Digital Library Research Articles

The impact of Library Size and Scale of Testing on Virtual Screening.

Virtual libraries for ligand discovery have recently increased 10,000-fold, and this is thought to have improved hit rates and potencies from library docking. This idea has not, however, been experimentally tested in direct comparisons of larger-vs-smaller libraries. Meanwhile, though libraries have exploded, the scale of experimental testing has little changed, with often only dozens of high-ranked molecules investigated, making interpretation of hit rates and affinities uncertain. Accordingly, we docked a 1.7 billion molecule virtual library against the model enzyme AmpC β-lactamase, testing 1,521 new molecules and comparing the results to the same screen with a library of 99 million molecules, where only 44 molecules were tested. Encouragingly, the larger screen outperformed the smaller one: hit rates improved by two-fold, more new scaffolds were discovered, and potency improved. Overall, 50-fold more inhibitors were found, supporting the idea that there are many more compounds to be discovered than are being tested. With so many compounds evaluated, we could ask how the results vary with number tested, sampling smaller sets at random from the 1521. Hit rates and affinities were highly variable when we only sampled dozens of molecules, and it was only when we included several hundred molecules that results converged. As docking scores improved, so too did the likelihood of a molecule binding; hit rates improved steadily with docking score, as did affinities. This also appeared true on reanalysis of large-scale results against the σ2 and dopamine D4 receptors. It may be that as the scale of both the virtual libraries and their testing grows, not only are better ligands found but so too does our ability to rank them.

Technologies for Supporting Individuals and Caregivers Living With Fetal Alcohol Spectrum Disorder: Scoping Review.

Fetal alcohol spectrum disorder (FASD) is a common developmental disability that requires lifelong and ongoing support but is often difficult to find due to the lack of trained professionals, funding, and support available. Technology could provide cost-effective, accessible, and effective support to those living with FASD and their caregivers. In this review, we aimed to explore the use of technology available for supporting people living with FASD and their caregivers. We conducted a scoping review to identify studies that included technology for people with FASD or their caregivers; focused on FASD; used an empirical study design; were published since 2005; and used technology for assessment, diagnosis, monitoring, or support for people with FASD. We searched MEDLINE, Web of Science, Scopus, Embase, APA PsycINFO, ACM Digital Library, JMIR Publications journals, the Cochrane Library, EBSCOhost, IEEE, study references, and gray literature to find studies. Searches were conducted in November 2022 and updated in January 2024. Two reviewers (CZC and HW) independently completed study selection and data extraction. In total, 17 studies exploring technology available for people with FASD showed that technology could be effective at teaching skills, supporting caregivers, and helping people with FASD develop skills. Technology could provide support for people affected by FASD; however, currently there is limited technology available, and the potential benefits are largely unexplored.

Health technologies for tackling client absenteeism in primary and secondary care services.

Tackling client absenteeism in primary and secondary care settings is crucial to ensure the continuity of care for individuals, familiesand communities, as well as preventing waste of resources within healthcare systems. This article is an integrative review to identify advancements in health technologies that addressclient absenteeism in primary and secondary care. The databases Medical Literature and Retrieval System Online (MEDLINE/PubMed®), Scientific Electronic Library Onlineand Virtual Health Librarywere consulted. The inclusion criteria were as follows: full papers, published between 2013 and 2023, in English, Portugueseor Spanish. The descriptors used were the following: patients, mobile applications, health services management, absenteeismand primary care, and secondary care. Eleven articles published from 2014 to 2021 were included. Most articles were identified in the MEDLINE/PUBMED database, employed a randomized controlled trial methodology (36.36%), and were published between 2019 and 2021 (90.0%) in English (63.7%). The applications had managerial, assistiveand/or educational purposes. In addition to absenteeism control, these applications strived to promote client engagement with health services, increase health literacyand tackle structural barriers to care, such as language barriers. Efforts are needed to ensure that providers receive training to educate clients on the applications. Moreover, community-based participatory studies to ensure the feasibility of applications are warranted.

Navigating the Multimodal Landscape: A Review on Integration of Text and Image Data in Machine Learning Architectures

Images and text have become essential parts of the multimodal machine learning (MMML) framework in today’s world because data are always available, and technological breakthroughs bring disparate forms together, and while text adds semantic richness and narrative to images, images capture visual subtleties and emotions. Together, these two media improve knowledge beyond what would be possible with just one revolutionary application. This paper investigates feature extraction and advancement from text and image data using pre-trained models in MMML. It offers a thorough analysis of fusion architectures, outlining text and image data integration and evaluating their overall advantages and effects. Furthermore, it draws attention to the shortcomings and difficulties that MMML currently faces and guides areas that need more research and development. We have gathered 341 research articles from five digital library databases to accomplish this. Following a thorough assessment procedure, we have 88 research papers that enable us to evaluate MMML in detail. Our findings demonstrate that pre-trained models, such as BERT for text and ResNet for images, are predominantly employed for feature extraction due to their robust performance in diverse applications. Fusion techniques, ranging from simple concatenation to advanced attention mechanisms, are extensively adopted to enhance the representation of multimodal data. Despite these advancements, MMML models face significant challenges, including handling noisy data, optimizing dataset size, and ensuring robustness against adversarial attacks. Our findings highlight the necessity for further research to address these challenges, particularly in developing methods to improve the robustness of MMML models.

Insulin resistance and metabolic syndrome as a risk factor for Alzheimer's Disease: systematic literature review

Introduction: It is estimated that worldwide, 65.7 million people will live with the disease in 2030, with Alzheimer's disease being the most prevalent in the world, accounting for 60% of dementia cases. The hypothesis was then raised that through the neuroprotective effect of insulin and insulin resistance in the genesis of Metabolic Syndrome, the hypothetical relationship is made that metabolic syndrome is a risk factor for Alzheimer's disease. Objective: The literature that verifies the impact of vitamin D deficiency on the quality of life of individuals undergoing bariatric surgery was reviewed. Methods: The search strategy was carried out in the virtual databases PubMed, Scielo, LILACS, Scopus, Web of Science, Embase, and Biblioteca Virtual em Saúde, in addition to gray literature such as Google Scholar, OpenGrey, Ibict/BDTD (Brazilian digital library of theses and dissertations) and ProQuest using the Medical Subject Headings (MeSH) and Health Sciences Descriptors (DeCS) descriptors with the Boolean logical operators AND, OR and NOT. The studies considered eligible were those that presented metabolic syndrome as a risk factor for the development of Alzheimer's disease. Results: The online search found 216 studies in virtual bibliographic databases and 70 in gray literature. After removing duplicates, 282 articles remained and were read the title and abstract, with 25 articles chosen for full-text reading, leaving 13 that met the inclusion criteria. Most of the studies included corroborated the hypothesis that metabolic syndrome is a risk factor for Alzheimer's disease. Even the two studies that provide some results in which BMI showed a slower decline in cognitive function, stated that the phenotype studied was that of metabolically healthy obese individuals. Conclusion: The results of this study confirmed the idea that there is an interaction between metabolic health and brain health. First, chronic inflammation and oxidative stress associated with metabolic syndrome can cause damage to blood vessels, compromising cerebral blood flow and impairing the supply of essential nutrients to the brain. Additionally, insulin resistance, one of the key components of metabolic syndrome, can hurt brain function by interfering with the absorption of glucose, a vital fuel for the brain. Finally, how changes in blood lipid levels can contribute to the accumulation of beta-amyloid protein plaques in the brain, one of the markers of Alzheimer's disease.

ROLE OF ACADEMIC LIBRARIES AND INFORMATION SERVICES: A STUDY

Role of academic libraries serve an important role in helping students, teachers, and staff with their academic and research needs. They provide a variety of services and resources to promote learning, teaching, and scholarship, including as access to scholarly databases, e-books, print collections, study spaces, and instructional support. In recent years, college libraries have also expanded their digital collections and services to meet the changing needs of users in the age of digital information. This paper explores how librarians must constantly evaluate and adapt their services to meet the changing demands of their users in order to ensure the success of college libraries. This includes creating user-friendly interfaces for accessing and using library materials, giving personalised guidance and support, and establishing creative programmes to improve the learning experience. As higher education institutions continue to evolve, college libraries will remain a vital resource for supporting academic success and lifelong learning.

Triglyceride glucose index as a predictor for non-alcoholic fatty liver disease: insights from a longitudinal analysis in non-obese individuals.

A substantial portion of non-obese population is afflicted with Non-alcoholic Fatty Liver Disease (NAFLD). The Triglyceride Glucose (TyG) index, a quantifier of insulin resistance magnitude, is determined by the product of fasting plasma glucose and triglyceride concentrations. The relationship between the TyG index and NAFLD within this cohort remains ambiguous. We conducted a retrospective analysis utilizing datasets acquired from the Dryad digital repository. Non-obese participants (BMI < 25 kg/m2) were enrolled at the Wenzhou Medical Center of Wenzhou People's Hospital between January 2010 and December 2014. Demographic information and biochemical parameters were systematically compiled, and the diagnosis of NAFLD was established through ultrasonographic evidence. This study cohort included 16,172 non-obese participants with a 5-year follow-up, among whom 2,322 (14.36%) developed NAFLD. The disparity between TyG index quartiles in the accumulative incidence of new-onset NAFLD was distinct, with an increasing risk of new-onset NAFLD as the TyG index increased. Participants in highest quartile exhibited the maximum risk of NAFLD. In the fully adjusted model 3, the hazard ratios for NAFLD in Q2, Q3, and Q4 were 2.15 (1.62, 2.87), 2.89 (2.20, 3.80) and 4.58 (3.48, 6.02), respectively. Meanwhile, the TyG index and NAFLD risk showed a highly significant overall correlation (p < 0.0001) and nonlinearity (p < 0.0001) according to the limited cubic splines. In subgroup analysis, a significant interaction was noted between new-onset NAFLD and SBP (<140 mmHg vs. ≥140 mmHg; P for interaction = 0.0114). The SBP < 140 mmHg subgroup demonstrated an enhanced TyG index influence on NAFLD risk (HR = 2.83, 95% CI: 2.48-3.23, p < 0.0001). The TyG index serves as a straightforward instrument for assessing NAFLD risk in non-obese individuals, enabling prompt identification and management in this population segment.

The Effects of Osteopathic Manipulative Treatment on Brain Activity: A Scoping Review of MRI and EEG Studies.

Osteopathic manipulative treatment (OMT) is a hands-on therapy aiming to achieve the global homeostasis of the patient. OMT focuses on treating the somatic dysfunctions characterized by tissue modifications, body asymmetry, and range-of-motion restrictions. The benefits related to OMT are thought to be associated with the interconnectedness of the body's systems and the inherent capacity for self-healing. However, whether OMT can influence brain activity, and, consequently, neurophysiological responses is an open research question. Our research investigates the literature to identify the effects of OMT on brain activity. The main purpose of the research question is: can OMT influence brain activity and consequently neurophysiological responses? A scoping review was conducted, searching the following databases: PubMed, Google Scholar, and OSTEOMED.DR (Osteopathic Medical Digital Repository), Scopus, Web of Science (WoS), and Science Direct. The initial search returned 114 articles, and after removing duplicates, 69 were considered eligible to be included in the final sample. In the end, eight studies (six randomized controlled trials, one pilot study, and one cross-over study) were finally included and analyzed in this review. In conclusion, OMT seems to have a role in influencing functional changes in brain activity in healthy individuals and even more in patients with chronic musculoskeletal pain. However, further RCT studies are needed to confirm these findings. Registration protocol: CRD42024525390.

COMPUTER PRODUCTION OF FACIAL EPITHETS

BACKGROUND: The issue of rehabilitation of patients with facial defects is extremely acute. In addition to the annual increase in the number of patients with cancer of the maxillofacial region, in recent years the number of people with shrapnel and gunshot wounds to the face has increased as a result of local wars and conflicts. Traditional methods of orthopedic rehabilitation of patients and the manufacture of facial epitheses are quite a complex and lengthy process. In the postoperative period, there is a sharp decrease in the quality of life of this category of patients, a violation of the basic body functions necessary for vital activity and poor social adaptation. Direct prosthetics of the face in the postoperative period was impossible due to the lack of necessary digital modeling technologies and structural materials for additive or subtractive production methods. The production of temporary or permanent facial epitheses using digital technologies is an urgent task that can improve the social and functional living conditions of patients. AIMS: Development of 3D modeling technology for additive manufacturing of facial epithets. METHODS: To achieve this goal, the first task was to develop specialized three-dimensional software for modeling defects in the facial area. The functionality of the program should allow you to virtually simulate the missing parts of the face (ear, eye, nose, orbit). To create a digital platform together with IT specialists, it was decided to use the following programming languages: C++ - Writing the software core, writing UI/UX interaction modules, interacting with the Windows operating system; C# - Complex assembly of the entire project; Python is an automated assembly of virtual library modules; OpenGL HSLS is a shader language for graphical visualization of objects; C is the creation of functions for interacting with shaders that require high speed. RESULTS: A specialized computer program has been developed for 3D modeling of prostheses in patients with defects in the middle zone of the face using combined facial scanning and computed tomography data (Computer program. Apresyan S.V., Stepanov A.G. "A program for 3D modeling of facial epitheses. Registration number (certificate) 2023663490, Registration date: 07/04/2023). Instead of obtaining analog impressions with plaster or silicone material, the developed technology uses a special 3D facial scanner, which greatly eases the suffering of patients. A virtual three-dimensional database of ears, noses, orbits, and zygomatic bones of patients of various ages and gender is integrated into the developed program. This allows the specialist to select the most adaptive part of the face to make up for the defect. Built-in modeling tools allow you to personalize a 3D model of a part of the face, based on the structural features of the maxillofacial region of a person. The finished three-dimensional model of a part of the face can be exported in various formats CONCLUSIONS: The developed 3D program for modeling defects allows to avoid invasive prosthetics approaches, to coordinate the shape of future structures with the patient. The built-in library of structures with a database provides remote manufacturing of the prosthesis without the presence of the patient, in case of a need to replace it. Among the undeniable advantages of the technology, it is important to include the fact that prostheses can be made directly on the day of surgery to remove part of the face, completely restoring lost functions and providing rapid social adaptation.

Interprofessional clinical reasoning education.

Clinical reasoning is considered one of the most important competencies but is not included in most healthcare curricula. The number and diversity of patient encounters arethe decisive factors in the development of clinical reasoning competence. Physical real patient encounters are considered optimal, but virtual patient cases also promote clinical reasoning. A high-volume, low-fidelity virtual patient library thus can support clinical reasoning training in a safe environment and can be tailored to the needs of learners from different health care professions. It may also stimulate interprofessional understanding and team shared decisions. Implementation will be challenged by tradition, the lack of educator competence and prior experience as well as the high-density curricula at medical and veterinary schools and will need explicit address from curriculum managers and education leads.

Serial Transverse Enteroplasty (STEP) versus Longitudinal Intestinal Lengthening and Tailoring (LILT): Systematic Review and Meta-Analysis of Outcomes and Complications

Abstract Background The prevalence of SBS is 3-4 per million. It occurs in about 15% of adult patients who undergo intestinal resection, with 3/4th of these cases resulting from massive intestinal resection and 1/4th from multiple sequential resections. About 70% of patients in whom SBS develops are discharged from the hospital and a similar percentage remain alive a year later. This improved survival rate has been achieved primarily by the ability to deliver long-term nutritional support. Objective To compare between Serial Transverse Enteroplasty (STEP) and Longitudinal Intestinal Lengthening and Tailoring (LILT) in the incidence of complications and clinical prognosis regarding morbidity and mortality in patients with Short Bowel Syndrome (SBS). Patients and Methods The search was carried out using the electronic national library of medicine PubMed database, Cochrane library and manual reference of articles published on serial transverse enteroplasty (STEP) versus longitudinal intestinal lengthening and tailoring (LILT) in management of patients with SBS. Conclusive search was done and duplicate studies were excluded. Data Sources Medline databases (PubMed, Medscape, ScienceDirect. EMF-Portal) and all materials available on the Internet till 2022. Results LILT and STEP are both valuable treatment strategies used in the management of pediatric SBS. However, currently, it is not possible to advise surgeons on accurate patient selection and to predict the result of either intervention. There is very limited published data on bowel lengthening procedure exclusively in adults. Most reported series exclusively or predominantly discuss the pediatric population with some adults included in one series and two additional single case reports. Conclusion Both STEP and LILT are potentially safe and effective methods for the treatment of SBS, under the conditions that the surgical techniques required have been mastered and the indications for surgery are observed. This review should be a gateway to open the scope on the field of Autologous Intestinal Reconstruction Surgeries (AIRS) and plan for a more detailed prospective studies with close monitoring of the data regarding outcomes, complications and follow up.

Cognitive intelligence-enabled requirements elicitation for design optimisation of smart product-service system

The rapid development of advanced technologies provides futuristic option to enhance product value with digital services, which the concept of Smart Product-Service System (SPSS) was proposed. SPSS focuses on usage data, the whole lifecycle, and the iterative optimisation. A large amount of data and context information can be collected during the usage stage, which can be used to elicit requirements to guide further design. How to realise the requirement elicitation with cognitive intelligence based on usage data is the key step for design optimisation. Therefore, this research proposes a cognitive intelligence-enabled requirements elicitation framework to help designers promote the design optimisation process. First, the digital twin-driven data collection architecture of SPSS is proposed by considering multi-sources and multi-stages. Second, the behaviour of SPSS is modelled based on Auto-Encoder which is constructed using deep learning to cognise SPSS performance. Third, the corresponding behaviour model is interpreted based on Shapley Addictive exPlanations (SHAP) to discover key factors with cognitive intelligence. Finally, the domain knowledge graph is used to generate the optimisation requirements for further design. To demonstrate the feasibility and advantages of the proposed framework, this study adopts the case study of wind turbines for illustration and verification.

Multiple biliary micro-hamartomas diagnosed in an unsuspecting elderly patient

BACKGROUND AND AIM: Multiple biliary hamartomas are a benign incidental finding in the hepatic context. Recognizing them is not easy if one has never seen them and does not have access to the right imagery. The aim of the study is to expand the radiologist's digital image library, enabling a quick and precise differential diagnosis. Indeed, multiple biliary hamartomas can be challenging to differentiate from other liver lesions based on imaging alone. This case highlights the importance of thorough radiological assessment and the need for a multidisciplinary approach, involving radiologists, hepatologists, and pathologists, to ensure a precise diagnosis. METHODS: The patient in the study presented at the hospital for a CT scan and after an abdominal MRI recommended by his general practitioner to assess the biliary tree (Magnetic Resonance Cholangiopancreatography, MRCP) due to persistent abdominal pain. They had never undergone an abdominal MRI before in their life. The discovery of hepatic lesions was incidental and unexpected RESULTS: The MRI investigation revealed multiple benign lesions in both hepatic lobes compatible with the von Meyenburg complex. These lesions are multiple hamartomas and behave differently in all MRI sequences. CONCLUSIONS: The images acquired with the different MRI sequences were carefully examined. Despite being multiple and scattered throughout the liver, the lesions appeared immediately benign and consistent with the incidental diagnosis of multiple biliary hamartomas. Medical practitioners should be aware of the existence of multiple biliary hamartomas and consider them in the differential diagnosis when patients present with hepatic abnormalities. This knowledge can prevent unnecessary interventions and guide appropriate patient management.

Untangling Indian Hemp: Identifying Woodlands Bast Fibers in Collections

ABSTRACT Many textiles produced by Native American Woodlands cultures are made from bast (phloem) fibers from North American plants. While bast fibers are easy to identify with microscopy, determining the exact species has long been a challenge. Historically, bast fibers from Native American communities have been referred to as “Indian hemp,” a confusing term at best. This project undertaken as part of an Andrew W. Mellon Fellowship at the National Museum of the American Indian (NMAI) focused on a combined approach by working with both community members and scientists to provide a cultural background for these important fibers as well as useful diagnostic tools for identification. Both macroscopic and microscopic characteristics were examined including color, feel, microfibrillar orientation, crystal species, and cross section analysis. A physical and digital reference collection was created for comparison. Eight fiber samples taken from six historic objects in NMAI’s collection were then examined to test effectiveness of bast fiber identification protocol. Results from this study confirm there continues to be limited success when identifying the exact bast fiber species in historic artifacts because of small sample size and aging characteristics.

Fostering Artificial Intelligence-based supports for informal caregivers: a systematic review of the literature

Informal or unpaid caregivers, commonly known as family caregivers, are responsible for providing the 80% of long-term care in Europe, which constitutes a significant portion of health and social care services offered to elderly or disabled individuals. However, the demand for informal care among the elderly is expected to outnumber available supply by 2060. The increasing decline in the caregiver-to-patient ratio is expected to lead to a substantial expansion in the integration of intelligent assistance within general care. The aim of this systematic review was to thoroughly investigate the most recent advancements in AI-enabled technologies, as well as those encompassed within the broader category of assistive technology (AT), which are designed with the primary or secondary goal to assist informal carers. The review sought to identify the specific needs that these technologies fulfill in the caregiver’s activities related to the care of older individuals, the identification of caregivers’ needs domains that are currently neglected by the existing AI-supporting technologies and ATs, as well as shedding light on the informal caregiver groups that are primarily targeted by those currently available. Three databases (Scopus, IEEE Xplore, ACM Digital Libraries) were searched. The search yielded 1002 articles, with 24 articles that met the inclusion and exclusion criteria. Our results showed that AI-powered technologies significantly facilitate ambient assisted living (AAL) applications, wherein the integration of home sensors serves to improve remote monitoring for informal caregivers. Additionally, AI solutions contribute to improve care coordination between formal and informal caregivers, that could lead to advanced telehealth assistance. However, limited research on assistive technologies like robots and mHealth apps suggests further exploration. Future AI-based solutions and assistive technologies (ATs) may benefit from a more targeted approach to appeasing specific user groups based on their informal care type. Potential areas for future research also include the integration of novel methodological approaches to improve the screening process of conventional systematic reviews through the automation of tasks using AI-powered technologies based on active learning approach.

The use of natural language processing for the identification of ageing syndromes including sarcopenia, frailty and falls in electronic healthcare records: a systematic review.

Recording and coding of ageing syndromes in hospital records is known to be suboptimal. Natural Language Processing algorithms may be useful to identify diagnoses in electronic healthcare records to improve the recording and coding of these ageing syndromes, but the feasibility and diagnostic accuracy of such algorithms are unclear. We conducted a systematic review according to a predefined protocol and in line with Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Searches were run from the inception of each database to the end of September 2023 in PubMed, Medline, Embase, CINAHL, ACM digital library, IEEE Xplore and Scopus. Eligible studies were identified via independent review of search results by two coauthors and data extracted from each study to identify the computational method, source of text, testing strategy and performance metrics. Data were synthesised narratively by ageing syndrome and computational method in line with the Studies Without Meta-analysis guidelines. From 1030 titles screened, 22 studies were eligible for inclusion. One study focussed on identifying sarcopenia, one frailty, twelve falls, five delirium, five dementia and four incontinence. Sensitivity (57.1%-100%) of algorithms compared with a reference standard was reported in 20 studies, and specificity (84.0%-100%) was reported in only 12 studies. Study design quality was variable with results relevant to diagnostic accuracy not always reported, and few studies undertaking external validation of algorithms. Current evidence suggests that Natural Language Processing algorithms can identify ageing syndromes in electronic health records. However, algorithms require testing in rigorously designed diagnostic accuracy studies with appropriate metrics reported.

Co-designing with library stakeholders: building a national virtual library

Co-designing with library stakeholders: building a national virtual library

Compounds from Natural Products Candidates to Drug for Chikungunya Virus Infection: A Systematic Review

Introduction: Chikungunya fever is a disease caused by infection with the Chikungunya virus, transmitted by Aedes aegypti and Aedes albopictus mosquitoes. Despite its self-limited character, more than 60% of patients have chronic recurrent arthralgia with debilitating pain that lasts for years. Aim: The objective of this review was to gather and analyze evidence from the literature on potential therapeutic strategies with molecules from natural products for the treatment of Chikungunya fever. Methods: A search was performed for clinical trials, observational studies, in vitro or in vivo, without restriction of the year of publication or language in electronic databases (Medline/PubMed, EMBASE, Google Scholar, The Cochrane Library, LILACS (BVS), clinical trial registries (Clinical Trials.gov), digital libraries from CAPES theses and dissertations (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil) and conference abstracts. A quality assessment of the selected studies was performed using the SYRCLE, RoB2 and SciRAP tools. Results: 42 studies were included, which showed molecules with potential antiviral pharmacological activity or with activity in reducing the joint complications caused by CHIKV infection. Conclusions: Among the molecules found in the survey of references, regarding the class of secondary metabolites, flavonoids stood out and for this reason, the molecules may be promising candidates for future clinical trials. Overall, evidence from in vitro studies was of acceptable quality; in vivo and intervention studies showed a high risk of bias, which is a limitation of these studies.

The Variables Associated with Burnout Among Korean Early Childhood Teachers: A Meta-Analysis

Researchers have done a great deal of research on the variables associated with early childhood teacher burnout, but the findings are numerous and inconsistent. Therefore, this study explored the variables most associated with burnout among early childhood teachers through meta-analysis. The National Assembly Electronic Library in Korea, Riss, the National Electronic Library, and DBpia databases were all thoroughly searched by researchers. Strict inclusion criteria resulted in the inclusion of 201 studies, and 35 variables total—divided into 5 variable groups—were analyzed. The results showed that the most correlated variable group with burnout was the psychological personality protective variable, and the largest effect size variables among the variable groups were age ( r = −.3052), resilience ( r = −.5415), calling ( r = −.526), turnover intention ( r = .5021), and interpersonal relationships ( r = −.4552). However, the variables in the psychological personality risk variable were not statistically significant. Although more thorough validation by follow-up studies is still required, these findings offer a more scientific data reference for the prevention and improvement of burnout among early childhood teachers in Korea and suggest a direction for future research.

The Attitudes of Some Media Instructors Towards Electronic Publishing Platforms During (December 2021 – 2022)

E_ publishing is considered one of the essential results of information technology because it helps improve scientific research. That is what makes me study electronic publishing, according to university teachers, especially those in the media field, because they are still on their way to learning. At the same time, they also need more knowledge as this field demands. That can be achieved by sharing knowledge and experience with other teachers and people from different cultures, countries, and experiences. Nowadays, all university teachers publish their scientific studies in e-magazines, which is an advantage of knowledge. Through the analysis, we will learn more about electronic publishing according to some specialists in communication sciences because many universities have begun to use electronic libraries. The study focuses on the importance of using the Internet in keeping scientific research, the significant role of electronic publishing in improving, to what extent learners and teachers can depend on electronic resources, and how to make it a helpful source of learning. It is a descriptive study. The author uses survey methods through university teachers. The study finds that 78% of researchers have their studies published online. 66% agree that e-publishing doesn’t affect the publishers. The study advises asking all university teachers to do their work and studies in electronic copies. This makes teachers more active and enables them to enlarge their knowledge about technological development in learning fields and create training courses and sessions to improve this. And keep those electronic lectures for use when needed. Keywords: Attitudes, Platforms, Electronic Publishing.