bluuebunny/crossref_metadata_2025 huggingface dataset:
Continuous-frequency electric field measurements of D- band terahertz wave based on Rydberg atoms
Authors: CHAI JIWANG , LIU YANG , ZHANG YINGYUN , LIU GUIXIANG , XUE GUANGTAI , XU CHUNSHEGN , HAN SHUNLI
Published: November 2024

We present an experimental investigation of continuous-frequency electric field measurement for D-band terahertz wavesbased on Rydberg atoms. Using the continuous superheterodyne methodin near-resonant and non-resonant regions in the center of a Rydberg energy level, a range of several GHz’s continuous-frequency field strength measurement can be realized. By using six Rydberg states, we accomplished continuous field strength measurement in all of D-band terahertz waves. A minimum measurableelectric field strength of 22.08μV/cm is realized, and the maximum value of minimum field strength is 287μV/cm. Our results may provide the support for the development of terahertz atomic spectrum analyzer.
Factors Influencing Radical Remission: A Cross-Sectional Examination of Conventional and Alternative Medicine Alongside Personal Life Attitudes in Chronic Illness.
Authors: Alexander Naida
Published: November 2024

Introduction
Radical remission, defined as the significant and not fully explained recovery from incurable diseases, is reported across various chronic conditions. Despite its significance, there has been limited empirical research on the underlying factors. While conventional medical approaches focus on symptomatic and disease-specific treatment, there is growing interest in complementary and alternative medicine and integrative practices as contributing factors to radical remission. This study aimed to identify common characteristics among patients with radical remission from chronic and incurable diseases and to explore patients’ experiences, specifically evaluating the perceived impact of conventional treatments, complementary and alternative practices, and personal life attitudes on their healing journey.
Methods
Employing a prospective, cross-sectional, survey-based design, this study recruited a diverse sample of individuals (n=61) reporting radical remission from chronic diseases. Participants completed a systematic set of systematic questionnaires regarding their use of conventional, complementary and alternative therapies, and personal life attitudes to determine the perceived effectiveness of each factor in their healing process. Data were analyzed using descriptive statistics and chi-square tests.
Results
While both conventional and complementary and alternative therapies were widely used, complementary and alternative practices, such as mind-body interventions, energy-based therapies, and lifestyle modifications, received higher perceived effectiveness ratings compared to conventional treatments. Personal life attitudes were also widely utilized. Furthermore, these attitudes —including emotional and social support, positive attitudes, and spiritual and religious factors— emerged as the most impactful perceived factor in healing, outperforming both traditional and complementary and alternative therapies. Gender differences also emerged, with women more frequently engaging in complementary and alternative therapies, especially in Eastern medicine and mind-body practices, as compared to men.
Conclusions
This study highlights the perceived roles of complementary and alternative therapies and personal life attitudes in radical remission. Findings suggest that an integrative approach combining conventional, complementary and alternative methods, along with fostering positive life attitudes, may be essential in promoting radical remission. These results advocate for further research on integrative health strategies and emphasize the potential benefits of addressing psychological and spiritual dimensions alongside conventional treatments in chronic disease management.
Fracture and Mechanical Properties of Layered Composite Rocks with Pre-existing Flaws: A Simulation Study Using RFPA2D
Authors: Zhao TENGYUAN
Published: November 2024

Layered composite rocks with pre-existing flaws are frequently encountered in engineering applications such as tunneling, mining, and slope excavation. These rocks, due to the interaction between bedding planes and flaws, are more prone to cracking under external loads, potentially leading to catastrophic engineering failures. Understanding the fracture behavior and mechanical properties of such rocks is therefore essential. In this study, the Rock Failure Process Analysis System (RFPA) was employed to simulate the cracking processes in five types of layered composite rocks with collinear flaw pairs at varying bedding angles (θ = 0°, 30°, 45°, 60°, 90°). Through uniaxial compression tests, we investigated how crack angle and crack length influence the uniaxial compressive strength of each rock type. Additionally, the patterns of crack initiation, propagation, and failure modes were analyzed. The findings provide valuable insights into the role of rock structure and flaw geometry in the cracking process, offering significant implications for disaster prevention in rock engineering involving layered composite rocks with flaws.
Predictive Modeling for Rectal Bleeding Risk in Functional Constipation: Integrating Lifestyle Factors and Machine Learning for Targeted Prevention
Authors: Ghosh Joyeta , Taneja Jyoti , Kant Ravi
Published: November 2024

Rectal bleeding is a prevalent but often underreported health concern in young adults, where functional constipation and lifestyle factors can play a pivotal role. This study investigates the influence of contemporary lifestyle factors—including dietary patterns, fibre intake, physical activity, and BMI—on rectal bleeding risk in young adults with functional constipation. Using a descriptive observational study design, data were collected from 875 college-aged individuals in India to analyse lifestyle and clinical factors associated with rectal bleeding. A variety of machine learning models were tested to develop an accurate predictive model for bleeding risk assessment. Findings revealed significant correlations between dietary habits and rectal bleeding; individuals consuming less than 50g of boiled vegetables or oatmeal daily experienced bleeding at a rate of 43.92% (p < 0.001), while low whole grain intake (> 25g daily) was linked to a 44.81% bleeding rate. BMI also significantly impacted bleeding risk (p = 0.008), with higher incidence among overweight/obese participants. The KNeighbors Classifier was identified as the most effective predictive model, achieving 98.86% accuracy with an ROC area of 0.994, where symptomatic factors outweighed lifestyle factors in predicting bleeding risk. This machine learning model offers a promising tool for early risk identification, supporting lifestyle interventions, particularly in fibre intake and weight management, to reduce bleeding risk in this population.
Ventricular septal defects in cats – a retrospective study
Authors: ŁUKASZ MAZUREK , MARCIN KALINOWSKI , MATEUSZ SZADKOWSKI , MARIA PISAREK , ŁUKASZ ADASZEK
Published: November 2024

Significant deterioration in semen quality is associated with increased male infertility. Alterations in the sperm proteome resulting from infertility are not well understood. The aim of this study was to examine the connection between the proteome and the quality of spermatozoa in fertile and infertile dogs. The research was conducted on 11 male dogs, including 3 German shepherds, 3 Turkish Kangal, 2 Cane Corso, and 3 Golden Retrievers, aged 4 and 6 years (4.81 ± 0.75). Four of the 11 dogs constituted the infertile study group because of conception failure observed in at least 3 (3-5) matings with different fertile females within 1 year, and seven dogs from different owners constituted the fertile control group. Semen was manually manipulated and collected from all dogs in the presence of a female dog in heat. Ejaculates were used for spermatological examination and protein analysis. Computer-assisted semen analysis (CASA) was used to evaluate semen samples. In spermatological parameters, motility, kinematic parameters, morphology and plasma membrane integrity were evaluated. Gel electrophoresis (SDS-PAGE) was used to analyze proteins in sperm. The semen quality of infertile dogs was significantly lower. Motility, progressive motility, viability and plasma membrane integrity were statistically significantly lower in the infertile group than in the fertile group (P < 0.05). In morphological parameters, acrosome, head, middle part, tail and total defects were found to be statistically significantly higher in sterile dogs than in fertile dogs (P < 0.05). In the study, a total of 8 protein bands with molecular weights (MW) ranging from 11.0 to 245.0 kDa were identified in the protein analysis of semen. Variations in the sperm proteome composition were shown to be dependent on fertility. These proteins were associated with important metabolite pathways. Additionally, correlations of these bands with various spermatological parameters were revealed. The result of the study suggests that seminal plasma proteins play a role in semen quality and may be potential fertility biomarkers.
The perceptions of secondary school students regarding the learning of computer programming at Key Stage 4 in the revised curriculum in England: problems and solutions.
Authors: Almdahem Almabrok
Published: November 2024

Programming is becoming progressively important for many societies in the world today. It is also required in educational institutions and is especially important for students who will be graduating and looking for employment opportunities in the future. However, the teaching of a programming is not well developed in many secondary schools in different areas in England. Today, teaching programming is considered to be of the priority domain of several countries in the twenty-first century.  Interest in this domain is wide and the amount of research conducted in the field is numerous.
This study was designed to investigate and to aid a critical students’ understanding of the learning of programming in the revised Key Stage 4 (KS4) Computer Science (CS) curriculum. It seeks to understand the impact of learning programming on student’s perceptions toward programming and how to improve the teaching and learning of programming.
The study found that the issues faced by students learning programming include a lack of time, the perception that it is a ‘difficult’ subject and students’ insufficient understanding of programming. The findings also suggest that schools have made efforts to overcome these challenges and are willing to adopt programming as a subject and to help, encourage, develop and improve students’ ability to learn programming.
Laying the groundwork for a Legionella pneumophila risk management program for public drinking water systems
Authors: Burlingame Gary A. , Bartrand Timothy A.
Published: November 2024

Legionella pneumophila is different from traditional drinking water contaminants because it presents a latent public health risk for public and private drinking water systems and for the building water systems they supply. This paper reviews information on the likelihood of occurrence of L. pneumophila in public water systems to lay a foundation for public water systems, as a stakeholder in public health risk management, to better manage L. pneumophila. Important to this approach is a literature review to identify conditions that could potentially promote L. pneumophila being present in drinking water systems at either an elevated abundance or at an increased frequency of occurrence, and/or water quality and supply conditions that would contribute to its amplification. The literature review allows the development of an inventory of hazardous conditions that a public water system could experience and, therefore, can be used by water systems to develop control and monitoring strategies. However, effective L. pneumophila risk management programs are hampered by significant data and knowledge gaps. Priority research to advance public water system's risk assessments and management of L. pneumophila is proposed.
A growing concern: investigating sustainable water quality and urban food production in Freetown, Sierra Leone
Authors: Bryant Lee , Maconachie Roy , Schnabel Bastian , Swaray Abubakarr , Howard Gigi , Gbanie Solomon , Bangura Kabba , Kamara Anthony , Antwi-Agyei Prince
Published: November 2024

Clean water and food security are central to sustainable urban living. Yet, in rapidly expanding African cities, they remain unobtainable for many and a barrier to the health and wellbeing of millions of people. In Freetown, Sierra Leone, a city that has experienced rapid in-migration in recent decades, urban food security has become a major concern. One critical response has been the proliferation of urban and peri-urban agriculture (UPA) to support food security and income generation for the poor. However, UPA sites are often exposed to a range of pollutants. This paper examines the environmental health status of three different UPA sites in Freetown. Qualitative and quantitative data show heavy metal concentrations that significantly exceed regulatory limits in crop leaves (sweet potato) and arable soil. Soaring readings of faecal coliform bacteria were observed in water used for irrigation, corroborating health-related findings which demonstrate a direct relationship between water supply, handwashing and diarrhoea. Elevated nutrient concentrations were also observed in surface water during the rainy season. Ultimately, crops were revealed to be hyperaccumulators for environmental contaminants, highlighting both the challenges and potential for nature-based solutions to strengthen food security and public health at UPA sites in Freetown and other growing cities.
Uncertainty in Evapotranspiration Inputs Impacts Hydrological Modeling
Authors: Akhter Mehnaza , Ahanger Manzoor Ahmad
Published: November 2024

This work addresses the role of accurate input data in hydrological model simulations and explores the often-overlooked errors associated with evapotranspiration (ET). While existing literature primarily focuses on uncertainties in rainfall, this study underscores the necessity of considering errors in ET, as evidenced by some studies suggesting their substantial impact on hydrological model responses. A comprehensive exploration of uncertainty quantification resulting from errors in ET in hydrological model simulations is presented, highlighting the imperative to scrutinize this facet amidst diverse uncertainties. There are two approaches for addressing uncertainty in potential evapotranspiration (PET) inputs as discussed: directly considering uncertainty in PET data series or accounting for uncertainty in the parameters used for PET estimation. Furthermore, details are provided about the existing error models for PET measurements, revealing a limited number of studies that specifically account for ET-related uncertainties. Researchers commonly address ET errors by considering both systematic and random errors; some studies suggest that systematic errors in PET have a more substantial impact compared to random errors on hydrological model responses. In summary, the objective of this paper is to offer an in-depth exploration of uncertainty associated with PET inputs and their influence on hydrological modeling.
Programas de saneamiento urbano en la frontera norte de México y el enfoque de economía circular
Authors: Aguilar Benitez Ismael
Published: November 2024

En este artículo se analizan el Programa de saneamiento de la frontera norte estudio gran visión y el Programa estratégico de saneamiento de la frontera norte, ambos se formularon luego de la introducción del capítulo ambiental del T-MEC en 2020. Se examinan tres casos relevantes de ciudades fronterizas: Tijuana, Baja California; Nogales, Sonora; y, Nuevo Laredo, Tamaulipas. La investigación se basa en una revisión documental y entrevistas a informantes clave. Se encontró que las soluciones propuestas se apoyan principalmente en el desarrollo de infraestructura convencional, con una incorporación limitada de estrategias de reutilización, reciclaje y recuperación de materiales, energía y agua. El estudio enfatiza la importancia de una planeación que incorpore principios de economía circular y formas de infraestructura verde para mejorar la sostenibilidad de los proyectos de saneamiento en la región.
FUTURO DOS HISTORIADORES E O USO DAS TECNOLOGIAS NA PESQUISA EM HISTÓRIA
Authors: SILVA Daniel Ferreira da , Demiciano Ygor
Published: November 2024

A presente entrevista foi disponibilizada em formato de podcast no final do ano de 2023, visando possibilitar uma reflexão sobre o estado atual das nossas pesquisas enquanto historiadores. A ênfase no uso das mídias e tecnologias digitais é o ponto central do debate, contando com a participação de uma profissional internacionalmente reconhecida na área de utilização de patrimônio com tecnologias e inteligências artificiais.
NARRATIVA E UMA CARNAVALESCA:
Authors: Nunes Mello Isabella
Published: November 2024

O objetivo central deste artigo é pensar como o universo dos desfiles das escolas de samba, pode contribuir para a produção do conhecimento, a partir do desfile de 1994 da Imperatriz Leopoldinense intitulado “Catarina de Médicis na Corte dos Tupinambôs e Tabajeres”. A análise do enredo ocorre sob a luz teórica da obra de Ferdinand Denis, “Uma festa brasileira” publicada originalmente em 1850, considerada uma das mais fieis fontes historiográficas sobre esse acontecimento. Criado pela carnavalesca Rosa Magalhães, o enredo se torna uma importante fonte histórica para contribuir com o campo do conhecimento e com o ensino de história, tendo em vista que a composição do enredo optou em assumir esse compromisso teórico educacional, mesmo não sendo pauta obrigatória. Nesse cenário, ainda trago uma breve passagem sobre a vida e a contribuição dessa carnavalesca de grande referência para o mundo do samba e para a produção do saber
PESQUISAS SOBRE ENSINO DE HISTÓRIA E TECNOLOGIAS DIGITAIS DA INFORMAÇÃO E COMUNICAÇÃO (TDCIs) NO PROFHISTÓRIA:
Authors: Rodrigues Junior Osvaldo , Rodrigo Soares Carlos
Published: November 2024

Este trabalho apresenta resultados parciais de pesquisa de mestrado com o objetivo de analisar os trabalhos sobre ensino de História e Tecnologias Digitais da Informação e Comunicação (TDICs). O estudo bibliográfico consistiu no levantamento de dados nos portais Educapes, ProfHistória Nacional e Catálogo de Teses e Dissertações da Capes. Através do software Iramuteq realizamos a análise fatorial de correspondência e análise de similitude. Os resultados parciais permitem observar que existe uma predominância do ProfHistória como espaço de produção de conhecimento sobre o ensino de História e as TDIC’s, além de uma pluralidade de abordagens teórico-metodológicas, objetos e produtos. Verifica-se também lacunas para pesquisas futuras e um campo extenso para a investigação histórica.
Adubação nitrogenada e potássica na produção e qualidade de goiabas no Distrito Irrigado do Baixo Açu (RN)
Authors:   , Alencar Renato Dantas
Published: November 2024

Avaliou-se o efeito da adubação nitrogenada e potássica na produção e qualidade de frutos de goiabeira Paluma cultivada em pomar comercial do Distrito Irrigado do Baixo Açu (DIBA). Foram realizados dois experimentos: um com doses crescentes de nitrogênio e outro com doses crescentes de potássio. Em ambos os experimentos foi utilizado o esquema de parcelas subdivididas, em delineamento de blocos ao acaso, com cinco tratamentos e quatro repetições. As subparcelas foram constituídas pelas safras (duas). Foi utilizada como parcela útil as três plantas centrais de cada subparcela. No experimento 1 os tratamentos foram as doses de nitrogênio (0; 0,4; 0,8; 1,2 e 1,6 kg planta-1) e no experimento 2, as doses de potássio (0; 0,5; 1,0; 1,5 e 2,0 kg planta-1). As fontes de nitrogênio e potássio foram uréia e cloreto de potássio, respectivamente. Os frutos foram avaliados quantitativamente (número por planta, peso médio, peso total por planta produtividade por hectare) e qualitativamente (firmeza de polpa, diâmetros longitudinal e transversal, potencial hidrogeniônico (pH), sólidos solúveis (SS), vitamina C e acidez total titulável). A adubação nitrogenada não promoveu efeito significativo na qualidade dos frutos, mas a maior produtividade foi obtida na dose de 0,4 kg de N planta-1, tendo as doses superiores a esta provocado redução na produtividade. A adubação potássica promoveu aumento linear no número de frutos em função do aumento da dose de K2O, mas a maior produtividade e a maior firmeza foram obtidas, respectivamente, com as doses estimadas de 0,37 e 1,21 kg planta-1 de K2O
Adubação verde na produtividade, qualidade e rentabilidade de beterraba e rabanete
Authors:   , Batista Marcos Antonio Vieira
Published: November 2024

Dois experimentos foram realizados durante o período de outubro de 2009 a fevereiro de 2010, na Universidade Federal Rural do Semi-Árido, Mossoró – RN, com o objetivo de avaliar a produtividade, qualidade e rentabilidade da beterraba e do rabanete submetido a diferentes espécies espontâneas da Caatinga e quantidades de adubos verdes. O delineamento experimental foi de blocos completos casualizados com três repetições, com os tratamentos arranjados em esquema fatorial 3 x 5. Os tratamentos consistiram da combinação de três adubos verdes (jitirana, mata pato e flor-de-seda) com cinco quantidades incorporadas ao solo (5,4; 8,8; 12,2; 15,6 e 21,0 t ha-1 em base seca). As características avaliadas em ambas as culturas foram: Produtividade de raízes total, produtividade de raízes comerciais, massa seca de raízes (MSR), massa seca da parte aérea (MSPA), altura de plantas, diâmetro de raízes, percentagem de raízes comerciais e percentagem de raízes refugo no rabanete e produtividade classificada de raízes na beterraba. Além disso, também foram determinadas as seguintes características de pós-colheita: Antocianina (beterraba), sólidos solúveis (SS), acidez titulável (AT), relação SS/AT, potencial hidrogeniônico (pH) e firmeza de raízes. Os indicadores econômicos avaliados foram: Renda bruta (RB), renda líquida (RL), taxa de retorno (TR) e índice de lucratividade (IL). Na beterraba, as espécies estudadas não se diferenciaram no crescimento dos actinomicetos do solo. A quantidade de actinomicetos do solo aumentou com as quantidades crescentes das espécies incorporadas ao solo. O melhor desempenho produtivo da beterraba foi obtido quando fertilizada com flor-de-seda e jitirana na quantidade de adubo de 21,0 t ha - 1. O maior conteúdo de sólidos solúveis foi observado nas parcelas tratadas com jitirana. As maiores rendas e eficiências monetárias foram observadas na maior quantidade de flor-de-seda incorporada. No rabanete, as maiores produtividades de raízes total e comercial foram observadas nos tratamentos com jitirana. A maior percentagem de raízes comerciais foi de 73,6 %, obtida na quantidade de adubo de 21,0 t ha-1. A maior firmeza de raízes foi observada nos tratamentos com a flor-deseda. As maiores rendas e eficiências monetárias foram observadas na maior quantidade de jitirana incorporada de 21,0 t ha-1
Quantum Gravity without Quantization
Authors: Ivanov Michael A.
Published: November 2024

Objective:

An alternative way to construct a quantum model of gravity is described in
this paper, not by quantizing the classical model, but by introducing a graviton background, which
has a low temperature, but strongly interacts with any particle.

Methods:

Gravity in this case is the effect of screening the background of gravitons by bodies;
several additional effects appear when photons or bodies move through the background.

Results:

Using Planck's formula for the graviton spectrum and taking into account the pairing
effect for some of the gravitons, Newton's constant can be calculated and the magnitudes of the
additional effects can be estimated.

Conclusion:

These small additional effects can be important for cosmology since they allow to
describe the results of cosmological observations without dark energy.
Antiviral Potential of 2-DG Used in Different Viral Infections
Authors: Prakash Shaurya , Minakshi  , Kumari Hemlata , Kumar Antresh
Published: November 2024

The evolution of viral infections has pushed researchers constantly to find
new approaches to disseminate these infections. One such promising finding in this
aspect is 2-deoxy-D-glucose (2-DG), a glucose analogue that gained attention for its
potential as an antiviral agent effective against a variety of viral infections. The
antiviral properties of 2-DG are due to its ability to interfere with viral replication
within host cells, hence reducing the severity of infections. 2-DG is easily taken up by
cells as it mimics glucose-like structure but interferes with glycolysis and other
metabolic pathways. It also acts as a glycosylation inhibitor that helps in the disruption
of viral assembly. Viruses are obligate and utilize the host cell machinery for
proliferation. 2-DG mechanistically disrupts the energy supply by inhibiting the
glycolysis cycle and providing an unfavourable environment for viral replication. 2-DG
elicits broad-spectrum antiviral activity as it was found to be very effective against
different families of viruses. By interfering with this process, 2-DG not only interferes
with viral replication but also with the ability of the virus to enter host cells and evade
the immune system. Although 2-DG has shown some promising antiviral potential, it
also possesses some side effects as well. All the attributes related to the antiviral
potential of 2-DG have been discussed in this chapter.
An Overview of Artificial Intelligence (AI) In Drug Delivery and Development
Authors: Mutha Rakesh E. , Bagul Vishal S. , Tade Rahul S. , Vinchurkar Kuldeep
Published: November 2024

The integration of Artificial Intelligence (AI) into pharmaceutical research
represents a transformative leap in drug development, addressing the challenges posed
by complex diseases and traditional methodologies. In this comprehensive overview,
we explore the historical evolution of AI's role in pharmaceutical research and its
crucial importance in drug delivery and development. The foundational elements of AI
in drug delivery and development are elucidated through an in-depth analysis of
machine learning (ML) algorithms, deep learning techniques, and natural language
processing in bioinformatics. These form the bedrock for understanding the subsequent
chapters that unravel the emerging roles of AI in drug discovery, formulation, and
delivery. An insightful examination of drug repurposing and interaction reveals AIdriven strategies, providing new therapeutic avenues. The chapters further unravel AI's
impact on pharmacokinetics, pharmacodynamics, and its data-driven approaches for
dose optimization. Clinical trials and patient recruitment witness a revolution through
AI, optimizing design and ensuring regulatory compliance and safety. This chapter
promises a holistic understanding of the symbiotic relationship between AI and
pharmaceuticals, offering a roadmap for innovation and efficiency in the pursuit of
advanced healthcare solutions.
Artificial Intelligence in Community and Hospital Pharmacy
Authors: Yadav Saloni , Jain Priya , Vinchurkar Kuldeep , Mane Sheetal
Published: November 2024

The integration of artificial intelligence (AI) into pharmaceutical research
represents a transformative leap in drug development, addressing the challenges posed
by complex diseases and traditional methodologies. In this comprehensive overview,
we explore the historical evolution of AI's role in pharmaceutical research and its
crucial importance in drug delivery and development. The foundational elements of AI
in drug delivery and development are elucidated through an in-depth analysis of
machine learning (ML) algorithms, deep learning techniques, and natural language
processing in bioinformatics. These form the bedrock for understanding the subsequent
chapters that unravel the emerging roles of AI in drug discovery, formulation, and
delivery. An insightful examination of drug repurposing and interaction reveals AIdriven strategies, providing new therapeutic avenues. The chapters further unravel AI's
impact on pharmacokinetics, pharmacodynamics, and its data-driven approaches for
dose optimization. Clinical trials and patient recruitment witness a revolution through
AI, optimizing design and ensuring regulatory compliance and safety. This chapter
promises a holistic understanding of the symbiotic relationship between AI and
pharmaceuticals, offering a roadmap for innovation and efficiency in the pursuit of
advanced healthcare solutions.
Artificial Intelligence in Herbal Medicine Formulations
Authors: Kumbhar Prashant , Pandey Narendra Kumar , Kumar Bimlesh , Vinchurkar Kuldeep
Published: November 2024

One promising way to optimize and improve the development of herbal
remedies is to incorporate artificial intelligence (AI) methodology into the field of
herbal medicinal formulations. AI methods are being used increasingly to analyze large
datasets that include traditional knowledge, pharmacological properties, botanical
compounds, and therapeutic effects. These methods include machine learning
algorithms, neural networks, and natural language processing. These computational
tools make it easier to identify bioactive ingredients, anticipate synergistic interactions,
and understand the molecular processes that underlie herbal formulations. Furthermore,
the process of drug discovery and development can be streamlined by using AI-driven
modeling to quickly screen formulations for safety, bioavailability, and efficacy. The
combination of AI and herbal medicine works well together to speed up the search for
new therapeutic combinations and facilitate comprehension of the complex interactions
between phytochemicals and their biological targets. However, issues like algorithm
robustness, ethical considerations, and data quality make more research and validation
in this emerging field necessary. However, the combination of AI techniques and
herbal medicine formulations has great potential to advance evidence-based and
personalized healthcare practices.
Muscle Atrophy and Weakness in Metabolic Disease
Authors: Eshima Hiroaki
Published: November 2024

Obesity and diabetes are associated with changes in skeletal muscle quantity
and quality, such as increased ectopic fat, muscle atrophy, and decreased muscle
strength. Skeletal muscle tissue is often affected by metabolic insult because it
remodels cellular size, composition, and function in response to a variety of nutritional
changes. Declining muscle quantity and quality are directly linked to falls and
bedriddenness; understanding the intracellular mechanisms may provide clues for
therapeutic strategies. How metabolic diseases via cellular mechanisms affect muscle
quality and muscle quantity are presented in this chapter.
Rasgos morfológicos de árboles de Pseudosamanea guachapele (Kunth) Harms en el municipio El Espinal, Tolima, Colombia
Authors: Castañeda-Garzón Sandra Liliana , Cervera Bonilla Diana Catalina , Zuluaga Peláez Jhon Jairo , Argüelles Cárdenas Jorge Humberto
Published: November 2024

la especie nativa Pseudosamanea guachapele (Kunth) Harms, conocida localmente como iguá, es importante por su uso en sistemas agroforestales y silvopastoriles; no obstante, se desconocen los rasgos de mayor aporte en la caracterización del recurso genético. Por lo anterior, en la plantación del Centro de Investigación Nataima de la Corporación Colombiana de Investigación Agropecuaria (Agrosavia), se evaluó la variabilidad fenotípica de 97 árboles de P. guachapele, por medio de 34 descriptores morfológicos cuantitativos y cualitativos de la planta (copa, fuste y hoja). Se empleó un análisis de componentes principales y correspondencias múltiples, para las variables cuantitativas y cualitativas, respectivamente, con el fin de reducir la dimensionalidad del conjunto de datos, complementados con un análisis de conglomerados, utilizando el algoritmo de WARD, el cual permitió clasificar a los individuos de P. guachapele en cinco grupos. Las variables que aportaron más información para la discriminación de los individuos fueron: rectitud del fuste, altura de la ramificación y bifurcación, forma y densidad de la copa, tipo de corteza, altura total y de copa, volumen del tronco, diámetro a la altura del pecho y diámetro de la copa. En la plantación de P. guachapele se identificaron individuos con potencial de uso maderable, conservación de suelos y uso en sistemas silvopastoriles (árboles dispersos en potreros o cercas vivas). Para la selección de árboles de P. guachapele para sombrío, son de utilidad las variables asociadas al porte del árbol, el diámetro y la forma de la copa.
Performance of Artificial Intelligence Chatbots on Ultrasound Examinations: Cross-Sectional Comparative Analysis
Authors: Zhang Yong , Lu Xiao , Luo Yan , Zhu Ying , Ling Wenwu
Published: November 2024

Background

Artificial intelligence chatbots are being increasingly used for medical inquiries, particularly in the field of ultrasound medicine. However, their performance varies and is influenced by factors such as language, question type, and topic.

Objective

This study aimed to evaluate the performance of ChatGPT and ERNIE Bot in answering ultrasound-related medical examination questions, providing insights for users and developers.

Methods

We curated 554 questions from ultrasound medicine examinations, covering various question types and topics. The questions were posed in both English and Chinese. Objective questions were scored based on accuracy rates, whereas subjective questions were rated by 5 experienced doctors using a Likert scale. The data were analyzed in Excel.

Results

Of the 554 questions included in this study, single-choice questions comprised the largest share (354/554, 64%), followed by short answers (69/554, 12%) and noun explanations (63/554, 11%). The accuracy rates for objective questions ranged from 8.33% to 80%, with true or false questions scoring highest. Subjective questions received acceptability rates ranging from 47.62% to 75.36%. ERNIE Bot was superior to ChatGPT in many aspects (P<.05). Both models showed a performance decline in English, but ERNIE Bot’s decline was less significant. The models performed better in terms of basic knowledge, ultrasound methods, and diseases than in terms of ultrasound signs and diagnosis.

Conclusions

Chatbots can provide valuable ultrasound-related answers, but performance differs by model and is influenced by language, question type, and topic. In general, ERNIE Bot outperforms ChatGPT. Users and developers should understand model performance characteristics and select appropriate models for different questions and languages to optimize chatbot use.
Data Ownership in the AI-Powered Integrative Health Care Landscape (Preprint)
Authors: Liu Shuimei , Guo L Raymond
Published: November 2024

UNSTRUCTURED

In the rapidly advancing landscape of artificial intelligence (AI) within integrative health care (IHC), the issue of data ownership has become pivotal. This study explores the intricate dynamics of data ownership in the context of IHC and the AI era, presenting the novel Collaborative Healthcare Data Ownership (CHDO) framework. The analysis delves into the multifaceted nature of data ownership, involving patients, providers, researchers, and AI developers, and addresses challenges such as ambiguous consent, attribution of insights, and international inconsistencies. Examining various ownership models, including privatization and communization postulates, as well as distributed access control, data trusts, and blockchain technology, the study assesses their potential and limitations. The proposed CHDO framework emphasizes shared ownership, defined access and control, and transparent governance, providing a promising avenue for responsible and collaborative AI integration in IHC. This comprehensive analysis offers valuable insights into the complex landscape of data ownership in IHC and the AI era, potentially paving the way for ethical and sustainable advancements in data-driven health care.
Use of Automated Machine Learning to Detect Undiagnosed Diabetes in U.S. Adults (Preprint)
Authors: Ji Mengmeng , An Ruopeng
Published: November 2024

BACKGROUND

Early diagnosis of diabetes is essential for early interventions to slow the progression of dysglycemia and its comorbidities. Diabetes screening that relies on blood testing are not widely followed, especially among high-risk groups.

OBJECTIVE

This study aims to investigate the potential use of automated machine learning (AutoML) models and self-reported data in detecting undiagnosed diabetes among U.S. adults.

METHODS

Individual-level data, including biochemical tests for diabetes, demographic characteristics, family history of diabetes, anthropometric measures, dietary intakes, health behaviors, and chronic conditions were retrieved from the National Health and Nutrition Examination Survey, 1999-2020. Undiagnosed diabetes was defined as having no prior self-reported diagnosis but meeting diagnostic criteria for elevated hemoglobin A1c, fasting plasma glucose, or 2-h plasma glucose. The H2O AutoML framework was used to automate the machine learning workflow. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and accuracy.

RESULTS

The study included 11,815 participants, comprising 2,256 patients with undiagnosed diabetes and 9,559 without diabetes. The average ages were 59.76 years for those with undiagnosed diabetes and 46.78 years for those without. The trained AutoML model achieved an AUC of 0.909 and an accuracy of 86.5% in the test set. The model demonstrated a sensitivity of 70.26%, specificity of 90.46%, positive predictive value of 64.10%, and negative predictive value of 92.61% for identifying undiagnosed diabetes from non-diabetes.

CONCLUSIONS

This study is the first to utilize the AutoML model for detecting undiagnosed diabetes in U.S. adults. The model’s high accuracy and applicability to the broader U.S. population make it a promising tool for large-scale diabetes screening efforts.
An adaptation of eCREST, an online patient simulation tool to support clinical reasoning: A mixed-methods evaluation comparing clinical reasoning styles of physician associate and medical students (Preprint)
Authors: Thorpe Alistair , Kassianos Angelos , Plackett Ruth , Krishnamurthy Vinodh , Kambouri Maria , Sheringham Jessica
Published: November 2024

BACKGROUND

Clinical reasoning is increasingly recognised as an important skill in the diagnosis of serious conditions. eCREST (electronic Clinical Reasoning Educational Simulation Tool), a clinical reasoning learning resource was developed to support medical students to learn clinical reasoning. However, primary care teams now encompass a wider range of professional groups, such as Physician Associates [PAs] who also have a need to develop clinical reasoning during their training.

OBJECTIVE

We sought to evaluate the suitability of eCREST for physician associates, by comparing reasoning styles of PA and medical students using the tool.

METHODS

Between 2017 and 2021, PA students and medical students used eCREST to learn clinical reasoning skills in an experimental or learning context. Students undertook a simulated case of a patient presenting with chest pain. They could ask questions, order bedside tests, and select physical exams during the case, to help them form, reflect on and reconsider diagnostic ideas and management strategies while completing a case. Exploratory analysis was undertaken by comparing students’ data gathering, flexibility in diagnosis and diagnostic ideas between medical and PA students.

RESULTS

In total 159 medical students and 54 PA students completed the case. PAs were older (M=27±7 vs. M=24±4 years, p<.001) and more likely to be female (80% vs. 53%, p<.001). Medical and PA students were similar in the proportion of essential questions asked (M=70.13±22.24 vs. M=73.24±17.40, p=.326), physical examinations requested (M=54.7±18.6 vs. M=54.0±21.1, 50, p=.586), bedside tests selected (M=74.4±29.1 vs. M=83.3±28.8, p=.053), and number of times they changed their diagnoses (M=2.8±1.4 vs. M=2.8±1.5, p=.993). PA students initially included a greater proportion of relevant diagnoses (M=51.5±14.2 vs. M=43.4±14.4, p<.001), but both student groups improved during the case, particularly medical students (p=.046), and finished the case with similar proportions of relevant diagnoses (M=65.7±14.6 vs. M=62.9±15.5, p=.226).

CONCLUSIONS

These results provide suggestive evidence that eCREST can serve the needs of both medical and PA students in developing clinical reasoning skills to support diagnosis in primary care.
Radiative equilibrium in the middle atmosphere
Authors: Gay C. , Thomas G. E.
Published: November 2024

En este trabajo se describe un estudio te6rico del estado de Equilibrio Radiactivo de la Atmósfera media; nuestro enfoque es básicamente analítico. Se introduce un nuevo método general de solución basado en las funciones radiactivas características (modos naturales de decaimiento de perturbaciones de temperatura en la atmósfera). Los resultados del método son comparados con otros obtenidos por métodos puramente numéricos, mostrando excelente precisión, además de la conveniencia del uso de métodos analíticos.
Disminución de la matrícula universitaria por deserción: una revisión estructurada
Authors: Zerpa Carlos , Rodríguez-Montoya Cristóbal
Published: November 2024

Este artículo presenta una revisión estructurada de la literatura sobre los factores que contribuyen a la disminución de la matrícula universitaria debido a la deserción, empleando la declaración PRISMA como modelo. Esta revisión considera un conjunto de 15 documentos seleccionados que abarcan un total de N = 19089 participantes. Los resultados de nuestro estudio evidencian una notable falta de consenso en los enfoques y métodos utilizados para tratar este fenómeno y resaltan varios factores críticos que contribuyen a la deserción universitaria: factores académicos, motivacionales, económicos, percepción de la calidad del sistema educativo, escasez de recursos de apoyo, baja valoración de la educación recibida, y problemas familiares. Los hallazgos proporcionan una base sólida para informar y diseñar políticas de retención efectivas en las instituciones de educación superior, lo cual es de suma importancia para el fortalecimiento del sector educativo.
Formación docente y práctica pedagógica en la educación inclusiva: revisión sistemática
Authors: Gordillo Magdaly , Prado Víctor
Published: November 2024

Las demandas de atención que emergen en el marco de la diversidad funcional de los estudiantes son desatendidas y en la actualidad exigen fortalecer los procesos de formación docente. Esta revisión sistemática propone identificar los planteamientos actuales sobre formación docente y su incidencia en la práctica pedagógica desde la educación inclusiva. Se realiza un análisis cualitativo de publicaciones científicas entre el año 2019 al primer trimestre del 2024 mediante la metodología PRISMA, consultando Scopus, Science Direct y WoS. Tras la identificación, selección y cribado, se hallaron 43 artículos. Los resultados revelan que conceptos como didáctica, educación inclusiva y sensibilización del ser permiten que la formación docente impacte en la práctica pedagógica, teniendo como eje central la educación inclusiva. Este estudio sugiere investigar alrededor de la formación de maestros en ejercicio y se invita a explorar nuevas estrategias que promuevan una educación inclusiva en las aulas.
Alternativa terapéutica para mejorar la calidad de vida en pacientes con fibrosis quística y discinesia ciliar primaria
Authors: Cordero Oñate Leandra , Estela Baez Laura
Published: November 2024

Objetivo: Evaluar la respuesta clínica de los pacientes con fibrosis quística y discinesia ciliar primaria posterior a la cirugía endoscópica de senos paranasales en el Hospital Infantil Dr. Robert Reid Cabral en el período septiembre 2021 a febrero 2022.
Métodos: Se realizó un estudio observacional tipo serie de casos, de corte transversal y ambispectivo, donde la población estudiada estuvo conformada por los pacientes con fibrosis quística y discinesia ciliar primaria del hospital infantil Dr. Robert Reid Cabral en el período de estudio.
Criterios de inclusión: Pacientes mayores de 6 años con diagnóstico confirmado de fibrosis quística y discinesia ciliar primaria (Prueba genética con 2 mutaciones homocigotas, electrolitos en sudor positivos), síntomas respiratorios severos de RSC que no mejoraron con tratamiento convencional y sometidos a la cirugía endoscópica de senos paranasales.
Resultados: De un total de 41 pacientes, sólo 10 cumplieron con los criterios de inclusión, el rango de edad más prevalente fue de 14 a 18 años. Tanto los pacientes con FQ como los de DCP disminuyeron la frecuencia de los síntomas de RSC. Posterior a la CEN hubo cambios discretos en la función pulmonar, y sólo los pacientes con enfermedad grave a moderada aumentaron el % de FEV1. La mayoría de los pacientes no ameritaron ingresos posterior a la cirugía. El germen más común encontrado en los cultivos nasofaríngeo y esputo en los pacientes preoperatorios fue la Pseudomonas aeruginosa en el 86%, luego de la CEN hubo un aumento significativo de la colonización por MRSA tanto en los pacientes con FQ como en los de DCP. Más del 50% de los pacientes postquirúrgicos mejoraron su calidad de vida, por lo que la cirugía endoscópica de senos paranasales es efectiva en dicha población en el tratamiento de la rinosinusitis crónica.
Perfil clínico y electromiográfico de las distrofias musculares en República Domincana
Authors: León Roa Freddy De , Polanco Melo Yaneris Cesarina , Herrera Demian , Moreno Reyes Andreina
Published: November 2024

Introducción: Las distrofias musculares son trastornos miogénicos hereditarios caracterizados por una atrofia muscular progresiva y una debilidad de distribución y gravedad variable. La población de Republica Dominicana es fruto de una mezcla de etnias, haciéndola portadora de una herencia cromosómica y ADN diverso, siendo susceptibles a poder presentar cualquier desorden de carácter hereditario.
Material y métodos: Con una muestra de 17 pacientes obtenidos entre septiembre 2019- marzo 2020, se realizó un estudio retrospectivo, descriptivo y transversal, en el cual se hizo una revisión de los expedientes de la clínica de miopatías en la consulta de neurología pediátrica del Hospital Infantil Doctor Robert Reid Cabral, para describir el perfil clínico de los pacientes con distrofia muscular y los hallazgos de electromiografía en los casos que la misma.
Resultados: se encontró que la distribución de la edad correspondió a 5-9 años en un 53%, siendo el sexo masculino, el más frecuente. En el 70.59% presentaron antecedentes familiares de distrofia muscular. Los principales motivos de consulta fueron cansancio y caídas frecuentes.
Conclusión: En los hallazgos de electromiografía, el porcentaje de pacientes que presentó esta prueba con alteraciones fue de 88.24% y sin alteraciones el 11.76%. Esto nos demuestra, la gran utilidad de dicho estudio en el diagnóstico de las distrofias musculares en países donde no se cuenta con estudio molecular, siendo una de las pruebas esenciales en el abordaje diagnóstico de los pacientes con sospecha clínica de dichas patologías.