bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Video-based Automated Tracking and Analysis System of Plaque Burden in
Carotid Artery using Deep Learning: A Comparison with Senior Sonographers
Authors: Gao Wenjing , Liu Mengmeng , Xu Jinfeng , Hong Shaofu , Chen Jiayi , Cui Chen , Shi Siyuan , Dong Yinghui , Song Di , Dong Fajin 
Published: April 2024

Background and Objective:
The incidence of stroke is rising, and it is the second major cause of mortality and the third leading cause of disability around the globe. The goal
of this study was to rapidly and accurately identify carotid plaques and automatically quantify plaque burden using our automated tracking and
segmentation US-video system.

Methods:
We collected 88 common carotid artery transection videos (11048 frames) with a history of atherosclerosis or risk factors for atherosclerosis,
which were randomly divided into training, test, and validation sets using a 6:3:1 ratio. We first trained different segmentation models to segment
the carotid intima and adventitia, and calculate the maximum plaque burden automatically. Finally, we statistically analyzed the plaque burden
calculated automatically by the best model and the results of manual labeling by senior sonographers.

Results:
Of the three Artificial Intelligence (AI) models, the Robust Video Matting (RVM) segmentation model's carotid intima and adventitia Dice
Coefficients (DC) were the highest, reaching 0.93 and 0.95, respectively. Moreover, the RVM model has shown the strongest correlation
coefficient (0.61±0.28) with senior sonographers, and the diagnostic effectiveness between the RVM model and experts was comparable with
paired-t test and Bland-Altman analysis [P= 0.632 and ICC 0.01 (95% CI: -0.24~0.27), respectively].

Conclusion:
Our findings have indicated that the RVM model can be used in ultrasound carotid video. The RVM model can automatically segment and quantify
atherosclerotic plaque burden at the same diagnostic level as senior sonographers. The application of AI to carotid videos offers more precise and
effective methods to evaluate carotid atherosclerosis in clinical practice.
GCMS Analysis of Bioactive Compounds and Evaluation of Anti-parkinson Activity of Leaf Extract of Curculigo orchioides in Experimental Animals
Authors: D’Souza Ullas Prakash , Kodangala Subraya Chandrashekar , Rao Shruthi , Pai Vasudev 
Published: April 2024

Background:
Curculigo orchioides Gaertn, a plant belonging to the Hypoxidaceae
family, is well-known for its traditional uses of all plant parts. This plant is commonly known
as golden eye grass, black musli, Kali musli, or Kali Musali. Parkinson's disease is a neurodegenerative disorder that is commonly observed in older adults. It is caused by a variety of mechanisms, including neuroinflammation, which results in the loss of dopamine release when triggered
and causes motor symptoms.

Methods:
Ethanolic extract was prepared by shade-drying the leaves, making them into a coarse
powder, and the extract was prepared by maceration technique with the help of ethanol. GCMS
analysis and Haloperidol-induced Parkinsonism study were carried out to evaluate the antiParkinson activity in albino Wistar rats. Ethanolic extract of Curculigo orchioides was subjected
to GCMS analysis. The National Institute of Standards and Technology database was used to interpret the mass spectrum of the GC-MS. The screening models were catalepsy, rotarod and a few
in vitro models, namely the estimation of catalase acetylcholinesterase levels. The animals were
divided into 6 groups, namely control, disease, standard (levodopa), low dose (100 mg/kg p.o.),
medium dose (200 mg/kg p.o.), high dose (400 mg/kg p.o.) groups having 6 animals each were
used for rotarod and catalepsy models for 14 days

Results:
The results obtained showed a dose-dependent increase in the anti-Parkinson activity.
The evaluation of neuromuscular movements of the ethanolic leaf extract of Curculigo orchioides
showed that the pre-treatment with different ranges of dose (100 mg/ml, 200 mg/kg, and 400
mg/kg) suggested a dose-dependent significant increase in fall-off time when compared with both
standard and disease groups GCMS analysis revealed the presence of flavonoids, Vitamin and
fatty acid esters.

Conclusion:
The anti-Parkinson activity of Flavonoids has been reported previously. Hence, the
activity may be attributed to kaempferol-3-O-glucuronide.
Optimization of Lead-Free Cs2TiBr6 Green Perovskite Solar Cell for Future Renewable Energy Applications
Authors: Jeepa K.J. , Subash T.D. , Wilson K.S.J. , Ajayan J. , Batumalay M. 
Published: April 2024

Introduction:
A modern genre of solar technology is Perovskite solar cells (PSCs),
which are growing rapidly because they work well. The composition of links within the hole
transport materials, electron transport materials and the footprint on PSCs is perovskite

Methods:
The traditional genre of lead halide perovskite can be swapped with a new perovskite compound
called Cs2TiBr6. Cs2TiBr6 has better properties when it comes to light, electricity, and solar energy. When comparing the performance of various electron transport films (ETFs) for the
effective operation of perovskite, TiO2 is recognized as an ETF as it has higher thermal stability,
low-cost, and appropriate energy level

Results:
The most productive hole transport film (HTF)
for these perovskite solar cells, compared to other HTFs, has been demonstrated as V2O5.

Conclusion:
The various solar cell characteristics of the proposed device, the
"Au/V2O5/Cs2TiBr6/TiO2/TCO" perovskite solar cell, are investigated in this examination by
tuning the parameters such as temperature, series resistance, defect density, etc.
Recombinant ACE2 - Opportunities and Challenges in COVID-19 Treatment
Authors: Kaur Mandeep , Sandhu Rahul , Aggarwal Akriti 
Published: April 2024

:
It was in 2019 that the world experienced the devastation caused by SARS-COV-2, contributing to a large number of deaths. This contagious virus not only challenged the health care system but has also hit the economy very badly. There has been a lot of research on effective vaccine development, and there has been some success in the same, but no effective antiviral drugs are available in the market. No doubt vaccination can prevent the disease, but it doesn’t have the potential to cure an infected person, for which there is a dire need to develop some effective drug. Angiotensin convertase enzyme 2 (ACE2) played a substantial role in SARS-COV2 pathogenesis and thus has gained much attention during the pandemic. Moreover, it has opened up new avenues for the cure of COVID-19.
The Association between Periodontal Status and Frailty in Elderly Individuals
Authors: Wibianty Vilia , Tadjoedin Fatimah Maria , Lessang Robert , Rizal Muhammad Ihsan , Sulijaya Benso ,   Natalina , Widaryono Adityo 
Published: April 2024

Background
The number of older people in Indonesia is projected to continue rising. Periodontal disease and frailty are frequent among the elderly. Both are recognized to share some existing risk factors.

Objectives
This study aimed to evaluate the association between periodontal status and frailty in elderly individuals.

Methods
This is a cross-sectional study of people aged 60 and older. Periodontal status assessed was plaque score, bleeding on probing (BOP) score, calculus index, number of teeth, and stage of periodontitis. The FRAIL scale, comprised of Fatigue, Resistance, Ambulation, Illness, and Loss of weight, was used to evaluate the frailty state.

Results
There were 60 subjects in total, with 46.6% having frailty. There was a significant correlation between periodontal status and frailty in older people (p<0.05). There were significant differences in plaque scores between frail and normal subject groups (p=0.000), in the BOP between the frail and normal subject groups (p=0.003) and the pre-frail and frail subject groups (p=0.003), and in the number of teeth between the subject groups, frail to normal (p=0.011) and pre-frail subjects to frail (p=0.023).

Conclusion
The findings of this study suggest a link between periodontal status and frailty in the elderly; however, longitudinal research is needed to confirm this.
Speech Acts on Instagram comments about G20 Indonesia
Authors: Ahmadi F Yusep , Syaifullah Aceng Ruhendi , Hermawan Budi 
Published: April 2024

Speech acts in someone's comments show a person's perception, interpretation and attitude towards something they read. This research aims to reveal the reading position in the comments of 3 posts on Instagram @indonesia.g20. The focus of this research is to describe the forms of comment speech acts on Instagram and show the reading position. The data source for this research has been the Instagram account @indonesia.g20 as the official Instagram account for the 2022 Indonesian G20 Presidency. This research method uses a mixed method. Comment data was analyzed using a speech act analysis framework and a reading position analysis framework. Quantitatively this research found 37 comments which included comments with 22% assertive speech act, 32% directive speech act, and 46% expressive speech acts. Meanwhile, reading positions based on performative speech acts include hegemonic reading position 62%, negotiated reading position 27%, and oppositional reading position 11%. Qualitatively it can be concluded that the comments on the 3 Instagram posts are positive comments in the form of expressive speech acts. This means that these commentators tend to like and support the implementation of the 2022 G20 Indonesia presidency on Instagram.
Information Literacy Skills in the Use of Electronic Resources among Undergraduate Students at Universiti Teknologi MARA
Authors: Hamizak NurHamizah Sakinah , Ahmad Uzir Nora’ayu 
Published: April 2024

Information literacy skills are a set of abilities requiring individuals to recognize when information is needed and have the ability to locate, evaluate and use effectively the needed information. This study aims to investigate the level of information literacy skills in the use of electronic resources among undergraduate students at UiTM Puncak Perdana and to identify the relationship between information literacy skills and the use of electronic resources. This study was conducted utilizing a quantitative approach, which is a questionnaire prepared with a Google form. There were 218 undergraduate students from the Puncak Perdana campus responded successfully. Findings show that most of the undergraduate students in UiTM Puncak Perdana have a high level of information literacy in the use of electronic resources. This study's findings indicate that information literacy is a critical ability for undergraduate students to have in the digital age.
Evaluating the Scholarly Trends on Issues, Strategies and Sustainable Development of Digitisation of Documentary Heritage: A Thematic Review
Authors: Che Hasssan Nor Hasni , Wan Mohd Saman Wan Satirah , Shaifuddin Norshila 
Published: April 2024

The transformation from conventional archival practices to the digitization of documentary heritage collections represents a pivotal undertaking in the safeguarding and facilitation of access to historical and cultural materials in the digital era. Digitization helps preserve precious materials, making high-quality digital images available electronically. In the context of this paper, manuscripts are categorized as valuable assets and historical documentary heritage and will be discussed in detail. The underpinning of this thematic review paper is to identify the issues that have been discussed in the digitization of documentary heritage publications from the years 2010-2021 using ATLAS.ti 8. A keyword search, followed by a filter using inclusion criteria from SCOPUS, Web of Science and Mendeley databases, identified 424 peer-reviewed journal articles and, after the inclusion and exclusion process, only 28 articles were used as the final articles to be reviewed. Findings show four distinct categories: collaboration and participation; disaster preparedness; crowdsourcing; and cultural heritage information system.
Potential of Large Language Models in Health Care: Delphi Study
Authors: Denecke Kerstin , May Richard ,   LLMHealthGroup, Rivera Romero Octavio 
Published: April 2024

Background
A large language model (LLM) is a machine learning model inferred from text data that captures subtle patterns of language use in context. Modern LLMs are based on neural network architectures that incorporate transformer methods. They allow the model to relate words together through attention to multiple words in a text sequence. LLMs have been shown to be highly effective for a range of tasks in natural language processing (NLP), including classification and information extraction tasks and generative applications.

Objective
The aim of this adapted Delphi study was to collect researchers’ opinions on how LLMs might influence health care and on the strengths, weaknesses, opportunities, and threats of LLM use in health care.

Methods
We invited researchers in the fields of health informatics, nursing informatics, and medical NLP to share their opinions on LLM use in health care. We started the first round with open questions based on our strengths, weaknesses, opportunities, and threats framework. In the second and third round, the participants scored these items.

Results
The first, second, and third rounds had 28, 23, and 21 participants, respectively. Almost all participants (26/28, 93% in round 1 and 20/21, 95% in round 3) were affiliated with academic institutions. Agreement was reached on 103 items related to use cases, benefits, risks, reliability, adoption aspects, and the future of LLMs in health care. Participants offered several use cases, including supporting clinical tasks, documentation tasks, and medical research and education, and agreed that LLM-based systems will act as health assistants for patient education. The agreed-upon benefits included increased efficiency in data handling and extraction, improved automation of processes, improved quality of health care services and overall health outcomes, provision of personalized care, accelerated diagnosis and treatment processes, and improved interaction between patients and health care professionals. In total, 5 risks to health care in general were identified: cybersecurity breaches, the potential for patient misinformation, ethical concerns, the likelihood of biased decision-making, and the risk associated with inaccurate communication. Overconfidence in LLM-based systems was recognized as a risk to the medical profession. The 6 agreed-upon privacy risks included the use of unregulated cloud services that compromise data security, exposure of sensitive patient data, breaches of confidentiality, fraudulent use of information, vulnerabilities in data storage and communication, and inappropriate access or use of patient data.

Conclusions
Future research related to LLMs should not only focus on testing their possibilities for NLP-related tasks but also consider the workflows the models could contribute to and the requirements regarding quality, integration, and regulations needed for successful implementation in practice.
Metabolic syndrome, dyssomnia, and melatonin
Authors: Serhiyenko V.О. , Sehin V.B. , Hotsko M.E. , Serhiyenko L.M. , Serhiyenko О.О. 
Published: April 2024

In recent years, there has been an interest in studying the specifics of the relationships between metabolic syndrome (MetS), sleep disorders and melatonin (MEL). Dyssomnia and insomnia are important risk factors for insulin resistance, obesity, MetS, and type 2 diabetes mellitus with a degree of influence similar to traditional factors. Thus, the treatment of dyssomnia is one of the key tasks in the prevention and treatment of MetS. The regulation of sleep and circadian rhythms by exogenous intervention (in particular, the use of melatonergic drugs) is likely to play a central role in the prevention and treatment of dyssomnia in MetS. MEL acts as a powerful antioxidant that can cross the blood-brain barrier, suppress oxidative stress, chronic inflammation, and interact with the gut microbiome. From a clinical point of view, an imbalance of MEL may indicate a “darkness deficit”. It has been proven that the neurohormone has systemic effects due to its mechanisms of action, the potential to influence the course of many chronic diseases. Currently, melatonergic drugs are approved exclusively for the treatment of insomnia, jetlag, and depression accompanied by sleep disorders. However, MEL potentially has therapeutic properties in the treatment of neurodegenerative diseases, post-traumatic stress disorder, neuropsychiatric disorders, dementia, autoimmune and allergic diseases. The increasing need for the use of MEL products has prompted the search for safe but environmentally friendly medicines. It is reported that phytomelatonin may have advantages related to improved bioavailability and efficacy. The purpose of this review is to analyze the specifics of the relationship between MetS, dyssomnia, and MEL. The search was conducted in Scopus, Science Direct (from Else­vier), and PubMed, including MEDLINE databases. The keywords used were “metabolic syndrome”, “dyssomnia”, “insomnia”, “obstructive sleep apnea”, and “melatonin”. We conducted a manual search of the bibliography of publications to identify research results that were eluded during the online search.
Integrating interdisciplinary data: The EMERGE Database and its broader lessons for data management best practices
Authors: Hodgkins Suzanne , Bolduc Benjamin , Miller Dustin , Rich Virginia , Institute EMERGE Biology Integration 
Published: April 2024

In environmental research, cross-disciplinary analyses enable the
discovery of novel insights that may not otherwise be evident. Doing
these analyses efficiently requires integration of heterogeneous data
into a common data structure; however, this type of data integration
represents a major challenge, especially for large, multi-institutional
projects. Not only should the sharing of individual datasets follow FAIR
principles (Findable, Accessible, Interoperable, Reusable), but the
ideal data management system should also include a central
multidisciplinary data organization framework.
The EMERGE Database (EMERGE-DB;
https://emerge-db.asc.ohio-state.edu/) is the central data hub of
the EMERGE Biology Integration Institute (NSF award # 2022070), which
investigates the changing dynamics of a thawing permafrost ecosystem in
Stordalen Mire, northern Sweden. The EMERGE-DB accomplishes the
essential tasks of data management (i.e., data storage and sharing),
while also offering more advanced functionality to facilitate
interdisciplinary collaboration. Data and standardized
metadata—including both sample and file metadata—are integrated
within a Neo4j graph database, which allows combined datasets from
different source files to be obtained via efficient custom queries. A
front-end web portal provides access to this data for both the public
and for EMERGE project members (who can access non-public data via
login), with different pages providing different “views” of the
database for different common use cases. Although data are still
deposited to external community repositories (e.g. Zenodo, NCBI
databases) to ensure cost-effective long-term accessibility, these
depositions are tracked within the EMERGE-DB’s standardized metadata
system, with all internally- and externally-stored datasets displayed
within a centralized page on the web portal. Although this data
integration and sharing framework is customized for the EMERGE project’s
needs, many of its guiding principles—such as the centralized web
access point for all datasets, and general file formatting standards to
streamline the detailed integration of sample metadata—are broadly
applicable as “best practices” that other projects can apply in their
own data management systems.
Análisis de riesgos en el proceso de limpia pública de un municipio de Veracruz, México
Authors: Tobon-Galicia Lucila-Guadalupe , Fuentes-Rosas Liliana , Flores-Serrano María-del Socorro , Gurruchaga-Rodríguez María-Eloísa 
Published: April 2024

Problemática. Los puestos de confianza del municipio de Tezonapa son otorgados a personas que apoyaron la campaña política del administrador municipal, a quienes la necesidad de emplearse les obliga a aceptar las actividades encomendadas sin previa capacitación, el desconocimiento los expone a peligros que terminan en lesiones y enfermedades relacionadas con el trabajo.
Objetivos. Identificar los peligros a los que están expuestos los trabajadores de limpia pública, evaluar los riesgos y establecer medidas para controlarlos y prevenir lesiones y/o enfermedades profesionales.
Materiales y métodos. Se utilizó la metodología para la identificación de peligros, riesgos y su control (IPERC), iniciando con el conocimiento de actividades en cada puesto y tipo de peligro, se determinó el escenario de riesgo, causas y consecuencias, se evaluó la magnitud del riesgo para finalmente establecer medidas de control.
Resultados. Se propusieron acciones encaminadas a disminuir los riesgos de trabajo, se logró la sensibilización del personal en materia de seguridad y se consiguió que la administración tomara conciencia del trabajo que se realiza y proporcionara equipo de protección personal, ambos, disminuyen la magnitud de los riesgos localizados.
Discusión. El análisis de riesgos debe de actualizarse conforme el seguimiento a las acciones, algunas pueden necesitar mayor tiempo de solución, ya que requieren inversión monetaria y la seguridad del personal no se considera prioridad, sin embargo, concientizar al personal de los riesgos e informarlos a la administración, es un avance considerable que respalda cualquier eventualidad futura.
Conclusiones. Los riesgos evaluados se clasifican de triviales a moderados, el puesto con mayor porcentaje de riesgos moderados es el colector; el cumplimiento de los controles, dependen en su mayoría del cuidado de los trabajadores al ejecutar sus funciones.
Contribución/originalidad. La implementación de la matriz IPERC produce el primer acercamiento a los problemas que presentan los trabajadores del área de limpia pública.
FormaCaracterización Del Clima Organizacional Y Bienestar Laboral De Los Asesores Comerciales De La Empresa Ktronix Unicentro Bogotá
Authors: Montoya Arévalo Nelson Leonardo 
Published: April 2024

Para las empresas en el siglo XXI es indispensable que las personas que ejecutan las labores se encuentren inmersas en una satisfacción personal, que forjen a través de sus actividades productos o servicios con efectividad para que la organización obtenga los objetivos de producción y su ejercicio económico Desde esta perspectiva, la investigación tiene como objetivo Caracterizar el clima organizacional y bienestar laboral de 55 asesores comerciales adscritos a la empresa Ktronix Unicentro Bogotá.
La investigación se realiza bajo un enfoque cuantitativo con alcance de carácter descriptivo y explicativo mediante la aplicación de un cuestionario de encuesta, Para el análisis de datos se recurre al análisis descriptivo a fin de explorar los datos para descubrir patrones o tendencias, la estadística descriptiva para determinar los niveles de satisfacción laboral, motivación, la estructura del equipo de trabajo y rasgos destacados de los datos encontrados.
Como resultados recalca la satisfacción favorable por parte del personal, hallando discrepancias explicativas según la antigüedad en la organización, la edad y el puesto que ocupan.