Search Results (201)

Industrial applications of xylanases in high-temperature settings are limited by enzyme instability. This study evaluated glycerol and phenolic compounds as modulators of the catalytic and structural properties of a recombinant Myceliophthora heterothallica endoxylanase (rMhXyn) expressed in Komagataella phaffii. Glycerol (20% v/v) significantly improved thermostability (5-fold increase in half-life at 55 °C), decreased the activation energy for catalysis, and enhanced structural rigidity as evidenced by molecular dynamics simulations (reduced RMSD and Rg). In contrast, phenolic acids provided only short-term stabilization at moderate temperatures and did not confer structural benefits. Enzyme kinetics revealed that glycerol enhanced catalytic turnover (↑V_max), while phenolic compounds modified both K′ and cooperativity (Hill coefficient). Thermodynamic analysis supported glycerol’s stabilizing effect, with increased ∆H_(D) and a positive shift in ∆S_(D). These results suggest glycerol as a superior stabilizer for rMhXyn in high-temperature bioprocesses such as lignocellulosic biomass hydrolysis. These findings highlight the potential of targeted additives to improve enzyme performance for biotechnological applications. Full article

This study investigates global innovation trends in machine learning (ML) and deep learning (DL) technologies within the automotive sector through a patent analysis of 5314 applications filed between 2005 and 2022 across the five major patent offices (IP5). Using Cooperative Patent Classification (CPC) codes and keyword analysis, we identify seven sub-technology domains and examine both geographical and corporate patenting strategies. Our findings show that the United States dominates in overall filings, while Japan demonstrates a notably high share of triadic patents, which reflects a strong global-reach strategy. Patent activity is heavily concentrated in vehicle control and infrastructure traffic control, with emerging growth observed in battery management and occupant analytics. In contrast, security-related technologies remain underrepresented, indicating a potential blind spot in current innovation efforts. Corporate strategies diverge markedly; for example, some firms, such as Toyota and Bosch, pursue balanced tri-regional protection, whereas others, including Ford and GM, focus on dual-market coverage in the United States and China. These patterns illustrate how market priorities, regulatory environments, and technological objectives influence patenting behavior. By mapping the technological and strategic landscape of ML/DL innovation in the automotive industry, this study provides actionable insights for industry practitioners seeking to optimize intellectual property portfolios and for policymakers aiming to address gaps such as automotive cybersecurity in future R&D agendas. Full article

This study evaluates the competitiveness and sustainable development prospects of French-speaking African countries by constructing a comprehensive framework integrating the TOPSIS method and adaptive LASSO algorithm. Using multivariate data from sources such as the World Bank, 30 indicators covering core, basic, and auxiliary competitiveness were selected to quantitatively analyze the competitiveness of 26 French-speaking African countries. Results show that their comprehensive competitiveness exhibits spatial patterns of “high in the north and south, low in the east and west” and “high in coastal areas, low in inland areas”. Algeria, Morocco, and six other countries demonstrate high competitiveness, while Central African countries generally show low competitiveness. The adaptive LASSO algorithm identifies three key influencing factors, including the proportion of R&D expenditure to GDP, high-tech exports, and total reserves, as well as five secondary key factors, including the number of patent applications and total number of domestic listed companies, revealing that scientific and technological investment, financial strength, and innovation transformation capabilities are core constraints. Based on these findings, sustainable development strategies are proposed, such as strengthening scientific and technological research and development and innovation transformation, optimizing financial reserves and capital markets, and promoting China–Africa collaborative cooperation, providing decision-making references for competitiveness improvement and regional cooperation of French-speaking African countries under the background of the “Belt and Road Initiative”. Full article

The development and implementation of microbial consortium-based biofertilizers represent a promising direction in sustainable agriculture, particularly in the context of the ongoing global ecological and agricultural crisis. This article examines the agroecological and economic impacts of applying microbial consortiums and explores the mechanisms of technology transfer using the example of two countries with differing levels of scientific and technological advancement–China and Kazakhstan. The analysis of the Chinese experience reveals that the successful integration of microbial biofertilizers into agricultural practice is made possible by a well-established institutional framework that includes strong governmental support for R&D, a robust scientific infrastructure, and effective coordination with the private sector. In contrast, Kazakhstan, despite its favorable agroecological conditions and growing interest among farmers in environmentally friendly technologies, faces several challenges from limited funding to a fragmented technology transfer system. The comparative study demonstrates that adapting Chinese models requires consideration of local specificities and the strengthening of intergovernmental cooperation. The article concludes by emphasizing the need to establish a multi-level innovation ecosystem encompassing the entire cycle of development and deployment of microbial biofertilizers, as a prerequisite for improving agricultural productivity and ensuring food security in countries at different stages of economic development. Full article

In the low-carbon era, there is a serious challenge of climate change, which urgently needs to promote low-carbon consumption behavior in order to build sustainable low-carbon consumption patterns. The establishment of this model not only requires in-depth theoretical research as support, but also requires tripartite cooperation between the government, enterprises and the public to jointly promote the popularization and practice of the low-carbon consumption concept. Therefore, by constructing a tripartite evolutionary game model and simulation analysis, this study deeply discusses the mechanism of government policy on the strategy choice of logistics enterprises. The stability strategy and satisfying conditions are deeply analyzed by constructing a tripartite evolutionary game model of the logistics industry, government, and consumers. With the help of MATLAB R2023b simulation analysis, the following key conclusions are drawn: (1) The strategic choice of logistics enterprises is affected by various government policies, including research and development intensity, construction intensity, and punishment intensity. These government policies and measures guide logistics enterprises toward low-carbon development. (2) The government’s research, development, and punishment intensity are vital in determining whether logistics enterprises adopt low-carbon strategies. R&D efforts incentivize logistics companies to adopt low-carbon technologies by driving technological innovation and reducing costs. The penalties include economic sanctions to restrain companies that do not comply with low-carbon standards. In contrast, construction intensity mainly affects the consumption behavior of consumers and then indirectly affects the strategic choice of logistics enterprises through market demand. (3) Although the government’s active supervision is a necessary guarantee for logistics enterprises to implement low-carbon strategies, more is needed. This means that in addition to the government’s policy support, it also needs the active efforts of the logistics enterprises themselves and the improvement of the market mechanism to promote the low-carbon development of the logistics industry jointly. This study quantifies the impact of different factors on the system’s evolution, providing a precise decision-making basis for policymakers and helping promote the logistics industry’s and consumers’ low-carbon transition. It also provides theoretical support for the logistics industry’s low-carbon development and green low-carbon consumption and essential guidance for sustainable development. Full article

As market competition intensifies, the survival and development of suppliers increasingly rely on research and development (R&D) investment and innovation. Due to the uncertainty of factors affecting supplier R&D investment, the risks faced by supplier R&D investment are also uncertain. Therefore, identifying and assessing risks in advance and controlling risks can provide effective support for suppliers to carry out risk management of R&D investment. This paper selects key factors through literature review and factor analysis, and establishes a risk index evaluation system for R&D investment of medical material suppliers. Seventeen indicators that affect and constrain project investment factors were identified as input variables of the back propagation (BP) neural network, the comprehensive score of the R&D investment risk assessment was used as the output variable of medical supplies suppliers, and a risk assessment model for the R&D investment of medical material suppliers was established. By leveraging the ability of particle swarm optimization (PSO), whale optimization algorithm (WOA), and genetic algorithm (GA) to search for global optimal solutions, the BP neural network is improved to avoid becoming trapped in local optimal solutions and enhance the model’s generalization ability. The improvement in accuracy and convergence speed of these three methods is compared and analyzed. The results show that the BP neural network improved by the genetic algorithm has better accuracy and faster convergence speed in predicting and assessing risks. This indicates that the BP neural network model improved by genetic algorithm is effective and feasible for predicting the risk assessment of the R&D investment of medical supplies suppliers. Full article

This paper focuses on the carbon emission problem of new energy vehicle (NEV) battery recycling, constructs a tripartite evolutionary game model of battery manufactures, new energy vehicle original equipment manufacturers (NEV OEMs) and certified recyclers, analyzes the stability of each party’s strategy selection and the relationship between the influence of the elements, and simulates to verify the validity of the conclusions, and arrives at the conditions for the occurrence of the lowest carbon emission stabilizing strategy combinations, and puts forward countermeasure suggestions accordingly, and analyzes the effects of the changes of the key parameters on the equilibrium results, and the study shows that (1) Carbon emission cost, battery decomposition cost, recycling channel construction cost and R&D cost are the main factors affecting the equilibrium results. (2) Under the carbon emission reduction policy, the battery manufacturer’s investment in low-carbon production can help other actors in the supply chain to reduce the negative impact of the policy so that they can reduce their costs. (3) The cooperative recycling model based on the recycling network constructed by vehicle manufacturers can maximize the interests of all parties in the supply chain. The findings of the study provide management insights for governments, battery manufacturers, NEV OEMs, and certified recyclers. Full article

The high-quality and sustainable development of the digital economy cannot be achieved without the support of the policy system. The purpose of this article is to scientifically analyze the laws and characteristics of the policy system that supports the sustainability of the digital economy. Specifically, based on public policy theory, this article constructs an analytical framework of “policy objectives—policy tools—organizational management” and incorporates the “central-local” relationship with Chinese characteristics into the framework. Meanwhile, text analysis was used to quantitatively analyze 971 digital economy policies issued by the central and local governments in China from 2000 to 2022. Research shows that the central government of China has taken the lead in introducing digital economy policies, and local governments are able to respond quickly. The central government’s digital economy policy goals fluctuate and change, while local governments pay more stable attention to the digital product service industry. Both central and local governments widely use supply oriented policy tools and environmental-oriented policy tools, while demand-oriented policy tools are not widely applied. The vertical relationship between central and local data management agencies is still unclear, and the degree of cross departmental and cross regional cooperation is not high. Meanwhile, empirical analysis based on the two-way fixed effects model shows that technological innovation, R&D funding, and industrial structure have a significant impact on changes in digital economy policies. This article summarizes the characteristics of the evolution of digital economy policies in the Chinese context, providing policy design references for promoting the sustainability of the digital economy and methodological insights for policy research in other fields. Full article

The literature regarding innovation drivers is usually based on variables taken from some theoretical approach and validated within a methodology. Some authors have included COVID-19 as a driver for innovations. In this paper, we address the pandemic from a different viewpoint: trying to find if innovation drivers for European countries are the same in pre- and post-pandemic years. The automated general-to-specific model selection algorithm—Autometrics—is used. The main potentially relevant drivers for which data were available for both years and two proxies of innovation (patents and the Summary Innovation Index) were considered. The final models provided by Autometrics allow for valid inference on retained innovation drivers since they have passed a plethora of diagnostic tests, ensuring congruency. The attractiveness of the research system is the most impactful driver on the index in both years but other drivers indeed differ. SMEs’ business process innovation and their cooperation networks matter only in 2022. We found crowding-out effects of public funding of R&D (in both years, for the index). Sustainability was a driver in both periods. The ranking of common drivers also changes. Non-R&D innovation expenditures, the second most relevant before COVID-19, concedes to digitalization. Surprisingly, when patents are the proxy, digitalization is retained before COVID-19, with the attractiveness of the research system replacing it afterwards. Explanations for our findings are suggested. The main implications of our findings for innovation policy seem to be the facilitating role that the government should have in fostering linkages between stakeholders and the capacity the government might have to improve the attractiveness of the research system. Policies based on the public funding of R&D appear ineffective for European countries. Full article

As a key driver of the green and low-carbon transformation of the energy sector, clean heating technology plays a crucial role in advancing sustainable energy development. However, the research and development (R&D) of clean heating technology is hindered by conflicting interests among key supply-side stakeholders, including heating enterprises, commercial banks, and government departments. These conflicts create challenges for promoting the diffusion of clean heating technology. To address this issue, this paper develops a tripartite evolutionary game model involving these stakeholders, with the aim of exploring strategies to facilitate clean heating technology diffusion from the supply side. Through mathematical modeling and numerical simulations, we examine how variables such as cost, subsidies, and penalties affect the strategic decisions of these participants. The results showusing that (1) the cost of clean heating technology R&D significantly influences commercial banks’ willingness to collaborate with heating enterprises; (2) increasing credit penalties for non-compliance and enhancing returns from clean heating technology can motivate heating enterprises to engage in technology R&D; (3) enhancing economic penalties and strengthening informal regulations can improve cooperation between commercial banks and heating enterprises; (4) moderate subsidies can positively influence the strategies adopted by commercial banks and heating enterprises. Based on these findings, we propose policy recommendations to promote clean heating technology diffusion from the supply side. This study offers both theoretical support and practical guidance for advancing clean heating technology diffusion, which is strategically important for sustainable energy development. Full article

The crystal structures, interactions, and contacts analyses of four N-(ferrocenylalkyl)benzene-carboxamide derivatives are described as the N-(ferrocenylmethyl)benzenecarboxamide 4a, N-(ferrocenylmethyl)-2,6-difluorobenzenecarboxamide 4e, N-(ferrocenylmethyl)pentafluorobenzenecarboxamide 4f and N-(ferrocenylethyl)-4-fluorobenzenecarboxamide 5. Intermolecular amide⋯amide hydrogen-bonding interactions as 1D intermolecular chains are present in all four crystal structures, with N⋯O distances ranging from 2.819 (2) to 2.924 (3) Å. Three of the crystal structures have one molecule per asymmetric unit, except the phenyl 4a, which has Z’=2. In the structure of 4a, Fc(C-H)⋯(phenyl) and _phenylC-H⋯π(C₅H₄) ring interactions dominate the interaction landscape, together with (1:1) face-to-face (phenyl)⋯(phenyl) and (C₅H₅)⋯(C₅H₅) ring stacked pairs (Fc = ferrocenyl moiety). In 4e, interlocking ferrocenyls, short C-H⋯(C-F) and C-H⋯O hydrogen bonds are the only additional notable intermolecular interactions. In the pentafluorophenyl derivative 4f, a remarkable selection of interactions is present with interwoven 1D ferrocenyl⋯(C₆F₅) stacking and C-H⋯F interactions; molecules aggregate forming impressive 1D columns comprising intertwined (Fc⋯C₆F₅⋯)_n ring stacking. In the ethyl bridged system 5, C-H⋯F and C-H⋯π (arene) contacts with (4-fluorobenzene) ring⋯ring pairs combine and stack about inversion centres. The reported para-F substituted structure REYWOU (4d) is used for comparisons with the 4a, 4e, 4f, and 5 crystal structures. In view of the rich interaction chemistry, contacts enrichment analyses of the Hirshfeld surface highlights several interesting features in all five ferrocenylalkylcarboxamide structures. Full article

This study evaluates the efficiency of EU countries in utilizing their geographical potential for wind and solar energy production. A two-stage radial network data envelopment analysis (NDEA) is used to estimate the efficiency of the utilization of natural resources. The research is of a computational-empirical nature on the basis of publicly available data. The basic variables included in the model are: mean wind speed, Global Horizontal Irradiance, population, land area, wind energy capacity, solar PV capacity, wind energy generation, and solar power generation. The relationship between the environmental potential and the installed power capacity is evaluated in the first stage. In the second stage, the actual production from the installed capacity is analyzed. The efficiency trends over time are also investigated. This approach offers a comprehensive assessment by considering both the technical performance and environmental constraints. Considering all studied countries together, a slight increase in the relative efficiency of renewable energy potential utilization is observed—from 23.2% in 2018 to 28.7% in 2022. Germany and the Netherlands achieved 100% relative efficiency in 2022. The results reveal that the development of alternative energy sources and the efficiency of the installed power capacity utilization are not always in line with the local environmental conditions. The average efficiency of the analyzed countries from this perspective was 26.8% in 2018, with an improvement to 37.4% in 2022. The relative efficiency of the installed capacity utilization was high in both periods (76.3% and 74.9%, respectively). The impact of exogenous variables on performance (GDP and R&D expenditures) is discussed. Broader implications of the results for a responsible renewable energy policy in the EU demonstrate the need to combine overarching targets with a flexible governance system. That flexibility should allow for individual energy transition pathways, cooperative mechanisms, market integration, and targeted funding in order to account for the diversity of renewable resource utilization potentials among countries. Full article

Urban digital intelligence transformation (DIT) has emerged as a key driver of sustainable development in the era of rapid technological advancement. This study utilized the spatial Durbin model with difference-in-differences (SDM-DID) to explore the intrinsic relationship between DIT and intercity collaborative innovation. The findings indicate that DIT significantly enhances collaborative innovation locally and in other cities. DIT accelerates the movement of R&D talent, capital, and knowledge while driving collaborative innovation across local and neighboring cities by enhancing market potential. Collaborations between enterprises and universities exhibit stronger direct and indirect positive effects, collectively driving the development of sustainable intercity collaborative innovation. Additionally, the study finds that the impact of DIT on substantial innovation is greater than that of non-substantial innovation. Furthermore, the digital transformation of large and central cities has a stronger promotional effect on both local and neighbor collaborative innovation, fostering the sustainable development of intercity innovation cooperation. These results deepen our understanding of the relationship between DIT and intercity collaborative innovation and provide policy insights for enhancing intercity collaboration and promoting regional sustainable development. Full article

The Inflation Reduction Act (IRA) passed by the United States in 2022 affected the global layout of electric vehicle (EV) supply chains. This paper explores the impacts of the IRA on the decisions of overseas battery suppliers and domestic EV manufacturers in the US. The main findings are that (1) the suppliers’ and manufacturers’ optimal decisions depend on the local subsidy, tariff, and battery R&D costs: tariffs (subsidies) reduce (increase) the battery R&D level for overseas (local) suppliers, EV prices, and supply chain members’ profits; (2) subsidies and tariffs are key factors in distinguishing manufacturers from overseas procurement and local procurement when R&D cost coefficients are determined; cost coefficients and service fees are the key factors for manufacturers to choose local procurement or R&D cooperation strategies; and (3) when local supply chains compete with overseas supply chains, subsidies will give the local supply chains a sales advantage while giving overseas supply chains a price advantage, and when local supply chains compete with cooperative supply chains, subsidies will give local supply chains a price disadvantage and a sales disadvantage. Full article

The Sustainable Development Goals 9 (known as the SDG9): Industry, Innovation, and Infrastructure are crucial objectives for Kuwait since they are essential to the nation’s attempts to achieve sustainable development and economic diversification. Using the recently available literature, this research attempts to understand and investigate the current level of SDG9 implementation in the context of Kuwait. Data from the SDGs database based on published studies and reports were used in this study. The actual level of SDG9 implementation in Kuwait still faces significant challenges. The roadmap to achieving the SDG9 goals was improved based on the analysis of SDG9 targets and identifying the reasons and factors for developing each target. The results indicate that Kuwait should encourage non-oil businesses, including manufacturing and renewable energy, to diversify its economy and reduce its dependency on oil. Efforts need to be taken to improve industrial infrastructure, encourage innovation, and advance research and development (R&D) activities. To attract capital and skills for infrastructure development, Kuwait should also promote public–private partnerships. In order to achieve the SDG9 goals, it is suggested that policymakers foster innovation and technology adoption, support small and medium-sized businesses (SMEs), promote sustainable industrial practices, build industrial infrastructure, improve vocational and technical education, encourage international cooperation and technology transfer, monitor progress, and set targets. Full article