Work-life balance: A landscape mapping of two decades of scholarly research.

Work-life balance has gained increasing popularity among scholars and practitioners since the beginning of the century. Despite significant attempts to consolidate this burgeoning field, the scholarly knowledge on work-life balance research remains fragmented and detached due to extant number of publications in the area and the mostly subjective approaches used to encapsulate the literature. As such, the current study presents an objective overview of work-life balance research between 2000 and 2020. Using bibliometric techniques, the authors examined 1190 articles indexed in Scopus database to identify the conceptual structure and current dynamics in the field. During the critical period between the reconceptualization of word-life balance and the emergence of COVID-19 pandemic, the findings reveal that the field was growing exponentially as a multidisciplinary research area. Most of the scholarly work originated in the US, UK, and Australia with a "locally-centralized-globally-discrete" collaboration pattern among scholars. The most relevant and developed research themes included, in addition to work-life balance, topics related to gender and family life. Furthermore, new emerging research directions had evolved beyond the traditional constructs including job security, flexible working hours, individual productivity, and work-life conflicts. The study contributes to the current knowledge on work-life balance by providing critical insights into the evolution of the field and offers potential avenues for scholars who are interested in this critical research domain and the changes it has experienced post pandemic.

Physical Reservoir Computing Using van der Waals Ferroelectrics for Acoustic Keyword Spotting.

Acoustic keyword spotting (KWS) plays a pivotal role in the voice-activated systems of artificial intelligence (AI), allowing for hands-free interactions between humans and smart devices through information retrieval of the voice commands. The cloud computing technology integrated with the artificial neural networks has been employed to execute the KWS tasks, which however suffers from propagation delay and the risk of privacy breach. Here, we report a single-node reservoir computing (RC) system based on the CuInP2S6 (CIPS)/graphene heterostructure planar device for implementing the KWS task with low computation cost. Through deliberately tuning the Schottky barrier height at the ferroelectric CIPS interfaces for the thermionic injection and transport of the electrons, the typical nonlinear current response and fading memory characteristics are achieved in the device. Additionally, the device exhibits diverse synaptic plasticity with an excellent separation capability of the temporal information. We construct a RC system through employing the ferroelectric device as the physical node to spot the acoustic keywords, i.e., the natural numbers from 1 to 9 based on simulation, in which the system demonstrates outstanding performance with high accuracy rate (>94.6%) and recall rate (>92.0%). Our work promises physical RC in single-node configuration as a prospective computing platform to process the acoustic keywords, promoting its applications in the artificial auditory system at the edge.

Overcoming challenges in nursing disaster preparedness and response: an umbrella review.

Disaster nursing plays a vital role in addressing the health needs of vulnerable populations affected by large scale emergencies. However, disaster nursing faces numerous challenges, including preparedness, logistics, education, ethics, recovery and legalities. To enhance healthcare system effectiveness during crises, it is essential to overcome these issues. This umbrella review, conducted using the Joanna Briggs Institute (JBI) methodology, synthesizes data from 24 studies to identify key strategies for improving disaster nursing. The review highlights nine key themes: Education and Training, Research and Development, Policy and Organizational Support, Technological Advancements, Psychological Preparedness and Support, Assessment and Evaluation, Role-Specific Preparedness, Interprofessional Collaboration and Cultural Competence, and Ethics and Decision-Making. The review emphasizes the importance of education, technological advancements, psychological support, and interprofessional collaboration in bolstering disaster nursing preparedness and response efforts. These elements are crucial for enhancing patient outcomes during emergencies and contributing to a more resilient healthcare system. This comprehensive analysis provides valuable insights into the various aspects essential for enhancing disaster nursing. By implementing evidence-based strategies within these nine themes, the nursing profession can enhance its capacity to effectively manage and respond to the complex needs of disaster-affected populations, ultimately improving patient care and outcomes during emergencies.

Anti-Angiogenic and Anti-Proliferative Activity of 4-2-(5-bromo-1H-indol-2-carbonyl)-N-(4-methoxyphenyl) Hydrazine-1-carbothioamide: Ex-vivo and in vitro Study.

Angiogenesis, the formation of new blood vessels, stimulates tumor growth and spread by delivering oxygen and nutrients, and is a key component of metastasis. This work aimed to evaluate the anti-angiogenic properties of a new synthesized compound. Rat aorta angiogenesis assay was used to evaluate the ability of the carbothioamide derivative to inhibit blood vessels sprouting. The tetrazolium (MTT) assay was used to evaluate the anti-proliferative effect of the synthetic compound on human umbilical vein endothelial cell line (HUVECs) and A549 lung cancer cells line. The (2, 2-diphenyl-1-picrylhydrazyl) DPPH was used to investigate the free radical scavenging action. The study showed that the compound has anti-angiogenic activity with IC50 56.9 µg/mL, moreover the compound managed to inhibit the proliferation of HUVECs and A549 cells (IC50 76.3 µg/mL and 45.5 µg/mL, respectively), and The IC50 concentration for free radical scavenging activity of the compound was 27.8 µg/ml. The study concluded that the compound has significant anti-angiogenic activity may be related to its significant anti-proliferative effect against HUVECs, these pharmacological effect may attributed to its potent free radical scavenging activity.

Barriers and Facilitators to Youth Decision-Making Involvement in Families Referred for Stem Cell Transplant.

Youth prefer to be involved in treatment decisions, yet youth participation is minimally present in decisions like stem cell transplant (SCT) that require frequent medications and social isolation to be successful in curing cancer and chronic illness. The purpose of our study is to identify the barriers and facilitators to youth decision-making involvement in the youth-parent interaction when referred for treatment with SCT. We report qualitative findings from our theory-driven mixed-methods study. We thematically analyzed our field notes of youth and parent observations and audio-recordings during SCT consultations and semi-structured interviews. Data were collected from 10 youth, 8 to 16 (median 12) years of age, and their parents (n = 20). Three themes emerged: (a) Reluctant unless motivated, (b) Uncertain but capable, and (c) Limited unless supported. Our findings emphasize the critical role parents may take in facilitating youth involvement in decisions.

The Effectiveness of On-Demand Health Education Systems in Assisting the Nursing Workload.

This article explores the "On-Demand Health Education System" in healthcare, highlighting its role in enhancing nursing efficiency and quality. Using a database, it allows nurses to provide tailored education via QR codes for patients and families. Key findings show its positive impact on education quality and efficiency, though improvements are needed in user interface and accessibility for certain groups like the elderly. Future enhancements should focus on user experience and expanding accessibility, acknowledging the potential of such systems in medical education with technological advancement.

Liquid biopsy as a tool for KRAS/NRAS/BRAF baseline testing in metastatic colorectal cancer.

BACKGROUND: The absence of KRAS and NRAS gene mutations (RAS wild type) in metastatic colorectal cancer (mCRC), is associated with a good response to targeted therapy with anti-EGFR receptor antibodies. The current gold standard for RAS mutational status identification is genetic testing on tissue biopsy samples. OBJECTIVE: This study aimed to assess the relevance of liquid biopsy as a less invasive alternative to tissue biopsy for detecting KRAS/NRAS and BRAF mutations in patients with metastatic colorectal cancer (mCRC). The study also aimed to determine the concordance between liquid biopsy and tissue biopsy. METHODS: This is a phase IV, observational, uncontrolled, non-comparative, non-randomized, open label study. RAS/BRAF status will be tested at baseline using tissue and liquid biopsy using the Idylla/Biocartis PCR-based device. The primary endpoint is the comparison of the RAS status based on liquid biopsy with the RAS status based on tissue biopsy. RESULTS: 100 patients with mCRC were included in the study. 75% of patients showed concordant results between liquid biopsy and tissue biopsy, while 25% had discordant results. Liquid biopsy demonstrated a sensitivity of 62% and a specificity of 93%. The accuracy of liquid biopsy was 75%, with a moderate agreement between the two tests. The most frequent mutations in concordant cases were in KRAS (41%), followed by NRAS (4%) and BRAF (3%). Mutations were not detected in 42% of tissue biopsy samples and 60% of liquid biopsy samples. The presence of hepatic metastases did not significantly affect the concordance between the biopsy methods. CONCLUSION: Liquid biopsy using the Idylla™ system showed a relatively low sensitivity but high specificity for detecting KRAS/NRAS and BRAF mutations in mCRC patients. Despite some discordant cases, liquid biopsy remains a promising alternative to tissue biopsy due to its non-invasiveness, ability to provide multiple samples, and better representation of tumor heterogeneity.

Multi-view graph-based interview representation to improve depression level estimation.

Depression is a serious mental illness that affects millions worldwide and consequently has attracted considerable research interest in recent years. Within the field of automated depression estimation, most researchers focus on neural network architectures while ignoring other research directions. Within this paper, we explore an alternate approach and study the impact of input representations on the learning ability of the models. In particular, we work with graph-based representations to highlight different aspects of input transcripts, both at the interview and corpus levels. We use sentence similarity graphs and keyword correlation graphs to exemplify the advantages of graphical representations over sequential models for binary classification problems within depression estimation. Additionally, we design multi-view architectures that split interview transcripts into question and answer views in order to take into account dialogue structure. Our experiments show the benefits of multi-view based graphical input encodings over sequential models and provide new state-of-the-art results for binary classification on the gold standard DAIC-WOZ dataset. Further analysis establishes our method as a means for generating meaningful insights and visual summaries of interview transcripts that can be used by medical professionals.

Analysis of human ABO Blood Group as a risk factor with knee osteoarthritis at tertiary care hospital in Pakistan.

Objective: To investigate the association and risk estimation of ABO blood group distribution and clinical attributes in patients with Knee Osteoarthritis. Method: This was a hospital-based study conducted at, Liaquat University Hospital Hyderabad from December, 2019 to December, 2022 to investigate this least researched area of highly prevalent musculoskeletal disease in Pakistan. Non-Probability Convenience Sampling was used for selecting 190 cases of confirm Knee Osteoarthritis patients diagnosed by Orthopedic surgeon based on standard clinical and radiographic criteria. Data were analyzed using IBM-SPSS version 23.0. Percentages and frequencies were counted for categorical data. Pearson Chi Square test and fisher's exact test were used to check the association and Multinomial Logistic Regression was used to estimate the risk for moderate and severe kellgren grading Knee Osteoarthritis (KOA) cases with ABO blood grouping in comparison of mild Kellgren grading. Results: A total of 190 cases of Knee Osteoarthritis (KOA) were included in the study. Females (61.6%) and patients with age 50 and above were 40.5 % were found in greater proportion. Majority (41.6%) were classified radiologically as mild cases with O group (39.5%) and positive Rh antigen (95.8%). Strong association (p = <0.01) was found between gender, age group and ABO blood group with KOA radiological Kellgren and Lawrence score. Conclusion: There is strong relation in between radiological grading of knee osteoarthritis severity and A blood group, gender and age.

Comprehensive Evaluation and Arthroscopic Management of Circumferential Labral Tears Following Traumatic First Time Shoulder Dislocation: A Case Report and Review.

Introduction: Pan-labral tears, commonly associated with recurrent shoulder dislocations, are a well-documented pathology. However, circumferential pan-labral tears following a first-time shoulder dislocation represent a rare and scarcely reported entity in the literature. Accurate diagnosis requires a comprehensive clinical history, physical examination, and further evaluation, often involving MRI. Even with advanced imaging, the acute nature of the injury can lead to the oversight of pan-labral tears, necessitating arthroscopic assessment for definitive diagnosis. Repairing such extensive glenoid labral tears presents a challenging task, requiring skilled surgeons to utilize accessory portals and percutaneous techniques for optimal visualization and anchor placement trajectory. To the best of our knowledge, this case report represents the first documentation of a pan-labral tear associated with a 1st-time shoulder dislocation. Case Report: A 27-year-old Asian male presented with pain and limited range of motion in the left shoulder following a single episode of anterior shoulder dislocation during cricket. Initial X-rays were unremarkable, but subsequent MRI revealed an anteroinferior labral tear with intact rotator cuffs. Arthroscopic evaluation disclosed a pan-labral tear, prompting meticulous repair under general and locoregional anesthesia. The patient achieved full recovery postoperatively. Conclusion: While pan-labral tears are typically linked to recurrent dislocations, this case underscores their occurrence in a 1st-time traumatic shoulder dislocation without overt clinical signs or fractures. Arthroscopic repair demands careful intraoperative planning to achieve optimal tensioning and alignment of labral and capsular tissues. This report contributes to the limited literature on pan-labral tears associated with initial shoulder dislocations, emphasizing the importance of arthroscopic evaluation for accurate diagnosis and successful repair.

Integrated Approach for Testing and Assessment for Developmental Neurotoxicity (DNT) to Prioritize Aromatic Organophosphorus Flame Retardants.

Organophosphorus flame retardants (OPFRs) are abundant and persistent in the environment but have limited toxicity information. Their similarity in structure to organophosphate pesticides presents great concern for developmental neurotoxicity (DNT). However, current in vivo testing is not suitable to provide DNT information on the amount of OPFRs that lack data. Over the past decade, an in vitro battery was developed to enhance DNT assessment, consisting of assays that evaluate cellular processes in neurodevelopment and function. In this study, behavioral data of small model organisms were also included. To assess if these assays provide sufficient mechanistic coverage to prioritize chemicals for further testing and/or identify hazards, an integrated approach to testing and assessment (IATA) was developed with additional information from the Integrated Chemical Environment (ICE) and the literature. Human biomonitoring and exposure data were identified and physiologically-based toxicokinetic models were applied to relate in vitro toxicity data to human exposure based on maximum plasma concentration. Eight OPFRs were evaluated, including aromatic OPFRs (triphenyl phosphate (TPHP), isopropylated phenyl phosphate (IPP), 2-ethylhexyl diphenyl phosphate (EHDP), tricresyl phosphate (TMPP), isodecyl diphenyl phosphate (IDDP), tert-butylphenyl diphenyl phosphate (BPDP)) and halogenated FRs ((Tris(1,3-dichloro-2-propyl) phosphate (TDCIPP), tris(2-chloroethyl) phosphate (TCEP)). Two representative brominated flame retardants (BFRs) (2,2'4,4'-tetrabromodiphenyl ether (BDE-47) and 3,3',5,5'-tetrabromobisphenol A (TBBPA)) with known DNT potential were selected for toxicity benchmarking. Data from the DNT battery indicate that the aromatic OPFRs have activity at similar concentrations as the BFRs and should therefore be evaluated further. However, these assays provide limited information on the mechanism of the compounds. By integrating information from ICE and the literature, endocrine disruption was identified as a potential mechanism. This IATA case study indicates that human exposure to some OPFRs could lead to a plasma concentration similar to those exerting in vitro activities, indicating potential concern for human health.

Investigation Into Novel Mukanadin B, Mukanadin D and Mukanadin F Derivatives as Antagonists of 5-HT1A Signalling.

Marine bromopyrrole alkaloids are a diverse family of natural products with a large array of biological applications. The mukanadin family is a group of molecules consisting of seven members (mukanadin A-G) that possess a range of biological activities. Inhibition of serotonergic signaling has been demonstrated by mukanadin B derivatives, presenting this chemical scaffold as a candidate for further SAR exploration. A library of thirteen novel mukanadin B and D derivatives with structural variation targeted at the pyrrole ring, central linker and hydantoin ring, were synthesized. These analogues were subsequently assessed for serotonergic antagonism, in addition to natural products, mukanadin B, D, F and 9-hydroxy mukanadin B. A collection of compounds exhibited significant 5-HT1A signaling, including five of the novel derivatives and two of the naturally occurring bromopyrroles, mukanadin B and F. Particular SAR information could be determined from these results, such as modification of the pyrrole ring being a well-tolerated strategy for improving serotonergic inhibition. Other changes to the pharmacophore led to significant reduction in activity such as saturation of the linker region, or no conclusive improvement in inhibitory activity such as a 9-OH group or replacement of the hydantoin ring with a triazole moiety.

A 70% Ethanol Neorhodomela munita Extract Attenuates RANKL-Induced Osteoclast Activation and H2O2-Induced Osteoblast Apoptosis In Vitro.

The rapid aging of the population worldwide presents a significant social and economic challenge, particularly due to osteoporotic fractures, primarily resulting from an imbalance between osteoclast-mediated bone resorption and osteoblast-mediated bone formation. While conventional therapies offer benefits, they also present limitations and a range of adverse effects. This study explores the protective impact of Neorhodomela munita ethanol extract (EN) on osteoporosis by modulating critical pathways in osteoclastogenesis and apoptosis. Raw264.7 cells and Saos-2 cells were used for in vitro osteoclast and osteoblast models, respectively. By utilizing various in vitro methods to detect osteoclast differentiation/activation and osteoblast death, it was demonstrated that the EN's potential to inhibit RANKL induced osteoclast formation and activation by targeting the MAPKs-NFATc1/c-Fos pathway and reducing H2O2-induced cell death through the downregulation of apoptotic signals. This study highlights the potential benefits of EN for osteoporosis and suggests that EN is a promising natural alternative to traditional treatments.

Educational technologies and elementary level education - A bibliometric review of scopus indexed journal articles.

This bibliometric study critically analyses 293 journal articles from the Scopus database, charting the trajectory of educational technology in primary and elementary education from 1986 to 2023. While limited to practical applications within primary or elementary contexts and excluding various scholarly work forms, the research unveils crucial insights. A significant uptick in publications during 2008-2016 and 2018-2023 highlights the growing importance and incorporation of digital technologies in early education. The analysis identifies recurrent themes like teacher education, game-based learning, and collaborative learning, pointing towards future research directions. The study also notes underexplored areas, including technology's role in specific subjects, ethical student engagement, gender and disability dynamics, and contributions from African contexts. It advocates for increased international collaboration, with a focus on partnerships with predominant Chinese institutions. Despite its limitations, this paper is foundational for future research, offering a roadmap for a nuanced understanding of technology's impact on young learners' educational experiences and outcomes globally.

Quadrivalent HPV vaccine effectiveness against cervical intraepithelial lesion grade 2 or worse in Norway: A registry-based study of 0,9 million Norwegian women.

In Norway, single cohort vaccination with quadrivalent HPV (qHPV) vaccine targeting 12-year-old girls took place from 2009-2016. In 2020, the oldest vaccinated cohort was 23 years old and had approached the age where risk of being diagnosed with cervical intraepithelial lesion grade 2 or worse (CIN2+) increases rapidly. The aim of this cohort study was to assess direct qHPV vaccine effectiveness (VE) against CIN2+ among Norwegian women aged 16-30 in 2007-2020. By using population-based health registries and individual-level data on vaccination status and potential subsequent CIN2+ incidence, we found 82% qHPV VE among women vaccinated before the age of 17.

Living review framework for better policy design and management of hazardous waste in Australia.

The significant increase in hazardous waste generation in Australia has led to the discussion over the incorporation of artificial intelligence into the hazardous waste management system. Recent studies explored the potential applications of artificial intelligence in various processes of managing waste. However, no study has examined the use of text mining in the hazardous waste management sector for the purpose of informing policymakers. This study developed a living review framework which applied supervised text classification and text mining techniques to extract knowledge using the domain literature data between 2022 and 2023. The framework employed statistical classification models trained using iterative training and the best model XGBoost achieved an F1 score of 0.87. Using a small set of 126 manually labelled global articles, XGBoost automatically predicted the labels of 678 Australian articles with high confidence. Then, keyword extraction and unsupervised topic modelling with Latent Dirichlet Allocation (LDA) were performed. Results indicated that there were 2 main research themes in Australian literature: (1) the key waste streams and (2) the resource recovery and recycling of waste. The implication of this framework would benefit the policymakers, researchers, and hazardous waste management organisations by serving as a real time guideline of the current key waste streams and research themes in the literature which allow robust knowledge to be applied to waste management and highlight where the gap in research remains.

Pros and cons of artificial intelligence implementation in diagnostic pathology.

The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.

Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis.

Digital twin technology has become increasingly popular and has revolutionized data integration and system modeling across various industries, such as manufacturing, energy, and healthcare. This study aims to explore the evolving research landscape of digital twins using Keyword Co-occurrence Network (KCN) analysis. We analyze metadata from 9639 peer-reviewed articles published between 2000 and 2023. The results unfold in two parts. The first part examines trends and keyword interconnection over time, and the second part maps sensing technology keywords to six application areas. This study reveals that research on digital twins is rapidly diversifying, with focused themes such as predictive and decision-making functions. Additionally, there is an emphasis on real-time data and point cloud technologies. The advent of federated learning and edge computing also highlights a shift toward distributed computation, prioritizing data privacy. This study confirms that digital twins have evolved into complex systems that can conduct predictive operations through advanced sensing technologies. The discussion also identifies challenges in sensor selection and empirical knowledge integration.

Graph neural networks for clinical risk prediction based on electronic health records: A survey.

OBJECTIVE: This study aims to comprehensively review the use of graph neural networks (GNNs) for clinical risk prediction based on electronic health records (EHRs). The primary goal is to provide an overview of the state-of-the-art of this subject, highlighting ongoing research efforts and identifying existing challenges in developing effective GNNs for improved prediction of clinical risks. METHODS: A search was conducted in the Scopus, PubMed, ACM Digital Library, and Embase databases to identify relevant English-language papers that used GNNs for clinical risk prediction based on EHR data. The study includes original research papers published between January 2009 and May 2023. RESULTS: Following the initial screening process, 50 articles were included in the data collection. A significant increase in publications from 2020 was observed, with most selected papers focusing on diagnosis prediction (n = 36). The study revealed that the graph attention network (GAT) (n = 19) was the most prevalent architecture, and MIMIC-III (n = 23) was the most common data resource. CONCLUSION: GNNs are relevant tools for predicting clinical risk by accounting for the relational aspects among medical events and entities and managing large volumes of EHR data. Future studies in this area may address challenges such as EHR data heterogeneity, multimodality, and model interpretability, aiming to develop more holistic GNN models that can produce more accurate predictions, be effectively implemented in clinical settings, and ultimately improve patient care.

Bibliometric insights into microalgae cultivation in wastewater: Trends and future prospects for biolipid production and environmental sustainability.

Cultivation of microalgae in wastewater stream has been extensively reported, especially for simultaneous production of biolipid and wastewater treatment process. This study aimed to derive the research trend and focus on biolipid production from microalgae cultivated in wastewater by using bibliometric approach. The search strategy used in Scopus database resulted in 1339 research articles from 1990 to November 2023. Majority of publications (46%) were affiliated to China and India, showing their predominance in this field. Keywords related to the center of attention included biodiesel, biofuel, biomass and nutrient removal. Meanwhile, keyword with recent publication year, indicating the emerging research trends, revolved around the cultivation techniques and application of the system. Co-culture involving more than one microalgae species, bacteria and yeast showed promising results, while addition of nanoparticles was also found to be beneficial. Increasing exploration on the application of microalgae for treatment of saline wastewater was also reported and the carbon fixation mechanism by microalgae has been widely investigated to promote less environmental impact. Future research on these topics were suggested based on the findings of the bibliometric analyses.