Environmental Research Research Articles

Making Metadata Machine-Readable as the First Step to Providing Findable, Accessible, Interoperable, and Reusable Population Health Data: Framework Development and Implementation Study.

Metadata describe and provide context for other data, playing a pivotal role in enabling findability, accessibility, interoperability, and reusability (FAIR) data principles. By providing comprehensive and machine-readable descriptions of digital resources, metadata empower both machines and human users to seamlessly discover, access, integrate, and reuse data or content across diverse platforms and applications. However, the limited accessibility and machine-interpretability of existing metadata for population health data hinder effective data discovery and reuse. To address these challenges, we propose a comprehensive framework using standardized formats, vocabularies, and protocols to render population health data machine-readable, significantly enhancing their FAIRness and enabling seamless discovery, access, and integration across diverse platforms and research applications. The framework implements a 3-stage approach. The first stage is Data Documentation Initiative (DDI) integration, which involves leveraging the DDI Codebook metadata and documentation of detailed information for data and associated assets, while ensuring transparency and comprehensiveness. The second stage is Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardization. In this stage, the data are harmonized and standardized into the OMOP CDM, facilitating unified analysis across heterogeneous data sets. The third stage involves the integration of Schema.org and JavaScript Object Notation for Linked Data (JSON-LD), in which machine-readable metadata are generated using Schema.org entities and embedded within the data using JSON-LD, boosting discoverability and comprehension for both machines and human users. We demonstrated the implementation of these 3 stages using the Integrated Disease Surveillance and Response (IDSR) data from Malawi and Kenya. The implementation of our framework significantly enhanced the FAIRness of population health data, resulting in improved discoverability through seamless integration with platforms such as Google Dataset Search. The adoption of standardized formats and protocols streamlined data accessibility and integration across various research environments, fostering collaboration and knowledge sharing. Additionally, the use of machine-interpretable metadata empowered researchers to efficiently reuse data for targeted analyses and insights, thereby maximizing the overall value of population health resources. The JSON-LD codes are accessible via a GitHub repository and the HTML code integrated with JSON-LD is available on the Implementation Network for Sharing Population Information from Research Entities website. The adoption of machine-readable metadata standards is essential for ensuring the FAIRness of population health data. By embracing these standards, organizations can enhance diverse resource visibility, accessibility, and utility, leading to a broader impact, particularly in low- and middle-income countries. Machine-readable metadata can accelerate research, improve health care decision-making, and ultimately promote better health outcomes for populations worldwide.

Efficient offloading and task scheduling in internet of thingth-cloud-fog environment

Efficient offloading and scientific task scheduling are crucial for managing computational tasks in research environments. This involves determining the optimal location for executing a workflow task and allocating the task to computing resources to optimize performance. The challenge is to minimize completion time, energy consumption, and cost. This study proposes three methods: latency-centric offloading (LCO) for delay-sensitive applications; energy-based offloading (EBO) for energy-saving; and efficient offloading (EO) for balanced task distribution across tiers. Scheduling in this paper uses a genetic algorithm (GA) with a weighted sum objective function considering makespan, cost, and energy for IoT-fog-cloud. Comparative studies involving Montage, Cybershake, and epigenomics workflows indicate that LCO excels in terms of makespan and cost but ranks the lowest in energy. EBO excels in energy efficiency, aligning closely with the base method. EO competes effectively with the base method in terms of makespan and cost but consumes more energy.<strong> </strong>This research enables the selection of the most suitable method based on the type of application and its prioritization of makespan, energy, or cost.

Red mud and bismuth oxide based X-ray shielding tiles for upcoming hospitals: A comprehensive study on phase quantification and physical properties

Red mud (RM) is a solid alumina industry waste generated in millions of tonnes and is stockpiled across the globe. From the environmental perspective, research and innovation strategies are utmost necessary for the minimization and utilization of red mud. In an attempt to develop an environmentally friendly technology, RM was utilized with Bi2O3 for the development of radiation shielding tiles. RM is a source of many metal oxides, which react with Bi2O3 during sintering and form various high-dense phases. The Rietveld refinement of the tiles sintered from 600 to 1100°C confirms the formations and transformations of several high-dense phases like Bi24Ti2O40, BiFeO3, and Na0.5Bi0.5TiO3. The RM-Bi2O3 mixture sintered at 1100°C (RMBi1100) exhibited high density (3.64 ×103 kg m−3), less porosity (10 %), and flexural strength of 24 MPa. The results showed that the developed sample has a half-value layer (HVL) of 1.15 mm at 140 kV. The 15.5 mm, 13.5 mm, and 7 mm thick RMBi1100 tiles can effectively replace 2.3 mm, 2 mm, and 1 mm thick lead sheets respectively, that are used to establish radiation shielding structures in computed tomography, radiography & fluoroscopy, and dental infra oral radiography installations, respectively. It can promote the utilization of red mud and thereby reduce the environmental pollution associated with lead and red mud.

Design of the electron cyclotron resonance (ECR) plasma source for the space plasma environment research facility.

The Space Plasma Environment Research Facility (SPERF) was built in Harbin to study the three-dimensional magnetic reconnection and wave-particle interactions relevant to space physics in laboratory settings. A 2.45GHz Electron Cyclotron Resonance (ECR) plasma source is adopted in the device to simulate the Earth's magnetosphere and achieve the scientific goals. In this paper, the design of the ECR plasma source is presented. The structures of the microwave source, the microwave transfer system, and the antenna are introduced. Additionally, the resonant surfaces are computed to predict the locations of microwave absorption. The absorption mechanisms of the microwave in the SPERF are also discussed. The discharge experiment demonstrates the utility of the ECR source in simulating the Earth's magnetosphere. The successful operation of the source indicates that the ECR discharge is a powerful tool for creating a plasma environment in a large plasma experimental device.

Communicating the use of artificial intelligence in agricultural and environmental research

Communicating the use of artificial intelligence in agricultural and environmental research

Tectonic and climate changes influences on distribution and morphology of Quaternary travertine, Kurkur oasis, Egypt

The present study aims to investigate the relationship between tectonic activity, climate changes and Quaternary travertine deposition around Kurkur Oasis in the southern Western Desert of Egypt. Our findings, based on field observations and structural investigations, revealed that extensional tectonics played a significant role in the formation and the distribution of travertine deposits in the study area. Three main travertine morphotypes are documented: fissure ridge, spring mound, and terrace mound along with four lithotypes: crystalline crust, fine-grained lithoclast, paper-thin raft, and reed. The spatial distribution of these travertine occurrences indicates that travertines located closest to the springs exhibit crystalline crust and paper-thin raft lithotypes. While, the reed and the fine-grained lithoclastic types are situated farther from the water sources. Terraces mounds are related to pluvial episodes, which led to travertine deposition in the suitable tectonically created depressions. A two-stage hypothesis for travertine deposition are proposed herein, involving tectonic fissuring and the circulation of carbonated water. These results may enhance our understanding of travertine formation and have broader implications for geological research in similar tectonic environments.

MOSkin dosimetry for an ultra-high dose-rate, very high-energy electron irradiation environment at PEER

FLASH radiotherapy, which refers to the delivery of radiation at ultra-high dose-rates (UHDRs), has been demonstrated with various forms of radiation and is the subject of intense research and development recently, including the use of very high-energy electrons (VHEEs) to treat deep-seated tumors. Delivering FLASH radiotherapy in a clinical setting is expected to place high demands on real-time quality assurance and dosimetry systems. Furthermore, very high-energy electron research currently requires the transformation of existing non-medical accelerators into radiotherapy research environments. Accurate dosimetry is crucial for any such transformation. In this article, we assess the response of the MOSkin, developed by the Center for Medical Radiation Physics, which is designed for on-patient, real-time skin dose measurements during radiotherapy, and whether it exhibits dose-rate independence when exposed to 100 MeV electron beams at the Pulsed Energetic Electrons for Research (PEER) end-station. PEER utilizes the electron beam from a 100 MeV linear accelerator when it is not used as the injector for the ANSTO Australian Synchrotron. With the estimated pulse dose-rates ranging from (7.84±0.21)×105 Gy/s to (1.28±0.03)×107 Gy/s and an estimated peak bunch dose-rate of (2.55±0.06)×108 Gy/s, MOSkin measurements were verified against a scintillating screen to confirm that the MOSkin responds proportionally to the charge delivered and, therefore, exhibits dose-rate independence in this irradiation environment.

Microbial communities on microplastics from seawater and mussels: Insights from the northern Adriatic Sea

Microplastics, synthetic solid particles of different sizes (< 5 mm), pose a major challenge to marine ecosystems. Introducing microplastics into the marine environment leads to the formation of complex microbial communities, a topic of growing interest in environmental research. For this study, we selected an area in the northern Adriatic Sea, less affected by human activities, to understand how pristine environmental conditions influence microbial colonization of microplastics. Samples of coastal seawater and Mediterranean mussels (Mytilus galloprovincialis) were collected in a mussel farm near Debeli rtič of the Slovenian coast. Microplastics were isolated, visually and chemically analyzed and DNA was extracted for metagenomics. In the marine water column, 12.7 microplastics per m3 water column and 0.58 microplastics per individual mussel were found. Sufficient DNA was available to analyze six particles, five originating from seawater, and one from a mussel. This was the first-ever sequenced microplastic particle from a mussel. Genera of Pseudomonas and Serratia were identified in all samples. In one of the samples, the most abundant was a marine genus Pseudoalteromonas, while in another sample Campylobacter was present with >30 % abundance. The microbiomes of the mussel- and seawater-isolated particles were similar, suggesting a common microbial colonization pattern, which may have implications for the transfer of microplastic-associated microbes, including potential pathogens, through the food web to the consumers. Microplastic pollution is a complex issue requiring further research, especially regarding microbial biofilms, pathogen colonization and the potential of pathogen transmission via microplastic particles. Our findings enhance the understanding of microplastic pollution in the Adriatic Sea and stress the necessity for comprehensive strategies to mitigate the impact on marine ecosystems.

Use of Machine Learning Models to Differentiate Neurodevelopment Conditions Through Digitally Collected Data: Cross-Sectional Questionnaire Study.

Diagnosis of child and adolescent psychopathologies involves a multifaceted approach, integrating clinical observations, behavioral assessments, medical history, cognitive testing, and familial context information. Digital technologies, especially internet-based platforms for administering caregiver-rated questionnaires, are increasingly used in this field, particularly during the screening phase. The ascent of digital platforms for data collection has propelled advanced psychopathology classification methods such as supervised machine learning (ML) into the forefront of both research and clinical environments. This shift, recently called psycho-informatics, has been facilitated by gradually incorporating computational devices into clinical workflows. However, an actual integration between telemedicine and the ML approach has yet to be fulfilled. Under these premises, exploring the potential of ML applications for analyzing digitally collected data may have significant implications for supporting the clinical practice of diagnosing early psychopathology. The purpose of this study was, therefore, to exploit ML models for the classification of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) using internet-based parent-reported socio-anamnestic data, aiming at obtaining accurate predictive models for new help-seeking families. In this retrospective, single-center observational study, socio-anamnestic data were collected from 1688 children and adolescents referred for suspected neurodevelopmental conditions. The data included sociodemographic, clinical, environmental, and developmental factors, collected remotely through the first Italian internet-based screening tool for neurodevelopmental disorders, the Medea Information and Clinical Assessment On-Line (MedicalBIT). Random forest (RF), decision tree, and logistic regression models were developed and evaluated using classification accuracy, sensitivity, specificity, and importance of independent variables. The RF model demonstrated robust accuracy, achieving 84% (95% CI 82-85; P<.001) for ADHD and 86% (95% CI 84-87; P<.001) for ASD classifications. Sensitivities were also high, with 93% for ADHD and 95% for ASD. In contrast, the DT and LR models exhibited lower accuracy (DT 74%, 95% CI 71-77; P<.001 for ADHD; DT 79%, 95% CI 77-82; P<.001 for ASD; LR 61%, 95% CI 57-64; P<.001 for ADHD; LR 63%, 95% CI 60-67; P<.001 for ASD) and sensitivities (DT: 82% for ADHD and 88% for ASD; LR: 62% for ADHD and 68% for ASD). The independent variables considered for classification differed in importance between the 2 models, reflecting the distinct characteristics of the 3 ML approaches. This study highlights the potential of ML models, particularly RF, in enhancing the diagnostic process of child and adolescent psychopathology. Altogether, the current findings underscore the significance of leveraging digital platforms and computational techniques in the diagnostic process. While interpretability remains crucial, the developed approach might provide valuable screening tools for clinicians, highlighting the significance of embedding computational techniques in the diagnostic process.

Molecular Screening for Cyanobacteria and Their Cyanotoxin Potential in Diverse Habitats

Cyanobacteria are adaptable and dominant organisms that exist in many harsh and extreme environments due to their great ecological tolerance. They produce various secondary metabolites, including cyanotoxins. While cyanobacteria are well studied in surface waters and some aerial habitats, numerous other habitats and niches remain underexplored. We collected 61 samples of: (i) biofilms from springs, (ii) aerial microbial mats from buildings and subaerial mats from caves, and (iii) water from borehole wells, caves, alkaline, saline, sulphidic, thermal, and iron springs, rivers, seas, and melted cave ice from five countries (Croatia, Georgia, Italy, Serbia, and Slovenia). We used (q)PCR to detect cyanobacteria (phycocyanin intergenic spacer—PC-IGS and cyanobacteria-specific 16S rRNA gene) and cyanotoxin genes (microcystins—mcyE, saxitoxins—sxtA, cylindrospermopsins—cyrJ), as well as amplicon sequencing and morphological observations for taxonomic identification. Cyanobacteria were detected in samples from caves, a saline spring, and an alkaline spring. While mcyE or sxtA genes were not observed in any sample, cyrJ results showed the presence of a potential cylindrospermopsin producer in a biofilm from a sulphidic spring in Slovenia. This study contributes to our understanding of cyanobacteria occurrence in diverse habitats, including rare and extreme ones, and provides relevant methodological considerations for future research in such environments.

THE WAR AS A SOCIO-CULTURAL PHENOMENON IN A CONTEMPORARY UKRAINIAN PHILOSOPHICAL DISCOURSE

An armed conflict between Ukraine and Russian Federation lasts for the past 10 years on and on February 24, 2022 it turned into full-scale war with all arsenal of conventional arm available used, nuclear excluded.The war turned into a new social and political reality that defined socio-political and socio-cultural vectors of development of Ukrainians and their state – focused on oppression to occupant’s conquer – for many years ahead.The war, as a socio-cultural phenomenon and the new stage of Ukrainian nation became a topic of research of the domestic academic environment. It defined in home philosophical research circles new polemic that aims at thinking through an ontological nature of the conflict, its social, cultural, and historical causes, to reveal its specific character in the past and in the present, to find out where the balance was lost in the structural order of the security, its lawful preventive mechanisms failure.Many analytical attempts to describe topological classification of that conflict (in the context of the growth of the contemporary philosophical discourse) were conducted. It were given some answers on the question on the roots of the conflict, on its continuity. It was pointed out its destructive impact on the condition of the Ukrainians, its social and cultural evolution from the point of view of different philosophical views and research programmes or contemporary historical narratives, modern principles of the native and Western-European philosophy.An evolution of the points of view on ontological and historical reasons of the war and philosophical reflections of the native scholars were considered in this article. Some problematic issues, determined by the different phases of the conflict were researched.

Vertical Distribution Characteristics and Ecological Risk Assessment of Mercury and Arsenic in Ice, Water, and Sediment at a Cold-Arid Lake

Mercury and arsenic are two highly toxic pollutants, and many researchers have explored the effects of the two substances on the environment. However, the research content of toxic substances in frozen periods is relatively small. To explore the spatial and vertical distribution of mercury and arsenic in the ice, water, and sediments of Wuliangsuhai Lake under ice conditions, and to assess the harm degree of the two toxic substances to human beings. We collected the ice, water, and sediments of the lake in December 2020, and tested the contents of Hg and As. The single-factor pollution index method, the local cumulative index method, and the ecological risk coding method were used to assess the pollution status in these three environmental media, and the Monte Carlo simulation combined with the quantitative model recommended by USEPA was used to assess the population health risk. The results showed that (1) The average single-factor pollution values of Hg and As in water were 0.367 and 0.114, both pollutants were at clean levels during the frozen period. (2) The mean Igeo values of Hg and As were 0.657 and −0.948. The bioavailability of Hg in the sediments of Wuliangsuhai Lake during the frozen period was high, and its average value was 7.8%, which belonged to the low-risk grade. The bioavailability of As ranged from 0.2% to 3.7%, with an average value of 1.3%. (3) Monte Carlo simulation results indicate acceptable levels of health risks in both water and ice. This study preliminarily investigated the distribution characteristics of toxic substances and their potential effects on human health in lakes in cold and arid regions during the frozen period. It not only clarified the pollution characteristics of lakes in cold and arid regions during the frozen period, but also provided beneficial supplements for the ecological protection of lake basins. This study lays a foundation for further environmental science research in the region in the future.

Nitrite facilitated transformation of halophenols in ice

This study investigated the expediated transformation of halophenols in the presence of nitrite (NO2−) under slightly acidic conditions in ice, whereas such transformation was negligible in liquid water at 4 °C. We proposed that this phenomenon was attributed to the freeze-concentration effect, incurring a pH drop and the aggregation of NO2− and halophenols within the liquid-like grain boundary layer amid ice crystals. Within this micro-environment, NO2− underwent protonation to generate reactive nitrous acid (HNO2) and nitrosonium ions (NO+) that facilitate the nitration and oxidation of halophenols. When 10 μМ halophenol was treated by freezing in the presence of 5 μМ NO2−, the total yields of nitrated products reached 2.4 μМ and 1.4 μМ within 12 h for 2-chlorophenol (2CP) and 2-bromophenol (2BP), respectively. NO+ drove oxidative coupling reactions, generating hydroxyl polyhalogenated diphenyl ethers (OH-PBDEs) and hydroxyl polyhalogenated diphenyls via C-O or C-C coupling. These two pathways were intricately intertwined. The presence of natural organic matter (NOM) mitigated the formation of nitrated products and completely suppressed the coupling products. This study offers valuable insights into the fate of halophenols in ice and suggests potential pathways for the formation of nitrophenolic compounds and OH-PBDEs in natural cold environments. These findings also open up a new avenue in environmental chemistry research.

Bootstrap Method as a Tool for Analyzing Data with Atypical Distributions Deviating from Parametric Assumptions: Critique and Effectiveness Evaluation

In today’s research environment characterized by exponential data growth and increasing complexity, the selection of appropriate statistical tests, tailored to research objectives and data distributions, is paramount for rigorous analysis and accurate interpretation. This article explores the growing prominence of bootstrapping, an advanced statistical technique for multiple comparisons analysis, offering flexibility and customization by estimating sample distributions without assuming population distributions, thus serving as a valuable alternative to traditional methods in various data scenarios. Computer simulations were conducted using data from cardiovascular disease patients. Two approaches, spontaneous partly controlled simulation and fully constrained simulation using self-written R scripts, were utilized to generate datasets with specified distributions and analyze the data using tests for comparing more than two groups. The utilization of the bootstrap method greatly improves statistical analysis, especially in overcoming the constraints of conventional parametric tests. Our research showcased its effectiveness in comparing multiple scenarios, yielding strong findings across diverse distributions, even with minor inflation in p values. Serving as a valuable substitute for parametric approaches, bootstrap promotes careful consideration when rejecting hypotheses, thus fostering a deeper understanding of statistical nuances and bolstering analytical rigor.

Situation Analysis of Sam's Club Based on the SWOT Model Based on the Research of Chinese Market Environment

Situation Analysis of Sam's Club Based on the SWOT Model Based on the Research of Chinese Market Environment

Leading impactful research: applying platform thinking to drive collaborative inquiry in the innovation field

PurposeThis study investigates the application of collaborative inquiry within innovation management, employing platform thinking to address challenges of generalizability and relevance. The aim is to integrate Collaborative Inquiry methods, characterized by participatory, diffuse, and reflective practices, to transform research into a tool for impactful change in organizations in the field of innovation management.Design/methodology/approachA longitudinal participatory case study approach focuses on the IDeaLs case—a research platform that collaborated with multiple companies over several years. The data gathered and analyzed comes from the research project within the research platforms over the first two editions and from the research platform management and coordination activities.FindingsThe study introduces the Collaborative Research Platform Approach (CRPA), demonstrating its effectiveness in addressing typical constraints of traditional research methodologies through a real-world application within the IDeaLs case. The findings highlight the CRPA's potential in fostering a dynamic, co-creative research environment that bridges theoretical knowledge with practical applications, thus enhancing both scholarly and organizational outcomes while pursuing a future change within the organizations.Research limitations/implicationsThere are two main research implications. First, it proposes platform thinking as a theoretical lens to read a multi-stakeholder phenomenon in the research domain, confirming its nature of value-creation mechanisms, using it outside the business model and strategic space. Second, it offers a methodological contribution by presenting the CRPA framework.Practical implicationsThe CRPA framework offers organizations a structured approach to managing collaborative research projects that align with both academic rigor and practical relevance. Companies engaged in the study reported enhanced ability to implement actionable insights from research, influencing real-time decision-making processes.Social implicationsBy fostering collaborative engagements across multiple stakeholders, the CRPA promotes a research culture that values inclusivity and practical impact, potentially leading to broader societal benefits through improved innovation management practices.Originality/valueThis paper contributes to the innovation management field by proposing the CRPA, which integrates principles of Platform Thinking with Collaborative Inquiry. This novel approach is designed to improve the applicability and scope of innovation research, offering a robust framework that enhances engagement and utility across academic and business domains. It uses platforms as a theoretical lens to read a multi-stakeholder environment in the research domain.

Harmless disposal of phosphogypsum synergized red mud: Harmful element control and material utilization

Soluble P2O5 and fluorine in phosphogypsum can jeopardize the environment and even human health. The application in building materials is a pathway to consume phosphogypsum on a large scale. However, the presence of soluble phosphorus causes significant retardation that reduces the early strength of building materials containing phosphogypsum. In this study, the mechanism of soluble phosphorus removal from phosphogypsum by red mud were studied. The synergistic effect of phosphogypsum, red mud and blast furnace slag for the preparation of high-sulfur cementitious materials was also investigated. The results demonstrated that the soluble phosphorus was transformed to inert material and was completely stabilized when red mud dosing reached 20 %. The slow setting was significantly improved, causing an increase in 3-d compressive strength. More hydration products were generated to enhance the early strength, indicating that the optimal synergistic effect of phosphogypsum, red mud and blast furnace slag occurred. In addition, the compressive strength reached 21.40 MPa (3 d), 29.60 MPa (7 d), and 48.60 MPa (28 d) when the total admixture of phosphogypsum and red mud was 45 %. The environmental performance research also shows that the material was green and non-polluting. This paper advocates the use of the physicochemical properties of different solid wastes to dispose of hazardous substances in phosphogypsum rather than the use of natural resources.

Blockchain technology for ecological and environmental applications

This research study examines the use of Blockchain technology for ecological and environmental applications. The study presents a conceptual view aided by a literature survey to identify three major Blockchain themes connecting with the research topic - Transparency and Traceability, Conservation and Incentives, and Data Management and Monitoring. The goal of the study is to use the features offered by Blockchain Technology for sustainability, ecology, and environmental applications. As this research shows, technology can help in conservation and incentive practices such as conservation finance, tokenized rewards for ecosystem services, and rewards for sustainable practices. Blockchain has good data management and monitoring practices that can help secure environmental data, monitor various environmental parameters in real time, and provide a decentralized platform/infrastructure for environmental data analytics. Findings from this study can help environmental practitioners and researchers, research bodies, and Governmental agencies keen to use technology to preserve ecology and the environment and encourage sustainable practices.

Deciphering the role and impact of India's pharmaceutical industries and its regulatory compliance

The pharmaceutical industry faces exceptionally high R&amp;D costs, with the US research-based sector investing about 17% of sales into R&amp;D. The cost of bringing a new compound to market was estimated at $802 million in 2001, up from $138 million in the 1970s and $318 million in the 1990s, necessitating stringent regulations. This study aims to determine the role and impact of India's pharmaceutical industry and its regulatory compliance. Personnel from organizations established between 1884 and 2004, with turnovers ranging from Rs. 25 crore (US $5.3 million) to Rs. 5500 crore (US $1.2 billion), were surveyed. Out of 150 companies approached, 73 responded, with 70 complete responses analyzed. Ongoing interactions with regulatory agencies helped companies better understand the regulatory system. Three key areas emerged as priorities: awareness of intellectual property rights (IPR) and patents, fostering a suitable environment for research and development, and implementing Good Manufacturing Practices (GMP), considered more critical than price control. The findings underscore the importance of regulatory compliance in promoting innovation and maintaining quality within the pharmaceutical industry, ensuring its competitiveness and ability to meet global standards.

PRE-SERVICE TEACHERS’ VIEWS ON DIJITAL ADDICTION

The aim of this study is to show the views of pre-service teachers on digital addiction. The study group of the research consisted of Eskişehir Osmangazi University Education Faculty, social studies teacher, primary school mathematics teacher, English teacher, science teacher, special education teacher, classroom teacher, preschool teacher and psychological counseling and guidance (PDR) in the spring term of 2021-2022 academic year consists of 90 pre-service teachers studying at the 2nd, 3rd and 4th grades at the undergraduate level.Purposive sampling method was used while forming the study group of the research. As a data collection tool in the research, a semi-structured interview form, which was collected by e-mail in the online environment and formed by taking expert opinion, was used.The There have been a number of attempts by pre-service teachers to reduce digital addiction and they have often been unsuccessful. Analysis was used in the analysis of the data. Findings show that the students generally evaluated themselves as addicted. The students participating in the research stated that they spend most of their time in the digital environment for research, doing homework, communicating, following social media, shopping online, watching TV series and movies, listening to music and playing games.The students participating in the study stated that digital addiction caused them to disrupt their responsibilities and There have been a number of attempts by pre-service teachers to reduce digital addiction and they have been unsuccessful.