bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic Analysis and Event Detection Technology of Sports Competition Video Based on Deep Learning
Authors: Lixin Lai
Published: May 2024

This paper presents an investigation into the application of advanced techniques, including deep learning classification and FCM centroid segmentation, for automated event detection and analysis in sports videos. Through a series of experiments and analyses, we demonstrate the effectiveness of deep learning models in accurately categorizing events within sports footage, alongside the insights provided by FCM segmentation into event occurrences at the frame level. This paper investigates the application of advanced techniques, such as deep learning classification and FCM centroid segmentation, for automated event detection in sports videos. Through experiments, we achieved an average accuracy of 93.2% using deep learning classification and identified key events with probabilities ranging from 0.01 to 0.90 using FCM segmentation.
Reinforcement Learning Algorithm to Optimize Players' Tactical Decisions and Round Planning in Tennis Matches
Authors: Chen Hang
Published: May 2024

This paper explores the application of the Ranking Genetic Optimization Reinforcement Learning (RGORL) algorithm to optimize players' tactical decisions and round planning in tennis matches. Leveraging evolutionary principles and reinforcement learning techniques, RGORL offers a data-driven framework for enhancing on-court performance. Extensive simulations demonstrate the algorithm's effectiveness in improving match outcomes, points won percentages, and games won percentages. Results illustrate a steady improvement in fitness scores over successive generations, indicating RGORL's ability to evolve and refine strategies over time. Analysis of tactical decisions reveals the superiority of strategies such as the "Net Approach" in terms of win rates, points won percentages, and games won percentages. Through extensive simulations, RGORL demonstrates a notable improvement in match outcomes, with a maximum increase of 13% in win rates. Analysis of tactical decisions reveals significant enhancements in points won percentages, with improvements of up to 34% observed across various strategies, notably the "Net Approach." Furthermore, the algorithm achieves substantial gains in games won percentages, with increases of up to 25% recorded.
Digital Computing-Based Course Recommendation Algorithm for Distance Education Platforms
Authors: Wu Wenqiu
Published: May 2024

A course recommendation algorithm utilizes data about a user's preferences, past behaviour, and possibly other factors like demographics or interests to suggest relevant courses. It employs techniques such as collaborative filtering, content-based filtering, or hybrid approaches to analyse similarities between users or courses and make personalized recommendations. By continuously refining its suggestions based on user feedback and interactions, the algorithm aims to enhance the user's learning experience by presenting courses that align with their interests and goals. This paper explores the integration of course design principles with recommendation systems to enhance personalized learning experiences in distance education platforms. The course design is performed with the integration of collaborative filtering with the edge computing model for the estimation of features in distance education. Collaborative filtering is applied in the education platform through the estimation of features and edge computing is implemented for the processing. With the increasing popularity of online learning, there is a growing need to tailor educational content to meet the diverse needs, preferences, and skill levels of individual learners. Course design plays a crucial role in shaping the structure and delivery of educational materials, while recommendation systems leverage user data to provide personalized course suggestions. By integrating these two components, distance education platforms can create tailored learning pathways that optimize user engagement, retention, and learning outcomes. The analysis is further enriched by showcasing the course recommendations for individual users, highlighting how recommendation systems leverage course design aspects to deliver personalized learning experiences.
Personalized Learning Path Recommendation Algorithm for English Listening Learning
Authors: Xiaomei Li
Published: May 2024

A personalized learning path recommendation algorithm for English listening learning leverages data on users' proficiency levels, learning preferences, and past performance to suggest tailored learning paths. By incorporating natural language processing (NLP) techniques, the algorithm can analyze audio content, transcripts, and user interactions to assess comprehension and identify areas for improvement. It then recommends a sequence of listening exercises, podcasts, audiobooks, or other resources matched to the user's skill level and interests. This paper introduces the Ranked Path Recommendation (RPR) algorithm, designed to facilitate personalized English listening learning. Leveraging data analytics and machine learning techniques, the RPR algorithm aims to provide tailored recommendations of listening materials based on individual learners' preferences, proficiency levels, and learning objectives. Through a series of experiments and analyses, the effectiveness of the algorithm is evaluated, considering factors such as recommendation accuracy, learner satisfaction, and adaptability. Results demonstrate the algorithm's ability to curate diverse and relevant listening materials, enhancing learner engagement and comprehension. However, challenges such as algorithmic biases and the need for ongoing refinement are acknowledged. Ultimately, the RPR algorithm represents a promising approach to adaptive learning in language education, contributing to the advancement of personalized and effective language learning experiences. Results demonstrate that the RPR algorithm achieved recommendation accuracy ranging from 85% to 92% across ten different scenarios, with corresponding learner satisfaction ratings ranging from 6.9 to 8.8 on a scale of 1 to 10. Learner feedback indicates that recommended materials were perceived as relevant, engaging, and diverse, contributing to enhanced comprehension and motivation.
Development and Application of Big Data-Driven Intelligent Evaluation System for Physical and Aesthetic Education
Authors: Wei Wu
Published: May 2024

Big data driven intelligence evaluation system for physical and aesthetic education are used to leverage vast amounts of data to provide more objective, nuanced, and personalized assessments of student performance and progress. This paper proposes a hybrid approach for development of big data driven intelligence evaluation system for physical and aesthetic education. The proposed hybrid approach is the combined performance of both the Dual attention graph convolution network (DAGCN) and Weibull time to event Recurrent Neural Network (WRNN).Commonly it is named as WRNN-DAGCN technique. The major objective of the proposed approach is to provide for development of big data driven intelligence evaluation system for physical and aesthetic education. WRNN is design to enhancing the efficiency of physical training. Enhance the physical training from the WRNN by using the DAGCN. By then, the MATLAB/Simulink working platform has the suggested model implemented, and the present processes are used to calculate the execution. The proposed method shows better results in all existing methods. The accuracy level of proposed BDEPA-WRNN-DAGCN approach is 98% that is higher than the other existing methods. From the result, it is conclude that the proposed approach based error rate is less compared to existing techniques.
Fused Attentive Generative Adversarial Network based Personalized English Learning Material Recommendation System utilizing Knowledge Graph
Authors: Xiaoli  Wang
Published: May 2024

The information era has arrived swiftly in the world. Because it is the universal language, English influences how information is transmitted and exchanged throughout the world. Learning English is like having a valuable instrument for learning priceless knowledge. For this reason, it is imperative that English instruction be improved. The Fused Attentive Generative Adversarial Network based Personalized English Learning Material Recommendation System utilizing Knowledge Graph. Initially, input data are collected, given to preprocessing method. In preprocessing remove data redundancy using Generalized Correntropy Sparse Gauss–Hermite Quadrature Filter (GCSG-HQF). In pre-processed output fed to Recommendation System. Here, FAGAN is used to recommend English Learning Material. In general, FAGAN classifier does not express any optimization adaption approaches for determining optimum parameters to assure the Knowledge Graph. Here Clouded Leopard Optimization Algorithm utilized to optimize FAGAN classifier, for Personalized English Learning Material Recommendation System. In Clouded Leopard Optimization Algorithm utilized to optimise weight parameter of the FAGAN. With the use of performance metrics likes accuracy, precision, sensitivity, specificity, F1-score, ROC, computational time are analyzed. The proposed FAGAN-ELMRS-CLOA method attains 30.58%, 28.73% and 35.62%, higher accuracy, 20.48%, 24.73%, 29.32% higher computational time and 30.98%, 26.66% and 21.32% higher ROC analysed with existing models such as personalized English learning material recommendation system depend on knowledge graph (CNN-ELMRS-KG), semantic method for document classification utilizing deep neural networks with multimedia knowledge graph (DNN- ELMRS-MKG), and personalized recommendation of English learning depend on knowledge graph with graph convolutional network (PR- ELMRS-GCN) respectively.
Game Analysis of Financial Regulation in International Financial Crisis using Multi-view Graph Convolutional Network
Authors: Fang Luo
Published: May 2024

The concept of "game analysis" generally refers to the study and assessment of video games, frequently from the viewpoints of player experience, story, mechanics, design, and other relevant variables. It can be used for a variety of games, such as sports, board, card, and video games. A sudden drop in the value of assets or financial institutions is referred to as a financial crisis. It frequently causes the regular operation of financial markets to be interrupted and may have negative impacts on the economy as a whole. In this manuscript, Game Analysis of Financial Regulation in International Financial Crisis using Multi-view Graph Convolutional Network (GA-FR-IFC-MGCN). The proposed method comprises of four phases: dataset, pre-processing, feature selection, classification. Initially, the data is taken from Analcat dataset. Then, Federated Neural Collaborative Filtering (FNCF) method is used to enhancing the networks data. For feature selection phase, the ideal features are chosen by Siberian Tiger Optimization (STO). After, the Multi-view graph convolutional network (MGCN) method is used to classifying international financial crisis as bankruptcy and Non-bankruptcy. In general, MGCN does not express some adaption of optimization strategies for determining optimal parameters to promise exact classification of International Financial Crisis. Therefore, Harbor Seal Whiskers Optimization Algorithm is proposed to enhance weight parameter of MGCN classifier, which precisely predicts the International Financial Crisis. The proposed technique is executed and efficiency of GA-FR-IFC-MGCN depend classification framework is assessed by support of numerous performances evaluating metrics likes accuracy, recall, precision, FI-score, specificity. Finally the performance of proposed GA-FR-IFC-MGCN methods provides 25.32%, 29.30% and 27.32% higher accuracy, 22.41%, 29.30% and 24.31% higher specificity and 25.71%, 27.12% and 25.31% higher precision though analyzed with existing method likes game analysis of financial supervision in international financial crisis(GA-FS-IFC), performance evaluation of clustering techniques for financial crisis prediction(PE-CT-FC) and modified grey wolf optimizer with sparse auto-encoder for financial crisis prediction in small marginal firms (MGWO-SA-FCP) respectively.
Optimizing Bio-energy Supply Chain to Achieve Alternative Energy Targets
Authors: Thomas Jubin
Published: May 2024

In response to global warming and the dwindling reservoirs of fossil fuels, Thailand has increasingly embraced alternative energy sources. Central to its energy development strategy is the Alternative Energy Development Plan (AEDP), which aims to reduce energy intensity, capitalize on residual resources, and mitigate greenhouse gas emissions. While significant strides have been made in meeting various consumption targets set forth by the AEDP, notable challenges persist, particularly in the realms of bio-mass-derived electricity generation, bio-gas utilization, and bio-ethanol production from bio-mass. Therefore, this study delves into the factors contributing to the shortfall in achieving AEDP targets and proposes strategies to enhance the efficiency of the bio-energy supply chain. Leveraging mathematical and linear programming techniques, our research optimizes the supply chain dynamics, accounting for monthly supplier profiles spanning 77 provinces, 17 distinct biomasses, and 427 bio-energy plants equipped with diverse energy conversion technologies. Our findings indicate that Thailand currently boasts adequate bio-mass resources to fulfill the electricity and bio-ethanol targets outlined in the AEDP—provided enhancements are made to supply chain efficiency. To fully realize the objectives of the AEDP, we recommend augmenting bio-mass cultivation efforts and implementing new power plant installations. Additionally, we advocate for the consideration of high-methane content fuels, such as solid waste, as a means to alleviate bio-mass demand. This study underscores the paramount importance of strategic planning and optimization in propelling Thailand towards its alternative energy ambitions while surmounting supply chain impediments.
Analysis of the impact of VR technology based on big data edge computing and deep learning on English short video teaching
Authors: Zhitong Cheng
Published: May 2024

VR (Virtual Reality) technology applied to English short video teaching, compared with traditional English short video teaching can change the teacher-student interaction mode, providing students with a new English learning environment, making the classroom teaching content more realistic presentation. This paper focuses on VR scenario teaching and short video teaching, taking the English course of a school in Shanghai as an example. The students of VR situational teaching group have made great progress in vocabulary judgment, complementary dialogue and Chinese-English translation, with the passing rates of 43% and 100% respectively. The real scene created by virtual reality technology has greatly improved students' interest in learning and the effectiveness of classroom teaching. The development trend of educational informatization is virtualization and intellectualization. The application of virtual reality technology in the process of education and teaching is of great significance to the modernization of secondary education in China.
Enhanced Diabetic Retinopathy Diagnosis: A Comparative Analysis of models with an Ensemble classifier and Deep Q Learning
Authors: Minakshee Chandankhede
Published: May 2024

- A novel method that combines the strengths of different classifiers such as Naive Bayes, Multi-Layer Perceptron (MLP), and Support Vector Machine (SVM) is introduced in this paper. This method tackles the urgent need for cutting-edge diagnostic methods in the field of ophthalmology, mainly for the identification of diabetic retinopathy (DR). The approach is ensemble-based. Classical methods in retinal analysis of images often fail as they are static and are unable to adjust to the unique details that each distinct image presents. This constraint results in less accurate and precise diagnostic results, highlighting the urgent need for more adaptable and dynamic methods. The suggested model differs significantly from previous methods. Through the use of an ensemble approach, it capitalizes on the distinct advantages of each classifier: the MLP process's sophisticated feature extraction skill, Naive Bayes' probabilistic analysis, and SVM's non-linear pattern recognition capacity. By combining these techniques, the inherent drawbacks of utilizing a single strategy are addressed, guaranteeing a more thorough examination of retinal samples and images. The core of this idea is the system using Deep Q Learning (DQL) for adaptive classifier selection. Using learned Q Values for various contexts, this reinforcement learning technique selects the best classifier adaptively for each unique retinal image, hence optimizing the ensemble.
This approach not only advances diagnosis accuracy and precision but also guarantees ongoing learning and adaptation to keep up with changing data patterns and advances in imaging technology. Extensive experiments on the IDRiD & EyePACS Dataset show the effectiveness of this model with a 5.5% increase in overall accuracy with other performance metrics, the results show a significant improvement over the current method. They represent a significant advancement in the timely and accurate identification of diabetic retinopathy, which will ultimately benefit patients and lessen the strain on healthcare systems.
Thus, this work represents a major step forward in patient care as well as a technological advance, opening the door to more efficient supervision and treatment of retinal illnesses.
Optimizing Fund Performance: A Communication Systems Approach to Data Mining in Large- Cap Equity Mutual Funds
Authors: Shikha Singla
Published: May 2024

Mutual funds represent a secure and technologically driven conduit for Indian investors to engage with the dynamic Indian financial markets. These professionally managed funds strategically allocate investments across a spectrum of securities, including equities, bonds, government securities, and gold, leveraging cutting-edge information technology infrastructure for seamless operation and optimization. Within this landscape, performance emerges as a pivotal metric, driving the flow of savings into these digitally enabled funds, indicative of investors' confidence and expectations in the realm of data-driven decision-making. The core objective of this paper is to construct a robust mutual fund performance evaluation model utilizing the Statistical Package for the Social Sciences (SPSS), a sophisticated software platform renowned for its advanced analytics and predictive modeling capabilities in the information technology domain. The work focused specifically on equity mutual funds, this study meticulously examines top-rated funds within the large-cap category, drawing insights from a comprehensive validation period spanning the last fifteen years from April 2007 to March 2021. Through the systematic evaluation of various performance metrics within the context of information technology-driven analysis, this model aims to deliver actionable insights and strategic foresight, benefiting researchers, society, and financial analysts alike, while catalyzing innovation and driving positive impacts in the intersection of technology and finance.
PEMIKIRAN KH. AHMAD DAHLAN TENTANG PENDIDIKAN ISLAM DAN RELEVANSINYA DENGAN PENDIDIKAN ISLAM KONTEMPORER
Authors: Nani Kuniasih
Published: May 2024

Absatrak
Pendidikan Islam prespektif KH. Ahmad Dahlan adalah merupakan  elemen penting dalam upaya melahirkan manusia muslim yang berkualitas haruslah mengarahkan manusia agar menjadi seseorang yang memiliki pribadi yang memiliki keteguhan iman, bertaqwa, berakhlak mulia sejalan dengan ajaran Islam yang berdasarkan Al Quran dan Hadist., serta memiliki ilmu pengetahuan yang luas, kuat jasmani dan rohani.Peran sebuah pendidikan Islam sangatlah besar yang dapat mempengaruhi pendidikan bangsa kedepan. Pendidikan Islam saat ini penyebarannya tidak merata, khususnya di daerah-daerah terpencil. Oleh karena itu, pelopor Muhammadiyah yakni KH. Ahmad Dahlan memberikan peranan penting dalam keberhasilan pendidikan Islam melalui beberapa pemikiran-pemikirannya yang seringkali menimbulkan berbagai permasalahan di wilayah yang sudah mendarah daging adat istiadatnya Penelitian ini jenisnya adalah library research (penelitian kepustakaan), yaitu data yang diteliti didapatkan dari berbagai buku/tulisan yang bersumber dari kepustakaan Metode yang digunakan dalam pembuatan makalah disini adalah “content analysis / Analsis Isi. Adapun hasil atau kesimpulan dalam makalah ini adalah. (1). KH. Ahmad Dahlan merupakan tokoh pembaharuan pendidikan Islam, lahir dan tumbuh dalam lingkungan dengan berlatar belakang sosial yang bernuansa agama. Beliau merupakan salah satu tokoh yang sangat berjasa bagi pendidikan Islam di Indonesia. (2). Tujuan pendidikan menurut KH. Ahmad Dahlan melahirkan individu yang utuh menguasai ilmu agama dan ilmu umum, material dan spritual serta dunia dan akhirat, sedangkan  ciri-ciri  pendidikan  yang  digagas olehnya, yaitu lahirnya manusia-manusia baru yang mampu tampil   sebagai  “ulama-intelek” atau  “intelek-ulama” yang berarti seorang Muslim yag memiliki keteguhan iman dan ilmu yang luas, kuat jasmani dan rohani. (3). Pembaruan yang dilakukan KH. Ahmad Dahlan dalam bidang pendidikan memberikan pengaruh perubahan yang  besar terhadap sistem pendidikan Islam saat itu. Sebelumnya, sistem pendidikan saat itu memisahkan antara ilmu agama dan ilmu umum, kemudian oleh KH. Ahmad Dahlan diintegrasikan menjadi suatu kesatuan ilmu dalam suatu lembaga pendidikan (4). KH. Ahmad Dahlan sekolah guru yang kemudian berkembang dan dikenal dengan Madrasah Mu’allimin Muhammadiyah (Kweekschool Muhammadiyah) dan Madrasah Mu’allimat Muhammadiyah. Hal ini adalah salah satu bentuk hasil Perjuangan dari K.H. Ahmad Dahlan bukan hanya dalam pemikiran saja. Namun, beliau merealiasikan buah pemikiran tersebut dalam suatu tindakan yang dapat memberikan kemaslahatan bagi seluruh umat
RURAL TOURISM–REALISTIC SOLUTION FOR SUSTAINABLE SOCIO-ECONOMIC
DEVELOPMENT: CASE STUDY OF VÂLCEA COUNTY, OLTENIA REGION
Authors:   University of Craiova, Craiova, Romania, Ionuț-Adrian DRĂGULEASA , Alexandru Andrei POPESCU ,   University of Craiova, Craiova, Romania, Emilia CONSTANTINESCU ,   University of Craiova, Craiova, Romania, Mirela MAZILU ,   University of Craiova, Craiova, Romania
Published: May 2024

Rural tourism is characterized as a form of self-initiated tourism, which has, in the foreground, the involvement of the local population, which helps considerably in supporting and promoting traditions, crafts, and customs. The methodology of this research is based on the study of the specialized literature by investigating a case study regarding the tourist activity of rural tourism in Vâlcea County. The research hypotheses forecast and serve the general objective of the study, namely presenting that rural tourism can be a realistic solution for the sustainable socio-economic development of Vâlcea County. This work aims to identify the main development areas of Vâlcea County where the trends of development and practice of rural tourism are significantly important for the Oltenia Region as a first step towards unique research for promotion, sustainability, and socio-economic development in rural areas.
THE FINTECH EFFECT ON ORGANIZATIONS MANAGEMENT
Authors:   University of Craiova, Craiova, Romania, Marius Sandy STANESCU
Published: May 2024

The article aims to identify and understand the effects that new financial technologies produce on the management of organizations and analyzes, on the one hand, the evolution over time of these technologies, corroborating the concepts and classifications used in the specialized literature, and on the other hand investigates the factors that influenced their appearance, examining in parallel the possible fields of the most critical technologies existing in the financial industry. This study highlights the production of new Fintech technologies, which results in increased competition for the supply of financial services and products and, in return, potentially disruptive changes in these sectors with a determining effect on the management of financial institutions.
EMPLOYER BRANDING IN EMPLOYEES’ PERCEPTION
Authors:   University of Craiova, Craiova, Romania, Iulia Georgiana UDRICĂ
Published: May 2024

Human resources are an organisation's most valuable asset. The advantage in a highly dynamic and challenging market economy will be gained by companies that motivate their employees, give them the opportunity to develop and broaden their perspectives in a healthy and professional working environment. Employer branding is a set of strategies used by companies as employers to attract employees and make them related to its organisational culture and values. This article highlights a number of key items that lead to the shaping of an attractive Employer Branding for HR, as well as some examples of values that are well known for effective HR management.
SOCIAL PROTECTION OF THE POPULATION IN THE CONTEXT OF THE SUSTAINABLE DEVELOPMENT GOALS
Authors:   Institute for Regional Economics Studies Russian Academy of Sciences, Skvortsova M.B.
Published: May 2024

The article analyzes SDG 1 – Poverty eradication within the framework of the National Set of SDG indicators developed in the Russian Federation. It can be stated that within the framework of this direction, systematic work is being carried out in the country, which has made it possible to reduce poverty rates both in the country as a whole and in the subjects of the Northwestern Federal District.
STRATEGIC DIRECTIONS OF SOCIAL POLICY REGULATION A COMPONENT OF THE ECOLOGICAL AND ECONOMIC DEVELOPMENT OF THE REGIONS IN IN THE CONTEXT OF PUBLIC HEALTH
Authors:   Institute for Regional Economics Studies Russian Academy of Sciences, Shabunina T.V.
Published: May 2024

The article considers strategic directions for regulating a safe and comfortable habitat. Viola-tions during the state regional environmental supervision in the field of environmental air protec-tion and water use in the subjects of the Northwestern Federal District of the Russian Federation were analyzed. The role of the institutional environment in regulating the social component of the ecological and economic development of the regions is shown and priority areas for the develop-ment of environmental education are highlighted.
THE RUSSIAN ECONOMY UNDER CONDITIONS OF COMBINED SHOCKS: DEMOGRAPHIC AND PERSONNEL ASPECTS
Authors:   Institute for Regional Economics Studies Russian Academy of Sciences, Shestakova N.N. , Djanelidze M.G. ,   Institute for Regional Economic Studies Russian Academy of Sciences
Published: May 2024

The purpose of this article is to consider the main consequences of global geopolitical situation changes for the Russian economy in terms of their impact on the demographic situation in the country, as well as on the staffing of the national economy. The hypothesis of the study is the position that the national economy will be forced to function in a new economic reality, which should be reflected in the adjustment of the goals and mechanisms of development of a number of industries and sectors. The authors analyzed and classified the sanctions currently imposed on the Russian Federation. The directions of increasing the resilience of the economy based on the author's concept of combined shocks in order to reduce their impact are formulated.
SOME SECURITY ISSUES NATIONAL SECURITY IN THE HOUSING AND COMMUNAL SERVICES SECTOR
Authors:   Institute for Regional Economics Studies Russian Academy of Sciences, Zhigalina M.V.
Published: May 2024

The article is devoted to the problems of ensuring the national security of the Russian Federa-tion in the housing and communal services sector.
RUSSIAN OIL AND GAS COMPLEX: RESULTS OF THE FIRST YEAR UNDER SANCTIONS AND DEVELOPMENT PROSPECTS
Authors:   Higher School of Economics, Larchenko L.V. , Gabibova M. S. ,   A.I. Herzen Russian State Pedagogical University
Published: May 2024

The article analyzes the main problems that have arisen as a result of the introduction of anti-Russian sanctions, as well as the measures taken to overcome or mitigate their impact. The most vulnerable and affected, as expected, was the oil and gas complex. Possible directions of further development of the complex are considered. Export supplies of hydrocarbons began to reorient mainly to the eastern world markets, however, since it is difficult to quickly rebuild gas pipeline supplies, the emphasis in the country is on increasing the production and supply of liquefied nat-ural gas to the myrrh market. The article shows that one of the main problems hindering the further development of the industry in the conditions of sanctions has become the problem of the lack of own modern equipment and technologies in many key areas of the complex's development, in-cluding the liquefaction and transportation of natural gas.
UNDERSTANDING THE PROBLEM OF CLIMATE CHANGE AND THE NEED FOR ENERGY TRANSITION IN THE HUMANITIES
Authors:   St. Petersburg State University of Economics, Rusetskaya O. V. ,   ICSEI Leontief Center
Published: May 2024

The historical and philosophical understanding of human influence on climate change allows us to conclude that a significant share of responsibility for the emergence of environmental and, in particular, climatic problems lies with science. According to the researchers, the natural scientific aspects of climate change are widely covered by the media, while ethical issues are ignored or blocked in media publications, negotiations and discussions on climate. Modern research also does not pay enough attention to the cultural, political and psychological aspects of the consequences of climate change, as well as their role in the development of effective climate change policy.
Food democracy as food security strategy: The case of a Costa Rican tourism town
Authors: Little Mary , Horn Taylor , Sit Madeline
Published: May 2024

Tourism communities such as Monteverde, Costa Rica, the site of this study, have been profoundly impacted by the loss of tourism revenue during COVID-19. Faced with intensified food insecurity caused by the cascading impacts of this pandemic, the community has organized initiatives to stimu­late local, sustainable food production to increase food security during the COVID-19 economic recovery. This paper adopts a food democracy framework to analyze restaurants’ regional food purchases, barriers to local purchasing, and tour­ists’ interest in and ability to identify local food products. Our findings show that nearly all restaurant owners identified benefits of purchasing regional food but reported multiple barriers to buying locally. Tourists reported high interest in eating locally produced food but do not have enough information to identify farm-to-fork options. Local food initiative stakeholder inter­views show that emergent strategies demonstrate a move toward food democracy actions by promot­ing communication and co-learning between res­taurants, food producers, and tourists to rein­force principles of food democracy. Based on our find­ings, we recommend (a) strengthening producer-to-restaurant networks, (b) enhancing communication of local food production benefits and responsi­bilities to restaurants, and (c) promot­ing the locally made certification for restaurants to strengthen localized food networks and direct tourists to transformative food strategies underway in Monteverde.
Public services provided after Earthquake 2023 in the Context of Central Government-Local Administration Relations: Mersin Metropolitan Municipality Case
Authors: Metin Hüseyin
Published: May 2024

Central government-local administration relations are one of the most problematic mechanisms of our administrative history in structural and functional terms. This study will examine the dynamics of central government and local administration relations from a public policy standpoint, emphasizing the importance of collaborative policymaking and cooperation between the two levels of government. AFAD (disaster and emergency management presidency) faced criticism during the February 2023 earthquake in Türkiye sparking a public debate on the relationship between central and local administrations. The study will focus on Mersin, one of the provinces most affected by the recent earthquakes, and the Mersin Metropolitan Municipality. The Metropolitan Municipality's response to the earthquake in Mersin and the public services provided during the aftermath will be analyzed. The role assumed by Mersin Metropolitan Municipality in the context of disaster management is studied to firstly reveal the potential of local administration in terms of disaster management and secondly to show its relations with the central government. In the study, the analysis of the aid provided to earthquake victims will be based on the data of AFAD and Mersin Metropolitan Municipality. The qualitative analysis of the obtained data will reveal the potential of the central government-local administration relationship with structural and functional mechanisms.
Pengaruh bursa saham Regional Asia Tenggara 5, Tiongkok dan USA terhadap IHSG
Authors: Nugraha Handy , Putriani Santi , Putriana Sinta
Published: May 2024

The 2018–2022 period is one of global economic uncertainty due to the US trade war with China and the economic recession due to the COVID-19 pandemic. These factors put pressure on the financial sector and influence investment behavior. This research aims to determine the influence of five regional stock exchanges in Southeast Asia, China, and the USA, domestic interest rates, and inflation on the IHSG, then compare the periods during the COVID-19 pandemic shock. The research method uses the Vector Error Correction Model (VECM). The analysis results show that the Southeast Asia regional stock exchange has a significant influence in the long term but no influence in the short term. An interesting finding in this research is that several stock exchange variables and domestic interest rates had different influences before and during the shock of the COVID-19 pandemic.
Denys Lombard dan Desakralisasi Proses Sejarah
Authors: Faidi Ahmad
Published: May 2024

This article is a critical study of “Le carrefour Javanais: essai d'historia globale.” by Dennys Lombard; as one of the most unique Historigraphy works compared to the works of other orientalist historians. The new approaches offered by Denys Lombard, such as the use of reverse periodization and the “cultural geology” approach, have made a valuable contribution to the development of Indonesian Historigraphy in particular. But on the other side, Denys Lombard's writing method which tends to ignore the historical periodization framework, which should be the main characteristic of history, actually makes him ignore the small changes that occurred in the past.
Moving towards local participation and comanagement of Tioman Island Marine Park
Authors: Yaman Shahir , Chelliah Alvin Jeyanathan , Hyde Julian , Yee Chen Sue
Published: May 2024

Tioman Archipelago is a Marine Protected Area (MPA) off the coast of Pahang, Malaysia. It is inhabited by a small local population that depends on tourism as its main source of income. Its rich biodiversity is the main attraction to visitors, yet it is threatened by the growing tourism market. In 1994 the waters extending 3.7 km from the shore surrounding the island were gazetted as an MPA under the provisions of the Fisheries Act of 1985. The Department of Fisheries Malaysia (DoF) is responsible for the management and enforcement of the MPA, with minimal or no involvement of the local communities. A study conducted by Reef Check Malaysia (RCM) in 2014 with the local communities revealed that the vast majority showed an interest in being involved in management and conservation efforts but did not have the qualifications or the means to do so. In 2015, the Tioman Marine Conservation Group (TMCG) was formalized as a platform for interested local communities to undergo a series of training programs to empower them in building ecological resilience and marine resource management processes. The TMCG has since executed many conservation programs including ghost net removals, mooring buoy management, coral predator control, coral rehabilitation, reef monitoring surveys, community consultations, promotion of responsible tourism standards, and cleanups. RCM provided training, oversight, and funding. As of 2023, there are 80 members from each of the island’s seven villages. In 2019 the TMCG was officially recognized by the DoF as one of its strategic partners under its Reef Care program. This paper details how Tioman Island Marine Park moves from a top-down management approach towards local participation and a comanagement approach.
Viruses, resilience, and their health implications
Authors: Suryasa Wayan , Rodríguez-Gámez María , Koldoris Tihnov , Menéndez-Meza Petter Bryan
Published: May 2024

Humanity is living a stage where different types of viruses have appeared, implying many problems at a social level, which is called upon to adapt to these adversities, so as not to have more relevant conditions than those that occurred with the appearance of COVID-19. The objective is Know the implications of these for human health and how to be resilient to them. The bibliographic review and the inductive-deductive method were used. The result was that humanity must reflect on joint actions to address the viral threat and draw up policies that help adapt to the change caused by them.
What future for environmental and climate litigation?
Authors: Kobylarz Natalia , Pane Giorgia , Luporini Riccardo , Masieri Carlo , Duarte Reyes Laura Andrea , Burri Nina , Magnaghi Rachele , Faina Alessandro , Di Landro Andrea , Confalonieri Sofia , Hajszan Jacob
Published: May 2024

The book provides in-depth analysis and innovative insights on the prospects of climate and environmental litigation, namely by exploring the ability of judicial remedies and sanctions to affect public and private decision-making in every context where natural resources, climate as well as human health are at stake. The chapters reproduce, with additional elaborations, the papers presented at the international workshop that gives the volume its title, held at the University of Milan on 16 September 2022. The underlying question is whether and to what extent, in the face of unsatisfactory and unreasonable political choices on the balance between the different interests at stake, resorting to national and supernational courts represents a valid alternative for a more sustainable future. The relevant contexts covered by the book include, for instance, industrial development, exploitation of natural resources, agricultural production, manufacturing techniques, as well as policies on energy, public and private transport, and urban development. The book is composed of three parts, each one addressing, from multiple perspectives, a specific category of judicial remedies in a certain area of legal studies: I) international human rights law; II) private international law and international trade law; II) domestic and international criminal law.
What future for litigation on climate change adaptation?
Authors:   Sant’Anna School of Advanced Studies, Pisa, Luporini Riccardo
Published: May 2024

Climate change litigation is rising on a global scale. In these cases, especially the high-profile or ‘strategic’ ones, litigants are focusing on mitigation, i.e., reducing sources or enhancing sinks of greenhouse gases, rather than on adaptation. The present contribution aims to investigate how and to what extent litigation on climate change adaptation can progress in the future. Adaptation obligations are less developed than those on mitigation, and this may explain, at least in part, why litigation on adaptation is less advanced. However, the contribution points out that human rights arguments can complement the paucity of binding obligations on climate change adaptation and serve as a basis for adaptation cases. To this end, the chapter surveys the extant rights-based cases aimed to advance adaptation action, distinguishing between cases brought before domestic courts and complaints filed with international judicial or quasi-judicial bodies. The chapter discusses these cases and concludes with some reflections on the future of litigation on climate change adaptation.
The protection of the environment under the ICC Rome Statute: does the wheel really need to be reinvented?
Authors:   Kosovo Specialist Chambers and Specialist Prosecutor’s Office, The Hague, Faina Alessandro
Published: May 2024

The need to improve the available legal instruments to protect the environment has led to a whirlwind of proposals in the field of criminal law and litigation, both domestically and internationally. One of the most mediatized proposals at the international level has perhaps been the inclusion within the Rome Statute of the International Criminal Court (“ICC”) of the crime of “ecocide”, with a view at heightening the environment to the level of those most fundamental legal interests whose protection against the most egregious violations is demanded to the ICC. 
Based on the suggested definition of the crime of “ecocide”, this chapter explores whether the environment should be protected under international criminal law as an independent legal interest or as enshrined in the multifaceted concept of human dignity that the Rome Statute already aims to protect. In this regard, the author argues that humankind and environment are so substantially entwined that whatever harm to the latter cannot but result in a harm to the former too. The author therefore suggests that the Rome Statute already includes tools to protect the environment from the most egregious violations and could constitute an important instrument of last resort in environmental and climate litigation.
Must environmental criminal law always be dependent on administrative law? Assessing the opportunity for a limited number of offences being autonomous from administrative law
Authors:   University of Central Sicily “Kore”, Di Landro Andrea
Published: May 2024

The chapter intends to analyse the pluses and minuses of traditional environmental criminal law’s dependence on administrative law. The two possible forms of integration between criminal and administrative law, i.e., the so-called ‘purely accessory’ and ‘partially accessory’ models, are evaluated from a comparative perspective, while also considering the European Directive 2008/99/European Community (EC) on the protection of the environment through criminal law, and the new proposal for a Directive, replacing the previous one, put forward by the European Commission in December 2021. Followed by a reflection on the different model of environmental criminal law, autonomous from administrative law (also called the ‘purely criminal’ model: a model that should be associated with the purely accessory one and the partially accessory one).
Applications of graphene in organic anticorrosive coatings
Authors: Xiao Waikong
Published: May 2024

The problem of corrosion of materials has lasted for a long time, corrosion causes damage to the structure of buildings and bringing loss of economy. The coating method, which is an easy and economical way to solve the problem, is still unable to satisfy the needs limited by the paints properties. However, this can be solved by introducing graphene, by its special 2-D material properties, to the paint. And a lot of researchers are working on this now. This paper mainly focuses on the overview of how graphene be applied to anti-corrosive coatings, the problems that are faced, what are solutions for those, and what are the advantages that graphene has in the area. Resulting that graphene is mainly used with organic anti-corrosion materials, by filling the holes in those materials to stop the corrosion molecules from infiltrating through. Graphene can also be used as containers, carrying corrosion inhibitors that would be released and fill the crack when the coating is damaged. By modifying graphene, problems like agglomeration and accelerating corrosion can be solved. The result will be used for researchers who are looking for a conclusion in the graphene anti-corrosive coatings research area and provide the main focuses and details.
The application of renewable energy in transportation systems in China
Authors: Chen Kaisen
Published: May 2024

The energy consumption level in transportation is projected to continue its current upward trend until the year 2040. Motor gasoline and diesel are the most consumed energy sources in common transportation, followed by jet fuel and natural gas. Regrettably, biofuel and electric energy, which are renewable energy sources, had only a little contribution to overall energy consumption in transportation. This indicates that the use of renewable energy sources in transportation is still in its early stages. The rapid advancement of energy innovation is causing alarm among the general people. In 2020, greenhouse gas emissions from transportation reached a record high. In order to predict the future trajectory of renewable energy, it is crucial to closely monitor the utilization of nonrenewable energy sources in transportation, which is currently at a high level. This study examines the existing energy sources in China and utilizes reliable research papers and data to demonstrate the practicality of several energy advancements in current transportation systems. The study will employ a literature review method to examine the advancements in energy innovation within the domains of internal combustion engines and electric motors in automobiles, waterborne transportation, and aircraft.
A computational enzymatic optimization for fixing carbon dioxide to starch
Authors: Gao Rong
Published: May 2024

Carbon dioxide is fixed and processed into starch by the plants photosynthesis through complicated molecular pathways. While planting and cultivating crops are the major ways to harvest starch, an artificial anabolic pathway has recently been realized in China. Traditional crop production demands extended harvest periods, extensive land, and substantial water use. In contrast, the artificial pathway enhances starch synthesis efficiently, using fewer resources for a more sustainable approach. In 2021, Chinese researchers reported the anabolic starch artificial pathway (ASAP) to synthesize starch in vitro. Although the previous research established a milestone, steps need to be optimized. In this work, enzymatic starch synthesis is chosen to be further engineered, building mutants with similar catalytic functions. Computational tools are used to build an iterative docking-mutating simulation (IDMS). It can automatically finish the cycle of protein mutations and docking. Autodock and Rosetta are used in the coding. 445 different protein mutants are generated and analyzed in silico, among which the best five were chosen for experimental investigation. In the experimental analysis, mutant E shows nearly the same catalytic efficiency as the wild-type in the first hour, with a 2.5-fold expression rate.