bluuebunny/crossref_metadata_2025_split huggingface dataset:
Empirical Evaluation of - LLM Performance Using K-S Test
Authors: Panta Sasikanth 
Published: July 2024

Abstract

This Research focuses on the novel empirical formulation of large language models which is an interface for scaling down repetitive tasks and back propagating the training dataset from text generation, network hierarchy, associative memory in linguistic dissemination and trained on set of information such as web and scientific literature, feedback score for prompting and building a loss function (Chain of thought) for accurate representation among validators and predictors of the model. This paper focuses on establishing the prompt deterministic function based on knowledge graphs . Models like GPT 4.0, Gemini 1.5 , Llama 2,3 , Anthropic etc. are evaluated using Kolmogorov Smirnov Test which address the bottlenecks of hallucination of prompts in large language models applications. So, Kolmogorov-Smirnov Test, is a non parametric statistical test to evaluate the benchmarks of a large language model application. Top Kolmogorov Tests are different during model training & safety of the model is ensured during benchmark assessment.
Factors associated with neurological manifestations in patients hospitalized with COVID-19 in a military hospital
Authors: BARDALES-RODRIGUEZ JOSE 
Published: July 2024

Abstract

Background: COVID-19 is a disease that affects mainly the respiratory system but can affect other systems, including the nervous system. The factors associated with neurological manifestations in patients with COVID-19 infection have been described in multiple studies. However, associated factors have not been explored in the military population.
Methods: An analytical cross-sectional study was carried out based on information from the medical records of patients hospitalized for COVID-19 during the 2020–2021 period. The variable of interest in the present study was the neurological manifestations presented by the patients during the acute stage of the disease. The factors evaluated were sociodemographic and clinical variables. Generalized linear models of the Poisson family with robust variance were used, with which crude prevalence ratios (cPRs) and adjusted prevalence ratios (aPRs) were calculated.
Results: Neurological manifestations were present in 49.2% of the patients, with headache (29.8%), myalgia (23.4%), and anosmia (9.68%) being the most frequent. High blood pressure was associated with neurological manifestations. Similarly, older adult patients were 1.84 times more likely to present with neurological manifestations (PR: 1.84; 95% CI: 1.08-3.13).
Conclusion: Hypertension and age greater than 60 years were associated with neurological manifestations. Longitudinal studies need to be conducted for possible causality.
Study of novel Zn-MOF-II modified polymeric membrane in wastewater treatment containing oily waste and humic acid (NOM)
Authors: Gawali Sapna , Gawali Ajay , Reddy Nagarjuna , Reddy P. Swapna , Dharaskar Swapnil , Khuntia Snigdha , Sinha Manish , Jampa Surendra Sasi Kumar 
Published: July 2024

ABSTRACT

The prime objective of the present work was to synthesise the polymeric membrane with Zn-MOF-II nanoparticles using the phase inversion method to purify oily wastewater and NOM. The dead-end filtration system was utilised to analyse the performance of fabricated membranes (without and with Zn-MOF-II), various feeds of 100 ppm concentration used, such as organic pollutants and oil effluent at 250 kPa and atmospheric temperature conditions. The following study involves the compaction factor, pure water flux, all mixed matrix membrane permeability, humic acid rejection, and oil–water emulsion rejection, contact angle, and liquid–liquid displacement porosimetry (LLDP). Scanning electron microscopy (SEM) and Fourier transforms infrared spectroscopy-attenuated total reflection (FTIR-ATR) goniometer were used to characterise the polymeric membranes. The FTIR-ATR spectra of the modified membrane exhibit a characteristic peak between 2,900 and 3,000 cm−1 associated with the presence of the –COOH group. The nanoparticles and polymer matrix were well compatible, as evidenced by SEM images of the polymeric membrane containing Zn-MOF-II nanoparticles. The maximum value of percentage rejection of oily wastewater (above 88.89%) and humic acid (above 86.88%) was obtained for the polymeric membrane containing Zn-MOF-II nanoparticles.
Groundwater modeling and estimation of the safe pumping rate for the sustainable use of groundwater resources in Kombolcha town, upper Borkena watershed, Ethiopia
Authors: Tsegawu Wasihun Deribe , Katebu Gurmu Deressa , Desta Shawl Abebe , Temtime Getnet Solomon , Ejigu Bezawit Tesfaye , Adamu Anteneh Yayeh , Amsie Ayalke Belete 
Published: July 2024

ABSTRACT
The rate of groundwater extraction is increasing due to population growth. Balancing pumping rates with natural recharge is necessary for sustainable use. The safe groundwater pumping rate was determined using the groundwater model ModelMuse. To determine the safe pumping rate, 39 borehole data points were gathered and adjusted for 4, 8, and 12 h of pumping scenarios for 50 years in a steady-state pumping condition. The recharge rates in the study area were calculated using four empirical approaches in addition to the water balance method. Of the four empirical methods, the water balance technique provided the most accurate estimates of groundwater recharge, with an estimated average recharge rate of 176.75 mm per year. The ModelMuse model water balance report demonstrated that there was positive storage for all boreholes to be pumped simultaneously under 4- and 8-h pumping rate scenarios, but that there would be a significant drawdown under 12-h pumping from the stress period of 2039–2065, and the summation of inflow and outflow would become negative, indicating that the withdrawal rate is greater than the recharge rate. Thus, the safe pumping rate for Borkena groundwater was calculated to be 975 L/s in 8-h pumping rate scenarios.
A CFD-based compartmental modelling approach for long-term dynamic simulation of water resource recovery facilities
Authors: Romay-Gainza A. , Elduayen-Echave B. , Hernández B. , Larraona G. S. , Arnau R. , Climent J. , Ayesa E. 
Published: July 2024

ABSTRACT

This article presents a methodology for compartmental model (CM) creation for long-term simulation of water resource recovery facilities (WRRFs). CMs are often focused on reproducing with a lower computational cost, previously simulated scenarios. In contrast, the methodology presented here can represent variable hydraulic conditions, based on the interpolation of data gathered from a set of computational fluid dynamics (CFD) simulations that reproduce representative hydraulic scenarios. This is achieved by modelling with bidirectional flows the exchange flows between fixed compartments, which are defined based on the geometry of the reactors. The resultant hydraulic surrogate model can be implemented in commercial water treatment software to solve biochemical kinetics. The methodology was applied to simulate in WEST®-DHI a WRRF in Vila-Real, Spain. In this contribution, the CM was validated with real plant data. The developed CM provided a quick response simulation with a high level of hydraulic and biochemical detail. This allowed observation of a spatial distribution of component concentration, which could help with sensor location or plant optimisation. The methodology presented here could also be a useful enabler of digital twins to be implemented in WRRF.
A dynamic compartmental model of a sequencing batch reactor (SBR) for biological phosphorus removal
Authors: Daneshgar Saba , Borzooei Sina , Debliek Lukas , Van Den Broeck Elias , Cornelissen Riet , de Langhe Piet , Piacezzi Cesare , Daza Miguel , Duchi Simon , Rehman Usman , Nopens Ingmar , Torfs Elena 
Published: July 2024

ABSTRACT
Bioreactors are usually modelled as continuous stirred tank reactors (CSTRs) or CSTRs connected in series (Tanks-In-Series configuration). In large systems with non-ideal mixing, such approaches do not sufficiently capture the complex hydrodynamics, leading to model inaccuracies due to the lumping of spatial gradients. Highly detailed computational fluid dynamics (CFD) models provide insight into complex hydrodynamics but are computationally too expensive for flow-sheet models and digital twin applications. A compartmental model (CM) can be a middle-ground by providing a more realistic representation of the hydrodynamics and still being computationally affordable. However, the hydrodynamics of a plant can be very different under varying flow conditions. Dynamic CMs can capture these changes in an elegant way. So far, the application of CMs has been limited mostly to continuous flow systems. In this study, a dynamic CM of a sequencing batch reactor (SBR) is developed for a bio-P removal process. The SBR comes with challenges for CM development due to its distinct operational stages. The dynamic CM shows significant improvements over the CSTR model (using the same biokinetic parameters) for dissolved oxygen and phosphate predictions reducing the need for model recalibration that can lead to over-fitting and limited extrapolation capability of the model.
Inversión en investigación y desarrollo y fluctuaciones macroeconómicas: un modelo de equilibrio general para una economía pequeña y abierta
Authors: Sanchez Tapia William Richard 
Published: July 2024

Se construye un modelo de Ciclos Económicos Reales que incorpora un sector generador de Investigación y Desarrollo (I+D) a nivel de productos, con el fin de evaluar la importancia cuantitativa de ese sector en la dinámica macroeconómica de una economía pequeña y abierta como la peruana. Se encuentra que un sector innovador eficiente a nivel de productos juega un rol importante como “escudo” de la economía ante choques exógenos y es amplificador de la dinámica macroeconómica ante políticas de I+D. Así, el sector I+D logra reducir el impacto inicial sobre el crecimiento económico de un choque interno negativo en 0.6 puntos porcentuales y de un choque externo negativo en casi 2 puntos porcentuales respecto al caso en que no hay un sector I+D. Asimismo, un aumento del 1 por ciento en la innovación a nivel de productos (más variedades de productos en la economía) genera un mayor crecimiento del Producto Bruto Interno (PBI) en 0.35 puntos porcentuales, un incremento en el crecimiento del empleo en 0.20 puntos porcentuales y un aumento en el crecimiento de la productividad de la economía en 0.90 puntos porcentuales.
Social Media Programs for Outreach and Recruitment Supporting Aging and Alzheimer Disease and Related Dementias Research: Longitudinal Descriptive Study
Authors: Teano Anthony L , Scott Ashley , Gipson Cassandra , Albert Marilyn , Pettigrew Corinne 
Published: July 2024

Background
Social media may be a useful method for research centers to deliver health messages, increase their visibility in the local community, and recruit study participants. Sharing examples of social media–based community outreach and educational programs, and evaluating their outcomes in this setting, is important for understanding whether these efforts have a measurable impact.

Objective
The aim of this study is to describe one center’s social media activities for community education on topics related to aging, memory loss, and Alzheimer disease and related dementias, and provide metrics related to recruitment into clinical research studies.

Methods
Several social media platforms were used, including Facebook, X (formerly Twitter), and YouTube. Objective assessments quantified monthly, based on each platform’s native dashboard, included the number of followers, number of posts, post reach and engagement, post impressions, and video views. The number of participants volunteering for research during this period was additionally tracked using a secure database. Educational material posted to social media most frequently included content developed by center staff, content from partner organizations, and news articles or resources featuring center researchers. Multiple educational programs were developed, including social media series, web-based talks, Twitter chats, and webinars. In more recent years, Facebook content was occasionally boosted to increase visibility in the local geographical region.

Results
Up to 4 years of page metrics demonstrated continuing growth in reaching social media audiences, as indicated by increases over time in the numbers of likes or followers on Facebook and X/Twitter and views of YouTube videos (growth trajectories). While Facebook reach and X/Twitter impression rates were reasonable, Facebook engagement rates were more modest. Months that included boosted Facebook posts resulted in a greater change in page followers and page likes, and higher reach and engagement rates (all P≤.002). Recruitment of participants into center-affiliated research studies increased during this time frame, particularly in response to boosted Facebook posts.

Conclusions
These data demonstrate that social media activities can provide meaningful community educational opportunities focused on Alzheimer disease and related dementias and have a measurable impact on the recruitment of participants into research studies. Additionally, this study highlights the importance of tracking outreach program outcomes for evaluating return on investment.
Remote Patient Monitoring and Machine Learning in Acute Exacerbations of Chronic Obstructive Pulmonary Disease: Dual Systematic Literature Review and Narrative Synthesis
Authors: Glyde Henry Mark Granger , Morgan Caitlin , Wilkinson Tom M A , Nabney Ian T , Dodd James W 
Published: July 2024

Background
Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are associated with high mortality, morbidity, and poor quality of life and constitute a substantial burden to patients and health care systems. New approaches to prevent or reduce the severity of AECOPD are urgently needed. Internationally, this has prompted increased interest in the potential of remote patient monitoring (RPM) and digital medicine. RPM refers to the direct transmission of patient-reported outcomes, physiological, and functional data, including heart rate, weight, blood pressure, oxygen saturation, physical activity, and lung function (spirometry), directly to health care professionals through automation, web-based data entry, or phone-based data entry. Machine learning has the potential to enhance RPM in chronic obstructive pulmonary disease by increasing the accuracy and precision of AECOPD prediction systems.

Objective
This study aimed to conduct a dual systematic review. The first review focuses on randomized controlled trials where RPM was used as an intervention to treat or improve AECOPD. The second review examines studies that combined machine learning with RPM to predict AECOPD. We review the evidence and concepts behind RPM and machine learning and discuss the strengths, limitations, and clinical use of available systems. We have generated a list of recommendations needed to deliver patient and health care system benefits.

Methods
A comprehensive search strategy, encompassing the Scopus and Web of Science databases, was used to identify relevant studies. A total of 2 independent reviewers (HMGG and CM) conducted study selection, data extraction, and quality assessment, with discrepancies resolved through consensus. Data synthesis involved evidence assessment using a Critical Appraisal Skills Programme checklist and a narrative synthesis. Reporting followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

Results
These narrative syntheses suggest that 57% (16/28) of the randomized controlled trials for RPM interventions fail to achieve the required level of evidence for better outcomes in AECOPD. However, the integration of machine learning into RPM demonstrates promise for increasing the predictive accuracy of AECOPD and, therefore, early intervention.

Conclusions
This review suggests a transition toward the integration of machine learning into RPM for predicting AECOPD. We discuss particular RPM indices that have the potential to improve AECOPD prediction and highlight research gaps concerning patient factors and the maintained adoption of RPM. Furthermore, we emphasize the importance of a more comprehensive examination of patient and health care burdens associated with RPM, along with the development of practical solutions.
Implementation of a Recovery College Embedded in a Swedish Psychiatry Organization: Qualitative Case Study
Authors: Al-Adili Lina , Malmqvist Moa , Reinius Maria , Helispää Rodriguez Inka , Stenfors Terese , Brommels Mats 
Published: July 2024

Background
Recovery colleges are service user–led educational interventions aiming at empowering people with mental health issues and promoting recovery through peer learning. Despite the increasing interest in recovery colleges in recent years and the demonstrated beneficial effects for users, there is limited research addressing aspects that influence their implementation. This knowledge is necessary for the successful integration of such interventions in various contexts.

Objective
This study aims to explore factors that influence the implementation of a recovery college embedded within a Swedish psychiatry organization.

Methods
A qualitative case study of a recovery college based on semistructured interviews with 8 course participants, 4 course leaders, and 4 clinical staff was conducted. The transcripts were scrutinized with conventional content analysis, and the interpretation of results was guided by the Consolidated Framework for Implementation Research.

Results
The findings highlight key areas that either hinder or promote the successful implementation of the recovery college. These areas included recruitment, resources, staff attitudes, and ways of organizing courses. Each area has elements that appear both as facilitators and barriers, demonstrating the duality of conditions.

Conclusions
Allocating dedicated resources, engaging individuals with service user experience as organizers who are willing to share their personal experience, having an open-door policy, creating an open space for participants to share their experiences, and offering practical advice and written material are useful to create favorable conditions for a recovery college to reach its goals of empowering psychiatry service users.
Nursing Regulation Literature in Canada: Protocol for a Scoping Review
Authors: Chiu Patrick , Leslie Kathleen , Kung Janice Y 
Published: July 2024

Background
Significant reforms are occurring in health practitioner regulation across Canada. Within the nursing profession, growing workforce challenges and health system demands have accelerated the pace of changes to nursing regulation policies and practices. There is significant political investment to modernize and harmonize nursing regulation across Canada, and evidence is needed to guide regulatory decision-making. To better understand the current state of scholarship and the gaps that exist, a comprehensive understanding of the available literature informing nursing regulation in Canada is first warranted.

Objective
The objective of this scoping review is to examine the nature, extent, and range of literature focused on nursing regulation in Canada.

Methods
The review will be conducted in accordance with the Joanna Briggs Institute guidelines for scoping reviews. We will search electronic databases, including Ovid MEDLINE, Ovid EMBASE, CINAHL, Scopus, and Web of Science Core Collection. We will also search for grey literature using the websites of Canadian nursing regulatory bodies, nursing organizations, and other leading Canadian regulatory organizations. No limitations will be placed on the year of publication. The review will include papers that explore nursing regulation in Canada, including topics such as education program accreditation or approval, licensure, standards of practice and code of conduct/ethics development and enforcement, continuing competence, discipline and conduct, regulatory models, governance, and reform. We will extract data using a predeveloped tool. Data will be analyzed using descriptive statistics and conventional content analysis.

Results
A preliminary search in Ovid MEDLINE was undertaken on December 7, 2023, and a full search was conducted in 5 academic databases on March 15, 2024. Findings will be presented using evidence tables and a narrative summary. Reporting will follow the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines. This scoping review is expected to be completed in early 2025.

Conclusions
The results will be disseminated through conference presentations and a publication in a peer-reviewed journal. The findings will provide a comprehensive overview of the state of nursing regulation literature across Canada and inform the development of a focused research agenda.

Trial Registration
Open Science Framework osf.io/3qk8t; https://osf.io/bm7jv

International Registered Report Identifier (IRRID)
DERR1-10.2196/56163
Effectiveness of a Virtual Reality Open-Air Bath Program in Reducing Loneliness and Improving Brain Function for Dementia Prevention in Older Adults: Protocol for a Prospective Randomized Crossover Study
Authors: Imai Ayu , Matsuoka Teruyuki , Nakayama Chikara , Hashimoto Nana , Sano Mutsuo , Narumoto Jin 
Published: July 2024

Background
Older adults often face loneliness due to chronic illness or loss of close ones, a situation worsened by the COVID-19 pandemic. Increased loneliness heightens the risk of diseases, especially dementia, necessitating urgent action.

Objective
This study aims to assess the impact of a virtual reality (VR)–based open-air bath program on depression and loneliness in older individuals with subjective cognitive decline/mild cognitive impairment attending the Dementia Medical Center in Kyoto, Japan. We further aim to evaluate the feasibility of the program (participant recruitment and adherence) and to measure program enjoyment and satisfaction.

Methods
The study design is a crossover trial with a 1:1 ratio, wherein 12 participants will be randomly assigned to groups 1 and 2, with group 2 serving as a waitlist control and group 1 receiving the VR program from the onset for 6 months; the VR program will be conducted 6 times (monthly). Program completion for group 1 will be followed by an observation period from months 7 to 12. Group 2 will participate in the VR program from months 7 to 12, with an observation period from months 1 to 6. Cognitive tests, psychiatric assessments, and the University of California, Los Angeles Loneliness Scale will be conducted before the study, at 6 months, and at 12 months. Results will be analyzed using repeated-measures ANOVA. Head magnetic resonance imaging and single-photon emission computed tomography scans will be performed before and after the VR program to evaluate changes and effects on brain regions.

Results
Recruitment began in September 2023 and data collection is expected to be completed by March 2025. Complete study results will be published by September 2025.

Conclusions
This study examines the preliminary effects of VR on loneliness in older adults with predementia through open-air bath simulations. VR experiences could benefit this population, particularly those with limited outdoor activities. Quantifying VR’s impact will aid in determining the size for a larger clinical trial. Qualitative results will inform participation mechanisms and guide the implementation and design of future trials.

Trial Registration
University hospital Medical Information Network UMIN000052667; https://tinyurl.com/3yaccay5

International Registered Report Identifier (IRRID)
DERR1-10.2196/57101