Does the openness of the Boundary Shell system influence the sustainable development of the high-tech industry?

High-technology industries have gained substantial recognition as pivotal drivers of economic growth and technological advancement in modern society. The imperative of sustainable development in high-tech industries cannot be overemphasized, as it plays a crucial role in enabling long-term growth, fostering innovation, and assuming environmental responsibility. This article presents a study on sustainable development in high-tech industries using Boundary Shell theory. The study investigates the role of the stable and sustainable entropy criterion for the Boundary Shell system of high-tech industries from an entropy balance perspective. It analyzes the upper and lower limits of the Boundary Shell support force. Additionally, it improves the traditional boundary system ratio model to comprehensively and objectively evaluate the sustainable development of high-tech industries. The results illustrate that the Boundary Shell of industrial innovation is stronger than that of external dependency, with a reversed ranking of internal evaluation factor strengths compared to the traditional model. This research integrates reaction-diffusion equations theory with entropy balance equations theory to address sustainability issues in the high-tech industry. We further analyze the sustainable development of the high-tech industry through a Boundary Shell theory perspective to advance sustainability in high-tech industries. Moreover, it provides useful insights into the sustainable development of high-tech industries.

Assessing the impact of blockchain technology on the overall performance of sustainable supply chains: an analytical perspective.

Supply chain control and sustainability can be significantly improved using distributed ledger technologies such as blockchain. The blockchain has the potential to facilitate responsible sourcing appropriately, compliance with weather requirements, and sustainable delivery chains. The purpose of this study is to address the hassle of managing conservatism when approaching era adoption and to explore the performance enhancements in blockchain-generated implementations. To achieve this goal, we introduce a scientific approach aimed at studying the outcomes of various factors in the adoption process in the blockchain era and verifying their impact on the overall performance of the delivery chain. Furthermore, a team of multidisciplinary professionals will establish causal relationships among these elements through a consensus-based approach. Ultimately, fuzzy reasoning tools can be used to determine the relative weights between identified factors and delivery chain performance goals. We will assemble causal representations of diagnoses using a dense scientific map model and dynamically generate scenarios for each. The study demonstrates that the integration of blockchain power generation can significantly improve the effectiveness of mineral supply chains. It uses smart contracts to promote environmental sustainability, traceability, and transparency.

Fabrication of water-floating litchi-like polystyrene-sphere-supported TiO2/Bi2O3 S-scheme heterojunction for efficient photocatalytic degradation of tetracycline.

The exploration of advanced photocatalysts for antibiotic degradation is critical, but it remains a challenge due to the lack of rational structural design and in-depth insights into molecular oxygen activation. Water-floating photocatalysts could be one of the best choices owing to their technical features in terms of reasonability and efficiency involving a high oxygenation of photocatalyst surface, fully solar irradiation, and simple recycling and reuse. Herein, a floatable litchi-like architecture of a polystyrene-sphere-supported TiO2/Bi2O3 (PS@TiO2/Bi2O3) S-scheme heterojunction was skillfully constructed and evaluated for photodegradation of model tetracycline (TC) antibiotics. By integrating the advantages of floatability and S-scheme, the TC removal rate of the optimal PS@TiO2/Bi2O3-0.4 catalyst can reach 88.4% under 1 h illumination, which is higher than that of pristine Bi2O3 (60.8%) and PS@TiO2 (40.1%). Moreover, PS@TiO2/Bi2O3-0.4 exhibits high recyclability and stability, and there is no significant loss of activity after five cycles of repeated use. With the aid of liquid chromatography-mass spectrometry analysis and density functional theory calculations, a reasonable degradation pathway for TC was proposed. The present work provides a recyclable and efficient approach for the photodegradation of TC, expecting to guide the innovative exploitation of other environmental systems.

Dynamic Evaluation of Transformation Ability for Emergency Scientific Research Achievements Based on an Improved Minimum Distance-Maximum Entropy Combination Weighting Method: A Case Study of COVID-19 Epidemic Data.

In the process of responding to major public health emergencies, the transformation of emergency scientific research results often faces many unfavourable factors such as limited resources, tight time, changes in needs, and lack of results. It is necessary to evaluate and analyze the ability to transform emergency scientific research results under public health emergencies, so as to rationally allocate emergency scientific research resources between subjects and regions, improve the efficiency of emergency results transformation, enhance emergency scientific research capabilities, and efficiently support incident prevention, control, and treatment. Starting from the patent level, this paper constructs an indicator system to evaluate the transformation ability of emergency scientific research results under major public health emergencies. It improves the minimum distance-maximum entropy combination weighting method to realize the static evaluation of transformation ability for emergency scientific research results from the perspective of patents, then constructs the dynamic evaluation model of transformation ability for emergency scientific research results in public health emergencies from the perspective of patents, and carries out the dynamic evaluation of the emergency scientific research achievements transformation ability of different subjects and different regions. We also improve the ER index, measure the static polarization effect of the transformation ability for regional emergency scientific research results, and consider the time factor to construct a dynamic polarization effect measurement model for the transformation ability of emergency scientific research achievement. Furthermore, this paper improves the measurement model of contribution degree to the polarization effect, and analyzes the contribution degree to polarization of the transformation ability for regional emergency scientific research results.

Analyzing farm households' perception and choice of adaptation strategies towards climate change impacts: a case study of vulnerable households in an emerging Asian region.

Poor agricultural communities are particularly more disruptive to changes in climate. In southeast Asian countries, Pakistan is extremely vulnerable to weather-related events including droughts and floods. This research study aims to determine the farmers' perception towards climatic risks, farmers' choice of adaptation strategies and factors influencing farmers' decision of adaptation measures. A face-to-face household survey was conducted to collect primary data of 378 farm households from three tehsils of district Charsadda-Khyber Pakhuntkhwa (KP) province of Pakistan. A structured questionnaire was utilized as an instrument to collect data from the targeted farmers in study areas (three tehsils of district Charsadda). A binary probit model approach was used to assess the major factors affecting farmers' decision towards adaptation measures. Results revealed that changing crop varieties, diversification of crops, changing crop calendar, and insurance of crops were the major adaptive measures exercised by farm households in their farms. Findings of the binary probit approach showed that age of the respondents, farm size, educational level, credit access, household size, extension services access and perception of increased floods, and reduction in precipitation had substantial effect on the farmers' adaptation strategies choice. Advanced agricultural practices in response to the climatic risks can thus have substantial effects and reduction in farmers' exposure to natural calamities. Study findings of our research can guide policy makers and concerned authorities and provide policy implications for future research studies.

Assessing Pakistan's energy use, environmental degradation, and economic progress based on Tapio decoupling model.

A comprehensive assessment of energy use, environmental degradation, and economic progress can play a significant role in transition towards low-carbon economy, and it can serve as a reference for the green economic development for the rest of the developing world. The objective of this paper is to empirically investigate the current status of conventional and renewable energy use and environmental degradation. Following this, we have analyzed the decoupling relation among environmental degradation, energy use, and economic progress in Pakistan. The study adopted the comprehensive data from year 1972-2017 and applied Tapio decoupling method to explore the decoupling status of environmental degradation, energy use, and economic progress in Pakistan. The key finding from the study shows that the overall value of carbon emissions in Pakistan is relatively increasing with the passage of time and shows about 5.26% average growth rate which is creating severe environmental degradation. There were observed several fluctuations in the trend of carbon emissions which is basically due to the policy changes in the country. From the decoupling point of view, we found the decoupling linkage between energy use and carbon emissions that is growth negative decoupling, whereas a weak decoupling relation has been observed among carbon emissions and economic progress which means that in most of the year's county has achieved more economic growth compared with the carbon emissions. In addition, the similar weak decoupling relationship was found among energy use and economic progress. In the light of these findings, it is suggested to policymakers to promote technological advancement and alternate energy that will not only improve environmental quality, but it will also promote a low-carbon economy.

Hybrid LSTM Self-Attention Mechanism Model for Forecasting the Reform of Scientific Research in Morocco.

Education is the cultivation of people to promote and guarantee the development of society. Education reforms can play a vital role in the development of a country. However, it is crucial to continually monitor the educational model's performance by forecasting the outcome's progress. Machine learning-based models are currently a hot topic in improving the forecasting research area. Forecasting models can help to analyse the impact of future outcomes by showing yearly trends. For this study, we developed a hybrid, forecasting time-series model by long short-term memory (LSTM) network and self-attention mechanism (SAM) to monitor Morocco's educational reform. We analysed six universities' performance and provided a prediction model to evaluate the best-performing university's performance after implementing the latest reform, i.e., from 2015-2030. We forecasted the six universities' research outcomes and tested our proposed methodology's accuracy against other time-series models. Results show that our model performs better for predicting research outcomes. The percentage increase in university performance after nine years is discussed to help predict the best-performing university. Our proposed algorithm accuracy and performance are better than other algorithms like LSTM and RNN.

Assessing energy efficiency in the Asia-Pacific region and the mediating role of environmental pollution: evidence from a super-efficiency model with a weighting preference scheme.

The demand for primary energy resources has increased significantly due to the rapid growth of the global economy and increasing greenhouse gas (GHG) emissions. Therefore, improving energy efficiency levels is essential for global energy, energy security, and environmental sustainability. In the context of the Asia-Pacific region, the study of energy efficiency among different countries can play a role in better energy utilization. These countries also provide a policy for the Asia-Pacific region to improve its energy utilization. This study's primary focus is to investigate the optimal efficiency score of 15 areas of the Asia-Pacific region, and the analysis is based on super-efficiency (radical) and super slacks-based measure (SBM) data in a nonparametric DEA model. Three areas in the Asia-Pacific are selected for energy efficiency measures: South Asia, East Asia, and Australasia. The results suggest that Bangladesh, Pakistan, China, Singapore, New Zealand, the Philippines, Japan, India, Indonesia, Malaysia, Thailand, and Vietnam obtain the most efficient score of 1 in both DEA models throughout the study period. Australia and Sri Lanka receive a low score during all study periods, while Hong Kong does not have data for all study years. The results of the study will help improve energy performance, cost-effectiveness, and environmental sustainability, increasing the competitiveness and scalability of efficient energy sources.

Exploring the impact of technological innovation, environmental regulations and urbanization on ecological efficiency of China in the context of COP21.

The objective of this study was to explore the roles of technological innovation, environmental regulations, and urbanization in ecological efficiency within the context of the 2015 Paris agreement. Initially, the study employed the super-efficiency DEA model to estimate the ecological efficiencies of 30 regions in China. Following this, the system GMM method was used to explore the impacts of technological innovation, environmental regulations, and urbanization on ecological efficiency. We used annual data from 2008 to 2018. The results indicate that, in terms of ecological efficiency, the eastern region was the highest ranked, followed by central and western regions, respectively. The urbanization index has a negative impact on ecological efficiency at a national level. However, in the context of regions, it is positively significant in the eastern region, while the results in the central and western regions are insignificant. The influence of technological innovation on ecological efficiency is found to be significantly positive at both national and regional levels. It is generally perceived that environmental regulations are pivotal for sustainability. Our results verify this argument and indicate that environmental regulations have a positive impact on ecological efficiency in the central and eastern regions. However, their impact is found to be negative in the western region. Policy suggestions are discussed, in order to further strengthen environmental laws and sustainability.

Trilemma assessment of energy intensity, efficiency, and environmental index: evidence from BRICS countries.

This paper provides an assessment of energy density and energy efficiency and creates an important indicator of environmental performance. This article applied two mathematical models and econometric techniques to obtain detailed and specific results. The DEA and the non-normative account aggregation mean a collective aggregation to form a mathematical aggregation tool to create an environmental index for the BRICS countries (Brazil, Russia, India, China, and South Africa) based on available data from 2011 to 2016. The advantage of the proposed approach is to manage the irregularities of the data and follow the desired properties of the index number. The current paper is relevant for the broad scope of construction, the environmental index, and the evolution of the rankings of countries based on multiple indicators. Our results indicate that Brazil and Russia have the highest values of the Environmental Performance Index, which range between 67.44 and 60.70, respectively. India has a minimum value of 30.57 of the environmental index. The analysis shows that Brazil, Russia, and South Africa have the best scores and that these countries have the best results, while China and India also have the best results. This study can help form a valuable political tool for the development and development of the country's politics.

Can government environmental auditing improve static and dynamic ecological efficiency in China?

As an important part of external supervision, government environmental auditing plays a significant role in the construction of ecological civilization. With the execution of environmental audit events by the National Audit Office of China (CNAO) during 2008 to 2018, we examine the impact of government environmental auditing on ecological efficiency by using multiple regression method and PSM method. Our analyses show that government environmental auditing can obviously improve both static and dynamic ecological efficiency. Further research suggests that (1) government environmental auditing has a short-term improvement effect on ecological efficiency but nothing in the long run. (2) Government environmental auditing plays a supervisory and warning role in improving ecological efficiency. Those findings provide empirical evidence for the effects of government environmental auditing on ecological efficiency. The current study has some theoretical and practical implications for the government in terms of strengthening the external supervision of environmental protection and improving the ecological efficiency.

Synergistic third-party rewarding and punishment in the public goods game.

We study the evolution of cooperation in the spatial public goods game in the presence of third-party rewarding and punishment. The third party executes public intervention, punishing groups where cooperation is weak and rewarding groups where cooperation is strong. We consider four different scenarios to determine what works best for cooperation, in particular, neither rewarding nor punishment, only rewarding, only punishment or both rewarding and punishment. We observe strong synergistic effects when rewarding and punishment are simultaneously applied, which are absent if neither of the two incentives or just each individual incentive is applied by the third party. We find that public cooperation can be sustained at comparatively low third-party costs under adverse conditions, which is impossible if just positive or negative incentives are applied. We also examine the impact of defection tolerance and application frequency, showing that the higher the tolerance and the frequency of rewarding and punishment, the more cooperation thrives. Phase diagrams and characteristic spatial distributions of strategies are presented to corroborate these results, which will hopefully prove useful for more efficient public policies in support of cooperation in social dilemmas.

How Does the Concentration of Determinants Affect Industrial Innovation Performance? - An Empirical Analysis of 23 Chinese Industrial Sectors.

The agglomeration of innovation determinants has a significant influence on the innovation performance of industries and enterprises. Such an effect has received less attention in empirical research studies. This study involves a survey of the agglomeration effect of two important innovation determinants, R&D investment and R&D personnel, and its influence on innovation performance from the perspective of the industrial level. We analysed the agglomeration features based on the panel data of 23 Chinese industrial sectors from 2001~2013. An interpretation model is proposed to examine the agglomeration effect on innovation performance for 4 industrial groups: state-owned enterprises, individual enterprises, foreign-owned enterprises and enterprises as a whole. We found two main results. First, the agglomeration of determinants has a clear positive effect on the innovation performance of all 4 groups but affects individual enterprises more significantly, followed by state-owned and foreign-owned enterprises. Second, the state-owned enterprises show a much higher concentration of R&D investment and R&D personnel than other groups. However, the induced innovation efficiency in the state-owned enterprises is worse than in the individual enterprises. The advantage of resources and capital does not translate into corresponding innovation output. The privately owned small and medium-sized enterprises (SMEs) show a high capability of technological innovation and mercerization but have limited innovation resources.

Vehicle scheduling schemes for commercial and emergency logistics integration.

In modern logistics operations, large-scale logistics companies, besides active participation in profit-seeking commercial business, also play an essential role during an emergency relief process by dispatching urgently-required materials to disaster-affected areas. Therefore, an issue has been widely addressed by logistics practitioners and caught researchers' more attention as to how the logistics companies achieve maximum commercial profit on condition that emergency tasks are effectively and performed satisfactorily. In this paper, two vehicle scheduling models are proposed to solve the problem. One is a prediction-related scheme, which predicts the amounts of disaster-relief materials and commercial business and then accepts the business that will generate maximum profits; the other is a priority-directed scheme, which, firstly groups commercial and emergency business according to priority grades and then schedules both types of business jointly and simultaneously by arriving at the maximum priority in total. Moreover, computer-based simulations are carried out to evaluate the performance of these two models by comparing them with two traditional disaster-relief tactics in China. The results testify the feasibility and effectiveness of the proposed models.