Land-population-industry based village evolution and its influencing factors in the upper Tuojiang River

With economic development and urbanization in China,the rural settlements have experienced great change.To explore the evolution process of rural settlements in terms of land,population and industry can reveal the development law of rural spatial distribution,population structure and industrial economy in different stages and regions.Studying the development status and evolution characteristics of villages in the upper Tuojiang River basin in Southwest China in the past 20 years are of significant value.The upper Tuojiang River basin includes the main types of terrain found in the Southwest region:mountainous,plains,and hills,exhibiting a certain typicality of geographical characteristics.This study took towns and townships at the town-level scale as the basic unit of research,and constructed an evaluation system for village evolution based on'land,population,and industry'.It employed Criteria Importance Through Inter-Criteria Correlation(CRITIC)analysis to examine the characteristics of village evolution in the area from 2000 to 2020,and used geographic detector analysis to identify the leading factors affecting village evolution.The results show that:(1)From 2000 to 2010,villages in the upper Tuojiang River basin experienced significant changes,and the pace of these transformations slowed from 2010 to 2020.(2)From a comprehensive perspective,from 2000 to 2020,villages in hilly areas show a decline,while villages in plain areas near the city center show a positive urbanization development.(3)Road accessibility and distance from the city center are the main factors that explain the spatial differentiation of village evolution degree in the study area.This study elucidates the spatiotemporal evolution characteristics of villages in the upper Tuojiang River basin and identifies the primary factors contributing to their changes,which will provide a reference for investigating the development of rural areas in different terrains of Southwest China.

Investigation into the Methodology and Implementation of Life Cycle Engineering under China’s Carbon Reduction Target in the Process Industry

The industrial sector is the primary source of carbon emissions in China.In pursuit of meeting its carbon reduction targets,China aims to promote resource consumption sustainability,reduce energy consumption,and achieve carbon neutrality within its processing industries.An effective strategy to promote energy savings and carbon reduction throughout the life cycle of materials is by applying life cycle engineering technology.This strategy aims to attain an optimal solution for material performance,resource consumption,and environmental impact.In this study,five types of technologies were considered:raw material replacement,process reengineering,fuel replacement,energy recycling and reutilization,and material recycling and reutilization.The meaning,methodology,and development status of life cycle engineering technology abroad and domestically are discussed in detail.A multidimensional analysis of ecological design was conducted from the perspectives of resource and energy consumption,carbon emissions,product performance,and recycling of secondary resources in a manufacturing process.This coupled with an integrated method to analyze carbon emissions in the entire life cycle of a material process industry was applied to the nonferrous industry,as an example.The results provide effective ideas and solutions for achieving low or zero carbon emission production in the Chinese industry as recycled aluminum and primary aluminum based on advanced technologies had reduced resource consumption and emissions as compared to primary aluminum production.

A Review on Security and Privacy Issues Pertaining to Cyber-Physical Systems in the Industry 5.0 Era

The advent of Industry 5.0 marks a transformative era where Cyber-Physical Systems(CPSs)seamlessly integrate physical processes with advanced digital technologies.However,as industries become increasingly interconnected and reliant on smart digital technologies,the intersection of physical and cyber domains introduces novel security considerations,endangering the entire industrial ecosystem.The transition towards a more cooperative setting,including humans and machines in Industry 5.0,together with the growing intricacy and interconnection of CPSs,presents distinct and diverse security and privacy challenges.In this regard,this study provides a comprehensive review of security and privacy concerns pertaining to CPSs in the context of Industry 5.0.The review commences by providing an outline of the role of CPSs in Industry 5.0 and then proceeds to conduct a thorough review of the different security risks associated with CPSs in the context of Industry 5.0.Afterward,the study also presents the privacy implications inherent in these systems,particularly in light of the massive data collection and processing required.In addition,the paper delineates potential avenues for future research and provides countermeasures to surmount these challenges.Overall,the study underscores the imperative of adopting comprehensive security and privacy strategies within the context of Industry 5.0.

An Integrated Analysis on the Synergistic Reduction of Carbon and Pollution Emissions from China’s Iron and Steel Industry

Decarbonization and decontamination of the iron and steel industry(ISI),which contributes up to 15%to anthropogenic CO_(2) emissions(or carbon emissions)and significant proportions of air and water pollutant emissions in China,are challenged by the huge demand for steel.Carbon and pollutants often share common emission sources,indicating that emission reduction could be achieved synergistically.Here,we explored the inherent potential of measures to adjust feedstock composition and technological structure and to control the size of the ISI to achieve carbon emission reduction(CER)and pollution emission reduction(PER).We investigated five typical pollutants in this study,namely,petroleum hydrocarbon pollutants and chemical oxygen demand in wastewater,particulate matter,SO_(2),and NO_(x) in off gases,and examined synergies between CER and PER by employing cross elasticity for the period between 2022 and 2035.The results suggest that a reduction of 8.7%-11.7%in carbon emissions and 20%-31%in pollution emissions(except for particulate matter emissions)could be achieved by 2025 under a high steel scrap ratio(SSR)scenario.Here,the SSR and electric arc furnace(EAF)ratio serve critical roles in enhancing synergies between CER and PER(which vary with the type of pollutant).However,subject to a limited volume of steel scrap,a focused increase in the EAF ratio with neglection of the available supply of steel scrap to EAF facilities would lead to an increase carbon and pollution emissions.Although CER can be achieved through SSR and EAF ratio optimization,only when the crude steel production growth rate remains below 2.2%can these optimization measures maintain the emissions in 2030 at a similar level to that in 2021.Therefore,the synergistic effects between PER and CER should be considered when formulating a development route for the ISI in the future.

A Multi-Stage Differential-Multifactorial Evolutionary Algorithm for Ingredient Optimization in the Copper Industry

Ingredient optimization plays a pivotal role in the copper industry,for which it is closely related to the concentrate utilization rate,stability of furnace conditions,and the quality of copper production.To acquire a practical ingredient plan,which should exhibit long duration time with sufficient utilization and feeding stability for real applications,an ingredient plan optimization model is proposed in this study to effectively guarantee continuous production and stable furnace conditions.To address the complex challenges posed by this integer programming model,including multiple coupling feeding stages,intricate constraints,and significant non-linearity,a multi-stage differential-multifactorial evolution algorithm is developed.In the proposed algorithm,the differential evolutionary(DE)algorithm is improved in three aspects to efficiently tackle challenges when optimizing the proposed model.First,unlike traditional time-consuming serial approaches,the multifactorial evolutionary algorithm is utilized to optimize multiple complex models contained in the population of evolutionary algorithm caused by the feeding stability in a parallel manner.Second,a repair algorithm is employed to adjust infeasible ingredient lists in a timely manner.In addition,a local search strategy taking feedback from the current optima and considering the different positions of global optimum is developed to avoiding premature convergence of the differential evolutionary algorithm.Finally,the simulation experiments considering different planning horizons using real data from the copper industry in China are conducted,which demonstrates the superiority of the proposed method on feeding duration and stability compared with other commonly deployed approaches.It is practically helpful for reducing material cost as well as increasing production profit for the copper industry.

Impacts of agri-food e-commerce on traditional wholesale industry:Evidence from China

Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)has not received enough attention in the existing literature.Based on the provincial panel data from 2013 to 2020 in China,this paper examines the effect of AEC on AWI,comprising three dimensions:digitalization(DIGITAL),agrifood e-commerce infrastructure and supporting services(AECI),and agri-food e-commerce economy(AECE).First,AWI and AEC are measured using an entropy-based combination of indicators.The results indicate that for China as a whole,AWI has remained practically unchanged,whereas AEC exhibits a significant rising trend.Second,the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI,whereas AECI negatively affects AWI.Third,threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity,which manifests as a first increase and then a drop in the inhibition degree.These results suggest that with the introduction of e-commerce for agricultural product circulation,digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress.Furthermore,the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.

City Network Evolution Characteristics of Smart Industry: Evidence from Yangtze River Delta, China

The dual-path model of industrial evolution and spatial progression has been widely acknowledged and incorporated into the strategic planning to promote the development of urban industries and regional collaborations.However,current research on inter-enter-prise city networks mainly focuses on the single sector of flows on all enterprise branches,such as product value chains and production factors,but neglects that of particular industry department.Built upon the new economic geography and city networks theory,this paper develops a methodological framework that focuses on the analysis of city network evolution characteristics of smart industry.Particu-larly,a conceptual model of smart industry enterprise-industry-city is proposed and then applied to a case study of smart industry in the Yangtze River Delta Region,China.Using enterprise supplier-customer data,a city network of smart industry is constructed and sub-sequently analyzed with the proposed model.Findings indicate that the smart industry network in Yangtze River Delta Region exhibits a hierarchical structure and the expansion of the network presents a small-world network characteristic.The study not only makes a meth-odological contribution for revealing the industrial and spatial evolution path of the current smart industry,but also provides empirical support for the formulation of new economic development policies focused on smart industries,demonstrating the role of city clusters as carriers of regional synergistic development.

Research status and application of artificial intelligence large models in the oil and gas industry

This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.

Production and achievements of Sesamum indicum industry in the world:Past and current state

Sesame production is important in agriculture,food industry,and the crop diversity due to its rich nutritional profile and health benefits.Despite its significant value,sesame is still an orphan crop that has received little scientific attention,resulting in low yield compared to other major oilseed crops.This review offers a comprehensive overview of the present state of production,knowledge,and research advancements concerning Sesamum indicum on a global scale.The FAOSTAT database was extensively used to examine the global trends from 1961 to 2021.In the past 60 years,global sesame production has substantially increased,with Asia and Africa being the primary producers.The integration of omics technologies and biotechnological interventions has revolutionized our understanding of the genetic basis of sesame,enhanced productivity,invigorated stress resilience,and improved seed quality.High-throughput sequencing methods such as RNA-seq,RAD-seq,SLAF-seq,and GBS technology are used in various studies,linkage mapping,and identification of trait-associated markers.Fine linkage maps,and multi-omics studies such as genomics,proteomics,transcriptomics,and metabolomics have been employed in sesame research for gene and QTL mapping.Proteins and metabolic pathways related to oil content,yield,and stress tolerance were reported.Genes and QTLs related to yield and its components,drought,salt,and osmotic stress tolerance were discovered.Candidate genes associated with capsule shattering and seed shattering were recently revealed.For more achievement in sesame,it is important to enhance sesame production efficiency through mechanization,advanced agricultural practices,and knowledge dissemination to farmers.MAS and multi-omics integration should be particularly reinforced.The advancements in sesame production present a significant and promising opportunity for farmers,governments,and stakeholders in the agricultural sector.

Academic productivity correlates with industry earnings in foot and ankle fellowship programs in the United States:A retrospective analysis

BACKGROUND The study investigates the connection between academic productivity and industry earnings in foot and ankle orthopedic surgery fellowships.Utilizing metrics like the H-index and Open Payments Database(OPD)data,it addresses a gap in understanding the relationship between scholarly achievements and financial outcomes,providing a basis for further exploration in this specialized medical field.AIM To elucidate the trends between academic productivity and industry earnings across foot and ankle orthopedic surgery fellowship programs in the United States.METHODS This study is a retrospective analysis of the relationship between academic productivity and industry earnings of foot and ankle orthopedic surgery fellowships at an individual faculty and fellowship level.Academic productivity was defined via H-index and recorded from the Scopus website.Industry earnings were recorded from the OPD.RESULTS Forty-eight foot and ankle orthopedic surgery fellowships(100%of fellowships)in the United States with a combined total of 165 physicians(95.9%of physicians)were included.Mean individual physician(n=165)total life-time earnings reported on the OPD website was United States Dollar(USD)451430.30±1851084.89(range:USD 25.16-21269249.85;median:USD 27839.80).Mean physician(n=165)H-index as reported on Scopus is 14.24±12.39(range:0-63;median:11).There was a significant but weak correlation between individual physician H-index and individual physician total life-time earnings(P<0.001;Spearman’s rho=0.334)and a significant and moderate positive correlation between combined fellowship H-index and total life-time earnings per fellowship(P=0.004,Spearman’s rho=0.409).CONCLUSION There is a significant and positive correlation between academic productivity and industry earnings at foot and ankle orthopedic surgery fellowships in the United States.This observation is true on an individual physician level as well as on a fellowship level.

The heterogeneous impact of China-Europe railway express on the efficiency of logistics industry in node cities

Purpose-The spatiotemporal compression effect of China-Europe Railway Express(CR-Express)can reduce the filow costs of resources between China's node cities.Additionally,it can break through the limitations of low-added-value marine products,significantly impacting the logistics industry efficiency.However,there are few literature verifying and analyzing its heterogeneity.This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.Design/methodology/approach-First,this study uses panel data to measure the efficiency of node city logistics industry.Secondiy,this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model.Finally,according to the node city difference,the sample city experimental group is grouped for heterogeneity analysis.Findings-The results show that CR-Express can promote the urban logistics industry efficiency,with an average effect of 4.55%.According to the urban characteristics classification,the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious.The improvement effect of node cities and central cities in central and western China is stronger,especially in the sample of megacities and type I big cities.Compared with non-value chain industrial products,the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.Originality/value-Under the background of double cycle development,this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

Exploring Paths for the High-Quality Development of Forest-Based Wel ness Industry:A Case Study of Sichuan Province

The forest-based wellness industry,as a rapidly growing sector that integrates various business forms with extensive coverage and an extended industrial chain,is undergoing rapid development due to the increasing aging population and people's suboptimal health conditions.As a forerunner in developing the forest-based wellness industry,Sichuan province is known for its early development,proactive efforts,diverse models,and significant impact in this industry.It has achieved certain milestones in terms of top-level design,pilot demonstration,standardized guidance,and public awareness campaigns to promote the development of this industry.Therefore,this paper utilizes Sichuan as a case study to systematically summarize and analyze the key practices made by the province in promoting the rapid development of the industry by investigating the development trajectory of the forest-based wellness industry.Additionally,it examines the development trends of this industry from the perspectives of supply,demand,and consumption.Finally,this paper proposes several measures to facilitate the high-quality development of the forest-based wellness industry.These measures encompass nurturing specialized talent in forest-based wellness,enhancing market players'capabilities in this domain,conducting extensive research on technologies that promote this industry,actively seeking support from relevant policies,and promoting integrated development across diverse sectors.

The Effects of Disruptive Thinking on the Food Industry*

This study aimed to understand disruptive thinking and how its ideas can change the food industry. This was achieved by identifying, studying, and understanding the impacts, current trends, and different disruptive ideas and innovations emerging in the food industry. The study was conducted through interpretive research philosophy by carrying out secondary data collection processes, where both qualitative and quantitative information was presented. Deductive approaches were also selected to apply existing theories and models, which were used to construct research hypotheses and present detailed findings. The study finds that, with disruptive thinking, enhancements in the product life cycle, new flavors, and improvements in food packaging have been possible. The supply chain, which is always considered a complex part of the food industry, has been streamlined, offering greater transparency and real-time tracking and improving quality control across distribution systems.

Research Progress and Prospects of Total Factor Productivity in the Construction Industry

The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the construction industry to a higher level by scientifically and accurately measuring the total factor productivity of the construction industry and deeply analyzing the influencing factors behind it.Based on a comprehensive consideration of research methods and influencing factors,this paper systematically reviews the existing relevant literature on total factor productivity in the construction industry,aiming to reveal the current research development trend in this field and point out potential problems.This effort aims to provide a solid theoretical foundation and valuable reference for further in-depth research,and jointly promote the continuous progress and development of total factor productivity research in the construction industry.

Carbon Emission Measurement and Regional Difference Analysis of China's Construction Industry

Green and low-carbon development of construction industry is one of the important ways to achieve the"dual carbon"goal in China.This study first measured the carbon emissions of the construction industry in 30 provinces in China,and then used the Dagum Gini coefficient and its decomposition method to explore the regional differences and sources of carbon emissions of the construction industry in China.The results show that the carbon emissions of construction industry in China generally show an upward trend,and there are significant differences in carbon emissions of construction industry among provinces,and the main source of regional differences is inter-regional differences.However,the contribution rate of inter-regional differences showed a significant downward trend,while the contribution rate of hyperbolic density increased day by day,and the contribution rate of intra-regional differences increased slightly.The results of this study will provide a reference for China to formulate more reasonable carbon emission reduction targets and differentiation strategies for the construction industry.

Carbon emission risk of construction industry in Hebei Province of China based on carbon sink thresholds

In order to assess the environmental risks caused by carbon emissions from the construction industry in Hebei Province of China,an environmental risk assessment model based on forest carbon sink threshold was constructed to evaluate the carbon emission risks of the construction industry in Hebei Province,China from 2005 to 2020.The results are shown as follows:(1)The overall carbon emissions of the construction industry in Hebei Province of China showed an inverted"V"-shaped evolution trend during the past 16 years.Tangshan and Shijiazhuang maintained high carbon emissions,while Langfang,Hengshui and Baoding saw rapid increases in carbon emissions.(2)The environmental safety threshold of carbon emission from the construction industry in Hebei Province,China,has been continuously improved,and the provincial environmental safety threshold is between 9475080-23144760 tons;The environmental safety threshold was the highest in Baoding and Langfang,and the lowest in Xingtai.(3)In the past 16 years,the carbon emission risk of the construction industry in Hebei Province of China has been in a state of extremely serious risk,and the risk index generally presents an inverted"V"type trend.(4)The carbon emission risk of Hebei city in China presents a spatial pattern of"high in the south and low in the north",which goes through two stages:risk increase period and risk reduction period.

Reform of Theory-practice Alternating Teaching of the Introduction to Architecture Course Oriented to“Employment Priority and Integration of Industry and Education”

In the new era of building a socialist modernization country with the goal of promoting high-quality development,we deeply analyze the knowledge system of the Introduction to Architecture course.This analysis is based on the cross-disciplinary specialties of local applied universities and the orientation of prioritizing employment and integrating industry and education.We propose the teaching reform of“theory-practice alternation”which is adapted to the current times and societal needs.Finally,we comprehensively summarize the effectiveness of curriculum construction,in order to provide theoretical references for the implementation of fostering character and civic virtue and deepening the reform of collaborative education mechanisms.

Guarantee Strategy for the Safety of Agricultural Industry in Hunan Province

The safety of agricultural industry in Hunan Province shows an upward trend from"basically safe"to"very safe",but the state in the"safe"or"very safe"range is still unstable.In view of this,Hunan Province should guarantee the agricultural production ability,cultivate and enhance the core competitiveness of agriculture,firmly grasp the agricultural control power,attach importance to the export quality of agri-cultural products and other aspects to ensure the safety of agricultural industry.

Application of Large Language Models in Data Governance in the Petroleum and Petrochemical Industry

This paper delves into the current application, challenges, and demands of data governance in the oil and gas industry, as well as methods and implementation strategies to enhance data governance efficacy through the latest technologies such as large language models and algorithm optimization. Through the analysis of the current application status of large language models in intelligent data classification, data quality improvement, knowledge extraction and management, and intelligent search and information retrieval, the main challenges and demands faced by the petroleum and petrochemical industry in data governance have been revealed. A set of data governance optimization solutions tailored for the oil and gas industry has been proposed. These solutions aim to address the current data management challenges in the industry through advanced data processing technologies and algorithmic optimization, enhance the efficiency and quality of data governance, and thereby support the digital transformation and development of the oil and gas industry.

Review on the Development of Cosmetic Industry from the Perspective of Group Standards

From the perspective of group standards, the dynamics of the cosmetic industry in the past few years were briefly reviewed and analyzed, including the number of group standards published, types of group standards, groups, and geographical distribution of the groups. The large number of participating groups and the wide range of geographical distribution indicated that group standards could play a positive role in the sustained and positive development of cosmetic industry. The future development of cosmetic industry was also prospected。