emission coefficient approach for measuring the CECL in the YRB from 2010 to 2021. The temporal and spatial variation features of CECL in the YRB were revealed using ArcGIS software and the standard deviation ellipse (SDE) model. The decoupling effect between CECL and EG was analyzed using the Tapio decoupling model and innovatively combined with the Logarithmic Mean Divisia Index (LMDI) method to explore the influence of five main drivers on the decoupling effect. This study found that: (1) The CECL rose from 2.463 billion tons in 2010 to 3.329 billion tons in 2021. The spatial layout of CECL is “high in the east and low in the west”. (2) The SDE of CECL is distributed in the direction of “northeast to southwest”, and the gravity center’s moving path is “northwest to northeast to northwest”; (3) weak decoupling (WD) is the main decoupling state between CECL and EG; (4) the economic output effect and the construction land (CL) scale effect are the two main factors inhibiting the decoupling of CECL, while the energy intensity effect, the population density effect, and the energy structure effect are the main elements motivating the decoupling of CECL. This study provides specific references and bases for the YRB in China and other countries and regions with similar levels of development in promoting green and ecologically friendly initiatives and achieving low-carbon utilization of regional land and sustainable development. Full article

The explosion of plastic waste generation, approaching 400 million tons per year, has created a worldwide environmental crisis that conventional waste management systems cannot handle. This problem can be solved through gasification, which converts nonrecyclable plastics to syngas with potential applications in electricity generation and synthetic fuel production. This study investigates whether syngas production from plastic waste by gasification is environmentally and economically feasible. Environmental impacts were assessed through a life cycle assessment framework using a life cycle impact assessment approach, ReCiPe 2016, with 10 midpoint/endpoint categories. Midpoint results of the baseline scenario with grid-mix electricity revealed climate change (GWP) of 775 kg CO₂ equivalent and fossil depletion potential (FDP) of 311 kg oil equivalent per ton of plastic waste. Meanwhile, a solar scenario showed GWP as 435 kg CO₂ equivalent and FDP as 166 kg oil equivalent per ton of plastic waste. Switching to solar energy cut GWP 44% and FDP 47%, respectively. However, the tradeoffs were higher human toxicity potential (HTP) and marine ecotoxicity potential (METP) due to upstream material extraction of renewable systems, respectively. Among environmental performance drivers, electricity inputs and operating materials were identified through sensitivity and uncertainty analyses. Syngas production from a plant of 50 tons per day can yield electricity sales revenue of USD 4.79 million, excluding USD 4.05 million in operational expenditures. Financial indicators like a 2.06-year payback period, USD 5.32 million net present value over a 20-year project life, and 38.2% internal rate of return indicate the profitability of the system. An external cost analysis showed emissions-related costs of USD 26.43 per ton of plastic waste processed, dominated by CO₂ and NO_x emissions. Despite these costs, the avoided impacts of less landfilling/incineration and electricity generation support gasification. Gasification should be promoted as a subsidy and incentive by policymakers for wider adoption and integration into municipal waste management systems. Findings show it can be adapted to global sustainability goals and circular economy principles while delivering strong economic returns. The study findings also contribute to several Sustainable Development Goals (SDGs), for instance, SDG 7 by promoting clean energy technologies, SDG 12 by implementing circular economy, and SDG 13 by reducing greenhouse gas (GHG) emissions. Full article

This paper examines the alignment of blockchain architecture with the specific requirements of public business registers in Europe. Through a comprehensive literature review, categorization of blockchain models, and analysis of European public business registry cases, this study develops a framework to guide blockchain adoption in public registries. A distributed ledger taxonomy tailored for business registers is presented. This article also introduces a registry mapping procedure and addresses security concerns essential for the transition to blockchain-based architectures. Blockchain technology, popularized in 2009, has evolved into a versatile tool with applications across various domains, including the public sector, where its potential for decentralized solutions is especially promising. In particular, strategic systems that constitute the backbone of the legal and economic order require special considerations providing superior quality and the appropriate level of security. This study proposes a categorization method, outlines a registry mapping procedure, and discusses security concerns integral to blockchain implementation in public registries. The potential of blockchain technology to change the architecture of public business registries is also discussed. Full article

Small and medium-sized businesses (SMEs) are an essential subject of economic activity in any country because, without their participation, the development and formation of the very structure of the economy are almost impossible. The role of SMEs is significant since these businesses allow for an increase in the number of jobs, develop competition, and, as a result, improve the quality of goods, creating different price segments. More than 4 million people are employed in this sector in the Republic of Kazakhstan, and their share of GDP is 36.7%. The accelerated contribution of the SME sector to Kazakhstan’s GDP has led to the need to conduct a study in this area. This study analyzes the impact of SME production output on Kazakhstan’s economic growth by considering some macroeconomic variables using the ARDL model. The study’s findings confirm that SME output positively and significantly impacts economic growth. The government of Kazakhstan has been implementing a series of policies and incentive programs to increase the contribution of the SME sector to economic growth since the years of independence. However, SMEs are not able to reach their full potential due to various restrictions that limit their expansion. This study offers some suggestions for the development of the SME sector. In order to ensure SME concentration in the economy, investment in R&D should be a priority incentive. On the other hand, we should recognize the shadow economy problem in the country. Full article

In the context of the worldwide attention on climate change, examining how land use relates to the carbon sink functions of regions is essential. This research innovatively utilizes the 2000–2020 land use data of Changde City, integrating the PLUS and InVEST models to analyze spatiotemporal changes and predict scenarios. It also combines the parameter geodetector and multiscale geographically weighted regression model to dissect driving factor distributions and mechanisms, capture interactions and multiscale impacts, uncover underlying laws, pioneer new paths for similar studies, and support regional ecological sustainability. The results show that from 2000–2020, forest and arable land areas declined while construction land expanded, leading to a yij1,172,200-ton carbon storage reduction in Changde City. Carbon storage decreased under natural development and arable land protection scenarios but increased in the ecological scenario. The main drivers of carbon storage in Changde City are the DEM, slope, and annual average temperature, with their interactions enhancing spatial heterogeneity. Human activities, especially in mountains and urbanizing regions, negatively impact carbon storage. This study aids in optimizing land resource allocation, improving land use efficiency, and promoting coordinated and sustainable development in Changde City’s ecological, economic, and social systems. Full article