Nature Of Science Research Articles (Page 1)

Performance management is a key link in an enterprise's human resource management. Its scientific nature and effectiveness have a significant impact on the implementation of corporate strategies, employee motivation, and the cultivation of core competitiveness. As a state-owned geological exploration unit, against the background of deepening the reform of state-owned enterprises and industrial transformation, the optimization of the performance management mechanism has become a core issue for Y Company to promote its sustainable development. Based on the expectancy theory, this study conducts an in-depth analysis of the current situation of Y Company's performance management through a questionnaire survey method, and finds that there are problems such as fragmented employee cognition, defects in the design of performance indicators and processes, and insufficient pertinence of the incentive mechanism. These shortcomings have weakened employee motivation and also restricted the achievement of the company's goals. Based on this, this study puts forward optimization suggestions from three dimensions: internal optimization, external adaptation, and implementation guarantee, aiming to provide a practical path for Y Company's performance management reform, and at the same time offer reference for the performance management optimization of similar state-owned geological exploration units.

With the in-depth development of the big data era, artificial intelligence (AI) technology, relying on its powerful data processing and pattern recognition capabilities, has become a core driver for advancing business analysis towards intelligence and automation. This paper aims to systematically explore the specific application models, significant advantages, and potential limitations of AI technology in the field of data analysis. First, from the perspective of technological development, the paper outlines the key technical components of current cutting-edge business analysis and explains the inevitability of AI becoming an indispensable element therein. Second, taking Uber's ride-sharing algorithm as a typical case, it deeply analyzes its core principlethe "Trip Chain"and working mechanism, revealing how AI achieves accurate resource matching and route planning in a highly dynamic environment to improve overall system efficiency and user experience. Finally, the paper dialectically analyzes the advantages and disadvantages of AI applications and concludes that AI technology significantly enhances the scientific nature and intelligence level of business decisions by improving the efficiency, scale, and depth of data analysis. However, its widespread application still needs to address multiple constraints in terms of technology itself and social acceptance. Technology is a lever, while humans remain the fulcrum. The future of AI-driven data analysis belongs to practitioners who skillfully wield these tools without succumbing to technological determinism.

ABSTRACT The voluntary compliance of ordinary citizens is pivotal for the seamless implementation of public policy and the achievement of desired policy outcomes. Government agencies often rely on expert endorsement in policy communication to bolster public support. However, recent scholarship indicates a decline in the perceived credibility of experts, particularly in China. With the rapid advancement of artificial intelligence (AI), this paper investigates whether large language models (LLMs) can notably endorse public policy and influence citizens' compliance willingness. Leveraging two controversial policies in China, we pre‐registered and performed two survey experiments. The findings reveal that policy endorsement from LLMs, especially Chinese LLMs, can effectively enhance public support for controversial policies, whereas endorsement from experts shows no significant effect. Moreover, exploratory analyses reveal that the improvement in public evaluation of the scientific nature of policymaking may mediate this causal relationship. This paper sheds light on the potential implications of AI on policy communication and citizens' policy perceptions.

This paper explores the role of interdisciplinary strategies in contemporary art practice at the intersection of cognitive science, art and virtual reality in the VR artwork Nature is an event that never stops. The artwork comprises six distinct virtual worlds and employs interactive colour-matching tasks in each world to investigate the interplay between sensation, expectation, and experience in colour perception. Drawing on theories of perception as a dynamic synthesis of sensory inputs and prior knowledge, the paper examines how the immersive environments of the VR experience influence participants’ colour choices. By linking colour to cultural transmission, lighting contexts, canonical colours, and personal identity, the artwork challenges conventional notions of colour as fixed and universal. The paper situates these findings within broader discussions on relational aesthetics, offering a model for interdisciplinary collaboration that engages sensory experience to foster introspection and shared responsibility, while emphasising perception as a deeply relational process shaped by cultural and material contexts.

ABSTRACT The campus culture map serves as a navigational tool and plays a crucial role in preserving, emphasizing, and disseminating campus culture due to its graphic, scientific, and portable nature. However, existing research predominantly focuses on evaluating the performance of maps while neglecting the user experience of campus cultural maps. This limits its potential in cultural communication and user interaction. Therefore, we designed a campus cultural landscape map, proposed our design approach at the same time, and then explored the user experience of the map in terms of usability, aesthetics and personal involvement. The experiment recruited 128 participants and evaluated the user experience of the campus cultural landscape map, including usability, personal involvement, and aesthetic evaluation. The findings indicate that the campus cultural landscape map has a high-quality user experience, with an appealing visual interface and high usability. At the same time, participants familiar with the campus cultural landscape have higher personal input when using the campus cultural landscape map. We hope the methods and case studies presented can help map makers and interface designers.

Background Bipolar disorder is a prevalent mental health issue characterized by recurrent episodes of mania and depression, significantly impacting patients’ quality of life. With the rise of short video sharing platforms, there is an urgent need to evaluate the quality and reliability of the medical information disseminated regarding this disorder. Objective This study aimed to assess the quality and reliability of videos related to bipolar disorder available on popular Chinese short video platforms, including TikTok, Kwai, Bilibili, WeChat, Xiaohongshu, and Baidu. Methods A cross-sectional content analysis was conducted in May 2025, using keywords related to bipolar disorder to retrieve relevant videos from selected platforms. The quality of the videos was evaluated using multiple standardized assessment tools, including the JAMA Benchmarking Criteria, GQS, modified DISCERN, PEMAT, and HONCODE. Results Significant differences in video quality and audience engagement metrics were observed across platforms. TikTok and Kwai had higher quality scores, while WeChat resulted in more comments. Most videos were created by medical professionals, although independent users also contributed content. Overall, video quality was inconsistent and not necessarily correlated with engagement metrics, highlighting the necessity for improved standards in disseminating health-related information on social media. Conclusion On Chinese short video platforms, clinical practitioners are the main creators of bipolar disorder-related content, but their scientific nature, production quality, and information transparency still need to be improved. It is suggested to improve the platform management, creator training, and algorithm optimization, so as to promote the improvement of public mental health literacy.

This study aims to analyze science teachers' perceptions of the Nature of Science (NOS) and Nature of Scientific Inquiry (NOSI), including their understanding of the nature of scientific knowledge, the scientific method, and the challenges in its implementation in the classroom. A survey method was employed, involving 61 science teachers from various educational levels. The findings reveal that 59% of teachers agreed and 34.4% strongly agreed that they understand the nature of science and apply it in their teaching. Additionally, 65.6% agreed and 26.2% strongly agreed that scientific knowledge is tentative and continually evolving. Regarding the scientific method, 49.2% agreed and 44.2% strongly agreed that science is based on empirical evidence and can be tested. However, despite a general understanding of the importance of inquiry-based approaches, 47.5% disagreed and 14.8% strongly disagreed with the effectiveness of the inquiry model in science education, indicating significant challenges in its implementation. Factors such as limited facilities, time constraints, and students' readiness were identified as key obstacles to the optimal integration of NOS and NOSI. Therefore, enhanced teacher training, infrastructure support, and more adaptable teaching strategies are essential to ensure the effective implementation of NOS and NOSI in science education.

Aiming at the problems of easy falsification of information and inaccurate evaluation results in the existing university bursary evaluation, a bursary evaluation model (XGBoost Model based on Blockchain, XMB) combining machine learning and blockchain was designed. The relevant basic data of the bursary evaluation is stored on the chain to solve the problem of easy falsification of data in the evaluation process. At the same time, the evaluation results of the student bursary are uploaded to the chain to realize the traceability of historical data. In addition, the improved XGBoost algorithm is used to intelligently analyze and evaluate the basic data of students, and objectively give the student a bursary grade, which realizes the intelligence and scientific nature of the evaluation process and ensures the accuracy of the evaluation results. The experimental results prove that the model proposed in this paper has an accuracy rate of about 6% higher than that of the traditional XGBoost model, which has higher evaluation accuracy, throughput, and time efficiency. The method proposed in this paper is suitable for the evaluation of scholarships and bursaries in the student management system of colleges and universities.

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.

To contribute towards the current revival of the philosophical thought of Ludwig Andreas Feuerbach (1804-1872) with his pioneering exposition of various contemporary issues (Individual Differences, Statue of Democracy and Sciences, Sustainable Development, Dietetics, Gymnastics, Unconscious Desires, Intercultural Dialogues, and others). The author applies Feuerbach's own organic or critical-genetic method, in which phenomena are understood through their origins, to grasp Feuerbachian insights. His Philosophy is examined through his concept of self-objectification (among his fundamental concepts) as the guiding principle of Feuerbach's formulations, both as a result of explicitly pantheistic, naturalistic and republican influences, and as a conceptual basis for transcending them as they evolved, philosophically, Italian philosophical pantheism through its genetic-critical methodology, Western scientific naturalism through its postulation of technological alliances with inhuman nature, and European democratic republicanism through its prediction of the institutional conditions for a future human community.

Conceptualizing the nature of science (NOS) is a crucial component of science education, as it facilitates students’ comprehension of how scientific knowledge is developed. Unfortunately, teachers can themselves hold inaccurate views of NOS or assume students can infer NOS ideas from instruction or by undertaking experiments. Building on previous research, this study explores how pre-service primary school teachers conceive NOS and their readiness and attitudes toward teaching NOS in primary school (grades 1-4). Data collected from future primary school teachers using the “Views on Science Education (VOSE)” instrument tend to align with previous studies, indicating that future primary school teachers generally hold positive attitudes toward the need to conceptualize NOS, but continue to belief in a single, universal scientific method, the idea that scientific theories and laws are discovered and the notion that science is entirely objective. Based on these findings, a restructured pre-service science education course is proposed.

Kazakhstan is one of the world's leading wheat exporters and performs a strategic function in ensuring global food security. The country's grain sector shows stable growth, self-sufficiency, an increase in export revenues and employment in rural areas. However, factors such as climate risks, high regional concentration of production, infrastructure constraints and institutional barriers have a significant impact on the sustainability of this agricultural segment. The goal is to assess the contribution of the grain industry to the domestic economy, determine its effective functioning and competitiveness on the basis of statistical indicators and an integral index. Methods - econometric, study of the dynamics of production processes by time series using official data of the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan for 2015-2024, normalization of indicators when comparing them, calculation of the integral index taking into account the position of an integrated approach, comparison and generalization for studying price trends and regional infrastructure. The methodology relies on the scientific approaches of the FAO. Results - positive growth rates of output, productivity and exports are shown. The grain self-sufficiency coefficient was 1.26, the share of exported goods – 31.2%, the Consumer Price Index - 9.92%, and the integral Balance Index - 0.87. Conclusions - a stable grain complex, but vulnerable to natural-climatic and territorial challenges. Measures are needed to diversify the territory, improve infrastructure, manage instability factors and adapt to climate change. Particular attention should be paid to the introduction of innovative technologies in grain farms in compliance with the rules of agricultural technology, as well as control over the supply of agricultural producers with fertilizers, plant protection products and new equipment. The results obtained can be used in long-term systemic planning to improve agrifood policy. This article is of an applied scientific and analytical nature and contributes to a comprehensive discussion of the problems of food self-sufficiency.

The article offers a series of methodological reflections on the culture of Western Europe during the High Middle Ages (11thÐ14th centuries). The progress of the science of nature in this period brought the West to leadership position in a wide range of spheres, a position it would maintain for centuries. Much less has been written about how this scientific progress influenced literary styles and styles of thought among Europeans. This is dewed to the vagueness inherent to the notion of style. It is therefore necessary to develop specific research techniques and a theoretical paradigm for the study of the texts and images concerned. Twentieth-century historiography in the major European languages provides a number of outstanding sources of inspiration for such methodological inquiry. The urgent task for medievalists is, finally, to reconsider translation practices.

The subject of the article is the legal aspects of protecting the productive capacity of soils. The study is of a scientific and research nature. The author starts from the statement that soils perform, in particular, environmental, economic, social and cultural functions, while for the protection of the characteristics that determine the possibility of using soils in food production, production functions, combined with the production function of agriculture, are important. Thus, the purpose of the analysis is to determine whether current Polish legislation sufficiently takes into account the need to protect the productive capacity of soils, understood as the possibility of sustainable use of these resources for food production. Consideration of this issue leads to the conclusion that the current legislation does not sufficiently take into account the need to protect the productive functions of soils, while a certain degree of protection is assumed by draft EU legislation on, among other things, soil monitoring granting Member States a significant role in tracking, assessing and managing the condition of soils.

Unitary Rogerian concepts are more evident in nursing's evolving disciplinary discourse since the seventies. This article explores ancient universal Laws of Nature that coincide with Unitary Nursing/Caring Science. These principles of life have not been addressed in nursing literature. Rogers' Science of Unitary Human Beings in convergence with Watson's Transpersonal Caring Science/Unitary Caring Science, are highlighted as evidentiary exemplars of the presence of these Natural Laws, referred to as Hermetic truths. By uncovering the universals that underpin Unitary Nursing/Caring Science, the discipline of Nursing is helped to mature to a higher level of consciousness, affirming the timeless universal unitary nature of Human-Universe phenomena of Nursing.

Environmental communication research on international rivers remains limited, particularly how they are represented in national media frameworks. Regarding international rivers, mainstream media in riparian countries can showcase their policies on river development and their stance on conflict or cooperation. The Mekong River is identified as common property but “appropriated for private gain,” and the communities living along it have suffered from various environmental impacts, especially in Vietnam’s Mekong Delta. Whereas most studies have focused on how environmental impacts are transforming the socio-economic life of local people there, this research aims to unpack Vietnamese press coverage on the Mekong Delta over a ten-year period, exploring how the scientific nature of environmental issues is interpreted in relevance to socio-economic and geopolitical context. In this study, reflexive thematic analysis was used to develop three themes: (1) “Climate change impacts, and upstream dams also to blame”; (2) “Those who control water, hold power: Chinese dams in Vietnamese news as geopolitics”; (3) “Illegal sand mining for ‘hungry’ construction industry, the toll worsened by upstream dams.” The analysis highlights a dynamic media representation which extends beyond specific natural hazards to encompass multifaceted human-environment relationships.

The impact of economic policy uncertainty on financial markets is becoming more and more significant. Through big data technology, time series analysis, and machine learning algorithm, the author of this paper discusses the impact of economic policy uncertainty on financial markets, especially under the background that globalization and informatization aggravate the complexity of the global economic environment. The author found that with the increase of economic policy uncertainty, the stock market yield decreases, the credit spread in the bond market expands, and the exchange rate fluctuation in the foreign exchange market intensifies. Based on data from 2010 to 2023, these hypotheses are verified by regression model analysis, and the significant relationship between economic policy uncertainty and financial markets is revealed. The research results provide not only a basis for policymakers to adjust the direction and intensity of policies but also support for investors to better understand market trends and improve the scientific nature of investment decisions.

Liberal naturalism has been widely misunderstood as a “middle” position situated between scientific naturalism on the one side and supernaturalism on the other. That (mis)characterization treats liberal naturalism as a form of “mild” metaphysics: a commitment to a more “liberal” ontology than reductive scientism; but one less expansive than supernaturalism (e.g. theism). I argue against this Ontology-centered understanding of the movement. Properly understood, liberal naturalism is fundamentally skepticism of metaphysics in any of its forms, including scientific naturalism and supernaturalism. Since metaphysics is a denigration or denial of the “appearances” – what Sellars called “the manifest image” of the world – then liberal naturalism is the recovery of the manifest image of the world and, in particular, the self to which this image is manifest. The self is not a scientific concept; in the last section, I argue that common sense (or “folk”) psychology is not proto-science. What understanding others requires is not science or metaphysics but what I call an “aesthetics of understanding others.”

There is a huge risk of dam failure during the operation of tailings ponds. Domestic and foreign scholars have conducted extensive research on the assessment and prevention of dam failure risks during the operation of tailings ponds, but there are still many shortcomings. On the basis of exploring the key issues of dam failure risk assessment during the operation of tailings dams, this paper establishes a comprehensive evaluation index system for dam failure risk during the operation of tailings dams based on ten principles including scientificity, systematicity, and operability. By exploring the use of the change statistical mapping method, we can determine the weight of indicators. A risk assessment model was constructed using the fuzzy comprehensive evaluation method; compared to the traditional fuzzy comprehensive evaluation method, this model determines weights in a more extensive and scientific manner. The scientific and effective nature of the model was verified through case analysis of the Shouyun Iron Mine and Shangyu Tailings Reservoir in Beijing. Finally, in response to the risk of dam failure during the operation of tailings ponds, scientific prevention and control measures were proposed from four aspects: personnel risk prevention and control, inherent risk prevention and control of tailings ponds, environmental factor risk prevention and control, and management risk prevention and control.

Abstract The growing public fascination with quantum technologies has inadvertently fueled the rise of pseudoscientific claims, particularly the misuse of quantum terminology in fields such as alternative medicine. This phenomenon poses a challenge for physics education, where the distinction between legitimate science and pseudoscience is essential. This paper examines how pre-service physics teachers (N = 28) respond to pseudoscientific uses of quantum terminology, particularly in the context of quantum healing. Therefore, the participants were asked to evaluate a pseudoscientific text about quantum healing in a classroom-like vignette, responding as if they were addressing a student. Their responses were analyzed using qualitative content analysis to categorize the types of reasoning used. Most participants were successful in identifying scientific inaccuracies and misuse of technical terms, although only a proportion applied broader Nature of Science (NOS)-related critiques. The findings suggest that although pre-service teachers are adept at identifying pseudoscientific claims, more emphasis on the principles of NOS could improve their ability to make comprehensive judgements.