Scientific Research Articles

Analysis Of Current Situation, Risk Causes and Countermeasures of Real Estate Finance--Taking Jiangsu Province as An Example

The real estate industry is not only an important engine of economic growth, but also a cornerstone of social stability and personal life. As a major economic province in China, Jiangsu Province is rich in natural resources and has a strong economic base. It is an important demonstration area for China's modernization and comprehensive development and plays an important role in promoting China's economic growth, scientific and technological innovation and social progress. In the economic structure of Jiangsu Province, the real estate market occupies a pivotal position, which not only contributes greatly to the local financial income, but also has a far-reaching impact on employment, consumption, investment and other aspects. The development of the real estate market in Jiangsu Province has an important impact on the national real estate market, thus this paper takes Jiangsu Province as the research object, discusses the credit risk of the real estate industry in Jiangsu Province from the perspectives of its status quo, risk causes, etc., and then puts forward policy recommendations to promote the sustainable development of the real estate market in Jiangsu Province.

Confined mass transport in two-dimensional capillary

Abstract Over the past decade, nanofluidics has undergone significant expansion, propelled by advances in crafting artificial channels at nanometric and sub-nanometric scales with diverse geometries. Central to this domain, two-dimensional capillaries have risen as a pivotal research platform, marked by their angstrom-level precision, unparalleled wall surface smoothness, and clearly defined surface charge states. Their advent has profoundly deepened our understanding of mass transport dynamics, spanning gases, water molecules, and ions, shedding light on the complex interactions among various influencing factors and revealing a range of previously undiscovered physical phenomena. This review delves into the development of 2D capillaries, the principal fluid transport phenomena observed within, and the critical elements that affect these processes. We also touch on a fascinating discovery - the quantum liquid friction seen in water moving over carbon surfaces. In anticipation of future explorations in nanofluidics, we envision a trajectory aimed at emulating the efficiency levels of biological protein channels, setting the stage for a new era of scientific inquiry and technological innovation.

Data protection legislation in Africa and pathways for enhancing compliance in big data health research

BackgroundThe increasing availability of large volumes of personal data from diverse sources such as electronic health records, research programmes, commercial genetic testing, national health surveys and wearable devices presents significant opportunities for advancing public health, disease surveillance, personalized medicine and scientific research and innovation. However, this potential is hampered by a lack of clarity related to the processing and sharing of personal health data, particularly across varying national regulatory frameworks. This often leaves researcher stakeholders uncertain about how to navigate issues around secondary data use, repurposing data for different research objectives and cross-border data sharing.MethodWe analysed 37 data protection legislation across Africa to identify key principles and requirements for processing and sharing of personal health and genetic data in scientific research. On the basis of this analysis, we propose strategies that data science research initiatives in Africa can implement to ensure compliance with data protection laws while effectively reusing and sharing personal data for health research and scientific innovation.ResultsIn many African countries, health and genetic data are categorized as sensitive and subject to stricter protection. Key principles guiding the processing of personal data include confidentiality, non-discrimination, transparency, storage limitation, legitimacy, purpose specification, integrity, fairness, non-excessiveness, accountability and data minimality. The rights of data subjects include the right to be informed, the right of access, the right to rectification, the right to erasure/deletion of data, the right to restrict processing, the right to data portability and the right to seek compensation. Consent and adequacy assessments were the most common legal grounds for cross-border data transfers. However, considerable variation exists in legal requirements for data transfer across countries, potentially creating barriers to collaborative health research across Africa.ConclusionsWe propose several strategies that data science research initiatives can adopt to align with data protection laws. These include developing a standardized module for safe data flows, using trusted data environments to minimize cross-border transfers, implementing dynamic consent mechanisms to comply with consent specificity and data subject rights and establishing codes of conduct to govern the secondary use of personal data for health research and innovation.

The Evolving Role of Prosecution in Pakistan's Criminal Justice System: A Comparative Analysis with India

The purpose of this research is to investigate the function of prosecution within the framework of Pakistan's criminal justice system as seen through the lens of India. Through the use of historical and doctrinal research methodologies, the examination dives into the development of prosecutorial functions in both nations. Within the scope of this study, a comparison and contrast of the legislative frameworks that control the prosecutorial function is carried out. Particular attention is paid to important aspects such as prosecutorial discretion, pre-trial investigation, and trial advocacy. The purpose of this research is to investigate the ways in which the courts in Pakistan and India have interpreted the powers and restrictions of the prosecutor by analyzing significant cases. This comparative technique allows the investigation to identify both commonalities, which are a result of a shared colonial past, and differences, which are a result of separate legal processes. The research provides an in-depth analysis of the efficiency of the prosecution process in each nation, stressing both the positive and negative aspects of the system as well as prospective areas for improvement. The findings of this study present suggestions for enhancing the prosecutorial position within Pakistan's criminal justice system. These recommendations are derived from the Indian experience, which the research draws upon. One of the goals of this research is to make a contribution to the continuing conversations that are taking place about how to assure a more strong and efficient prosecutorial role, which would eventually result in a criminal justice system in Pakistan that is more effective and just.

From human-centered to social-centered artificial intelligence: Assessing ChatGPT's impact through disruptive events

Large language models (LLMs) and dialogue agents represent a significant shift in artificial intelligence (AI) research, particularly with the recent release of the GPT family of models. ChatGPT's generative capabilities and versatility across technical and creative domains led to its widespread adoption, marking a departure from more limited deployments of previous AI systems. While society grapples with the emerging cultural impacts of this new societal-scale technology, critiques of ChatGPT's impact within machine learning research communities have coalesced around its performance or other conventional safety evaluations relating to bias, toxicity, and “hallucination.” We argue that these critiques draw heavily on a particular conceptualization of the “human-centered” framework, which tends to cast atomized individuals as the key recipients of technology's benefits and detriments. In this article, we direct attention to another dimension of LLMs and dialogue agents’ impact: their effects on social groups, institutions, and accompanying norms and practices. By analyzing ChatGPT's social impact through a social-centered framework, we challenge individualistic approaches in AI development and contribute to ongoing debates around the ethical and responsible deployment of AI systems. We hope this effort will call attention to more comprehensive and longitudinal evaluation tools (e.g., including more ethnographic analyses and participatory approaches) and compel technologists to complement human-centered thinking with social-centered approaches.

Making the most of bioimaging data through interdisciplinary interactions.

The increasing technical complexity of all aspects involving bioimages, ranging from their acquisition to their analysis, has led to a diversification in the expertise of scientists engaged at the different stages of the discovery process. Although this diversity of profiles comes with the major challenge of establishing fruitful interdisciplinary collaboration, such collaboration also offers a superb opportunity for scientific discovery. In this Perspective, we review the different actors within the bioimaging research universe and identify the primary obstacles that hinder their interactions. We advocate that data sharing, which lies at the heart of innovation, is finally within reach after decades of being viewed as next to impossible in bioimaging. Building on recent community efforts, we propose actions to consolidate the development of a truly interdisciplinary bioimaging culture based on open data exchange and highlight the promising outlook of bioimaging as an example of multidisciplinary scientific endeavour.

Enabling sustainable crop protection with induced resistance in plants

Induced resistance (IR), which enables plants to increase their resilience against insect pests and microbial pathogens by promoting their own immunity, has been recognized for its value in crop protection schemes. Despite promising applications, the use of IR in crop protection has remained marginal compared with pesticides and single resistance genes. This review aims to shed light on this disparity by examining the scientific milestones achieved over the past decades for both internal (immunological) and external (ecological) IR strategies. The multifaceted advantages of IR, particularly its ability to provide broad-spectrum protection and enhance the nutritional and nutraceutical value of certain crops, are also discussed. The various obstacles hindering the widespread adoption of IR strategies are then revealed. After considering recent scientific discoveries and insights, potential solutions are proposed, including leveraging epigenetic approaches to understand the mechanisms involved in IR. By acknowledging that the future sustainability of crop protection is irreconcilable with single-use technologies, this review proposes taking advantage of the latest insights regarding the adaptive nature of the plant immune system and its ecological interactions to safely integrate IR into existing crop protection schemes. By emphasizing the need for comprehensive and holistic approaches to basic and translational research, this review sets the stage for leveraging IR alongside other strategies to foster a resilient, environmentally friendly, and economically viable future, thereby ensuring the health of crops.

Can AI Get a Degree in Geoscience? Performance Analysis of a GPT-Based Artificial Intelligence System Trained for Earth Science (GeologyOracle)

Generative artificial intelligence systems based on the GPT model have shown groundbreaking capabilities in producing scientific texts, revolutionising how geoscientists research and teach. However, there is a noticeable absence of generative AI systems tailored specifically for geoscience, and the efficacy of GPT technology has not been examined within the Earth Science realm. To fill these gaps, we propose a new artificial intelligence system (GeologyOracle) built upon the GPT-4o model and trained on Earth Science data. It is designed to simulate a conversation with a geoscientist, having the capabilities to analyse geologic datasets, suggest new geoscience hypotheses, explain Earth-Science concepts, and interpret geosites. To evaluate the performance of GeologyOracle, the system was tested with 152 geoscience questions provided and evaluated by a panel of geoscience academics on a scale of 0–10. Performance analysis revealed that 79.6% of the answers scored equal to or above the passing mark of 5, with a tendency to deliver high-quality responses (mean: 6.5; median = 7; interquartile range: 5–8). The results demonstrate that GeologyOracle is effective in performing complex geoscience tasks, such as identifying rocks, fossils, and minerals, and interpreting outcrop, core data, and quantitative datasets. The new AI system has exhibited noteworthy ability in the interpretation of internationally-acknowledged geosites situated within geoparks and nature reserves. The performance of the AI system is comparable to that of trained geoscience specialists, suggesting its potential as an assistant in various geoscience fields, including structural geology, palaeontology, geomorphology, sedimentology, and economic geology. While AI does not render geoscientists obsolete, it offers significant potential for accelerating scientific discovery, automating geoscience research, and assisting educators, students, and geotourists.

Tatars in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814

One of the topical issues of historical science in the Russian Federation is the analysis and popularization of historical information about the participation of the peoples of the country in military campaigns to protect the Fatherland from foreign intervention. The purpose of the study is to tell about the service of Tatars, both officers and lower ranks, in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814. Actualization of interest to the military history of the Tatar people during the period of the Russian Empire as a whole, with the search and bringing into the public space the names of heroes and participants of military campaigns, is also one of the tasks of this study. The leading method in studying this problem was an integrated approach based on the study of different types of sources. Research materials: the work involves special historical research (monographs and scientific articles), published and unpublished historical sources of the first quarter of the 19th century, reference publications. Results and scientific novelty of the work: the facts of the service of the Tatar people in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814 have been established, the personalities of Tatar officers, both from among the nobility and from the lower ranks, as well as soldiers and sailors from the Tatars who served in the regular army have been identified. Biographies of veterans of the Patriotic War of 1812 and the foreign campaigns of 1813–1814 from the Tatars are given. For citation: Abdullin Kh.M. Tatars in the regular army during the Patriotic War of 1812 and the foreign campaigns of 1813–1814. From History and Culture of Peoples of the Middle Volga Region. 2024, vol.14, no.3, pp.96–107. https://doi.org/10.22378/2410-0765.2024-14-3.96-107

Citizen Science for Invertebrate Biodiversity: Mobilizing Spider Occurrence Data through Facebook in India

India accommodates a huge diversity of plant and animal life across a variety of biomes. However, the degree of research, funding, and attention is asymmetric, largely focused on its charismatic vertebrates. Invertebrates, despite their megadiversity, are generally overlooked with some exceptions (for example, lepidoterans). One species-rich group, spiders, exemplifies this knowledge gap. More than 1,800 species from 63 families have been reported in the country (Mondal et al. 2020), even though the true number may be much higher, in part, owing to the need for taxonomic revisions. Several spider systematics and biogeographic studies have pointed out that spatial distribution, seasonality, and natural history data are lacking from India. The lack of foundational biodiversity information has led to poor opportunities to share knowledge between researchers and community scientists. Mining occurrences through scientific publications or databases (in some cases behind paywalls) may require specialized training. This restricted access inhibits more people from using the abundance of information. The prevalence of social media posts showcasing photographs of species in biodiversity contexts has experienced a significant increase, with a multitude of users sharing wildlife photographs on social media sites such as Instagram®, Facebook®, and Flickr®. These observations on social media are a potential source of primary biodiversity data when curated and validated (Barman and Barve 2022, Barman et al. 2022a). Such data can enhance biodiversity monitoring by expanding spatial and temporal coverage and involving a global network of citizen scientists in conservation research (Barve et al. 2023, Roy 2022, Kulkarni 2023). The India Biodiversity Portal (IBP, Vattakaven et al. 2016) has been cataloguing species diversity and spider data through citizen science. Meanwhile, major social media sites report many more species sightings than citizen science platforms. SpiderIndia, a popular Facebook group, has collected over 20,000 observations from 8,500 spider enthusiasts. However, these data remain unorganised and inaccessible to academic researchers and the public. In order to tackle these problems, we implemented a methodical process to enhance the occurrence data on spiders from well-known social media platforms, such as the SpiderIndia project. The procedure involved retrieving the relevant data, and ingesting it through a custom pipeline to parse and extract, scientific names, spatial and temporal data to generate occurrence records on the IBP. The data was then presented on a curation interface, enabling taxonomic experts to verify the records, and finally publishing the verified records on the Global Biodiversity Information Facility (GBIF) (Global Biodiversity Information Facility 2022, Barman et al. 2022b) to improve the records of spider species occurrence in India. This project showcases the capacity of citizen science via social media to involve citizen scientists in generating extensive datasets that make a significant contribution to scientific knowledge and improve our comprehension of invertebrate biodiversity. The final dataset encompasses over 15,000 observations, providing valuable insights into spider diversity and distribution across India (Fig. 1). This data is publicly available on GBIF, facilitating further research on Indian spider populations.

Demystifying Higher Education: An Analysis of Competing Perspectives in Institutional Theory

Abstract This paper scrutinises and interprets the competing perspectives arising from institutional analysis in higher education studies. Contradictory views in this field include the perception of converging trends versus escalating diversification, and the view of universities as entities resisting change contrasted with those characterised by continual evolution or innovation. These different viewpoints are methodically examined, informed by a wide range of literature on institutional theory and institutional analysis in higher education. In endeavouring to reconcile these divergent perspectives, this paper illuminates the intricacies of institutional behaviour in higher education. The theoretical discussions also pave the way for developing a holistic approach to institutional analysis in the field of higher education research.

Smart Vision Transparency: Efficient Ocular Disease Prediction Model Using Explainable Artificial Intelligence

The early prediction of ocular disease is certainly an obligatory concern in the domain of ophthalmic medicine. Although modern scientific discoveries have shown the potential to treat eye diseases by using artificial intelligence (AI) and machine learning, explainable AI remains a crucial challenge confronting this area of research. Although some traditional methods put in significant effort, they cannot accurately predict the proper ocular diseases. However, incorporating AI into diagnosing eye diseases in healthcare complicates the situation as the decision-making process of AI demonstrates complexity, which is a significant concern, especially in major sectors like ocular disease prediction. The lack of transparency in the AI models may hinder the confidence and trust of the doctors and the patients, as well as their perception of the AI and its abilities. Accordingly, explainable AI is significant in ensuring trust in the technology, enhancing clinical decision-making ability, and deploying ocular disease detection. This research proposed an efficient transfer learning model for eye disease prediction to transform smart vision potential in the healthcare sector and meet conventional approaches’ challenges while integrating explainable artificial intelligence (XAI). The integration of XAI in the proposed model ensures the transparency of the decision-making process through the comprehensive provision of rationale. This proposed model provides promising results with 95.74% accuracy and explains the transformative potential of XAI in advancing ocular healthcare. This significant milestone underscores the effectiveness of the proposed model in accurately determining various types of ocular disease. It is clearly shown that the proposed model is performing better than the previously published methods.

Balancing Playability and Historical Accuracy in Game Design - Developing the Struve Geodetic Arc Mobile Game

Numerous digital games and media with historical themes aim to educate or engage audiences with heritage. When developing a historical video game, some of the most critical design decisions are centered around finding the balance between an accurate presentation of historical facts and engaging gameplay. This paper examines the game developer's role in selecting and presenting historical content through a case study of a mobile game development process. The design choices and developers' positions related to using historical facts are examined through thematic analysis of interview data and game design documents. Recurring themes in the data reveal a constant interplay between game features and historical content, supported by historical knowledge and technology. In small teams, individual developers often make crucial design decisions while performing multiple roles. As key findings, we report that the resourcing and timing of historical research significantly impacts developers' decisions, and note varying degrees of interest in historical accuracy within the development team.

Research on Emotion about Media Memory of Wenxi Fire in Central Daily News

The author conducted a comprehensive study on the emotions reflected in The Central Daily News coverage of the Wenxi Fire, utilizing the digital analysis tool ROST CM6 in combination with historical research. The media memory of the Wenxi Fire in The Central Daily News reflects the emotional response and guidance of the National Government towards this disastrous event. The newspaper's spirited stance on the War of Resistance against Japan invigorated the public’s morale. Through selective reporting and, at times, the outright omission of facts, the newspaper initially mitigated the public’s criticism towards the central and Hunan provincial governments during the first phase, when the cause of the fire was still under investigation. In the second phase, after the cause was determined, the newspaper successfully shifted the blame for this governmental failure to the Japanese invaders, the Hunan provincial government, and the “righteously indignant” public. Through a series of carefully orchestrated actions, the newspaper managed to quell public anger, boost morale, and foster a stronger sense of national unity under the National Government, ultimately enhancing its image.

BENN: Balanced Ensemble Neural Network for Handling Class Imbalance in Big Data

ABSTRACTClass imbalance is a critical challenge in big data analytics, often leading to biased predictive models. This imbalance can lead to biased models that perform well on the majority class but poorly on the minority class. Many machine learning models tend to be biased towards the majority class because they aim to minimise overall error, often leading to poor performance on the minority class. This paper presents the balanced ensemble neural network, a novel solution to effectively address class imbalance in big data. Balanced ensemble neural network combines the robust capabilities of neural networks with the power of ensemble learning, incorporating class balancing strategies to ensure fair representation of minority classes. The methodology involves integrating multiple neural networks, each trained on balanced subsets of data using techniques like Synthetic Minority Over‐sampling Technique and Random Undersampling. This integration aims to leverage the strengths of individual networks while reducing their inherent biases. Our extensive experiments across various datasets reveal that BENN achieves an AUC‐ROC score of 0.94, surpassing other models such as random forest (0.88), support vector (0.84) and single neural net (0.80). It was also observed that BENN's performance is better compared to traditional neural network models and standard ensemble methods in key metrics like accuracy, precision, recall, F1‐score and AUC‐ROC. The results specifically highlight BENN's effectiveness in accurately classifying instances of minority classes, a notable challenge in many existing models. These findings underscore BENN's potential as a substantial advancement in handling class imbalance within big data environments, offering a promising direction for future research and application in machine learning.

ChatGPT and scientific research in university higher education

In the present study, the influence of ChatGPT on scientific research in university higher education was determined. The deductive method, quantitative approach, explanatory level, and pre-experimental design were used. The sample consisted of 36 students coursing a Master's Degree in University Research and Teaching at the Graduate School of the Universidad Nacional del Altiplano, Puno, Peru. The results showed that ChatGPT significantly influences scientific research, with an increase in results from the pretest of 2.8% to the posttest of 80.6%. In conclusion, ChatGPT has a positive impact on the formulation of scientific research, demonstrating its potential to improve the academic quality and impact of research papers.

The Impact of Key Performance Indicators on Faculty Research in Higher Education

This study investigates the effectiveness of key performance indicators (KPIs) in evaluating the research contributions of academic staff in Uzbekistan, aiming to provide a nuanced understanding of faculty performance assessment. Employing a mixed-methods approach, the research integrates quantitative bibliometric analysis of publication data from 500 faculty members with qualitative interviews from 30 academics. The quantitative analysis focuses on metrics such as total publications, citation counts, and h-index scores, while the qualitative component explores faculty perceptions regarding the influence of KPIs on their research activities and career development. The analysis reveals significant variability in research productivity, with faculty averaging 12.4 publications and 110.2 citations. Econometric modeling indicates a strong positive correlation between publication metrics and citation impact, suggesting that higher publication output enhances academic visibility. Qualitative insights highlight the pressures of a "publish-or-perish" culture, which adversely affects research quality and faculty morale, particularly in contexts with limited institutional support. This research contributes to the discourse on academic performance evaluation by emphasizing the limitations of traditional metrics and advocating for a more holistic assessment framework. It highlights the need for higher education institutions to consider both quantitative and qualitative measures to better reflect the complexities of academic contributions in Uzbekistan.

Adaptive Reuse of Abandoned Churches in the Walled City of Famagusta, North Cyprus

There are so many abandoned heritage buildings worldwide and due to the lack of function and maintenance, they are ruined, deteriorate easily, and are forgotten. Similarly, abandoned valuable religious buildings faced vandalism deliberately because of the decreasing demand for use or lack of their communities. Some churches in Islamic countries are left useless and with no function, and North Cyprus is one of them. The Walled City of Famagusta has many historic religious buildings like cathedrals and churches. This research aims to develop proposals for the adaptive reuse of abandoned churches in the Walled City of Famagusta to overcome their current problems. The methodology of this historical research is qualitative and comparative. The data collection techniques are based on literature review and observation. This research will bring new perspectives on these churches' conservation for architects, historical researchers, and conservationists.

Appreciating dyslexic thinking in qualitative research: reflections and recommendations for culturally competent, neuro-inclusive academia

AbstractDyslexia and its associated learning challenges are often misconstrued as intellectual deficits, leading to erroneous assumptions that individuals with dyslexia cannot thrive or contribute meaningfully to academic institutions. However, this article contends that the unique thinking patterns associated with dyslexia are complementary to and can substantially enrich the professional practice of qualitative research. The social model of disability emphasises how Higher Education Institutions, rooted in ableist and neurotypical norms, often marginalise and fail to accommodate dyslexic cognitive profiles. Conversely, cultural competency, as an actionable conceptual framework, calls for transformative changes that promote understanding, build meaningful relationships, and ensure effective communication with neurodivergent individuals. Drawing on my experience as a dyslexic academic, I examine critical discussions on disability, neurodiversity, higher education, and qualitative research. Adopting an autoethnographic methodological approach, I highlight my professional strengths within this context, and propose an adaptable cultural competency framework aimed at cultivating neuro-inclusive—and specifically dyslexic-friendly practices, at the individual and organisational levels within academia.

Does the Three-Year Action Plan for Winning the Blue Sky Defense Battle implementation enabling the high-quality development of regional energy? A quasi-natural experiment from China

Energy is the lifeline of modern economy and industrial development. Promoting the high-quality development of regional energy is an important step to achieve high-quality economic and social development. This paper takes the energy policy of the Three-Year Action Plan for Winning the Blue Sky Defense Battle (the Blue Sky Defense Battle) in China as a quasi-natural experiment, and builds a two-way fixed effects difference-in-differences (DID) model to explore the impact of this policy on the high-quality development of regional energy based on the panel data of China's 31 provinces from 2015 to 2021. The results show that the Blue Sky Defense Battle has a significant positive effect on regional energy high-quality development, and this conclusion is robust under a series of robustness tests. Heterogeneity analysis indicates that the Blue Sky Defense Battle has a more promote effect on the high-quality development of regional energy in the western and eastern region, as well as in the low and middle income provinces. Mechanism analysis reveals that the Blue Sky Defense Battle promotes the high-quality development of regional energy by improving the level of scientific and technological innovation. Nonlinear analysis verifies that there is a single threshold effect of the level of scientific and technological innovation, the influence of the Blue Sky Defense Battle on the regional energy high-quality development becomes stronger when the scientific and technological innovation level above the threshold. The study provides a reference for policy makers to support the implementation of energy policies such as the Blue Sky Defense Battle and enhance the high-quality development level of regional energy.