bluuebunny/crossref_metadata_2025 huggingface dataset:
STUDYING THE PROCESS OF MIXING THE MAIN COMPONENTS OF AN ADSORBENT HYGIENIC PRODUCTS
Authors: Zagorodnyuk L. , Bogdanov V. , Kikalishvili E. , Gaziev H. , Sumskoy D.
Published: September 2024

The results of research on the study of the mixing process to develop the basic composition of an adsorbent hygienic product for keeping animals and birds in accordance with sanitary standards are presented. The possibility of using a rotary ball mill as the most effective apparatus for grinding and mixing and a turbulent mixer, ensuring high homogeneity when mixing the main ingredients of mixtures, is investigated. In result of studying the processes of mixing the main ingredients in the preparation of an adsorbent hygiene product in various mixing units, an effective basic composition of an adsorbent hygiene product is obtained. Moreover, the components chalk M-5, attapulgite and synthetic amorphous silicon dioxide, obtained by mixing in a turbulent mixer and corresponding to the required specific surface area of 12000 cm2/g, which will provide the necessary sorption capacity and thereby ensure a reduction in pathogenic microflora in places where farm animals and poultry are kept. The developed basis of an adsorbent hygienic powder product, due to its significant specific surface area, will provide a high degree of moisture absorption and create the required level of sanitary and hygienic conditions for keeping animals and birds. Creating a favorable climate for keeping farm animals and poultry will significantly prevent the proliferation of bacteria, which will entail a significant reduction in the consumption of antibiotics when raising farm animals, reduce the level of unpleasant odors, and provide a dry environment for keeping animals and birds
INVESTIGATION OF THE EFFECTIVENESS OF THE SCREENING PROCESS ON A VIBRATING SCREEN WITH A COMPOSITE CONSTRUCTION OF A TRELLIS SIEVE
Authors: Khanin S. , Malakhov M. , Mordovskaya O. , Anciferov S.
Published: September 2024

Screens based on the principle of the vibrating effect of the sifting surface on the processed material provide the re-quired separation efficiency and high productivity, which makes them indispensable in various industries, including mining, building materials and many others. The main directions of improvement of vibrating screens are considered. The advantages of trellis sieves of various designs and their disadvantages are shown, indicating the need to find solutions to improve the quality of the screening product produced on them. The description of the developed compo-site structure of the trellis sieve and the predominant features of the implemented two-stage process of separation of material particles by size due to its design are given. The expediency of conducting experimental studies aimed at in-vestigating the screening process of dry bulk materials in a vibrating screen with a trellis screen of the developed de-sign, which allows effectively separating "obstructing" particles, is substantiated. In the Altair EDEM software prod-uct, simulation modeling of the screening process using the method of mathematical planning of the experiment was carried out on models of the composite structure of a trellis sieve and its prototype. For the composite structure of a trellis sieve, a regression dependence of the efficiency of the screening process on the amplitude of the sieve vibra-tions, the width of the slots of the first screening surface and the mass of the supplied material was obtained, and its study was performed. The influence of the considered factors on the values of the function is established, their ration-al values are determined. A comparison of the screening efficiency indicators of the developed design of a trellis sieve with its prototype is carried out.
Transtornos mentais comuns associados a acidentes e violência
Authors: Anjos Rosana Maria Paiva dos , Assis Veronica Fontes de , Alves Rebeca Santana
Published: September 2024

Os transtornos mentais comuns (TMC) são caracterizados por um conjunto de sintomas não psicóticos que afetam diretamente a rotina do paciente e contribuem significativamente para a redução da qualidade de vida do indivíduo afetado. A literatura evidencia que indivíduos com diagnóstico de TMC, são considerados de três a quatro vezes mais propensos a apresentar algum tipo de comportamento violento. Ademais, um histórico de violência física ou psicológica tem influência direta com o TMC, de forma que a violência pode ser um preditor de TMC e os problemas de saúde mental podem ser um fator de risco para se tornar vítima de violência ou, até mesmo, para se tornar o agressor. Objetivo: Analisar pessoas portadoras de TMC e a sua associação com acidentes e violências, segundo respostas registradas em Inquérito de Saúde, realizado no município de São Paulo, em 2014. Metodologia: Trata-se de um estudo observacional, transversal analítico realizado através das respostas obtidas em Inquérito de Saúde, realizada no Município de São Paulo, no ano de 2014. O arquivo foi analisado através do programa STATA, para o gerenciamento dos dados e análise estatística, sendo calculados a razão das chances e intervalos de confiança. Resultados: A um nível de significância de 5% são estatisticamente diferentes a proporção dos grupos com TMC e sem TMC, no relacionado a violência nos referentes à sequelas ou incapacidades resultantes da violência; entre as vítimas de algum tipo de violência, como insulto, humilhação, ameaça, ferimento por algum tipo de arma ou agressão física nos últimos 12 meses. Também no que se refere as vítimas de insultos, humilhações ou xingamentos nos últimos 12 meses; e entre os indivíduos que afirmaram que o(s) problema(s) de saúde decorrente(s) dessa violência limitou/limitaram suas atividades do dia a dia. Conclusão: A razão de chances de transtornos mentais comuns foi duas vezes mais alta entre as vítimas de violência, em comparação com os indivíduos que não relataram terem sofrido algum tipo de violência, essa associação pode ser explicada em razão do TMC estar correlacionado ao mais alto risco condicional de sofrer ou até mesmo provocar a violência.
Diurnal Carbon Monoxide Retrieval from FY-4B/GIIRS Using a Novel Machine Learning Method
Authors: Liang Zhenxing , Gu Dasa , Zhang Mingshuai , Yang Ning , Zhao Chun , Li Rui , Wang Qiaoqiao , Ye Yuxuan , Liu Jian , Li Xin , Liu Rui , Zhang Yisheng , Cao Xiangyunong
Published: September 2024

Carbon monoxide (CO) is one of the primary reactive trace gases in the Earth’s atmosphere and plays an important role in atmospheric chemistry. The Geostationary Interferometric Infrared Sounder (GIIRS) onboard the FY-4 series satellites is currently the only geostationary hyperspectral thermal infrared sensor capable of monitoring the unprecedented hourly CO concentrations in East Asia during both daytime and nighttime. In this study, we presented a radiative transfer model-driven machine learning approach to quickly convert CO spectral features extracted from FY-4B/GIIRS into CO total columns. We built machine learning models for land and ocean regions separately from July 2022 to June 2023, and these models reproduced more than 97.77% (land) and 98.49% (ocean) of the CO column variance in the training set. We estimated the absolute uncertainty of the retrieved CO column based on error propagation theory and found that it is dominated by GIIRS measurement noise. We compared the machine learning retrieval results with optimal estimation and ground-based Fourier transform infrared measurements, and the results reveal the consistent spatial distribution and temporal variation across these different datasets. Our results confirm that the machine learning method has the potential to provide reliable CO products without the computationally intensive iterative process required by traditional retrieval methods. The diel cycle and monthly variation of CO over land and ocean demonstrate the value of GIIRS in monitoring the long-range transport of anthropogenic pollutants and biomass burning emissions.
Influence of the long-term postbiotics prescription on cardiometabolic risk factors in patients with coronary
Authors: Melnychuk I.O. , Kramarova V.N.
Published: September 2024

The aim of this research was to evaluate the influence of long-term postbiotics prescription on CardioMetabolic Risk Factors (CMRF) in patients with Coronary Artery Disease (CAD) and Atrial Fibrillation (AF). 124 patients with CAD and AF paroxysm patients were divided by stratified randomization 1:3 into two groups: I (31 patients) and II (93 patients). Stratification was done according to the patient's age, gender, body mass index, and Total Cholesterol (TC). All patients received Standard Therapy (ST), according to the latest European Society of Cardiology guidelines: β-blockers, HMG-CoA-inhibitors (statins), anticoagulants, and, if necessary, angiotensin-converting enzyme inhibitors or angiotensin-II receptor blockers, calcium antagonists, diuretics, and/or antiarrhythmics. The I group patients’ received ST and postbiotic prescription during 6 months: rebamipide (2-(4-chlorobenzolamino)-3-[2(1H))-quinolon-4-yl] propionic acid) (100 mg 3 times a day) and glycine (100 mg 3 times a day). The II group patients received only ST. All patients were examined two times: during the initial investigation and after 6 months of treatment. After treatment in I group patients’ a significant decrease in TC (by 10.00%), low density lipoproteins (by 19.50%), Apolipoprotein B (by 12.92%), Interleucin-6 (by 12.40%), C-reactive protein (by 15.89%), TriMethylAmine (TMA) (by 19.32%), TriMethylAmine-N-Oxide (TMAO) (by 27.24%) was found (p<0.05) versus II group patients. After treatment all patients had significant improvement in CMRF (p<0.05): TC (by 44.01%), low density lipoproteins (by 52.90%), Interleucin-6 (by 27.52%), C-reactive protein (by 20.13%), TMA (by 14.66%), TMAO (by 33.91%), and significant increase in TMA/TMAO (by 23.45%), but I group got better values. In conclusion, long-term (6 months) postbiotics (propionic acid and glycine) prescription has a marked positive influence on CMRF in patients with CAD and AF.

Keywords: glycine, propionic acid, arrhythmia, cardiovascular disorders, dyslipidemia, inflammation.
Análisis de la comunicación alumno-profesor en la enseñanza universitaria
Authors: Dávila-Cisneros Juan Diego , Fernández-Celis María del Pilar , Tello-Flores Raquel Yovana , Puican-Carreño Alfredo
Published: September 2024

La comunicación entre alumnos y profesores es significativa para el éxito del proceso de aprendizaje. El objetivo del artículo es analizar la dinámica de la comunicación alumno-profesor en la enseñanza universitaria. El método utilizado fue la revisión sistemática, con alcance exploratorio, no experimental y transeccional enfocada en diversos métodos, procedimientos y tecnologías que han influido en la dinámica de la comunicación universitaria. También trata el impacto de la educación virtual, especialmente durante la pandemia del COVID-19, y cómo la inteligencia artificial ha influido en esta dinámica. Se resalta la necesidad de adaptarse a los desafíos que surgen en entornos virtuales, como la educación a distancia y la importancia de la comunicación efectiva entre profesores y alumnos en la educación universitaria, enfatizando la relevancia de estrategias innovadoras y tecnologías emergentes para enriquecer la interacción en el aula y adaptarse a entornos virtuales.
La gestión de la calidad y los objetivos de desarrollo sostenible en universidades latinoamericanas
Authors: Izquierdo-Morán Aída Margarita , Mercedes-Ramos Marcos Antonio , Álvarez-Laborde Arturo Omar , Echeagaray-Solorza Neiba Yadira
Published: September 2024

La excelencia universitaria, orientada hacia la mejora continua, debe incorporar la responsabilidad social universitaria, por su contribución con los Objetivos de Desarrollo Sostenible (ODS). Por lo tanto, es esencial integrar estos objetivos en el sistema de gestión de calidad de las universidades. Es por ello que, este artículo tiene como objetivo analizar los desafíos y perspectivas de la integración de la gestión de calidad y los ODS en las universidades de América Latina. En este sentido, se lleva a cabo una revisión bibliográfica de carácter exploratorio, no experimental y transversal, la cual concluye con los beneficios e impactos de esta integración para las universidades latinoamericanas.
B-Learning para la innovación en la gestión pedagógica de los docentes
Authors: Espinoza Espinoza Víctor Oswaldo
Published: September 2024

La virtualización acelerada de la educación que generó la pandemia ha forjado cambios paradigmáticos formativos, propiciando el desarrollo de modelos de aprendizaje híbrido que combinan herramientas y recursos digitales con la enseñanza presencial. Por consiguiente, se presenta este articulo con el propósito de describir cómo el enfoque B-learning ha coadyuvado a la innovación de la gestión pedagógica de docentes. Metodológicamente es una investigación documental bibliográfica, guiada por el método hermenéutico. El B-learning, al estar fundamentado en la interacción y la comunicación es una herramienta capaz de innovar y transformar la gestión pedagógica de los docentes, favoreciendo su desarrollo profesional en correspondencia con las demandas de la sociedad digital. Además, lo incita al despliegue de metodologías afines al aprendizaje de doble bucle, las cuales retan al estudiante a cuestionar y reflexionar sus estructuras mentales, creencias y suposiciones que subyacen a los actos inmersos en su propio proceso pedagógico y formativo.
Estrategias tributarias utilizadas por distintos países para prevenir y detectar la evasión tributaria
Authors: Guamán-Reinoso Víctor Fabián , Andrade-Amoroso Rolando Patricio
Published: September 2024

En un contexto global de evolución de políticas fiscales, se analizó la efectividad de estrategias tributarias internacionales en la prevención de la evasión. Con métodos cualitativos y documentales, se examinaron reformas fiscales en EE.UU. y la UE, así como acciones en América Latina. Los resultados revelaron avances en el intercambio de información en la región, especialmente en Colombia y México. Se identificaron prácticas exitosas, como la fiscalización basada en tecnología en México, la colaboración interinstitucional en el Reino Unido y el anticipo del pago del impuesto a la renta en ecuador. Se destacó la necesidad de cooperación internacional y medidas disuasorias efectivas, como en Alemania y Suiza, para combatir la evasión. Se concluyó que, ante la globalización y los desafíos fiscales, fortalecer la recaudación y la transparencia son esenciales, requiriendo reformas que promuevan la equidad y la eficiencia tributaria.
Implementación de las NIIF en PYMES ecuatorianas: retos y transformaciones en sus prácticas contables
Authors: Solórzano-Cedeño Pamela Maribel , Vásconez-Acuña Lenyn Geovanny
Published: September 2024

El estudio sobre la adopción de las NIIF para PYMES en Ecuador se enfocó en comprender su impacto en las empresas del país. Utilizando técnicas como la exploración bibliográfica y el análisis documental, se identificaron los desafíos y cambios derivados de esta adopción. Se encontró que las NIIF han mejorado la transparencia y comparabilidad de la información financiera, aunque su implementación ha sido compleja debido a la falta de capacitación y la crisis económica. Las empresas han tenido que ajustar sus procesos operativos y contables, y han experimentado cambios en la estructura patrimonial. A pesar de los desafíos, la adopción de las NIIF ha sido fundamental para alinear los estándares contables locales con los internacionales, fortaleciendo así la posición de las PYMES en el mercado ecuatoriano
Auditoría forense en el contexto latinoamericano: comparación de prácticas y normativas
Authors: Vásquez Tacuri Gema Yamilet , Narváez-Zurita Cecilia Ivonne
Published: September 2024

Este estudio sobre la Auditoría Forense en América Latina ha revelado la importancia en la detección y prevención del fraude financiero en la región. Con el objetivo de explorar su aplicación, alcance y desafíos, se utilizó un enfoque comparativo que analizó prácticas y regulaciones en diferentes países latinoamericanos. Se destacó la falta de una normativa específica en algunos lugares, lo que plantea desafíos para los auditores forenses. Sin embargo, se identificaron oportunidades para mejorar la eficacia de la Auditoría Forense mediante la adopción de normativas internacionales y la capacitación especializada. Los resultados enfatizan la necesidad de fortalecer el control interno en las organizaciones y la importancia de la colaboración entre entidades gubernamentales y auditores forenses para combatir el fraude y la corrupción en la región. En conclusión, la Auditoría Forense surge como una herramienta decisiva en la construcción de sociedades más transparentes y resistentes frente a los delitos financieros
El rol determinante de la educación tributaria en el cumplimiento del impuesto a la renta
Authors: Yupangui-Castelo Johana Alexandra , Torres-Palacios Mireya Magdalena
Published: September 2024

La educación tributaria es esencial para fortalecer la comprensión de los deberes fiscales, formando ciudadanos responsables y mejorando la calidad de vida. Este estudio se centra en examinar el papel de la educación tributaria en el cumplimiento del impuesto a la renta en Ecuador, considerando su influencia en el conocimiento fiscal, la conciencia ciudadana y las prácticas de cumplimiento tributario. Siguiendo un enfoque no experimental y cualitativo, se analizó esta relación sin intervenir o manipular las variables. Se identificó la necesidad de abordar las deficiencias en el sistema tributario actual, sobre todo en el control de la evasión fiscal. Las reformas recientes en Ecuador recalcan la importancia de revisar con frecuencia las leyes fiscales para garantizar una recaudación justa. Desarrollar programas educativos tributarios y construir una cultura tributaria sólida en las pequeñas empresas es concluyente para el desarrollo económico sostenible del país.
El marketing de influencers como estrategia efectiva en la era digital: beneficios y desafíos
Authors: Mogrovejo-Campoverde Oscar Benito , Rivera-Costales José Alberto , Jácome-Ortega Mariella Johanna
Published: September 2024

El marketing de influencers ha tenido un impacto significativo en la visibilidad de los negocios en Cuenca, Ecuador. El objetivo de esta investigación es evaluar el impacto de las campañas promocionales con influencers en la visibilidad de negocios gastronómicos en Cuenca. Se empleó metodología descriptiva. Los resultados mostraron una correlación positiva entre la exposición a recomendaciones de influencers y la visita a restaurantes, indicando su influencia en los consumidores. Aunque las recomendaciones personales siguen siendo importantes, las redes sociales juegan un papel significativo en la búsqueda de opciones gastronómicas. Sin embargo, persiste la incertidumbre sobre la efectividad de las campañas con influencers, señalando la necesidad de educación sobre el tema. Por ende, la presencia sólida en plataformas digitales es crucial para los restaurantes, destacando la importancia de adaptarse a las tendencias digitales para garantizar visibilidad y atractivo para el público.
Evaluación de la calidad de los servicios en la Empresa Pública de Movilidad, Latacunga, Ecuador
Authors: Villacis-López Juan Fernando , Romero-Fernández Ariel José
Published: September 2024

El objetivo general de la investigación fue evaluar la calidad de los servicios en la Empresa Pública de Movilidad, Latacunga, Ecuador. Desde la perspectiva cuantitativa, la investigación de desarrolló apoyada en una tipología bibliográfica, descriptiva y de campo. La población de estudio se conformó por 220 trabajadores de la EPMOL y la cantidad de clientes externos se tomó la cantidad atendida en el mes de mayo de 2024 un total 6245. Luego se determinó la muestra de cada uno de los estratos mencionados, aplicando la formula respectiva, y se obtuvo 68 trabajadores y 97 clientes externos.  A los cuales se les aplicó una encuesta. Se concluye que, la evaluación de la calidad es una necesidad para el sostenimiento de las empresas pues les permite contar con información para el mejoramiento de su gestión y desempeño.
Gestión de pérdidas incobrables del sector productivo del Azuay: análisis de normativas contables y financieras
Authors: Cuenca-Panamá Olga Beatriz , Vásconez-Acuña Lenyn Geovanny
Published: September 2024

El objetivo es analizar la gestión de pérdidas incobrables en el sector productivo del Azuay: análisis de normativas contables y financieras. De tipo descriptivo para comprender la gestión empresarial y las regulaciones contables y tributarias relevantes. Los resultados resaltan que la adopción de las NIIF en Ecuador ha generado mejoras en la transparencia y calidad de la información financiera. Se destaca la importancia de alinear las prácticas contables locales con estándares internacionales para fortalecer la confianza en el mercado financiero local. Además, se concluye que la correcta integración de métodos contables y normativas tributarias es esencial para garantizar la precisión de la información financiera y el cumplimiento de las obligaciones fiscales.
Optimización de sistemas de contabilidad de costos en empresas manufactureras en Ecuador: un enfoque integrado
Authors: Duran-Chacho Fernanda Lucia , Moreno-Narváez Verónica Paulina
Published: September 2024

La investigación tiene por objetivo analizar la optimización de sistemas de contabilidad de costos en empresas manufactureras en Ecuador. A través de encuestas a 84 empleados de estas empresas, se evaluaron los métodos de costeo y la percepción de la precisión del sistema contable. Los resultados resaltaron la diversidad de funciones en los departamentos de contabilidad de costos, con roles como contadores, analistas de costos y supervisores predominantes. Las empresas revisan sus costos de manera mensual utilizando métodos como el Costeo Directo y el Costeo Basado en Actividades. Sin embargo, la percepción general de la precisión contable fue negativa, señalando desafíos en la asignación de costos indirectos y la comunicación interdepartamental. Se concluye que mejorar la precisión en la asignación de costos y fortalecer la colaboración entre departamentos son aspectos críticos para una gestión financiera estratégica y eficiente.
Integración del internet de las cosas en los sistemas contables en el sector comercial
Authors: Raúl Flores-Tunja Jonnathan Raúl , Zapata-Sánchez Pedro Enrique
Published: September 2024

La integración del Internet de las Cosas (IoT) en los sistemas contables está transformando la gestión de datos financieros, mejorando la eficiencia y precisión. El objetivo consiste en evaluar el impacto de la integración del internet de las cosas en los sistemas contables de las empresas comerciales de la ciudad de Quito, Ecuador. De metodología descriptiva. Los resultados muestran que el 97.22% de los encuestados están familiarizados con el IoT, con una adopción variada en las organizaciones, el 38.89% ha implementado IoT en menos de un año y el 30.56% por más de cinco años. Los principales beneficios percibidos son la mejora en la eficiencia operativa (55.56%) y la reducción de costos (25%). Las conclusiones destacan que la integración del IoT permite una toma de decisiones más ágil y precisa, y que la ciudad de Quito tiene un potencial alto para modernizar sus sistemas contables.
Impacto de las Normas Internacionales de Información Financiera en valoración de activos intangibles
Authors: Peñaloza-Argudo Juana Mariela , Jaramillo-Calle Carmen Yolanda
Published: September 2024

El objetivo del estudio consiste en analizar el impacto de las NIIF en la valoración de activos intangibles en las empresas comerciales de la ciudad de Cuenca, Ecuador. De tipo descriptiva. Se aplicó una encuesta a 32 contadores de empresas de la ciudad de Cuenca, Ecuador. Los resultados revelan que la mayoría de contadores encuestados en Cuenca tienen un nivel aceptable de familiaridad con las NIIF y no todos han implementado estas normativas. La valoración de activos intangibles sigue siendo desafiante, en la medición y valoración. A pesar de algunos obstáculos, el impacto general de las NIIF en la competitividad y la gestión interna es positivo para la mayoría, aunque se necesita más capacitación continua y claridad en las directrices para mejorar su aplicación y comprensión. Las conclusiones resaltan la valoración de activos intangibles como un desafío global. Se sugiere promover la transparencia y eficacia en la contabilidad.
TRABALHO E EDUCAÇÃO EM 60 ANOS DE RESISTÊNCIA AO GOLPE MILITAR
Authors: Aranha Antônia Vitória Soares , Lopes Frederico Alves , Zucon Camila Ramos de Siqueira , Santos Caio César Siqueira
Published: September 2024

Interview carried out with professor Antônia Vitória Soares Aranha, in July 2023, covering her family, educational, political and ethical trajectory, discussing the fight for truth, memory and justice against the military coup and dictatorship in Brazil
Defense of thesis works in the specialty «Water supply, wastewater disposal, construction systems for water resources protection»
Authors: Стрелков А.К. , Теплых С.Ю. , Горшкалев П.А. , Черносвитов М.Д.
Published: September 2024

Приведены качественные и количественные характеристики и показатели в области защиты диссертационных работ с 1984 до середины 2024 г. Рассмотрены временные закономерности, пики и спады в научных работах по научной специальности 2.1.4 «Водоснабжение, канализация, строительные системы охраны водных ресурсов». Приведены примеры правильных формулировок элементов научной новизны в авторефератах диссертаций. Выполнен анализ категорий научной новизны, как общей, так и в методах очистки природных и сточных вод. Представлена организационно-правовая структура защит диссертационных работ. Приведены рекомендации по определению границ между элементами научной новизны.

The qualitative and quantitative characteristics and indicators in the field of thesis works defense from 1984 to mid-2024 are presented. The time patterns, peaks and decays in scientific papers in the specialty 2.1.4 «Water supply, wastewater disposal, construction systems for water resources protection» are analyzed. Examples of correct formulations of elements of scientific novelty in the thesis synopses are given. An analysis of the categories of scientific novelty, both in general and in the methods of natural and wastewater treatment, is performed. The organizational and legal structure of thesis works defense is presented. Recommendations for defining the boundaries between the elements of the scientific novelty are given.
Justification for the use of sludge of biologically treated wastewater in the production of ceramic materials
Authors: Стрелков А.К. , Теплых С.Ю. , Теплых Е.А. , Поршина Е.Г.
Published: September 2024

Загрязнения производственных сточных вод представляют собой остатки обрабатываемого сырья и реагентов, участвующих в технологическом процессе при очистке. Рассмотрены условия образования и свойства осадков биологически очищенных сточных вод и вылежанного осадка. Приведены основные направления утилизации и свойства осадков городских сточных вод, а также теоретическое обоснование использования вылежанных осадков биологических очистных сооружений при производстве керамических материалов. Представлены следующие характеристики осадков городских сточных вод: фракционный состав, динамика изменения массы различных фракций осадка при его термообработке, химический состав.

Pollution in industrial wastewater comprises the scraps of processed raw materials and chemicals used in the treatment process. The conditions of the generation and properties of sludge of wastewater biological treatment and of matured sludge are considered. The properties of municipal wastewater sludge and main ways of utilization are given, as well as theoretical justification for the use of matured sludge from biological wastewater treatment facilities in the production of ceramic materials. The following characteristics of municipal wastewater sludge are presented: fractional makeup, dynamic pattern of the mass of various sludge fractions in the process of thermal processing, chemical composition.
Baby Cry Sound Detection: A Comparison of Mel Spectrogram Image on Convolutional Neural Network Models
Authors: Junaidi Ridha Fahmi , Faisal Mohammad Reza , Farmadi Andi , Herteno Rudy , Nugrahadi Dodon Turianto , Ngo Luu Duc , Abapihi Bahriddin
Published: September 2024

Baby cries contain patterns that indicate their needs, such as pain, hunger, discomfort, colic, or fatigue. This study explores the use of Convolutional Neural Network (CNN) architectures for classifying baby cries using Mel Spectrogram images. The primary objective of this research is to compare the effectiveness of various CNN architectures such as VGG-16, VGG-19, LeNet-5, AlexNet, ResNet-50, and ResNet-152 in detecting baby needs based on their cries. The datasets used include the Donate-a-Cry Corpus and Dunstan Baby Language. The results show that AlexNet achieved the best performance with an accuracy of 84.78% on the Donate-a-Cry Corpus dataset and 72.73% on the Dunstan Baby Language dataset. Other models like ResNet-50 and LeNet-5 also demonstrated good performance although their computational efficiency varied, while VGG-16 and VGG-19 exhibited lower performance. This research provides significant contributions to the understanding and application of CNN models for baby cry classification. Practical implications include the development of baby cry detection applications that can assist parents and healthcare provide.
Optimization of Backward Elimination for Software Defect Prediction with Correlation Coefficient Filter Method
Authors: Muhammad Noor  , Radityo Adi Nugroho  , Setyo Wahyu Saputro  , Rudy Herteno  , Friska Abadi
Published: September 2024

Detecting software defects is a crucial step for software development not only to reduce cost and save time, but also to mitigate more costly losses. Backward Elimination is one method for detecting software defects. Notably Backward Elimination may remove features that may later become significant to the outcome affecting the performance of Backward Elimination. The aim of this study is to improve Backward Elimination performance. In this study, several features were selected based on their correlation coefficient, with the selected feature applied to improve Backward Elimination final model performance. The final model was validated using cross validation with Naïve Bayes as the classification method on the NASA MDP dataset to determine the accuracy and Area Under the Curve (AUC) of the final model. Using top 10 correlation feature and Backward Elimination achieve an average result of 86.6% accuracy and 0.797 AUC, while using top 20 correlation feature and Backward Elimination achieved an average result of 84% accuracy and 0.812 AUC. Compare to using Backward Elimination and Naïve Bayes respectively the improvement using top 10 correlation feature as follows: AUC:1.52%, 13.53% and Accuracy: 13%, 12.4% while the improvement using top 20 correlation feature as follows: AUC:3.43%, 15.66% and Accuracy: 10.4%, 9.8%. Results showed that selecting the top 10 and top 20 feature based on its correlation before using Backward Elimination have better result than only using Backward Elimination. This result shows that combining Backward Elimination with correlation coefficient feature selection does improve Backward Elimination’s final model and yielding good results for detecting software defects.
The Comparison of Extreme Machine Learning and Hidden Markov Model Algorithm in Predicting The Recurrence Of Differentiated Thyroid Cancer Using SMOTE
Authors: Aida Nor , Saragih Triando Hamonangan , Kartini Dwi , Nugroho Radityo Adi , Nugrahadi Dodon Turianto
Published: September 2024

Differentiated thyroid cancer is the most common type of thyroid cancer; the types in this category are papillary, follicular, and hurthel cell carcinoma. Up to 20% of DTCs will experience recurrence, although this figure reduces to 5% in low-risk patients. There is still little research on thyroid cancer prediction using a machine learning approach, especially the prediction recurrence of DTCs. This research aims to compare the performance of the Extreme Learning Machine and the Hidden Markov Model using SMOTE in predicting the recurrence of DTCs. The dataset used in this research is differentiated thyroid cancer recurrence from Kaggle. This research methodology comprises preprocessing, data sharing, SMOTE, ELM and HMM modeling algorithms, and evaluation. ELM with SMOTE gets the best results at a ratio of 90:10 with 35 hidden neurons that get an accuracy value of 1.00, precision 1.00, recall 1.00, and AUC 1.00. ELM modeling gets the best results at a ratio of 90:10 with 45 hidden neurons that get an accuracy value of 1.00, precision 1.00, recall 1.00, and AUC 1.00. HMM modeling gets the best value at a ratio of 70:30 with two hidden states and two iterations, which get an accuracy value of 0.8696, precision 0.8696, recall 0.7944, and AUC 0.9575. Last, HMM modeling with SMOTE gets the best results at a ratio of 60:40 with two hidden states and two iterations, with an accuracy value of 0.8696, precision of 0.8832, recall of 0.7848, and AUC of 0.9174. Based on the results of this study, it can be concluded that ELM with SMOTE gets the best performance, followed by ELM without SMOTE, HMM without SMOTE, and finally, HMM with SMOTE. The implication is that ELM with SMOTE can produce high accuracy in predicting the recurrence of DTCs.
Unlocking Early Detection and Intervention Potential: Analyzing Visual Evoked Potentials (VEPs) in Adolescents/Teenagers with Narcotics Abuse Tendencies from the TelUnisba Neuropsychology EEG Dataset (TUNDA)
Authors: Wijayanto Inung , Sulistyo Tobias Mikha , Nur Pratama Yohanes Juan , Safitri Ayu Sekar , Rahmaniar Thalita Dewi , Sa’idah Sofia , Hadiyoso Sugondo , Wibowo Raiyan Adi , Kurnia Ismanto Rima Ananda , Putri Athaliqa Ananda , Khasanah Andhita Nurul , Diliana Faizza Haya , Azzahra Salwa , Gadama Melsan , Utami Ayu Tuty
Published: September 2024

Narcotics abuse has extensive negative impacts on individuals, families, and society, including physical harm to organs and mental health disorders. Addressing teenage narcotics problems requires collaborative efforts involving educational institutions, families, and psychologists. Currently, narcotics has increasingly targeted teenagers, becoming a serious issue that demands special attention in prevention and treatment. Handling narcotic problems at the adolescent level necessitates close collaboration among educational institutions, families, and the community, including psychologists. Emphasizing the importance of early detection and prevention, this study proposes a method to detect the possibility of narcotic abuse in adolescents using the Go/No-Go Association Task (GNAT) test designed by psychologists. The study introduced the TelUnisba Neuropsychology EEG Dataset (TUNDA), an open EEG dataset with data on the emotional and habitual aspects of drug abuse in Indonesia, classified into "normal" and "risk" by psychologists. The processed EEG signal is the visual evoked potential (VEP) within 1000 milliseconds following the visual stimulus onset. The data is classified as “slow” and “fast” based on respondent's responses using MobileNetV2 architecture. Results showed MobileNetV2 achieved the highest accuracy for both normal and risk categories, with accuracies of 0.86 and 0.85 respectively. This study obtained ethical clearance and received funding support from Telkom University and Universitas Islam Bandung, with technical assistance from the Smart Data Sensing Laboratory. The authors declare no conflicts of interest related to this study.
A Framework for Prediction of Type II Diabetes through Ensemble Stacking Model
Authors: Patil Rohini , Anant Patil  , Surekha Janrao  , Sandip Bankar  , Kamal Shah
Published: September 2024

In order to prevent long term complications of diabetes its early diagnosis is crucial. With Increasing advances in Artifical Intelligence (AI) and Machine Learning(ML) researchers are increasingly focusing on using them for early diagnosis of diseases.AI and ML has significant potential for early prediction of type 2 diabetes. In this article we have described a  ML based framework for prediction of type 2 diabetes -Improved Ensemble Learning with Dimensionality Reduction Model (IELDR) and discussed its result. An IELDR algorithm is an Auto encoder-based feature extraction method with ensemble learning. The experiments were carried out using the LS_diabetes dataset. LS_diabetes dataset containing 374 records with 35 features related to lifestyle and stress. Accuracy, precision, specificity, sensitivity, f1 score, roc and Mathew correlation coefficient (MCC) were measured. After this results were tested  and validated using Diabetes_2019 dataset and PIMA diabetes dataset. The IELDR model showed results in terms accuracy, precision, specificity, sensitivity, f1 score, roc and Mathew correlation coefficient (MCC) of 98.67%, 95.24%, 100%, 98.18%, 97.56%, 99.09% and 0.97 respectively. In comparison with PIMA diabetes dataset, LS_diabetes dataset showed  an accuracy, precision, sensitivity, specificity, f1-score,roc and mcc value by 17.96%,13.15% 40.22%,5.59%,28.38%,22.09% and 0.4 respectively. The IELDR model achieved the best result on the LS_diabetes dataset showed an accuracy, sensitivity, roc and mcc value improved by 1.82%, 1.58%, 3.01%and 0.04 % compared to the Diabetes_2019 dataset .This proposed IELDR system predicts the risk of type 2 diabetes in a healthy person based on the person’s current lifestyle pattern. This system can be  helpful for early prediction of type2 diabetes.
Deep learning Methods for ECG-Based Heart Disease Detection
Authors: Irsyad Akhmad , Widagdo Putut Pamilih , Widagdo Putut Pamilih , Wardhana Reza
Published: September 2024

Cardiovascular disease (CVD) continues to be a primary cause of death globally, and early detection plays a critical role in improving patient outcomes. This research introduces the development of a deep learning model designed to automatically categorize heart diseases using Electrocardiogram (ECG) data. The model utilizes a 1D Convolutional Neural Network (CNN) structure and makes use of the MIT-BIH Arrhythmia dataset from Physionet. The dataset was split into training, validation, and testing subsets. Our proposed design incorporates convolutional layers, max-pooling, ReLU activation functions, and dropout layers to prevent overfitting. Comparative assessment against conventional methods such as logistic regression and Support Vector Machines (SVM) shows superior performance, achieving an accuracy of 98.29%, recall of 87.60%, precision of 93.75%, and F1 score of 90.37%. The potential of deep learning to enhance the accuracy and efficiency of diagnosing CVD from ECG data is highlighted in this study, introducing a reliable tool for clinical application.
Dental Caries Segmentation using Deformable Dense Residual Half U-Net for Teledentistry System
Authors: Trie Maya Kadarina
Published: September 2024

Clinical practitioners’ workload and challenges are significantly reduced by classifying, predicting, and localizing lesions or dental caries. In recent research, a high-reliability diagnostic system within deep learning models has been implemented in a clinical teledentistry system. In order to construct an efficient, precise, and lightweight deep learning architecture, it is dynamically structured. In this paper, we present an efficient, accurate, and lightweight deep learning architecture for augmenting spatial locations and improving the transformation modeling abilities of fixed-structure CNNs. Deformable Dense Residual (DDR) enhances the efficacy of the residual convolution block by optimizing its structure, thereby mitigating model redundancy and ameliorating the challenge of vanishing gradients encountered during the training stages. DDR Half U-Net presents notable advancements to the simplified U-Net framework across three pivotal domains: the encoder, decoder, and loss function. Specifically, the encoder integrates deformable convolutions, thereby enhancing the model's capacity to discern features of diverse scales and configurations. In the decoder, a sophisticated arrangement of dense residual connections facilitates the fusion of low-level and high-level features, contributing to comprehensive feature extraction. Moreover, the utilization of a weight-adaptive loss function ensures equitable consideration of both caries and non-caries samples, thereby promoting balanced optimization during training.
Implementation of Extreme Learning Machine Method with Particle Swarm Optimization to Classify of Chronic Kidney Disease
Authors: Muhammad Mursyidan Amini
Published: September 2024

Kidney Disease (CKD) appears as a pathological condition due to infection of the kidneys and blockages due to the formation of kidney stones. In the Indonesian context, kidney disease is the second most common disease after heart disease based on BPJS Health data. Notably, in this scenario, medical practitioners and individuals with specialized knowledge in the field are still faced with challenges in effectively classifying CKD cases, thereby making them vulnerable to erroneous diagnostic conclusions. The main objective underlying this particular research effort revolves around increasing the level of accuracy that characterizes the CKD classification process by orchestrating the incorporation of Particle Swarm Optimization (PSO) techniques into the operational framework of Extreme Learning Machines (ELM) with the aim of ensuring optimal results. Configuration of input weights and critical biases to achieve superior diagnostic results. The results obtained from the investigation process include many numerical parameters including but not limited to determining the ideal number of hidden nodes set at 11, population size 80, identification of the most preferred number of iterations denoted by the Best value of 20, aggregate inertia weight assessed at 0.5, along with the constants 1 (c1) and 2 (c2) each registering a value of 1, culminating in the achievement of an accuracy metric pegged at an impressive level of 98.50%. Consequently, the implications obtained from this empirical investigation strengthen the assertion that the use of PSO optimization strategies within the operational framework of ELM has the potential to yield major advances in the classification evaluation domain related to CKD diagnosis.
A RARE CASE OF MISDIAGNOSED SINUS VENOSUS ATRIAL SEPTAL DEFECT
Authors: Stasilo Radoslavas
Published: September 2024

Sinus venosus atrial septal defects (SVASDs) are rare congenital cardiac abnormalities (5%–10% of all ASDs). They occur at the posterior aspect of the interatrial sep­tum. In this case report we present a case of a patient with heart insufficiency and misdiagnosed SVASD. A 34-year-old man presented to emergency department after one of the implantable cardioverter-defibrillator (ICD) electro­des was observed in the left ventricle and SVASD was suspected. Patient was treated conservatively.
A CASE REPORT: PHEOCHROMOCYTOMA-INDUCED HYPERTENSION IN A 65-YEAR-OLD PATIENT – AN ANESTHESIOLOGIST’S PERSPECTIVE
Authors: Visockas Lukas , Kireilis Benas , Alksnytė Aurelija , Kupčinskienė Kristina , Macas Andrius , Daukša Albertas
Published: September 2024

Pheochromocytoma is a rare adrenal gland tumor that produces excessive amounts of adrenaline and noradre­naline, leading to a surge in blood pressure. This condi­tion often goes undiagnosed due to its infrequency and diverse symptom presentation, surgery is considered as the definitive treatment. We report a 65-year-old male patient, initially referred to an endocrinologist for further evaluation of a mass in the right kidney discovered via Magnetic Resonance Imaging (MRI), leading to a diagno­sis of pheochromocytoma. Following a successful surgi­cal procedure and peri-operative period, the patient was discharged and advised to return to the hospital 1 month after the surgery and every 1 year for regular follow-ups.
LĖTINIS BRONCHITAS: KLINIKINIAI POŽYMIAI, DIAGNOSTIKA, GYDYMO BŪDAI
Authors: Griškutė Patricija
Published: September 2024

Lėtinis bronchitas – tai lėtai prasidedantis ir progresuo­jantis difuzinis bronchų gleivinės uždegimas. Riziką sirgti lėtiniu bronchitu didina rūkymas, oro užterštumas, a1-antitripsino stoka, nuolat pasikartojančios infekci­nės plaučių ligos bei prasta mityba. Sergantieji lėtiniu bronchitu dažniausiai skundžiasi dusuliu. Lėtinio bron­chito diagnostikai atliekama spirometrija, krūtinės ląs­tos rentgeninis tyrimas, bendras kraujo ir kraujo dujų tyrimas, citologinis ir mikrobiologinis skreplių tyrimas bei bronchoskopija. Lėtinio bronchito gydymui svarbūs gyvenimo būdo pokyčiai. Medikamentiniam gydymui naudojami bronchodilatatoriai, sunkesniais atvejais pa­pildomai skiriami gliukokortikosteroidai.
OBSESINIS-KOMPULSINIS SUTRIKIMAS: SIMPTOMAI, ETIOLOGIJA, GYDYMAS
Patricija Griškutė
Authors: Griškutė Patricija
Published: September 2024

Obsesinis-kompulsinis sutrikimas (OKS) yra neurop­sichiatrinis sutrikimas, kuriam būdingos ilgalaikės pa­sikartojančios mintys (obsesijos) ir (ar) kompulsinė veikla. OKS patofiziologija nėra tiksliai žinoma, tačiau pastebėta, kad ligos išsivystymui svarbūs genetiniai, neu­robiologiniai ir aplinkos veiksniai. Obsesinio-kompul­sinio sutrikimo gydymui kognityvinė elgesio terapija (KET) arba selektyvūs serotonino reabsorbcijos inhibi­toriai (SSRI) yra pirmosios eilės pasirinkimas, o paci­entams, kurių OKS yra atsparus gydymui, taikoma neu­romoduliacija ir neurochirurgija.
KASOS VĖŽYS: EPIDEMIOLOGIJA, RIZIKOS VEIKSNIAI, DIAGNOSTIKA IR CHIRURGINIAI GYDYMO BŪDAI
Authors: Kirstukaitė Beata
Published: September 2024

Kasos vėžys yra vienas iš agresyviausių onkologinių susirgimų, turintis aukštus mirtingumo rodiklius. Pa­grindiniai rizikos veiksniai, lemiantys ligos atsiradimą, yra rūkymas, nutukimas, cukrinis diabetas bei genetinė predispozicija. Ankstyva kasos vėžio diagnostika sudė­tinga, todėl liga dažniausiai diagnozuojama vėlyvose stadijose. Kasos vėžio diagnostika apima vaizdo tyrimus ir specifinį kraujo serumo žymenį CA19-9. Chirurginis gydymas užtikrina gerus išgyvenamumo rezultatus, bet gali būti taikomas tik neišplitusios ligos atvejais.
PERFORACIJA KOMPLIKUOTOS SKRANDŽIO OPALIGĖS EPIDEMIOLOGIJA, ETIOLOGIJA IR KLINIKA
Authors: Liekis Rokas
Published: September 2024

Opaligė − liga, kuriai dažniausiai būdingas pasikar­tojantis peptinės opos/opųatsiradimas skrandyje ar dvylikapirštėje žarnoje dėl sutrikusios pusiausvyros tarp gleivinęagresyviai veikiančiųir jąsaugančiųveiksnių. Identifikavus H.pylori bei sukūrus protonųsiurblio in­hibitorius, sergamumas opalige sumažėjo, tačiau opos prakiurimas yra dažna komplikacija, kurios skaičiai Eu­ropoje svyruoja nuo 4 iki 14 atvejų/100 000 gyventojų. Tikėtina, jog didžiausiąįtakąopai perforuoti turi H.pylori infekcija, nesteroidiniųvaistųnuo uždegimo (NVNU) vartojimas ir rūkymas. Skrandžio opaligės klinikiniai simptomai yra nespecifiniai. Svarbiausias ir dažniau­sias prakiurusios opos simptomas – skausmas. Skausmas būna lokalizuotas epigastriume, dešiniajame ar kairiajame viršutiniame pilvo kvadrante, pacientas epigastriume jau­čia tartum peilio dūrį.