Metodología para construir una red de investigadores con base en teoría de redes complejas / Methodology for building a network of researchers based on complex network theory / Metodologia para criar uma rede de pesquisadores com base na teoria de redes complexas

RESUMEN Este artículo tiene como objetivo desarrollar una herramienta computacional basada en la teoría de redes y vigilancia científico-tecnológica para fortalecer los procesos de investigación en una institución de educación superior: Corporación Universitaria Empresarial Alexander von Humboldt en Colombia. Se construyeron dos redes: una de investigadores y coinvestigadores, y otra de palabras clave de proyectos de investigación. El análisis de centralidad reveló grupos de colaboración interdisciplinarios y la existencia de investigadores aislados. Los resultados destacan la importancia de fomentar la colaboración entre investigadores y la interdisciplinariedad. Se proponen futuras investigaciones para mejorar la herramienta y su aplicación en la toma de decisiones estratégicas en una Institución de Educación Superior Esta aproximación basada en redes complejas proporciona percepciones sobre la investigación en la institución y su potencial para enriquecer la producción investigativa y el desarrollo tecnológico.

AВSTRАСT The objective of this article is to develop a computational tool based on network theory and scientific-technological surveillance to strengthen research processes in a higher education institution, case study: The Alexander von Humboldt University Business Corporation in Colombia. Two networks were constructed: one of researchers and co-researchers, and another of keywords of research projects. The centrality analysis revealed interdisciplinary collaborative groups and the existence of isolated researchers. The results highlight the importance of fostering collaboration among researchers and interdisciplinarity Future research is proposed to improve the tool and its application in strategic decision-making in a Higher Education Institution. This approach based on complex networks provides insights about research in the institution and its potential to enrich research production and technological development.

RESUMO Este artigo tem como objetivo desenvolver uma ferramenta computacional baseada na teoria de redes e na vigilância científico-tecnológica para fortalecer os processos de pesquisa em uma instituição de ensino superior, estudo de caso da Corporación Universitaria Empresarial Alexander von Humboldt na Colômbia. Foram construídas duas redes: uma de pesquisadores e co-pesquisadores e outra de palavras-chave de projetos de pesquisa. A análise de centralidade revelou grupos colaborativos interdisciplinares e a existência de pesquisadores isolados. Os resultados destacam a importância de promover a colaboração entre pesquisadores e a interdisciplinaridade. Propõe-se uma pesquisa futura para aprimorar a ferramenta e sua aplicação na tomada de decisões estratégicas em uma instituição de ensino superior Essa abordagem de rede complexa fornece percepções sobre a pesquisa na instituição e seu potencial para enriquecer a produção de pesquisa e o desenvolvimento tecnológico.

Application of machine learning in predictive analysis of blood usage for liver transplantation surgery / 中国输血杂志

【Objective】 To explore the application of machine learning in scientific and rational blood preparation and predictive analysis for surgical blood usage before liver transplantation surgery. 【Methods】 Clinical basic information including gender, age, clinical diagnosis and surgical methods of 356 liver transplantation patients were collected. The duration (Time) and preoperative laboratory test results of hemoglobin (Hb), hematocrit (Hct), platelet count (Plt), prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (Fib), total bilirubin (TBIL), albumin (ALB), creatinine (Crea) and total protein (TP), as well as the amount of intraoperative blood transfusion were collected. A machine learning model capable of predicting the risk of massive blood transfusion during liver transplantation surgery was established by Python, and was evaluated to select the optimal predictive model. 【Results】 Among the 7 machine learning models constructed, the logistic regression model performed the best (AUROC: 0.90, F1 score: 0.82), with an accuracy of 79.44% and precision of 79.69%, followed by the random forest classifier (AUROC: 0.87, F1 score: 0.83), with an accuracy of 79.44% and precision of 77.94%. 【Conclusion】 Establishing a machine learning prediction model by Python is of significant clinical importance for scientific blood preparation, predicting the risk of massive blood transfusion and ensuring the safety of blood use in liver transplantation surgery.

GeoCNES: healthcare mapping in Brazilian cities - a computational tool for improved decision-making / GeoCNES: mapeamento da saúde em cidades do Brasil - uma aplicação automatizada para auxiliar na tomada de decisão / GeoCNES: mapeo de la salud en ciudades de Brasil - una aplicación automatizada para ayudar en la toma de decisiones

Abstract Ensuring equitable access to healthcare facilities is crucial for urban well-being, but geographical barriers often impede this access. This paper introduces GeoCNES, an open-source tool developed in Python to address this challenge. GeoCNES establishes a connection to the Brazilian national healthcare establishments register and the census data, to process and geocoding them to automatically generate an interactive map that display the distribution of healthcare facilities and a heat map of the same facilities in Brazilian municipalities. To do so the user must enter the municipality code and facility type, then GeoCNES retrieves, geolocates, and exhibit the information in interactive maps. This paper details the development process, functionalities, and limitations of GeoCNES, demonstrating its application in the Brazilian cities of São Carlos-SP, Rondonópolis-MT, Chapecó-SC, Parnamirim-RN and Parauapebas-PA. While challenges related to data inconsistency were encountered, GeoCNES successfully maps healthcare facilities, offering valuable insights for urban planning and promoting equitable access to healthcare.

Resumo Garantir acesso equitativo a unidades de saúde é crucial para o bem-estar urbano, mas barreiras geográficas muitas vezes impedem esse acesso. Este artigo apresenta o GeoCNES, uma ferramenta de código aberto desenvolvida em Python para enfrentar esse desafio. O GeoCNES se conecta ao CNES e aos dados censitários brasileiros e aplica técnicas de geocodificação para gerar automaticamente mapas interativos que mostram a distribuição de unidades de saúde e sua concentração por meio de mapas de calor, em municípios brasileiros. Os usuários utilizam código do município e o tipo de unidade a ser analisado como parâmetros, e o GeoCNES recupera, geolocaliza e exibe os dados em mapas. Este artigo detalha o processo de desenvolvimento, funcionalidades e limitações do GeoCNES, demonstrando sua aplicação nas cidades de São Carlos-SP, Rondonópolis-MT, Chapecó-SC, Parnamirim-RN e Parauapebas-PA. Embora tenham sido encontrados desafios relacionados à inconsistência de dados, o GeoCNES é capaz de mapear com sucesso as unidades de saúde de diferentes regiões do país e gerar mapas com potencial para auxiliar no planejamento urbano voltado para a equidade na saúde.

Resumen Garantizar un acceso equitativo a las unidades de salud es crucial para el bienestar urbano, pero las barreras geográficas a menudo obstaculizan este acceso. Este artículo presenta GeoCNES, una herramienta de código abierto desarrollada en Python para abordar este desafío. GeoCNES se conecta al CNES y a los datos censales brasileños y aplica técnicas de geocodificación para generar automáticamente mapas interactivos que muestran la distribución de las unidades de salud y su concentración a través de mapas de calor en municipios brasileños. Los usuarios utilizan el código municipal y el tipo de unidad a analizar como parámetros, y GeoCNES recupera, geolocaliza y muestra los datos en mapas. Este artículo detalla el proceso de desarrollo, las funcionalidades y las limitaciones de GeoCNES, demostrando su aplicación en las ciudades de São Carlos-SP, Rondonópolis-MT, Chapecó-SC, Parnamirim-RN y Parauapebas-PA. Aunque se encontraron desafíos relacionados con la inconsistencia de datos, GeoCNES es capaz de mapear con éxito las unidades de salud de diferentes regiones del país y generar mapas con potencial para ayudar en la planificación urbana orientada a la equidad en la salud.

Research and Design of Automatic Test System for Ventilator Performance / 中国医疗器械杂志

Ventilator is an important medical instrument which can replace the function of autonomous ventilation artificially. Its safety and reliability are related to the health and even life safety of patients. With the publishing of the new national standard and international standard for ventilators, higher requirements are put forward for the detection and evaluation. This study mainly introduces an automatic test system for ventilator performance. The test system is based on PF-300 air-flow analyzer of Imtmedical and standard simulation lung. The automatic switch module of simulation lung is developed, and the automatic test system of ventilator is designed using the software development platform based on Python. It can not only automatically test all ventilation control parameters and monitoring parameters of the ventilator, but also realize automatic data recording, form reports and data analysis, and improve the efficiency and quality of inspection, detection and quality control.

Uso de Python para detecção de fake news sobre a covid-19: desafios e possibilidades / Using Python to detect fake news about covid-19: challenges and possibilities / Usar Python para detectar noticias falsas sobre covid-19: desafíos y posibilidades

Este trabalho tem como objetivo relatar estratégias para coleta de um conjunto de dados em português para treinamento de modelos de Inteligência Artificial com vistas a identificar de forma automática fake news sobre covid-19 disseminadas durante a pandemia, a partir de código Python. Analisamos um método de detecção de fake news baseado em uma Rede Neural Recorrente e de aprendizagem supervisionada. Selecionamos um corpus com 7,2 mil textos coletados em websites e agências de notícias por Monteiro et al. (2018) com cada um previamente catalogado como verdadeiro ou falso como conjunto de dados de treino e validação. O modelo foi usado para detecção de fake news sobre covid-19 em um conjunto de notícias coletadas e classificadas pelos autores deste trabalho. O índice de acerto foi de 70%, ou seja, essa foi a taxa de sucesso da detecção dos itens catalogados.

This work aims to report strategies for collecting a dataset in Portuguese for training Artificial Intelligence models to automatically identify fake news about covid-19 disseminated during the pandemic, using Python code. We analyze a fake news detection method based on a Recurrent Neural Network and supervised learning. We selected a corpus with 7,200 texts collected on websites and news agencies by Monteiro et al. (2018), each one of them previously cataloged as true or false as a training and validation dataset. This model was used to detect fake news about covid-19 in a set of news collected and classified by the authors of this work. The hit rate was 70%.

Este trabajo tiene como objetivo informar estrategias para recopilar un conjunto de datos en portugués para entrenar modelos de Inteligencia Artificial para identificar automáticamente noticias falsas sobre covid-19 difundidas durante la pandemia, utilizando el código Python. Analizamos un método de detección de noticias falsas basado en una Red Neuronal Recurrente y de aprendizaje supervisado. Seleccionamos un corpus de 7.200 textos recogidos en webs y agencias de noticias por Monteiro et al. (2018) con cada uno catalogado previamente como verdadero o falso como un conjunto de datos de entrenamiento y validación. El modelo se utilizó para detectar noticias falsas sobre covid-19 en un conjunto de noticias recopiladas y clasificadas por los autores de este trabajo. La tasa de acierto fue del 70%, es decir, esta fue la tasa de éxito de detección de los artículos catalogados.

Coactivación Muscular. Una Propuesta para Calcular su Índice utilizando Python / Muscle coactivation. A proposal to calculate its index utilising Python

Introducción. Fenómenos neurofisiológicos, como la coactivación muscular, se han utilizado para identificar tareas motoras que requieren una mayor estabilidad articular en personas sanas o con trastornos del movimiento. Sin embargo, existen varias formas de calcular el índice de coactivación (IC) muscular. Objetivo. El objetivo de este artículo fue crear una propuesta de procesamiento para calcular el IC muscular mediante el diseño de dos funciones utilizando el lenguaje Python. La primera función calcula el IC utilizando la fórmula planteada por Falconer y Winter, definida como "coactivation index". Se requiere introducir dos señales de músculos antagonistas con una misma longitud de datos y frecuencia de muestreo. Estas señales son previamente normalizadas a la contracción voluntaria máxima utilizando valores promedios rectificados. La segunda función definida como "plot_coactivacion" despliega una figura con los cambios de amplitud de ambos músculos y su área común. Estas funciones fueron creadas con un lenguaje de libre acceso (Python), destacando su clara sintaxis y la amplia gama de librerías en el procesamiento de señales biomédicas.

Introduction. Neurophysiological phenomena, such as muscle coactivation, have been used to identify motor tasks requiring greater joint stability in healthy people or with movement disorders. Nonetheless, there are many ways to calculate the coactivation index (CI). This article aimed to create a processing pipeline to calculate the muscular CI by designing two functions with the Python language. The first function calculates the CI utilising the formula proposed by Falconer and Winter, defined as "coactivation_index". It is required to introduce two signals of antagonist muscles with the same data long and sample frequency. These signals were previously normalised to the maximum voluntary contraction using the averaged rectified values. The second function was defined as "plot_coactivacion", which unfolds a figure that describes the amplitude changes for both muscles and their common area. These functions were designed with a freely accessible language (Python), highlighting its clear syntax and the number of libraries associated with biomedical signal processing.

Arsenicum albumas a treatment for pneumonia in snakes: three serial cases

two Python bivittatussnakes were received at Project Selva Viva, a zoo in Taubaté, Brazil, both presenting respiratory noises and oro-nasal discharge. A thoracic ultrasonographic examination was performed for evaluation on February 25th,2022, which diagnosed the presence of multiple vertical hyperechoic artifactsemerging from the pleural line, coalescing in some of the examined areas, and the presence a hypoechoic structure located in the subpleural region. Another serpent, from the Boa constrictor species, was apprehended and arrived at the same zoo without medical history, showing a low body score. During a thoracic ultrasonographic evaluation realized on April 1st,2022, B lines emerging from the pleural line were found. These vertical reverberating lines are a result of respiratory illness (SOLDATI et al., 2014).Methodology:The report was authorized by the owner of the zoo. All the patients received homeopathic therapy with 2 globules of Arsenicum album30 cH/ BID into the mouth, after being diagnosed with the respiratory condition by the ultrasonographic examination. The medication was chosen according to the similarity with the symptoms. The snakes had a runny nose and hissing breathing noise. Weekly ultrasound scans were performed on the Python bivittatus snakes to follow up on the respiratory condition. Results: On March 04th, it was observed that both snakes showed a reduction in respiratory noises and were more active. Ars 30 cH was maintained BID. On March 25th, both presented significant improvement in the ultrasound images, which showed only A lines, compatible with a healthy lung, and the treatment was suspended. Boa constrictor snake ́streatment started on April 1st. On April 8th, the ultrasonographic examination performed only presented A lines, which are characterized in ultrasound by parallel horizontal lines in the near field with the loss of image continuity in the far field, indicating improvement of the condition (LICHTENSTEIN et al., 2003). Conclusion:Given these results, the homeopathic treatment is an option to be considered for the treatment of respiratory symptoms in snakes, although the duration of the therapy varies based on the stage and chronicity of the disease.

Auxiliary role of Python-based handover database in online teaching activities for medical clerks / 中华医学教育探索杂志

Objective:To evaluate the auxiliary role of the Python-based handover database in online teaching activities for medical clerks and to complete the teaching tasks during the COVID-19 epidemic.Method:Sixteen teachers were randomized into two groups, experimental group and control group, with 8 ones in each group. The experimental group used the self-built handover database, while the control group used the hospital's HIS system. To make multimedia courseware for medical students, suitable cases were screened. The time to acquire cases and picture data, and the index like numbers were statistically analyzed, and the quality of multimedia courseware was scored. All the data were analyzed by SPSS 25.0 statistical software.Results:The time for the two groups of teachers to acquire target cases during making multimedia coursewares were (8.88±3.48) min and (43.50±5.26) min respectively; the time to obtain the pictures were (5.62±1.92) min and (30.25±5.39) min; the numbers of obtained pictures were (11.12±2.17) and (6.12±2.80); and the scores of coursewares were (92.62 ± 4.93) points and (84.75 ± 6.20) points respectively, all with significant differences.Conclusion:The application of the self-made handover database can significantly improve the speed of teachers' access to related teaching data, and also can improve the quality of multimedia courseware.

Construction of Tibetan Medicine Prescription Database for Treating "Gnyan-rims" and Analysis of Their Medication Law Based on Python Language / 中国实验方剂学杂志

Objective:To construct the database of Tibetan medicine prescriptions for "Gnyan-rims" disease， and to explore the invisible medication law of Tibetan medicine in the treatment of "Gnyan-rims" disease， such as prescription compatibility and combination of drug properties. Method:The prescriptions for treating "Gnyan-rims" were retrieved from four Tibetan medical literatures such as <italic>The Four Medical Tantras</italic>，<italic> Kong-sprul-zin-tig，</italic> <italic>Phyag-rdor-gso-rig-phyogs-bsgrigs</italic> and <italic>Sman-sbyor-lag-len-phyogs-bsgrigs</italic>， and the database was constructed under Python code， and the Apriori algorithm and the vector structure model of taste property flavor transformation were used for analysis. Result:According to the characteristics of Tibetan medicine prescription data， with six fields of prescription name， formula， dosage， efficacy， source and original text as the core， a Tibetan medicine treatment "Gnyan-rims" prescription database with functions of cleaning， searching and exporting was established. A total of 7 602 prescriptions were included in the database， among which 598 prescriptions had therapeutic effects of "Gnyan" and "Rims". The results of compatibility analysis showed that Shexiang， Hezi， Honghua， Mukuer Moyao， Tiebangchui， Tianzhuhuang and Bangga were the most frequently used drugs， while the correlation degrees of Shexiang-Mukuer Moyao， Honghua-Tianzhuhuang， Shexiang-Hezi and Shexiang-Tiebangchui were the strongest， and all the drug composition of Wuwei Shexiang pills appeared in the top ten correlations. According to the property analysis of 40 prescriptions containing high-frequency drugs， 19 prescriptions were found to have excessive bitter taste， followed by 9 prescriptions such as Sanchen powders with excessive sweetish taste， and the ratios of sweetish and bitter tastes in six tastes were >35%. The total of sweetish and bitter prescriptions accounted for 70% of the total prescriptions. Among the three flavors， the bitter flavor was the most abundant. The cool effect， dull effect and heavy effect were prominent among the seventeen effects. Conclusion:The prescription database of Tibetan medicine for "Gnyan-rims" can promote the high-quality development of research on prevention and treatment of plague with ethnic medicine. Tibetan medicine treatment of "Gnyan-rims" focuses on the composition of Wuwei Shexiang pills， with the property combination of "cool-bitter and sweet-bitter flavor-cool， dull and heavy"， which mainly treats diseases such as "heat sharp light-mkhris pa-heat". These studies can provide data basis and theoretical reference for the selection of Tibetan medicine prescription and its composition for treating plague.

Preliminary study on exploring the trajectory of patients with COVID-19 by Data mining algorithms / 中华医学科研管理杂志

Objective@#To explore data mining methods and tools for the activity paths of confirmed patients, and provide data analysis tools for epidemic control.@*Methods@#The data used came from the trajectory data of confirmed cases collected by Tencent. The jieba word segmentation and word cloud map function of Python 3.6 were used to calculate the high-frequency vocabulary in the trajectory of confirmed patients. The epidemic prevention and control strategy was developed based on the high-frequency vocabulary.@*Results@#Taking Guangdong Province, the second most confirmed patients in the country, as an example, the key areas of epidemic control obtained through data mining involve Wuhan (epidemiological history), Zhuhai and Guangzhou. The key control activities include family visiting, traveling and shopping. Means of transportation include self-driving, trains and airplanes; the key patients studied were Li and Ding; the symptoms of this patient group were mainly fever and cough.@*Conclusions@#The data mining algorithm in this paper can provide an advantageous tool for epidemic prevention and control, also assist frontline personnel to adjust the deployment of epidemic prevention and control according to their priorities.

Applying Deep Learning in Medical Images: The Case of Bone Age Estimation / 대한의료정보학회지

OBJECTIVES: A diagnostic need often arises to estimate bone age from X-ray images of the hand of a subject during the growth period. Together with measured physical height, such information may be used as indicators for the height growth prognosis of the subject. We present a way to apply the deep learning technique to medical image analysis using hand bone age estimation as an example. METHODS: Age estimation was formulated as a regression problem with hand X-ray images as input and estimated age as output. A set of hand X-ray images was used to form a training set with which a regression model was trained. An image preprocessing procedure is described which reduces image variations across data instances that are unrelated to age-wise variation. The use of Caffe, a deep learning tool is demonstrated. A rather simple deep learning network was adopted and trained for tutorial purpose. RESULTS: A test set distinct from the training set was formed to assess the validity of the approach. The measured mean absolute difference value was 18.9 months, and the concordance correlation coefficient was 0.78. CONCLUSIONS: It is shown that the proposed deep learning-based neural network can be used to estimate a subject's age from hand X-ray images, which eliminates the need for tedious atlas look-ups in clinical environments and should improve the time and cost efficiency of the estimation process.

Physicochemical, Trace Metal Analysis and Fatty Acid Profile of Python regius Fat.

Physicochemical properties, metal analysis and fatty acid profile were carried out on Python regius fat with a view to ascertaining the immense therapeutic claim by traditional medical practitioners. Physicochemical analysis showed that the fat is lower than that of animal fats: cow fat, swine fat and goat fat. Trace metal analysis indicated that it contains 10000ppm Sodium, 620.00ppm Calcium, 94.26ppm Magnesium and 114.00ppm Iron. Python regius fat was found to contain 62% monounsaturated fatty acid, 10% polyunsaturated fatty acid and 28% saturated fatty acid. These results indicated that Python regius fat is a rich source of monounsaturated fatty acids; the healthy edible fat and can also be a good raw material for the soap and cosmetics industry. The results of the study showed that the fat has acid value and therefore less susceptible to rancidity. The saponification value of the fat is 164.09 mg KOH g-l showing its high triglyceride content, indicating its potential usefulness in the soap making industry. Its mineral content makes it a potentially useful source of electrolytes, which function in cellular activities such as enzyme action, muscle contraction, nerve action, blood clotting and water balance. The iodine value of 97.2 mg KOH g-l also indicated a fairly high amount of unsaturated fatty acids. The higher the iodine value, the greater the degree of unsaturation and the greater the susceptibility to oxidative rancidity. Overall, we therefore recommend the fat for use due to its diverse medicinal and industrial potentials.

Biochemical values of red-tailed boa (Boa constrictor) / Valores bioquímicos de jiboia (Boa constrictor)

It was determined the average values of the following blood biochemical indicators of boas (Boa constrictor): glucose, urea, creatinine, aspartate aminotransferase (AST), alanine transaminase (ALT), amylase and lipase, and compared the results obtained concerning sex. A total of 12 Boa constrictor specimens were used, seven males and five females. The average of the biochemical indicators between males and females had no significant difference. The traditional biochemical techniques have been useful to determine these indicators to this species...

Foram determinados os valores médios dos indicadores bioquímicos sanguíneos: glicose, ureia, creatinina, aspartato aminotransferase (AST), alanina aminotransferase (ALT), amilase e lipase de jiboias (Boa constrictor) e comparados os valores das concentrações encontradas entre os grupos de machos e fêmeas. Foram utilizados 12 espécimes de Boa constrictor, dos quais sete machos e cinco fêmeas. A comparação das médias dos indicadores bioquímicos entre os grupos de machos e fêmeas indicou ausência de influência significativa de fatores sexuais. As técnicas bioquímicas tradicionais foram adequadas para a determinação desses indicadores para esta espécie...

Identification of bacteria from the oral cavity and cloaca of snakes imported from Vietnam / 한국실험동물학회지

Reptiles are used for various purposes these days, including public exhibits, medicinal applications, and as laboratory animals. As the international exchange of reptiles has gradually increased, more people have had the opportunity to come in contact with these animals. Snakes typically live in the rhizosphere where various bacterial strains exist and as such they can lead to opportunistic human diseases. When snakes are encountered in veterinary medicine, it is necessary to monitor their microflora. Native microflora of reptiles imported from other countries has not yet been reported in Korea. In this study, oral and cloacae samples were collected from 18 Burmese pythons transported from Vietnam. The specimens were incubated at 37degrees C for 18 h to produce colony growth under aerobic condition and isolated colonies were then identified using a VITEK automated identification system. There were fourteen types of aerobic bacteria isolated from both oral and cloacae samples, nine from only oral specimens, and fifteen from only cloacae specimens. Most bacteria isolated were opportunistic pathogens of humans which therefore have the potential to induce disease in people. Based on the microflora and the prevalence of bacterial strains in snakes, quarantine procedures for reptiles transported internationally should be strengthened. Characterization of the microflora of reptiles with the potential to induce zoonosis should be performed in those used as laboratory animals and to prevent zoonotic outbreaks in the general population as well as among veterinarians.