Search Results (57)

Agricultural development is vital for East Africa’s economic growth, yet the region faces significant disparities and systemic barriers. A critical problem exists due to the lack of an integrated quantitative framework to systematically comparing agricultural capacities and facilitate optimal resource allocation, as existing studies often overlook combined internal and external factors. This study proposes a comprehensive multi-criteria decision-making (MCDM) model to assess, categorize, and strategically profile the agricultural development capacity of 18 East African countries. The method employed is an integrated Entropy-MAIRCA model, which objectively weighs six criteria (the food production index, arable land, production fluctuation, food export/import ratios, and the political stability index) and ranks countries by their distance from an ideal development state. The experiment applied this framework to 18 East African nations using official data. The results revealed significant differences, forming four distinct strategic groups: frontier, emerging, trade-dependent, and high risk. The food export index (C4) and production volatility (C3) were identified as the most influential criteria. This model’s contribution is providing a science-based, transparent decision support tool for designing sustainable agricultural policies, aiding investment planning, and promoting regional cooperation, while emphasizing the crucial role of institutional factors. Full article

This study addresses the increasing emphasis on sustainability and the importance of understanding how environmental risk influences business failure, a factor unexplored in traditional financial prediction models. Environmental risk, or environmental financial exposure, refers to the potential percentage of a company’s revenue at risk due to the environmental damage it causes. Previous research has not sufficiently integrated environmental variables into failure prediction models. This study aims to determine whether environmental risk significantly predicts business failure and how it interacts with conventional financial indicators. Utilizing data from 971 Spanish cooperative companies in 2022, including financial ratios, the VADIS bankruptcy propensity indicator, and the TRUCAM environmental risk score, the study employs the Extreme Gradient Boosting (XGBoost) machine learning algorithm, chosen for its robustness in handling multicollinearity and nonlinear relationships. The methodology involves training and validation samples, cross-validation for hyperparameter tuning, and interpretability techniques such as variable importance analysis and partial dependence plots. Results demonstrate that the variable related to environmental risk (TRUCAM) ranks among the top predictors, alongside liquidity, profitability, and labor costs, with higher TRUCAM values correlating positively with failure risk, underscoring the importance of sustainable cost management. These findings suggest that firms facing substantial environmental risk are more prone to financial distress. By incorporating this environmental variable into a machine learning framework, this work contributes to the interaction between sustainability practices and corporate viability. Full article

Existing research on the vulnerability of knowledge innovation networks (KINs) primarily falls into two categories: random attacks and deliberate attacks. This study introduces a novel centrality-based attack framework for the deliberate attack group and systematically examines the impact of different attack mechanisms (such as loss of connectivity, propagation delays, and structural fragmentation) on KINs. Using SCI/SSCI co-authorship data across 286 Chinese cities, this research evaluated network resilience through six key metrics, average clustering coefficient, average degree, average path length, global efficiency, isolated nodes ratio, and largest connected component ratio, thus revealing three key conclusions: First, network density and regional integration surged after 2015, peaking in localized clustering during 2021–2022; yet, post-2022, structural fragmentation and efficiency declines exposed critical vulnerabilities. Second, network disruption simulations revealed that attacks based on structural fragmentation mechanisms have the most significant impact, demonstrating the need to promote polycentric development to reduce core dependency risks and highlighting the importance of protecting high-centrality nodes such as Beijing, Shanghai, and Shenzhen. Third, the inhibitory effect of economic proximity weakened significantly by 2024, suggesting reduced economic disparity barriers to collaboration. Notably, emerging synergies between geographic and economic proximity enhanced innovation cooperation potential, emphasizing spatial–economic coordination as a crucial factor in development-stage planning. By integrating spatiotemporal dynamics with attack taxonomy, our framework advances network theory and equips policymakers with actionable strategies to optimize knowledge flows and mitigate systemic risks. Bridging structural resilience with innovation-driven development, this study offers new insights into China’s urban knowledge networks. Full article

To enhance product greenness and operational performance, this study designs a Nash bargaining contract incorporating consumer environmental awareness in an agricultural supply chain consisting of one manufacturer and one retailer. The manufacturer invests in green technologies and the retailer shares partial green costs to improve greenness and efficiency. Using game theory, theoretical models for competitive scenario without Nash bargaining, local cooperative scenario with given ratio, and global cooperative scenario with Nash bargaining are constructed. Through comparison and sensitivity analysis, the enhancements from Nash bargaining are explored, and the effects of consumer environmental awareness on these enhancements are examined. The findings reveal several key insights. First, the process of bargaining determines the optimal contract ratio, which also depends on the magnitude of price sensitivity, marginal green costs, and consumer environmental awareness. Second, the Nash bargaining contract significantly improves product greenness, increases retail prices, and boosts profits for both the manufacturer and the retailer. Finally, consumer environmental awareness amplifies the effectiveness of the Nash bargaining contract, leading to greener products, higher prices, and greater overall supply chain profits. This research contributes to agricultural supply chain management by providing a theoretically rigorous Nash bargaining mechanism alongside a real-world case study, which harmonizes environmental stewardship and economic viability in agricultural supply chains. The findings offer actionable insights for supply chain managers and policymakers seeking to promote green innovation while maintaining profitability. Full article

With global population growth and accelerated technological innovation, human activities have expanded, leading to worsening ecological degradation and more frequent disasters, particularly in vulnerable and underdeveloped mountainous areas. Western Sichuan, predominantly consisting of mountainous cities, has unique geographical conditions that not only hinder socioeconomic development but also create an environment conducive to disaster occurrence. This study, therefore, investigates the disaster resilience of mountainous cities in western Sichuan. Using support vector machine (SVM), this study predicts geo-disaster risks. Shapley values from cooperative game theory are employed to optimize three evaluation methods, TOPSIS, Grey Relational Analysis (GRA), and Rank Sum Ratio (RSR), to calculate social resilience values. Finally, disaster resilience values are determined by integrating geo-disaster risk with socioeconomic resilience. Kernel density estimation and GeoDetector are then used to analyze the disaster resilience values. The findings reveal that (1) the disaster resilience of mountainous cities is generally improving, with a gradual decrease in the number of cities with low resilience, though the overall level remains low; (2) resilience disparities among cities are evident, showing an “east-high, west-low” distribution, primarily due to the eastern region’s proximity to developed cities and the socioeconomic support it has received; (3) the proliferation of information technology and the development of tourism are key drivers of resilience development, while human activities exacerbate geo-disaster risks; (4) the enhancement of disaster resilience is more dependent on the interaction of multiple driving factors than on any single factor. This study, aligned with the United Nations Sustainable Development Goals (SDG3, SDG4, SDG8, SDG9, SDG11, and SDG15), offers recommendations for disaster resilience development and provides theoretical support for policy formulation in mountainous cities. Full article

The structural behavior of ionic aggregates in semi-crystalline ethylene-based ionomers during heating was studied to understand the influence of different ionic groups on their properties. The ionomers were synthesized by neutralizing carboxylic acid groups with Zn and Na ions at varying ratios. Differential scanning calorimetry (DSC) revealed two distinct endothermic peaks, with the melting point being largely unaffected by the Zn/Na ion ratio. However, the melting enthalpy of T_i is maximum at Na/Zn ratios of 3:7 and 5:5, suggesting that crystallites preferentially grow in the presence of both ions are present. In situ wide-angle X-ray scattering (WAXS) identified temperature-dependent transitions, where monoclinic crystals melted near T_i and recrystallized into orthorhombic forms, which subsequently melted as the temperature approached T_m. Small-angle X-ray scattering (SAXS) analysis, employing the Yarusso–Cooper equation, indicated a temporary expansion of ionic aggregates near T_i, followed by further expansion near T_m. These expansions were attributed to the melting of polyethylene crystals, which were found to compress the aggregates under normal conditions. These findings provide insights into the relationship between ionic group composition, microstructural evolution, and thermal behavior in ethylene-based ionomers, with implications for their application in temperature-sensitive environments. Full article

The rapid development of the logistics industry and its cooperation with other production factors have an impact on the promotion of new-type urbanization (NTU), a more sustainable and inclusive model of urban growth. This article analyzes in-depth the impact mechanism of logistics industry agglomeration, a new way to promote innovation and improve industrial efficiency, on NTU from various dimensions, including population, economy, society, space, ecology, and urban-rural coordination. Using panel data from 31 provinces in China between 2002 and 2021, the level of NTU was calculated using the entropy weight method, and a spatial econometric model was employed to examine the impact of logistics industry agglomeration on NTU and its spatial spillover effects. The research findings are as follows. The study reveals a spatial correlation between logistics industry agglomeration and NTU across Chinese regions. Logistics industry agglomeration significantly enhances NTU levels and generates spatial spillover effects, facilitating urban development in surrounding areas. The influence of regional logistics industry agglomeration on NTU demonstrates notable spatial heterogeneity, with the central region exerting a greater impact than the eastern and western regions. It can help in the understanding of regional differences and help policy makers optimize resource allocation. The impact of logistics industry agglomeration on NTU is nonlinear, primarily characterized by a substantial improvement in NTU at the medium and low levels due to logistics industry agglomeration. It helps identify regional differences and supports personalized decision making. The level of human capital, the degree of government intervention, the degree of marketization, the level of technological industrialization, the ratio of elderly dependency, and the level of innovation have direct effects and spillover effects on NTU. This paper elaborates on the mechanism of logistics industry agglomeration on NTU in China and proposes targeted proposals for promoting the development of NTU, which is highly important for promoting urbanization in other regions of the world from the perspective of industry. Full article

The mass of nutrients accumulated in the vegetative parts of winter wheat (WW) in the period from the beginning of booting to the full flowering stage (Critical Cereal Window, CCW) allows for the reliable prediction of the grain yield (GY) and its components, and the grain protein content (GPC) and its yield. This hypothesis was verified in a one-factor field experiment carried out in the 2013/2014, 2014/2015, and 2015/2016 growing seasons. The field experiment included seven nitrogen-fertilized variants: 0, 40, 80, 120, 160, 200, and 240 kg N ha⁻¹. The N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu content in wheat vegetative parts (leaves, stems) was determined in two growth stages: (i) beginning of booting (BBCH 40) and (ii) full flowering (BBCH 65). We examined the response of eight WW traits (ear biomass at BBCH 65, EAB; grain yield, GY; grain protein content, GPC; grain protein yield, GPY; canopy ear density, CED; number of grains per ear, GE; number of grains per m⁻²—canopy grain density, CGD; and thousand grain weight, TGW) to the amount of a given nutrient accumulated in the given vegetative part of WW before flowering. The average GY was very high and ranged from 7.2 t ha⁻¹ in 2016 to 11.3 t ha⁻¹ in 2015. The mass of ears in the full flowering stage was highest in 2016, a year with the lowest GY. The highest N mass in leaves was also recorded in 2016. Only the biomass of the stems at the BBCH 65 stage was the highest in 2015, the year with the highest yield. Despite this variability, 99% of GY variability was explained by the interaction of CGD and TGW. Based on the analyses performed, it can be concluded that in the case of large yields of winter wheat, GE is a critical yield component that determines the CGD, and in consequence the GY. The leaf nutrient mass at the BBCH 40 stage was a reliable predictor of the GPC (R² = 0.93), GPY (0.92), GE (0.84), and CED (0.76). The prediction of the GY (0.89), CGD (0.90), and TGW (0.89) was most reliable based on the leaf nutrient mass at the BBCH 65 stage. The best EAB prediction was obtained based on the mass of nutrients in WW stems at the BBCH 65 stage. The magnesium accumulated in WW parts turned out to be, with the exception of TGW, a key predictor of the examined traits. In the case of the TGW, the main predictor was Ca. The effect of Mg on the tested WW traits most often occurred in cooperation with other nutrients. Its presence in the developed stepwise regression models varied depending on the plant part and the WW trait. The most common nutrients accompanying Mg were micronutrients, while Zn, Fe, Mn, and Ca were the most common macronutrients accompanying Mg. Despite the apparently small impact of N, its yield-forming role was indirect. Excessive N accumulation in leaves in relation to its mass in stems, which appeared in the full flowering phase, positively impacted the EAB and GPC, but negatively affected the GE. Increasing the LE/ST ratio for both Mg and Ca resulted in a better formation of the yield components, which, consequently, led to a higher yield. This study clearly showed that nutritional control of WW during the CCW should focus on nutrients controlling N action. Full article

Underwater optical wireless communication (UOWC) is a field of research that has gained popularity with the development of unmanned underwater vehicle (UUV) technologies. Its utilization is crucial in offshore industries engaging in sustainable alternatives for food production and energy security. Although UOWC can meet the high data rate and low latency requirements of underwater video transmission for UUV operations, the links that enable such communication are affected by the inhomogeneous light attenuation and the presence of sunlight. Here, we present how the underwater spectral distribution of the light field can be modeled along the depths of eight stratified oceanic water types. We considered other established models, such as SPCTRL2, Haltrin’s single parameter model for inherent optical properties, and a model for the estimation of the depth distribution of chlorophyll-a, and present insights based on transmission wavelength for the maximum signal-to-noise ratio (SNR) under different optical link parameter combinations such as beam divergence and transmit power under “daytime” and “nighttime” conditions. The results seem to challenge the common notion that the blue-green spectrum is the most suitable for underwater optical communication. We highlight a unique relationship between the transmission wavelength for the optimal SNR and the link parameters and distance, which varies with depth depending on the type of oceanic water stratification. Our analyses further highlighted potential implications for solar discriminatory approaches and strategies for routing in cooperative optical wireless networks in the photic region. Full article

Forestry in Japan and Austria share many similarities in their natural and social conditions. However, the Family Forest Owners (FFOs) in Japan seem not to be active and sustainable. To understand the factors affecting activeness and sustainability in family-owned forests in Japan, in 2021 and 2022, questionnaire surveys were done with members of Forest Owners’ Cooperatives (FOCs) in Aso, Japan, and Styria, Austria. Survey responses were comparatively analyzed via correlation analysis and binary logistic regression. Timber production was found to be more active in FOC Styria than in FOC Aso. One reason for this was the high-income dependence on forestry in Styria. Higher income was realized by self-harvest and the larger size of forest holdings and forest stands. The younger age of the members in FOC Styria, strongly affected by the pension system, leads to a higher self-harvest ratio. The culture of a sole child inheriting the family forest maintains the general size and scale of owned forests and stands in Styria. High distribution costs in FOC Aso reduced forestry income. As a result, sustainability was reduced in Aso because the availability of successors was low, and elderly forest owners who were once motivated by forestry tended to quit forestry. Full article

The aqueous solution of binary mixtures of amphiphilic copolymers is a potential platform for fabricating mixed polymeric micelles for pharmaceutical applications, particularly in developing drug delivery depots for a poorly water-soluble compound. This study fabricated and investigated binary mixtures of poloxamer 403 (P403) and poloxamer 407 (P407) at varying P403:P407 molar ratios to develop a vehicle for the poorly water-soluble compound, using ibuprofen as a model drug. The cooperative formation of mixed micelles was obtained, and the solubility of ibuprofen in the binary mixtures was enhanced compared to the solubility in pure water and an aqueous single P407 solution. The binary mixture with the P403:P407 molar ratio of 0.75:0.25 at a total polymer concentration of 19% w/v exhibited the temperature dependence of micellization and sol-to-gel characteristics of the thermosensitive mixed micellar gels. It possessed suitable micellization and gelation characteristics for in situ gelling systems. The release of ibuprofen from the thermosensitive mixed micellar depots was sustained through a diffusion-controlled mechanism. The findings can aid in formulating binary mixtures of P403 and P407 to achieve the desired properties of mixed micelles and micellar gels. Full article

The rapid progress of the modern world has resulted in new materials and products created at an accelerating pace. As such, nanoparticles have widespread applications and often find their way into the aquatic ecosystem. In the case of freshwater ecosystems, one of the commonly used bioindicators species used for pollution assessment is Daphnid magna. The Organization for Economic Co-operation and Development (OECD), and other organizations such as the European Chemicals Agency (ECHA) and Environmental Protection Agency (EPA), have set guidelines for acute toxicity testing in daphnids that are severely lacking in terms of information on the characteristics of the exposure vessel when studying the adverse effects of nanoparticles (NPs). Understanding the toxicity mechanisms of nanomaterials is imperative given the scarcity of information on their adverse effects. Furthermore, miniaturization of nanotoxicity assays can reduce the number of daphnids used, as well as the cost and nanomaterial waste, and provide results even at the individual animal level with enhanced reproducibility of testing. In this study, the impact of the exposure vessel on the observed physiological changes of daphnids was investigated for a silver nano ink. Exposures in eleven commercially available vessels; nine made of plastic and two made of glass were compared for 24 h. The effect of surface to volume ratio of the exposure vessel and the animal number or “crowding” during exposure was investigated in the context of miniaturizing biomarker assays as alternatives to traditional experimental setups in Daphnid magna. Toxicity curves showed differences depending on the vessel used, while a novel feeding rate assay and the activity of key enzymes were assessed as physiology endpoints. Full article

This study seeks to investigate the potential effects of the recent pandemic (COVID-19) on capital structure dynamics. The Gulf Cooperation Council (GCC) is a fascinating topic for this study because of its distinct economic characteristics. The analysis draws upon a cross-country dataset covering 208 non-financial listed firms across five GCC countries, with data spanning the years 2010 to 2022. Capital structure is a dependent variable and is measured by total debt to equity, equity multiplier, and short-term debt ratios, while the COVID-19 pandemic, firm size growth, return on assets, tangibility, and growth were applied as independent variables. Using the generalized least squares (GLS) method, findings demonstrated that COVID-19 has a significant and positive influence on debt-to-equity and equity multiplier ratios but a negative one on short-term debt ratio. Thus, non-financial firms increased their debt financing and transferred debt from short-term to long-term funding. In addition, firm-specific factors, such as firm size, tangibility, and macroeconomic factors, such as GDP growth, positively and significantly impact capital financing. Conversely, profitability has a negative relationship with financial leverage. There is a lack of empirical research on how COVID-19 affects the financial structure of non-financial listed companies in GCC nations. Consequently, by filling the previously specified gaps, this study provides proof to support the idea of using debt financing to raise capital for economic recovery. GCC policymakers need to give priority to ensuring that firms have convenient access to inexpensive finance in light of the financial consequences caused by COVID-19. This will guarantee that companies have the resources necessary to bounce back and support economic growth. Full article

To accurately predict the matching relationships between the various components and the engine performance in the whole aero-engine environment, this study introduces a two-dimensional throughflow simulation method for the whole aero-engine. This method is based on individual throughflow solvers for the turbo-machinery and the combustor. It establishes a throughflow simulation model for the whole engine by integrating with the compressor-turbine co-operating equations and boundary conditions. The turbo-machinery throughflow solver employs a circumferentially averaged form of the time-dependent Navier–Stokes equations (N-S) as the governing equation. The combustor solver uses the Reynolds Average Navier–Stokes (RANS) method to solve flow and chemical reaction processes by constructing turbulence, combustion, and radiation models. The accuracy of the component solver is validated using Pratt and Whitney’s three-stage axial compressor (P&W3S1) and General Electric’s high-pressure turbine (GE-EEE HPT), and the predicted results are consistent with the experimental data. Finally, the developed throughflow method is applied to simulate the throttling characteristics of the WZ-X turboshaft engine. The results predicted by the throughflow program are consistent with the GasTurb calculations, including the trends of shaft power delivered, specific fuel consumption (SFC), inlet airflow, and total pressure ratio of the compressor. The developed method to perform throughflow simulation of the whole aero-engine eliminates the dependence on a general component map. It can quickly obtain the meridian flow field parameters and overall engine characteristics, which is expected to guide the design and modification of the engine in the future. Full article

The “One Belt and One Road” strategy provides a new opportunity for deepening oil and gas energy cooperation between China and Central-North Asian countries. This paper systematically studies the supply and demand characteristics, interdependence and cooperation prospects of oil and gas between them using relevant oil and gas energy data of these countries from 2016 to 2021. The objective of this research is to provide a basis for the overall planning of oil and gas energy cooperation between China and Central-North Asian countries in the future. The results show that the proven reserves of oil and gas in Central-North Asian countries are high; particularly, the proven reserves of natural gas account for 30% of the world. These countries also have high oil and gas self-sufficiency rates. These have laid a material foundation for China to strive for the sustained and stable import of oil and gas energy from Central-North Asian countries. At the same time, there are great imbalances in oil and gas reserves, production, consumption, available exports and their growth rates among Central-North Asian countries, which provide a basis for China and Central-North Asian countries to make strategic decisions on oil and gas energy differential cooperation. China imports 80 × 10⁶ tons of oil and 490 × 10⁸ cubic meters of gas from Central-North Asian countries every year and Chinese dependence on oil and gas imports in this region is 16% and 37%, respectively. The study believes that China has certain potential to increase the import of oil and gas from Central-North Asian countries and has good prospects for oil and gas cooperation. It is proposed that China should give priority to increasing oil and gas exploration and development cooperation with Central-North Asian countries with high oil and gas reserve–production ratios, and should strengthen oil and gas resource trade cooperation with Central-North Asian countries with high oil and gas self-sufficiency rates. At the same time, China should increase investment and cooperation in the midstream and downstream business of the oil industry in major Central-North Asian countries through various financing channels. China should uphold the principle of win–win cooperation to promote the in-depth and steady development of oil and gas energy cooperation between China and Central-North Asian countries. Full article