Scientific Research Data Research Articles

Intelligent Monitoring of Data Quality Based on Multiple Data Structures

In the current context of big data, data quality management has become a hot topic in data science research. This article focused on the intelligent monitoring needs of complex data structures and explored data quality evaluation indicators and monitoring methods for complex environments. Key technologies such as data fusion, cleaning, and quality evaluation were focused on research, and a data quality monitoring system for multi-dimensional data environments was constructed to verify its application effectiveness in multi-source data environments, as well as specific measures to improve data quality. On this basis, a data quality evaluation model based on data mining was utilized, and a real-time monitoring system was established for application research. When the number of consistency issues was 30, the response time was 300ms, and the success rate of processing was 95%. The lowest processing success rate was 88%, and the highest was 100%. The overall processing success rate of the system was very good. The research results of this article provided theoretical and methodological support for enterprises to effectively carry out data quality management, which has important theoretical significance and application value.

Research on the Construction of Statistical Data Management Platform under Big Data

Purpose: Under the construction of Statistical data management platform, the problems such as low accuracy of data, difficult effective integration of data, low efficiency, etc., are solved, and the clinical research workflow is improved. Methods: Based on the integration platform and big data related technologies, multi-source heterogeneous data are integrated and cleaned to form a scientific research data center. What's more, the scientific research retrieval system is used for high-speed retrieval, analysis and utilization of the data in the scientific research data center. Results: The built scientific research retrieval system has the functions of integrating statistical methods, flexibly configuring statistical indicators, customizing queries, etc., which reduces the pressure of scientific researchers in data collection, statistics and analysis, and improves the statistical analysis quality of scientific research data. Conclusion: It has improved the quality and efficiency of scientific research, accelerated the transformation of scientific research achievements, and indirectly promoted the improvement of medical quality.

The health of the population of the region as a systemic object of sociological analysis (results of the pilot study)

The purpose of the study was to identify and study the systemic links between the basic factors of health and mortality in Russian regions based on correlation analysis methods, i.e., to study the relationship between health, morbidity and mortality. The object of the study was the regions of the Central Federal District (16 regions). The choice of this district as an object of study is due, firstly, to the significant population of Russians living in them. Secondly, in the regions of this district, a significant number of social relations significant for the health of the entire Russian society are collectively represented. Thirdly, numerous statistical and scientific research data have been accumulated on the state of health, diseases and mortality in these regions. The subject of the study is to identify the degree of influence of both objective and subjective factors of health, morbidity and mortality in the regions. The article shows that the understanding of the category of health in sociology has gone through several stages of understanding the category: as a combination of intrapersonal physiological and mental phenomena; as a complex of bodily, social and natural living conditions; as a systemic object of research, understood as a result of the interaction of individual and social factors. The results of studies in which health is analyzed as a systemic object of study, as well as the principles of an approach to the study of health as a systemic education, are summarized. The obtained data of the theoretical part of the study were tested in a pilot study, during which, based on correlation analysis, a significant relationship between social factors of health formation, disease prevention and mortality was confirmed. The conclusions of the pilot study showed the expediency of a systematic approach to the analysis and diagnosis of regional health, both in theoretical developments of the problem and in management activities to promote health. The use of the results of the pilot study is relevant for the development of regional health research problems, as well as for the organization of health diagnostics in the activities of administrative and managerial health management organizations.

Історичні аспекти та сучасні підходи до реєстрації рухів нижньої щелепи

Objective: To systematize and review available scientific research data over twenty years regarding systems and methods for recording lower jaw movements. Materials and Methods: A literature search was conducted on the PubMed service. Publications up to 2024 were considered. The primary filter in the search system was used to select publications based on the following criteria: metaanalysis, review, systematic review. Only publications in English were selected for the initial data set. The primary search yielded 45 publications. After a detailed analysis of the selected publications, 35 publications that best met the needs were retained for further processing. Additionally, 3 publications from other services that addressed the topic were added manually. Thus, the total number of publications used for the analysis amounted to 37 articles. Results: The analysis of lower jaw movements provides the clinician with important parameters for evaluating the function of the temporomandibular joint (TMJ). These parameters are crucial for modeling the normal functioning of the masticatory apparatus. Therefore, in-depth knowledge of lower jaw movements is necessary for dentists of various profiles, especially prosthodontists and orthodontists. Familiarity with various methods used to measure lower jaw movements is key in clinical analysis. The hardware for recording lower jaw movements has evolved significantly from purely mechanical methods to modern electronic systems with multi-functional software, ensuring high-level functional rehabilitation of the dentoalveolar system. Key words: lower jaw, temporomandibular joint, function, registration of lower jaw movements, hardware.

Opening a conversation on responsible environmental data science in the age of large language models

Abstract The general public and scientific community alike are abuzz over the release of ChatGPT and GPT-4. Among many concerns being raised about the emergence and widespread use of tools based on large language models (LLMs) is the potential for them to propagate biases and inequities. We hope to open a conversation within the environmental data science community to encourage the circumspect and responsible use of LLMs. Here, we pose a series of questions aimed at fostering discussion and initiating a larger dialogue. To improve literacy on these tools, we provide background information on the LLMs that underpin tools like ChatGPT. We identify key areas in research and teaching in environmental data science where these tools may be applied, and discuss limitations to their use and points of concern. We also discuss ethical considerations surrounding the use of LLMs to ensure that as environmental data scientists, researchers, and instructors, we can make well-considered and informed choices about engagement with these tools. Our goal is to spark forward-looking discussion and research on how as a community we can responsibly integrate generative AI technologies into our work.

The blind spot in data donations: who is (not) willing to donate digital data in social scientific research

The blind spot in data donations: who is (not) willing to donate digital data in social scientific research

Proposal to improve the transparency and efficiency of the CONFEA/CREA system using the Gaussian AHP Method

The present work and its applications are based on the necessity for the Brazilian Public Administration, in general, to comply with the constitutional principles established in Article 37 of the current Federal Constitution of Brazil. The primary focus is to address the principles of transparency and efficiency, which are central to this study and supported by the Transparency Law (LC nº 131/2009) and the Access to Information Law (Law nº 12,527/2011). The analysis will explore intrinsic elements of the CONFEA/CREA system to process and analyze data related to airfare, daily allowances, and accommodation expenses of the Regional Council of Engineering, Agronomy and Geosciences of the State of São Paulo – Brazil (CREA/SP). The objective is to propose compliance solutions linked to Data Science and Operational Research to standardize the aforementioned Councils in promoting transparency. Technological enhancements are suggested to improve the transparency of public acts, aiming to maximize efficiency. To achieve greater administrative and operational efficiency and effectiveness for Local Authorities, the Gaussian AHP Method is proposed. Key outcomes include improved information on the transparency portal, enhanced data accessibility, clarity, and completeness, increased analytical capacity for management and supervision, and greater visibility of administrative actions. These efforts aim to foster better public management practices and enhance decision-making precision through the application of Multi-Criteria Decision Support methods.

VICR: A novel software for unbiased video and image analysis in scientific research.

In scientific research, objectivity and unbiased data analysis is crucial for the validity and reproducibility of outcomes. This is particularly important for studies involving video or image categorization. A common approach of decreasing the bias is delegating data analysis to researchers unfamiliar with the experimental settings. However, this requires additional personnel and is prone to cognitive biases. Here we describe the Video & Image Cutter & Randomizer (VICR) software (https://github.com/kkihnphd/VICR), designed for unbiased analysis by segmenting and then randomizing the segmented videos or still images. VICR allows a single researcher to conduct and analyze studies in a blinded manner, eliminating the bias in analysis and streamlining the research process. We describe the features of the VICR software and demonstrate its capabilities using zebrafish behavior studies. To our knowledge, VICR is the only software for the randomization of video and image segments capable of eliminating bias in data analysis in a variety of research fields.

ФОРМИРОВАНИЕ КОМАНД СПЕЦИАЛИСТОВ И ИХ РОЛЬ В ЭКОНОМИЧЕСКОМ РАЗВИТИИ И СТРАТЕГИЧЕСКОМ УПРАВЛЕНИИ БИЗНЕСОМ

The article is devoted to the analysis of the processes of forming teams of specialists and their impact on economic development and strategic directions of business management. The purpose of the article is to study the importance of forming teams of specialists, as well as to clarify their role in the economic development of business in the context of strategic business management. To achieve this goal, the following main tasks were set and solved: the components of the formation of teams of specialists were analyzed and their impact on economic development and strategic business management was established, the structural and functional characteristics of a team of specialists were identified, the main models of the effectiveness of teams of specialists that determine the economic growth of a business and strategic guidelines for its development were described. The following general scientific methods were used in the course of the study: generalization – to clarify the content of the category t«eam», analysis – to critically comprehend the approaches and proposals of leading scientists regarding the formation, functioning and development of teams of specialists in the context of economic development and strategic business management; systematization and a systematic approach – to address the issue of identifying the main structural and functional characteristics a team of specialists; schematic and graphical images are used to visually represent the results of scientific research and analytical data. Based on the conducted research, it has been determined that today one of the important factors influencing the development of business and strategic areas of activity is the formation of an effective team of specialists, which leads to an improvement in economic indicators, contributes to economic growth, as well as the formation of competitive advantages for the strategic perspective.

Purpose definition as a crucial step for determining the legal basis under the GDPR: implications for scientific research.

The General Data Protection Regulation (GDPR) of the European Union, which became applicable in 2018, contains a new accountability principle. Under this principle, controllers (ie parties determining the purposes and the means of the processing of personal data) are responsible for ensuring and demonstrating the overall compliance with the GDPR. However, interpretive uncertainties of the GDPR mean that controllers must exercise considerable judgement in designing and implementing an appropriate compliance strategy, making GDPR compliance both complex and resource-intensive. In this article, we provide conceptual clarity around GDPR compliance with respect to one core aspect of the law: the determination and relevance of the purpose of personal data processing. We derive from the GDPR's text concrete requirements for purpose specification, which we subsequently apply to the area of secondary use of personal data for scientific research. We offer guidance for correctly specifying purposes of data processing under different research scenarios. To illustrate the practical necessity of purpose specification for GDPR compliance, we then show how our proposed approach can enable controllers to meet their compliance obligations, using the example of the overarching GDPR principle of lawfulness to highlight the relevance of purpose specification for the identification of a suitable legal basis.

Вплив стресофакторів на стан організму людини та органів і тканин порожнини рота (огляд літератури)

Abstracts. In today’s environment, every citizen of Ukraine is exposed to varying degrees of psycho-emotional and physical stress. It is impossible to underestimate the negative impact of stressors on the tissues and organs of the oral cavity in particular, as quite often the first signs of general pathologies appear in this complex. The aim of the study is to analyse data from scientific literature sources and provide updated information on the impact of psycho-emotional stress on the development of periodontal diseases in the current conditions. Materials and Methods. The bibliosemantic method was used to clarify the state of the problem, to study the analysis of the results of previous scientific research based on the sources of literature and electronic resources. Research results and discussion. The current conditions dictated by the war on the territory of our country is cause a state of permanent stress among the population of Ukraine, which is related to the basic human instinct of survival. In general, a person can be affected by one or more groups of objective causes of stress. The citizens of Ukraine are experiencing severe stress as a result of the ongoing conflict. This includes combatants, relatives and friends of these combatants, civilians living in the area close to the hostilities, the wounded, medical workers, and internally displaced persons. The stress factor provokes the emergence and rapid development of new mental and somatic diseases, it leads to the progression of existing diseases, but the reaction to the stimulus is different for each person and is an individual manifestation. The state of the oral cavity is a very sensitive complex to any changes in the body’s homeostasis, and often the first signs of general pathologies appear in it. Among the significant risk factors that contribute to the development and aggravate the course of periodontal disease, stress is one of the most important. Long-term exposure to stress can suppress the acquired immune response, causing an imbalance between pro-inflammatory and anti-inflammatory factors. Experimental studies in rat glands have demonstrated that acute stress induces dystrophic and necrobiotic changes in the gland, resulting in a reduction in its protein synthesis function. Psychological stress can contribute to disruption of the usual lifestyle, which adversely affects hygiene. Conclusions. After analysing scientific research data and reports on the current state of psycho-somatic health of people in Ukraine in modern realities, it is obvious that the prevalence and intensity of periodontal tissue diseases may have a new negative development. The peculiarities of the development, prevention and treatment of periodontal diseases in people experiencing severe psycho-emotional and sometimes physical stress require additional study and analysis. Key words: psycho-emotional stress, stress factor, periodontium, oral cavity

Research on Holographic Retrieval and Analysis System for Scientific Research Data Based on SSH Framework and Lucene Engine

Research on Holographic Retrieval and Analysis System for Scientific Research Data Based on SSH Framework and Lucene Engine

2013–2022年云南丽江森林生物多样性国家野外科学观测研究站日气象数据集

Meteorological factors are important environmental elements of field positioning observation stations of CNERN, CERN and CFERN. The acquisition of high-quality observational data through long-term positioning observations is beneficial for advancing our scientific understanding of ecosystem processes and tracking dynamic changes in biodiversity. It also provides important support for the development of regional and national ecological, environmental, and resource security construction initiatives. As one of the Forest Biodiversity National Observation and Research Stations approved in 2021, Lijiang Station has been collecting data in accordance with the CERN meteorological monitoring standards for past consecutive years. Up to now, Lijiang Station has consistently maintained comprehensive data parameters, a structured approach, and a high level of data standardization. These data can serve as important foundation for various research endeavors, including dynamic changes in the structure, processes, and functions of regional forest ecosystems, the formation, evolution, and preservation of regional biodiversity mechanisms, forest biodiversity and ecosystem functioning, the monitoring, evaluation, and conservation of biodiversity for key wild protected species, and the assessment and innovative exploitation of distinctive biological resources. This dataset comprises 3,652 entries and 39 fields of daily meteorological data spanning from 2013 to 2022. It covers atmospheric elements (air temperature and humidity, atmospheric pressure, wind speed and direction, precipitation, radiation elements) and soil elements (soil stratified temperature and soil heat flux). The release of the dataset offers comprehensive fundamental meteorological data for scientific research in related fields and provides essential data support for local and large-scale networking research.

Defining Medical AI Competencies for Medical School Graduates: Outcomes of a Delphi Survey and Medical Student/Educator Questionnaire of South Korean Medical Schools.

Given the increasing significance and potential impact of artificial intelligence (AI) technology on health care delivery, there is an increasing demand to integrate AI into medical school curricula. This study aimed to define medical AI competencies and identify the essential competencies for medical graduates in South Korea. An initial Delphi survey conducted in 2022 involving 4 groups of medical AI experts (n = 28) yielded 42 competency items. Subsequently, an online questionnaire survey was carried out with 1,955 participants (1,174 students and 781 professors) from medical schools across South Korea, utilizing the list of 42 competencies developed from the first Delphi round. A subsequent Delphi survey was conducted with 33 medical educators from 21 medical schools to differentiate the essential AI competences from the optional ones. The study identified 6 domains encompassing 36 AI competencies essential for medical graduates: (1) understanding digital health and changes driven by AI; (2) fundamental knowledge and skills in medical AI; (3) ethics and legal aspects in the use of medical AI; (4) medical AI application in clinical practice; (5) processing, analyzing, and evaluating medical data; and (6) research and development of medical AI, as well as subcompetencies within each domain. While numerous competencies within the first 4 domains were deemed essential, a higher percentage of experts indicated responses in the last 2 domains, data science and medical AI research and development, were optional. This medical AI framework of 6 competencies and their subcompetencies for medical graduates exhibits promising potential for guiding the integration of AI into medical curricula. Further studies conducted in diverse contexts and countries are necessary to validate and confirm the applicability of these findings. Additional research is imperative for developing specific and feasible educational models to integrate these proposed competencies into pre-existing curricula.

A Synthetic Time-Series Generation Using a Variational Recurrent Autoencoder with an Attention Mechanism in an Industrial Control System.

Data scarcity is a significant obstacle for modern data science and artificial intelligence research communities. The fact that abundant data are a key element of a powerful prediction model is well known through various past studies. However, industrial control systems (ICS) are operated in a closed environment due to security and privacy issues, so collected data are generally not disclosed. In this environment, synthetic data generation can be a good alternative. However, ICS datasets have time-series characteristics and include features with short- and long-term temporal dependencies. In this paper, we propose the attention-based variational recurrent autoencoder (AVRAE) for generating time-series ICS data. We first extend the evidence lower bound of the variational inference to time-series data. Then, a recurrent neural-network-based autoencoder is designed to take this as the objective. AVRAE employs the attention mechanism to effectively learn the long-term and short-term temporal dependencies ICS data implies. Finally, we present an algorithm for generating synthetic ICS time-series data using learned AVRAE. In a comprehensive evaluation using the ICS dataset HAI and various performance indicators, AVRAE successfully generated visually and statistically plausible synthetic ICS data.

Impact of Biodex systems equipment in prevention of ankle joint instability in junior footballers

Background: The aim of this study was to identify differences in impact in the prevention of second-degree ankle sprain recurrence, more precisely agonist-antagonist muscle rebalance, recovery of proprioception junior footballers will have a different impact on patients undergoing rehabilitation program with the help of Biodex 4 Pro and Biodex balance compared to those who perform physical therapy using classical exercise programs. (2) Methods: the study included 30 subjects divided into two equal groups according to the agreement to practice modern exercise programs and soccer-specific exercises: the experimental group which performed exercises through Biodex 4 pro and biodex balance and the control group which performed classical exercises. Part evaluations included: Biodex balance for a range of stability assessments and the PodoSmart device for running assessment. (3) Results: Analyzing the data of the present scientific research, it can be concluded that the athletes belonging to experimental group 1, for which the intervention was carried out using modern means, did not register any recurrence at the level of the ankle, compared to the athletes included in the experimental group 2 for which the intervention was carried out with the help of classic means of recovery and which recorded an average of 1.46 recurrences (sprains) at the level of the ankle.(4) Conclusion: The study has shown that the Biodex System 4 Pro and Biodex Balance (together with the other modern therapies mentioned in the current paper) are very helpful in the recovery process.

Using Data Interviews to Map Research Data Services (RDS) Needs at a Health Science Institution

Objective: On January 21, 2023 the National Institutes of Health Data Management and Sharing Policy (NIH DMSP 2023) went into effect. Ahead of these expanded data sharing requirements, the Health Sciences Library at the University of Tennessee Health Science Center (UTHSC) set out to better understand health science research data service (RDS) needs and how the Library could develop new services in alignment with existing institutional support.Methods: Building upon a set of data interview questions created by Read et al. (2015), the author conducted a series of semi-structured interviews with 10 researchers in the fall of 2022. The interview transcripts were inductively coded and analyzed for themes relevant to RDS needs.Results: Analysis of the interviews identified several opportunities for the Library to take ownership of RDS activities in the areas of support services, training and instruction, and tools and technology. Additionally, these interviews helped to characterize existing institutional support and to develop an informal community of practice at the University of Tennessee Health Science Center (UTHSC). These RDS topics were mapped onto Harvard’s Biomedical Data Lifecyle to further clarify areas of need and opportunities for growth for the Library and institutional RDS partners. Conclusions: The study identified critical RDS needs among UTHSC researchers and highlighted the potential role of the Library as a valuable partner in addressing these needs and fostering collaboration among campus stakeholders. Conversations informed by these findings continue with stakeholders about the best way to meet the needs of researchers on campus as well as centralize and coordinate existing endeavors.

Improving the usability of open health service delivery simulation models using Python and web apps

One aim of Open Science is to increase the accessibility of research. Within health services research that uses discrete-event simulation, Free and Open Source Software (FOSS), such as Python, offers a way for research teams to share their models with other researchers and NHS decision makers. Although the code for healthcare discrete-event simulation models can be shared alongside publications, it may require specialist skills to use and run. This is a disincentive to researchers adopting Free and Open Source Software and open science practices. Building on work from other health data science disciplines, we propose that web apps offer a user-friendly interface for healthcare models that increase the accessibility of research to the NHS, and researchers from other disciplines. We focus on models coded in Python deployed as streamlit web apps. To increase uptake of these methods, we provide an approach to structuring discrete-event simulation model code in Python so that models are web app ready. The method is general across discrete-event simulation Python packages, and we include code for both simpy and ciw implementations of a simple urgent care call centre model. We then provide a step-by-step tutorial for linking the model to a streamlit web app interface, to enable other health data science researchers to reproduce and implement our method.

Recent Books and Journal Articles in Public Opinion, Survey Methods, Survey Statistics, Big Data, Data Science, and User Experience Research. 2022 Update

Recent Books and Journal Articles in Public Opinion, Survey Methods, Survey Statistics, Big Data, Data Science, and User Experience Research. 2022 Update

The Public Interest Requirement in the Secondary Use of Health Data in Scientific Research: The Examples of Estonia and Finland

The General Data Protection Regulation (GDPR) foresees a flexible data processing regime for conducting scientific research with health data. This regime also enables extensive limitations on data subjects' rights to privacy and self-determination. Concern has been expressed that the notion of 'scientific research' may encompass conducting also profit-oriented commercial research that might not justify such limitations to data subjects' rights. Some authors have suggested a restriction on benefiting from the flexible scientific research regime: public interest should be set as a prerequisite for any scientific research employing health data without the data subject's consent. While the GDPR does not explicitly require that scientific research be in the public interest, it allows Member States to choose their policies. In light of this, the article examines the examples of Estonia and Finland to analyse whether national law should require the processing of health data in scientific research in the absence of the data subject's consent to be in the public interest. The article demonstrates on the basis of the two countries’ examples that it is possible to set a public interest standard without explicitly requiring the existence of a public interest via national legislation. Considering the future, the article also shows that, under the proposed European Health Data Space regulation, Member States may retain the public interest standard through the ethics-review requirement in their national law.