Assessment of challenges and strategies for driving energy transitions in emerging markets:A socio-technological systems perspective

The pursuit of improved quality of life standards has significantly influenced the contemporary mining model in the 21st century.This era is witnessing an unprecedented transformation driven by pressing concerns related to sustainability,climate change,the just energy transition,dynamic operating environments,and complex social challenges.Such transitions present both opportunities and obstacles.The aim of this study is to provide an extensive literature review on energy transition to identify the challenges and strategies associated with navigating transformations in energy systems.Understanding these transformations is particularly critical in the face of the severe consequences of global warming,where an accelerated energy transition is viewed as a universal remedy.Adopting a socio-technological systems perspective,specifically through the application of Actor Network Theory(ANT),this research provides a theoretical foundation while categorising challenges into five distinct domains and outlining strategies across these different dimensions.These insights are specifically tailored for emerging market countries to effectively navigate energy transition while fostering the development of resilient societies.Furthermore,our findings highlight that energy transition encompasses more than a mere technological shift;it entails fundamental changes in various systemic socio-economic imperatives.Through focusing on the role of social structures in transitions,this study makes a significant and innovative contribution to ANT,which has historically been criticised for its limited acknowledgement of social structures.Consequently,we propose an emerging market energy transition framework,which not only addresses technological aspects,but also integrates social considerations.This framework paves the way for future research and exploration of energy transition dynamics.The outcomes of this study offer valuable insights to policymakers,researchers,and practitioners engaged in the mining industry,enabling them to comprehend the multifaceted challenges involved and providing practical strategies for effective resolution.Through incorporating the social dimension into the analysis,we enhance the understanding of the complex nature of energy system transformations,facilitating a more holistic approach towards achieving sustainable and resilient energy transitions in emerging markets and beyond.

Metabolic dysfunction-associated steatotic liver disease:Navigating terminological evolution,diagnostic frontiers and therapeutic horizon-an editorial exploration

Metabolic dysfunction-associated steatotic liver disease(MASLD),once known as non-alcoholic fatty liver disease(NAFLD),represents a spectrum of liver disorders characterized by lipid accumulation within hepatocytes.The redefinition of NAFLD in 2023 marked a significant reposition in terminology,emphasizing a broader understanding of liver steatosis and its associated risks.MASLD is now recognized as a major risk factor for liver cirrhosis,hepatocellular carcinoma,and systemic complications such as cardiovascular diseases or systemic inflammation.Diagnostic challenges arise,particularly in identifying MASLD in lean individuals,necessitating updated diagnostic protocols and investing in non-invasive diagnostic tools.Therapeutically,there is an urgent need for effective treatments targeting MASLD,with emerging pharmacological options focusing on,among others,carbohydrate and lipid metabolism.Additionally,understanding the roles of bile acid metabolism,the microbiome,and dietary interventions in MASLD pathogenesis and management holds promise for innovative therapeutic approaches.There is a strong need to emphasize the importance of collaborative efforts in understanding,diagnosing,and managing MASLD to improve physicians’approaches and patient outcomes.

Improving innovation and entrepreneurship education in higher institutions: the impact of "Mass Entrepreneurship and Innovation" education on undergraduates' entrepreneurial intentions

The exploration of the way"mass entrepreneurship and innovation"(MEI)education influences students'aspirations to become entrepreneurs has grown into an important area of analysis in studies related to higher education.This research intends to examine the consequences of MEI education on students'tendency towards entrepreneurship,and to put forward methods for augmenting the teaching of innovation and entrepreneurship in private higher educational establishments.To achieve this objective,questionnaires and semi-structured interviews were employed in the study,which involved a total of 197 students and five education experts.The statistical analysis of the questionnaire data revealed that MEI education was positively related to students'entrepreneurial intentions,and that both entrepreneurial experience and family entrepreneurial background played moderating roles in this relationship.The interview findings indicated that private universities could enhance educational reforms by designing talent training programs,developing diversified curricula,and developing more professional entrepreneurial platforms to encourage students'entrepreneurial intentions.This study offers fresh insights for improving and perfecting the mechanism of innovation and entrepreneurship education in private universities.

Influence mechanism of government subsidy on the green transformation of coal company in China

The optimization of government subsidies to enhance the efficiency of coal companies’green transformation constitutes a critical component in the pursuit of global sustainability.We investigate the influence mechanism of government subsidies on the green transformation using data from the listed coal companies in China from 2007 to 2022.According to our findings and hypothesis testing,previous government subsidies did not have a significant direct impact on coal companies’green transformation.Nevertheless,government subsidies can help coal companies transition to greener practices by promoting innovative green initiatives.Furthermore,we confirmed an indirect route:that government subsidies enable the adoption of low-carbon initiatives,which in turn could facilitate the transition of coal companies towards green practices.In addition,we discovered that the coal company’s digitization will improve this indirect route.Thus,we propose increasing the effectiveness of government subsidies in facilitating coal companies’transition to green practices by focusing on technological advancements and enhancing company digitalization.

Addressing inclusion,innovation,and sustainability challenges through the lens of economic geography:Introducing the hierarchical regional innovation system

The world is facing dramatic challenges related to environmental sustainability at an accelerating pace.In this context,the field of economic geography(EG)has been playing an important role in understanding both the socioeconomic and technological dimensions of these challenges,as it deals with a variety of complementary notions and perspectives.Departing from this lens,our aim is to explore a conceptual framework that can help us to understand environmental changes relating to multi-dimensional territorial development,notably in eco-nomic contexts where inequality is high,and stratification based on hierarchies regulate social and economic life.Based on the territory concept,we propose the original notion of a hierarchical regional innovation system(HRIS)that emphasises the pervasive role of hierarchies(powers)in regional innovation systems and illustrate its value with evidence and case studies from extant literature on sustainability transitions.The HRIS can help us understand and promote development paths considering the contribution of inclusive eco-innovations(another original conceptual amalgam).Through some empirical cases from other studies in low-carbon transitions,we show the application of the HRIS(and inclusive eco-innovation)framework.In conclusion,we provide incen-tives to explore new regional innovation systems,alongside the HRIS,adapted to different regions worldwide and centred on the inclusiveness of people and places.

Editorial for the Special Issue on Natural Medicine

As the world continues to search for innovative therapeutic solutions,the field of natural medicines has emerged as a vibrant area of research.The potential of natural products to treat a wide range of diseases,coupled with the relatively low sideeffects of such products,has captured the attention of scientists,clinicians,and the general public alike.This Special Issue on Natural Medicine aims to present the latest advancements in this exciting field,highlighting both fundamental research and clinical applications.The collection of articles in this Special Issue covers a broad spectrum of topics,ranging from medicinal chemistry to biological mechanisms,and from the study of single botanic compounds to complex plant formulas.We are particularly pleased to include a comprehensive review by Yi Wang et al.on the bioactivities,mechanisms,production,and potential application of bile acids in preventing and treating infectious diseases.This review not only summarizes the current landscape of bile acids research but also highlights several promising compounds for future investigations,such as the recent interest in ursodeoxycholic acid.In a related topic,Shishan Yu’s team has developed artificial bear bile using synthetic chemistry and enzyme engineering,providing a sustainable substitute for natural bear bile.This innovation meets medical needs while addressing animal welfare issues,representing a notable progression in the field.

Callfor Papersfor Special Issue Innovative Pharmaceutical Research Facilitated by Ai

Al is revolutionizing the current paradigm of pharmaceutical research,addressing the challenges encountered at all stages of the process.Al driven drug discovery is based on biomedical big data and new algorithms to identify drug targets,screen and optimize active compounds,analyze drug properties,and facilitate drug production and quality control.On this basis,we are organize this special issue entitled“Innovative Pharmaceutical Research Driven by Al”,to collect Research articles,Review papers,and Short communications,facilitating pharmaceutical research.

Innovation and Firm Co-ownership Network in China’s Electric Vehicle Industry

Firms are embedded in complex networks,where diverse ideas combine and generate new ideas.Shareholders of firms are of-ten seen as critical external resources that have significant influence on firm innovation.The current literature tends to focus on the rela-tionship between firms and their shareholders,while paying less attention to the connections between firms with the same shareholders.This article identifies two types of network spillover effects,intra-city network effect and inter-city network effect,by visualizing the co-ownership networks in China’s electric vehicle(EV)industry.We find that firms with the same shareholders,which are defined as co-owned EV firms,are more innovative than non-co-owned ones.Furthermore,there are two dominant types of firm co-ownership ties formed by corporate and financial institution shareholders.While corporate shareholders help exploiting local tacit knowledge,financial institutions are more active in bridging inter-city connections.The conclusion is confirmed at both firm and city levels.This paper theor-izes the firm co-ownership network as a new form of institutional proximity and tested the result empirically.For policy consideration,we have emphasized the importance of building formal or informal inter-firm network,and the government should further enhance the knowledge flow channel by institutional construction.

Message from animal models and experimental medicine for 2024-Striving for excellence with distinctive features

Since its inception,Animal Models and Experimental Medicine(AMEM)has received 632 articles in total from 52 countries and regions includ-ing China,Iran,the United States,India,Nigeria,Israel,Germany,Iraq,Italy,Japan,Australia,Bangladesh,Belgium,Brazil,and Canada,among others.AMEM has become an important international exchange plat-form for innovative research achievements in the field of laboratory animal science and basic medicine.

Towards cultivar-oriented gene discovery for better crops

The continued expansion of the world population,increasingly inconsistent climate and shrinking agricultural resources present major challenges to crop breeding.Fortunately,the increasing ability to discover and manipulate genes creates new opportunities to develop more productive and resilient cultivars.Many genes have been described in papers as being beneficial for yield increase.However,few of them have been translated into increased yield on farms.In contrast,commercial breeders are facing gene decidophobia,i.e.,puzzled about which gene to choose for breeding among the many identified,a huge chasm between gene discovery and cultivar innovation.The purpose of this paper is to draw attention to the shortfalls in current gene discovery research and to emphasise the need to align with cultivar innovation.The methodology dictates that genetic studies not only focus on gene discovery but also pay good attention to the genetic backgrounds,experimental validation in relevant environments,appropriate crop management,and data reusability.The close of the gaps should accelerate the application of molecular study in breeding and contribute to future global food security.

The Future of Environmental Engineering Technology:A Disruptive Innovation Perspective

Scientific and technological revolutions and industrial transformations have accelerated the rate of innovation in environmental engineering technologies.However,few researchers have evaluated the current status and future trends of technologies.This paper summarizes the current research status in eight major subfields of environmental engineering—water treatment,air pollution control,soil/solid waste management,environmental biotechnology,environmental engineering equipment,emerging contaminants,synergistic reduction of pollution and carbon emissions,and environmental risk and intelligent management—based on bibliometric analysis and future trends in greenization,low carbonization,and intelligentization.Disruptive technologies are further identified based on discontinuous transformation,and ten such technologies are proposed,covering general and specific fields,technical links,and value sources.Additionally,the background and key innovations in disruptive technologies are elucidated in detail.This study not only provides a scientific basis for strategic decision-making,planning,and implementation in the environmental engineering field but also offers methodological guidance for the research and determination of breakthrough technologies in other areas.

Kinematic-mapping-model-guided analysis and optimization of 2-PSS&1-RR circular-rail parallel mechanism for fully steerable phased array antennas

This paper presents a systematic methodology for analyzing and optimizing an innovative antenna mount designed for phased array antennas, implemented through a novel 2-PSS&1-RR circular-rail parallel mechanism. Initially, a comparative motion analysis between the 3D model of the mount and its full-scale prototype is conducted to validate effectiveness. Given the inherent complexity, a kinematic mapping model is established between the mount and the crank-slider linkage, providing a guiding framework for subsequent analysis and optimization. Guided by this model, feasible inverse and forward solutions are derived, enabling precise identification of stiffness singularities. The concept of singularity distance is thus introduced to reflect the structural stiffness of the mount. Subsequently, also guided by the mapping model, a heuristic algorithm incorporating two backtracking procedures is developed to reduce the mount's mass. Additionally, a parametric finite-element model is employed to explore the relation between singularity distance and structural stiffness. The results indicate a significant reduction(about 16%) in the antenna mount's mass through the developed algorithm, while highlighting the singularity distance as an effective stiffness indicator for this type of antenna mount.

A novel multi-channel porous structure facilitating mass transport towards highly efficient alkaline water electrolysis

An advantageous porous architecture of electrodes is pivotal in significantly enhancing alkaline water electrolysis(AWE)efficiency by optimizing the mass transport mechanisms.This effect becomes even more pronounced when aiming to achieve elevated current densities.Herein,we employed a rapid and scalable laser texturing process to craft novel multi-channel porous electrodes.Particularly,the obtained electrodes exhibit the lowest Tafel slope of 79 mV dec^(-1)(HER)and 49 mV dec^(-1)(OER).As anticipated,the alkaline electrolyzer(AEL)cell incorporating multi-channel porous electrodes(NP-LT30)exhibited a remarkable improvement in cell efficiency,with voltage drops(from 2.28 to 1.97 V)exceeding 300 mV under 1 A cm^(-1),compared to conventional perforated Ni plate electrodes.This enhancement mainly stemmed from the employed multi-channel porous structure,facilitating mass transport and bubble dynamics through an innovative convection mode,surpassing the traditional convection mode.Furthermore,the NP-LT30-based AEL cell demonstrated exceptional durability for 300 h under 1.0 A cm^(-2).This study underscores the capability of the novel multi-channel porous electrodes to expedite mass transport in practical AWE applications.

Image Fusion Using Wavelet Transformation and XGboost Algorithm

Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same item.Image fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual perception.Image fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on application.The research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet transform.Image fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient manner.More precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain characteristics.To tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is proposed.The use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter choice.The simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original images.This study enhances the performance of the eXtreme Gradient Boosting(XGBoost)algorithm in detecting brain malignancies with greater precision through the integration of computational image analysis and feature selection.The performance of images is improved by segmenting them employing the K-Means algorithm.The segmentation method aids in identifying specific regions of interest,using Particle Swarm Optimization(PCA)for trait selection and XGBoost for data classification.Extensive trials confirm the model’s exceptional visual performance,achieving an accuracy of up to 97.067%and providing good objective indicators.

An Update on the Clinical Pipelines of New Antibacterial Drugs Developed in China

Antibacterial resistance is a global health threat that requires further concrete action on the part of all countries.In this context,one of the biggest concerns is whether enough new antibacterial drugs are being discovered and developed.Although several high-quality reviews on clinical antibacterial drug pipelines from a global perspective were published recently,none provides comprehensive information on original antibacterial drugs at clinical stages in China.In this review,we summarize the latest progress of novel antibacterial drugs approved for marketing and under clinical evaluation in China since 2019.Information was obtained by consulting official websites,searching commercial databases,retrieving literature,asking personnel from institutions or companies,and other means,and a considerable part of the data covered here has not been included in other reviews.As of June 30,2023,a total of 20 antibacterial projects from 17 Chinese pharmaceutical companies or developers were identified and updated.Among them,two new antibacterial drugs that belong to traditional antibiotic classes were approved by the National Medical Products Administration(NMPA)in China in 2019 and 2021,respectively,and 18 antibacterial agents are in clinical development,with one under regulatory evaluation,five in phase-3,six in phase-2,and six in phase-1.Most of the clinical candidates are new analogs or monocomponents of traditional antibacterial pharmacophore types,including two dual-acting hybrid antibiotics and a recombinant antibacterial protein.Overall,despite there being 17 antibacterial clinical candidates,our analysis indicates that there are still relatively few clinically differentiated antibacterial agents in stages of clinical development in China.Hopefully,Chinese pharmaceutical companies and institutions will develop more innovative and clinically differentiated candidates with good market potential in the future research and development(R&D)of original antibacterial drugs.

Drivers for Inter-city Innovation Networks Across Chinese Cities:Modelling Physical Versus Intangible Effects

Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.

Coordination Mechanism and Empirical Research on Marine Science Technology Innovation and Marine Eco-civilization:A Case Study of Coastal Areas of China

Marine science technology innovation provides power and guarantees for marine eco-civilization construction,which provides direction and material support for marine science technology innovation.Therefore,the coordinated development of the two is of great significance to the marine economy sustainable development in China’s coastal areas.On the basis of clarifying the connotations of marine science technology innovation and marine eco-civilization in China’s coastal areas from 2006 to 2019,the mechanism for their coordinated development was analysed.A comprehensive indicator system based on the connotation of the two was constructed,and the coordinated development relationship was empirically tested using the coupled coordination model and the panel vector autoregressive(PVAR)model.The results show that:1)the level of China’s coastal marine science technology innovation continues to improve,gradually forming the core of the development of marine science technology innovation in the north,east and south of Shandong,Shanghai and Guangdong;the level of marine eco-civilization development fluctuating upward trend,showing obvious spatial differentiation characteristics.2)The degree of coordination of marine science technology innovation and marine eco-civilization is growing over time.There is no causal relationship between marine science technology innovation and marine eco-civilization in the northern marine economic circle,but there is a two-way causal relationship between the two in the eastern and southern marine economic circles.3)Marine eco-civilization shows a significant positive and continuous impact on marine science technology innovation,and marine science technology innovation shows a long-term,continuous,fluctuating,and lagging impact on marine eco-civilization.The overall role of marine eco-civilization on marine science technology innovation is dominant,and there are significant differences in the impact effects of the two major marine economic circles.

Research on Innovation-Driven Expansion of Regional OFDI: New Evidence From a Business Environment Perspective

This paper investigates the impact of provincial innovation-driven efficiency on the expansion of regional Outward Foreign Direct Investment(OFDI)flows within the context of China’s economy during the period 2011 to 2020 by measuring the innovation-driven efficiency and business environment index using the DEA-Malmquist index and the combined CRITIC weighting method from the new perspective of business environment improvement.The findings reveal that:(a)There is an inverted U-shaped relationship between provincial innovation-driven efficiency and regional OFDI flows.This increase in innovation-driven efficiency can promote OFDI expansion of the region by improving its business environment.(b)The improvement of the business environments plays a significant intermediary and synergistic role in OFDI expansion driven by improved innovation efficiency.(c)The study of regional heterogeneity suggests that the central region enjoys the longest window period in terms of innovation-driven OFDI expansion,followed by the eastern region while the western region has the shortest window period.The improvement of the business environment in the western region is more effective in driving regional OFDI expansion.This conclusion remained true after the robustness test.In conclusion,this paper offers a few policy recommendations that can help Chinese capital of various kinds go global more effectively.

A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the Internet.Regrettably,this development has expanded the potential targets that hackers might exploit.Without adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or alteration.The identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious attacks.This research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)units.The proposed model can identify various types of cyberattacks,including conventional and distinctive forms.Recurrent networks,a specific kind of feedforward neural networks,possess an intrinsic memory component.Recurrent Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended periods.Metrics such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual cyberattacks.RNNs are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection Model.This model utilises Recurrent Neural Networks,specifically exploiting LSTM techniques.The proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

How to promote cooperative innovation in environmentally friendly technology:a case of agricultural biotechnology in China

This study explored the factors influencing cooperative innovation in environmentally friendly agricultural biotechnology in China.First,we constructed an evolutionary game model comprising the factors of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies.Using MATLAB simulation,we assigned different values to the aforementioned variables to explore the evolutionary trend of innovators’willingness to cooperate.Results showed that when the values of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies exceeded the threshold,innovators’willingness to cooperate was significantly enhanced.Furthermore,the proportion of innovators who cooperated with others gradually increased to 100%;otherwise,it gradually decreased to 0%.Comparing the simulation curve with the real evolution curve of cooperative innovation in agricultural biotechnology in China,we found that the gradual decline in the willingness to cooperate could be due to insufficient subsidies for cooperative innovation,low income from cooperative innovation,weak profitability of innovators,and weak market constraints.