bluuebunny/crossref_metadata_2025 huggingface dataset:
Pengabdian Masyarakat Melalui Pelatihan Pemasaran Digital Menggunakan Ecommerce Shopee Pada UMKM Majun Jaya Di Kp. Pasir Pogor Rt/Rw 009/005 Ds. Nagacipta Kec. Serang Baru Kab. Bekasi
Authors: Istiqomah Anisah , Kartika Dewi , Safira Occha Putrie
Published: June 2024

Saat ini pemanfaatan teknologi Internet menjadi salah satu cara untuk mendorong berkembangnya pasar UMKM karna Di era yang serba digital ini sudah sepantasnya pelaku UMKM memasarkan produknya melalui digital marketing agar produk yang dihasilkan bisa dikenal oleh konsumen secara luas. Strategi pemasaran digital Menggunakan e-commerce shopee sebagai alat pemasaran online memiliki beberapa manfaat bagi penjual. Diantaranya fleksibilitas waktu, tidak ada biaya operasional, tidak perlu beriklan karena platform marketplace memiliki strategi periklanan tersendiri, tidak ada biaya sewa, dan pengguna hanya perlu mendaftarkan toko onlinenya. Metode pelaksanaan dilakukan dengan sosialisasi dan pelatihan melalui pemaparan materi, pelatihan pembuatan akun merchant shopee, pengambilan gambar dan deskripsi produk serta melakukan live streaming dan pengelolaan akun. Hasil yang diperoleh dari kegiatan pengabdian masyarakat ini mitra sebagai pelaku UMKM Majun jaya yang sebelumnya belum mengetahui tentang pemasaran digital dan manfaat penjualan melalui e-commerce shopee kini mulai memasarkan produknya menggunakan e-commerce.
Pemberdayaan Masyarakat Melalui Peningkatan Kualitas Pendidikan Agama, Ekonomi, Dan Hukum Di Lingkungan Kelurahan Petukangan Selatan RW 02
Authors: Madina Nur , Jalaluddin Engga , Azhar Muhammada , Anjeli Nur , Pebriyanti Pebriyanti
Published: June 2024

Pemberdayaan masyarakat adalah kemampuan melakukan sesuatu dalam upaya peningkatan kualitas kesejahteraan di masyarakat. Kegiatan dilaksanakan melalui program Kuliah Kerja Nyata (KKN) yang merupakan aktivitas barbasis pengabdian masyarakat untuk meningkatkan empati serta keterampilan mahasiswa pada kondisi lingkungan masyarakat. Kuliah Kerja Nyata (KKN) kelompok 8 Universitas Darunnajah yang di selenggarakan lingkungan Kelurahan Petukangan Selatan RW 02, Kecamatan Pesanggarahan, Jakarta Selatan dengan metode penyuluhan, pelatihan, demonstrasi Dan pendampingan kelompok melalui peningkatan kualitas pendidikan Agama, Ekonomi, dan hukum di lingkungan Kelurahan Petukangan Selatan RW 02. Hasil menunjukan response positive yang tinggi dari pemerintahan sampai masyarakat sekitar dalam berpartisipasi di antaranya mengikuti kegiatan belajar mengajar SD SLB Sumber Budi, kegiatan pelayanan bimbingan sosial emosional pada anak tuna grahita, kegiatan pelayanan bimbingan Bahama isyarat pada anak tuna rungu, pengajaran PAUD Cempaka di RW 02, kegiatan pelayanan pengajaran TPA Nurul Huda, kegiatan Hidroponik bersama pengelola RPTRA Manunggal, Membuat keterampilan pupil dari kulit telur bersama Ibu Lurah Petukangan Selatan, membuat kreativitas dari stik ice cream dan bahan sampah menjadi tas/barang bermanfaat, melatih dan mengajarkan  anak - anak bermain bola Dan menari di RPTRA Manunggal, dan Kegiatan Seminar Kewirausahaan. Disisi lain terjadi peningkatan kedispilinan dan partisipasi mahasiswa KKN dan masyarakat, dengan keberhasilan kegiatan yang dilaksanakan.
The Influence of Quality of Work Life, Mental Workload, and Self-Efficacy on Job Performance Mediated by Job Satisfaction in Nurses at Panglima Besar Soedirman Hospital
Authors: Sormin Marlin Feriani , Oscar Jayanagara
Published: June 2024

Nurses have a very important role in patient care in hospitals, namely integrated and quality nursing care for each patient. One of the most important things in Human Resources management is the performance of nurses. This study aims to analyze the direct influence of quality of work life, mental workload and self-efficacy on nurse performance, as well as the indirect influence of quality of work life, mental workload on nurse performance which is mediated by nurse job satisfaction at the Panglima Besar Soedirman National Defense Central Hospital, Jakarta. This research design is quantitative. Data collection used a non-probability sampling technique with a purposive sampling method. The sample used was 160 active nurses. This research data was collected using a questionnaire via Googleform. The data obtained was processed using the PLS-SEM multivariate analysis method with SmartPLS software. The results showed that quality of work life, mental workload and self-efficacy had a positive effect on nurses' job satisfaction. The results show that there is a positive influence on the quality of work life on nurse performance, then job satisfaction has a positive influence on nurse performance, but mental workload has a negative influence on nurse performance. The research results also show that self-efficacy has no effect on nurse performance. Quality of work life, mental workload and self-efficacy have an indirect influence on nurse performance through nurse job satisfaction. It is hoped that future research can conduct comparative studies between the health sector and other sectors to compare how factors such as quality of work life, mental workload, and self-efficacy influence job satisfaction and job performance.
Rol del enfermero docente universitario: Revisión sistemática
Authors: Zamora Pazmiño Leisberth , Bailón Mieles José , Orlando Zantana Belén , García León Karla
Published: June 2024

La educación en enfermería es un pilar fundamental en la prestación de servicios de salud de calidad. En el contexto educativo contemporáneo, se requiere una optimización constante de la formación de enfermeros para satisfacer las demandas clínicas y académicas actuales. Esta investigación tuvo como objetivo identificar el rol del enfermero docente universitario en la formación de los futuros profesionales en enfermería. Se llevó a cabo una revisión sistemática, utilizando las bases de datos PubMed y Google Scholar para recopilar trabajos publicados entre 2013 y 2023. La búsqueda se centró en competencias clínicas como académicas, y evaluando las metodologías pedagógicas actuales en programas de formación en enfermería. Del análisis de contenido de los artículos seleccionados se identificaron cinco categorías: Docencia, Investigación e Innovación Pedagógica; Enfoque Práctico y Asistencial; Identidad Profesional y Docente; Humanización y Cultura de Cuidado; y Adaptación y Desafíos de la Docencia. Se destaca la importancia de una formación pedagógica robusta, la incorporación de tecnologías educativas y la promoción de una cultura de cuidado y humanización en la educación en enfermería, la necesidad de fortalecer la identidad profesional y docente, además de proponer una mayor integración entre teoría y práctica.
The Roadmap of a Cash Dupont Analysis and Its Impact on Stock Valuation Strategy
Authors: Alan Lifland Steven
Published: June 2024

It is a common belief that capital intensive corporations are associated with relatively low profit margins. They operate in environments where it may be a struggle to keep returns in excess of their capital costs. This further implies a possible decline in stock value because of these lower margins. This paper extends the financial literature on the effects of capital intensity on firm performance through the introduction of the Cash DuPont Model in conjunction with a Monte Carlo Simulation. The model’s use of the free cash flow to equity (FCFE), cash conversion factor (CCF), and resulting Cash ROE ultimately leads to the determination of the fair price to book value multiple. All of these data metrics are blended into a process of stock price valuation that explains both the possibility and probability of the mispricing of a stock. The results reveal that a capital-intensive firm can show undervalued tendencies despite low profit margins.
Investigating Patient Uncertainty in Virtual Consultation: A Content Analysis Study
Authors: Vania Shi Yuxi , Komiak Sherrie
Published: June 2024

Despite the benefits of conveniences and flexibilities, widespread adoption of virtual consultation systems remains elusive among patients. This exploratory study aims to uncover the underlying reasons behind this phenomenon by investigating patient uncertainties about virtual consultation and their impact on patient satisfaction. Leveraging a content analysis methodology, we scrutinize patient-generated online reviews on five prominent virtual consultation platforms. Our findings delineate the primary sources of patient uncertainty, ranked in descending order of significance: (1) ambiguity surrounding virtual consultation processes, (2) concerns regarding doctors' behavior, (3) challenges in articulating symptoms, (4) apprehensions regarding doctors' attitudes, (5) difficulties in understanding doctors, and (6) uncertainty about doctor’s feelings and emotions. Moreover, our analysis suggests a potential link between heightened uncertainties and patient dissatisfaction, albeit contingent on various factors, including perceived benefits and how virtual consultation systems address patient uncertainties. This study sheds light on the intricate dynamics of uncertainties in virtual consultations, providing valuable insights for researchers, system designers, and healthcare providers. By elucidating patient perspectives and apprehensions, our findings offer a roadmap for refining virtual consultation systems to mitigate uncertainties and enhance patient satisfaction, thereby advancing the quality and efficacy of telemedicine services.
The right of deaf people to access health care
Authors: Murray Joseph J , Le Marie Delphine , Bergmann Kasper
Published: June 2024

Deaf people, especially in the Global South, face significant barriers in their access to ear and hearing care, as such care is often inaccessible in their national sign languages
On the front line of ear and hearing care in low-income countries
Authors: Chidziva Clemence , Nkomo Lucia , Nguruye Natasha
Published: June 2024

Ear and hearing care in Zimbabwe: an oasis in the desert
การพัฒนารูปแบบการดูแลผู้ป่วยระยะสุดท้ายแบบประคับประคองที่บ้าน โรงพยาบาลวานรนิวาส จังหวัดสกลนคร
Authors: วิทยาภูมิ ณิชาดา
Published: June 2024

การวิจัยครั้งนี้เป็นการวิจัยแบบผสมผสาน (Mixed method) มีวัตถุประสงค์ เพื่อศึกษาผลของรูปแบบการดูแลผู้ป่วยระยะสุดท้ายแบบประคับประคองที่บ้าน โรงพยาบาลวานรนิวาส จังหวัดสกลนคร กลุ่มตัวอย่าง เป็นผู้ดูแลผู้ป่วยระยะสุดท้ายแบบประคับประคองที่บ้านทั้งหมดในเขตรับผิดชอบโรงพยาบาลวานรนิวาส จำนวน 51 คน วิเคราะห์ข้อมูลโดยใช้สถิติเชิงพรรณนา และ Paired t-testผลการศึกษา พบว่า ความต้องการช่องทางการติดต่อสื่อสารในการดูแลผู้ป่วยจากเจ้าหน้าที่สาธารณสุขอย่างรวดเร็วและในการเดินทางมาขอคำแนะนำจากเจ้าหน้าที่สาธารณสุขไม่ได้ทุกครั้งตามที่ต้องการเป็นปัญหาในการดูแลผู้ป่วยตามหลักเกณฑ์การดูแลผู้ป่วยระยะสุดท้ายแบบประคับประคองที่บ้าน โดยการประเมินความพึงพอใจต่อรูปแบบการดูแลผู้ป่วยก่อนและหลังทดลองใช้กิจกรรมแตกต่างกันทุกด้านอย่างมีนัยสำคัญทางสถิติ (p – value ≤0.001)สรุปได้ว่ารูปแบบการดูแลผู้ป่วยระยะสุดท้ายแบบประคับประคองที่บ้านโรงพยาบาลวานรนิวาส  ที่ดำเนินการเป็นระเวลา 3 เดือน ผู้ดูแลผู้ป่วยมีการเปลี่ยนแปลงทางด้านพฤติกรรมการดูแลผู้ป่วยก่อนและหลังการเข้าร่วมกิจกรรมอย่างเห็นได้ชัดเจน
ผลของโปรแกรมการจัดการโรคไตเรื้อรังโดยใช้รูปแบบการดูแลโรคเรื้อรังผู้ป่วยโรคไตเรื้อรังระยะที่ 3 และระยะที่ 4 ในโรงพยาบาลวานรนิวาส จังหวัดสกลนคร
Authors: โคตรพรหม ราวดี
Published: June 2024

การวิจัยแบบกึ่งทดลอง (Quasi experimental research) นี้ เป็นการศึกษาผลของโปรแกรมการจัดการโรคไตเรื้อรังระยะที่ 3 และระยะที่ 4 โดยใช้รูปแบบการดูแลโรคเรื้อรังโรงพยาบาลวานรนิวาส จังหวัดสกลนคร ประชากรและกลุ่มตัวอย่างของการศึกษา คือผู้ป่วยเพศหญิงที่มารับการนอนโรงพยาบาลในหอผู้ป่วยอายุรกรรมหญิงตึกอินทนิล โรงพยาบาลวานรนิวาส จำนวน 20 ราย เครื่องมือในการวิจัยเป็นแบบสัมภาษณ์ปลายเปิด วิเคราะห์โดยใช้สถิติ Paired t-testผลการศึกษาพบว่าการทดสอบความรู้ก่อนและหลังการจัดการตนเองเพื่อชะลอไตเสื่อม ด้านอาหาร ด้านการใช้ยา การควบคุมระดับความดันและน้ำตาล การออกกำลังกาย และการจัดการความเครียด การจัดการความเครียด ทั้งหมดมีระดับคะแนนเพิ่มขึ้น อยู่ในระดับมากที่สุด ผลการประเมินประสิทธิผลของโปรแกรมก่อนและหลังการทดลองโดยการประเมินผลลัพธ์ทางคลินิกค่าเฉลี่ย BUN (Blood urea nitrogen) ก่อนการใช้โปรแกรม 24.61 mg/dl ค่าเฉลี่ย BUN 18.23 mg/dl ค่าเฉลี่ย Creatinine 2.24 หลังการใช้โปรแกรม ค่า BUN มีค่าเท่ากับ 1.39 eGFR มีค่าเท่ากับ 22.36 มล./นาที มีค่าเท่ากับ 44.45 มล./นาทีการที่ผู้ป่วยได้รับความรู้และการดูแลอย่างใกล้สามารถส่งผลใหผู้ป่วยชะลอความเสื่อมของไตได้   ซึ่งรูปแบบการดูแลโรคเรื้อรังผู้ป่วยโรคไตเรื้อรังระยะที่ 3 และระยะที่ 4  ในโรงพยาบาลวานรนิวาส จังหวัดสกลนคร สามารถนำไปเป็นข้อมูลสนับสนุนหรือเป็นแนวทางในการพัฒนาการดูแลผู้ป่วยโรคไตเรื้อรัง
Enhanced Semantic Segmentation of Retinal Microlesions through R2U-Net Architecture
Authors: Pereira Alejandro , Santos Carlos , Aguiar Marilton , Welfer Daniel , Dias Marcelo , Menezes Rafaela de , Santana Douglas
Published: June 2024

Diabetic Retinopathy (DR) is a microvascular complication related to diabetes that affects approximately 33% of individuals with this condition and, if not detected and treated early, can lead to irreversible vision loss. Fundus lesions such as Hard and Soft Exudates, Hemorrhages, and Microaneurysms typically identify DR. The development of computational methods to segment these lesions plays a fundamental role in the early diagnosis of the disease. This article proposes a new approach that uses an R2U-Net combined with data augmentation techniques for segmenting fundus lesions. We trained, adjusted, and evaluated the proposed approach in the DDR dataset, achieving an accuracy of 99.87% and an mIoU equal to 59.69%. Furthermore, we assessed it in the IDRiD dataset, achieving an mIoU of 49.92%. The results obtained in the experiments highlight the potential contribution of the approach in generating lesion annotations in creating new DR datasets, which is essential given the scarcity of annotations in publicly available datasets.
Automatic Segmentation of Skeletal Muscle Tissue in L3 CT Images Based on Random Forests and CNN Using Coarse Ground Truth Masks
Authors: Santos Domingos B. S. , Melo Gabriel F. L. , Araujo Thelmo de
Published: June 2024

Estimates of the composition of skeletal muscle tissue (SMT) and adipose tissues are important in the treatment of debilitating diseases, such as cancer, and in the control of overweight and obesity. Several studies have shown a high correlation between the percentage of SMT in computed tomography (CT) images corresponding to the cross-section at the level of the third lumbar vertebra (L3) and the percentage of this tissue in the whole body. A large number of models has been proposed to automatically segment CT images in order to estimate tissue compositions, many of them use supervised Machine Learning (ML) methods, such as neural networks, which require large amounts of labeled images, i.e., images and ground truth masks obtained from manual segmentation by human experts. These large labeled datasets are not easily available to the public, thus the present work proposes a methodology capable of performing the automatic segmentation of SMT in single-slice CT images (at L3) using only “coarse” segmentation masks as ground truth in the ML algorithms’s training phases. By “coarse segmentation” we mean a semiautomated segmentation performed by a person without specialized knowledge of human anatomy. The proposed methodology oversegments the image into superpixels, which are classified by a Random Forest (RF) model. Then, a U-Net CNN refines the classification, using as input the pixels in the superpixel segments classified as SMT by the RF. The methodology achieved 99.21% of the accuracy obtained by the same CNN trained with golden standard ground truth masks, i.e., segmentation masks manually created by a medical expert.
Analyzing the COVID-19 parameters for large Brazilian municipalities using a model with fuzzy transitions between epidemic periods
Authors: Lima Hélder Seixas , Guimarães Frederico Gadelha
Published: June 2024

This study investigates the dynamics of the COVID-19 pandemic across the 41 largest Brazilian municipalities from 2020 to 2022. We used a mathematical model with fuzzy transitions between epidemic periods to estimate epidemiological parameters such as basic reproduction number (R0) and the Infection Fatality Rate (IFR). We provide insights into the trajectory of the pandemic by correlating these parameters with data on social isolation, vaccination efforts, and the emergence of new variants. Our findings highlight the role of social isolation in reducing R0 in 2020 and the impact of mass vaccination on lowering the IFR in 2022. However, the highest mortality rates recorded in 2021 underscore the complex interplay of various factors observed in that moment.
A Hierarchical Approach for Extracting and Displaying Entities and Relations from Radiology Medical Reports
Authors: Toyoda Gabriel , Rojas Yunevda , Colonna Juan G. , Gama Joao
Published: June 2024

Extracting information from medical reports can be challenging due to the large volume of data. Therefore, this study proposes a method that uses a hierarchical classification approach with two levels, each consisting of a neural network instance. One for extracting clinical anatomical or observational entities along with their levels of uncertainty, and another for classifying the relations that exist between these entities. For this research, 600 radiological reports from the RadGraph dataset were used. The entity extraction task achieved an F1-score of 91%, while the entity classification and relation classification tasks achieved 88% each. Our hierarchical method enhances entity and relation classification performance by filtering and double checking classified entries.
EfficientEnsemble: Diagnóstico de câncer de mama em imagens de ultrassom utilizando processamento de imagens e Ensemble de EfficientNets
Authors: Diniz João O. B. , Dias Jr Domingos A. , Cruz Luana B. da , Marques Ricardo C. S. , Gomes Jr Daniel L. , Cortês Omar A. C. , Carvalho Filho Antônio O. de , Quintanilha Darlan B. P.
Published: June 2024

O diagnóstico de câncer de mama por meio de ultrassom é desafiador devido à complexidade das imagens e à variação nas características. O objetivo deste trabalho é propor um método que combina pré-processamento, aumento de dados balanceados e um Ensemble de EfficientNet para melhorar a precisão do diagnóstico. Os resultados mostram métricas de validação robustas, alcançando uma acurácia de 96,67%, uma especificidade de 97,67%, uma sensibilidade de 94,12%, um F1-score de 94,96%, e uma AUC-ROC de 0,95896. A abordagem proposta pode ser uma ferramenta valiosa para auxiliar no diagnóstico de câncer de mama em imagens de ultrassom, potencialmente aumentando a eficiência do tratamento e melhorando os resultados clínicos.
High-level classification using complex networks for Autism Spectrum Disorder detection
Authors: Araújo Lucas G. T. , Sabino-Silva Robinson , Carneiro Murillo G.
Published: June 2024

The diagnosis of Autism Spectrum Disorder (ASD) is typically based on behavioral observation, which is a process time-consuming, subjective and reliant on professional judgment. This study leverages research on salivary biomarkers to develop a tool capable of adding objectivity to this process. A high-level classifier based on complex networks was employed using different network formation methods based on Attenuated Total Reflection Fourier-Transform Infrared spectroscopy (ATR-FTIR) data from saliva samples. The results indicate the use of high-level classifiers as a promising tool for ASD detection.
Classificação de Tumores Cerebrais em Imagens de Ressonância Magnética
Authors: Moreira Andressa G. , Santos Stefane A. dos , Oliveira Michele F. de , Paula Júnior Iális C. de , Assis Débora F. de
Published: June 2024

O câncer de cérebro é caracterizado pelo desenvolvimento de tumores cerebrais malignos. Dessa forma, a detecção precoce é crucial para a sobrevivência dos pacientes. Os avanços em Inteligência Artificial (IA) têm aprimorado a análise de imagens médicas. Entretanto, a classificação de tumores cerebrais ainda é uma tarefa desafiadora. Neste estudo, é utilizada a técnica de transfer learning para classificar os tipos de tumores cerebrais em Meningioma, Glioma, Hipofisário e casos sem tumor, a partir de imagens de ressonância magnética. Para isso, são empregadas as arquiteturas AlexNet, DenseNet201, EfficientNetB7, MobileNetV2 e ResNet50. A rede EfficientNetB7 obteve os resultados mais promissores, alcançando 97,68% para a acurácia de teste.
Aprendizado de máquina para o diagnóstico da hipersensibilidade dentinária utilizando espectroscopia no infravermelho por transformada de Fourier
Authors: Souza Paulo D. S. , Souza Paola G. , Soares Paulo V. , Sabino-Silva Robinson , Carneiro Murillo G.
Published: June 2024

Neste estudo desenvolvemos um pipeline de ponta a ponta para o diagnóstico da hipersensibilidade dentinária. O pipeline possui dois componentes principais: coleta e preparação de dados, e aprendizado de máquina. No primeiro, amostras do fluido crevicular gengival de pacientes foram submetidas à análise por espectroscopia de infravermelho por transformada de Fourier (FTIR), com etapas de pré-processamento incluindo normalização via Amida I e aplicação de Savitzky-Golay com derivadas. No segundo, diversos modelos de aprendizado de máquina foram desenvolvidos e avaliados. Nossos resultados evidenciaram a viabilidade dos modelos de XGBoost e BiLSTM e a importância da adequada seleção de parâmetros e preparação dos dados de FTIR.
O uso da metodologia CRISP-DM para apoiar a análise de dados no aplicativo mHealth IUProst
Authors: Vaz Noelí Antonia Pimentel , Fernandes Deborah Silva Alves , Carvalho Sergio T.
Published: June 2024

O uso de dispositivos móveis na saúde visa auxiliar no controle e monitoramento de doenças e condições clínicas, colaborando com o autocuidado das pessoas. Nesse contexto, o IUProst destaca-se como uma aplicação mHealth que auxilia pacientes durante o tratamento da incontinência urinária, uma comorbidade decorrente da cirurgia de retirada de próstata em pacientes que enfrentaram o câncer. Apesar do potencial das aplicações mHealth, como o IUProst, para auxiliar no tratamento da incontinência urinária, a baixa adesão dos usuários destaca a urgência de implementar mecanismos de engajamento eficazes. O objetivo deste artigo é relatar uma pesquisa que utiliza a metodologia CRISP-DM para identificar padrões, tendências e percepções nos dados do IUProst, visando levantar demandas para subsidiar os próximos ciclos de evolução e o aprimoramento da aplicação. Análises dos resultados obtidos nas fases de compreensão do negócio e compreensão dos dados, revelaram um número significativo de usuários e exercícios realizados, porém com baixa participação no tratamento cognitivo comportamental proposto.
Segmentação Automática de Endometriose Profunda em Imagens de Ressonância Magnética Baseada em Swin-Unet
Authors: Pinto Daniel M. , Figueredo Weslley K. R. , Silva Italo F. S. da , Silva Aristófanes C. , Paiva Anselmo C. de , Salomão Alice C. C. B. , Oliveira Marco A. P. de
Published: June 2024

A endometriose profunda é a doença caracterizada pela presença do endométrio fora da cavidade uterina, causando agudo desconforto para as pessoas afetadas. Métodos não invasivos baseados em imagem para a aferição do grau de evolução da doença são eficazes mas custosos em tempo dos especialistas. Este trabalho propõe um método automático de segmentação de lesões de endometriose em imagens de ressonância magnética utilizando uma Swin-Unet. O método alcançou uma precisão de 45, 6%, sensibilidade 61, 9%, dice de 47, 7% e jaccard de 36, 2%. Foi segmentada com boa qualidade ao menos uma imagem por paciente em 17 dos 18 pacientes utilizados para teste.
A Extração de Entidades Nomeadas em Bulas de Medicamentos e em Relatos de Casos Clínicos
Authors: Colombo Cristiano da Silveira , Oliveira Elias de
Published: June 2024

As bulas farmacêuticas são documentos com informações sobre medicamentos como a sua posologia, as reações adversas, dentre outras informações. Os relatos de casos clínicos são narrativas descritivas e detalhadas das experiências médicas com pacientes. A proposta deste artigo é apresentar e descrever o método de trabalho utilizado para a Extração de Informação automática das bulas farmacêuticas e de relatos de casos clínicos através do Reconhecimento de Entidades Nomeadas. Um modelo de Inteligência Artificial foi treinado a partir de uma abordagem híbrida baseada em Conditional Random Fields (CRF) e Local Grammar (LG), denominada CRF+LG. Os resultados obtidos em medida F1 nos testes com as bulas foram de 94.85% na extração das entidades sobre doenças e 68.63% na extração das entidades sobre medicamentos. Os resultados obtidos nos testes com os relatos de casos clínicos foram de 77.42% na extração das entidades sobre doenças e 87.34% na extração das entidades sobre medicamentos. Os resultados demonstraram que a iniciativa apresentada pode contribuir para auxiliar profissionais de saúde na extração de informações de bulas e de relatos de casos clínicos.
Elderly Fall Detection Algorithm Based on Improved YOLOv5s
Authors: Luo Zhongze , Jia Siying , Niu Hongjun , Zhao Yifu , Zeng Xiaoyu , Dong Guanghui
Published: June 2024

The indoor fall detection for the elderly can effectively help the treatment after falling, but many existing detection methods have the problems of inconvenient use, high misjudgement rate and slow speed. Using deep learning methods can effectively solve these problems, and YOLOv5s is a kind of deep learning algorithm that can perform real-time fall detection. In order to achieve a more lightweight and higher detection accuracy, this paper proposes a fall detection algorithm for the elderly based on improved YOLOv5s, called YOLOv5s-GCC. Firstly, the original Conv and C3 structures are replaced by GhostConv and C3GhostV2 structures in backbone to achieve model lightweight, which reduces model computation and improves accuracy. Secondly, the lightweight upsampling operator CARAFE is introduced to expand the receptive field for data feature fusion and reduce the loss of feature information in upsampling. Finally, the deepest C3 is integrated with CBAM attention mechanism in the neck, because the deepest neck receives more abundant feature information, and CBAM can increase the efficiency of the algorithm in extracting important information from the feature map. Experimental results show that YOLOv5s-GCC has increased by 1.2% to 0.935 on the hybrid open source fall dataset mAP@0.5; FLOPs decreased by 29.1%. Params are reduced by 27.5% and have obvious advantages oversimilar object detection algorithms.
Autonomy-Related Personality Factors in Patients with Functional Neurological Symptom Disorder
Authors: Stroink Luuk
Published: June 2024

Functional neurological disorder (FND), formerly called hysteria and conversion disorder, is a complicated condition that is empirically difficult to investigate. The study of personality factors in FND has a long tradition in which there is still uncertainty about which personality factors play an important role in FND. Only in recent years has there been more evidence of certain important personality factors. These factors are now hypothetically understood and summarized as ‘premorbid autonomy-related variables.’ This provides a research framework for more empirical research. Several premorbid autonomy-related variables such as insecure attachment, suggestibility, alexithymia, interoception, sense of agency, fear avoidance/openness to experience, and autonomy-connectedness are discussed. In addition, a hypothetical working model will be discussed in this chapter. This may provide important clues to the etiology, diagnosis, and treatment for patients with FND.
A Study on the Applicability of A-TIG Welding of Semi-Automatic Cold Wire Feeding Process for Cryogenic Stainless Steel Pipes
Authors: Lee Hee-Keun , Yun Kwang-Hee
Published: June 2024

Activated Tungsten Inert Gas (A-TIG) welding with deeper penetration characteristic than manual Tungsten Inert Gas (TIG) welding is one of developed TIG welding processes for higher welding productivity. However, underfill phenomena often occurs when A-TIG welding applies to butt joints of Stainless steels with gap and misalignment. In order to complete welding, additional welding passes are needed. To prevent the underfill phenomena, A-TIG welding using semi-automatic cold wire feeding process can be one of alternatives. In this study, semi-automatic cold wire feeding condition for sound A-TIG weld profiles and characteristics of A-TIG welds were investigated. A-TIG welds without underfill were obtained by front feeding and placing the wire at the point about 1mm below from a TIG welding electrode. On the basis of mechanical and corrosion test results, A-TIG welds using semi-automatic cold wire feeding process have similar mechanical and corrosion characteristics with manual TIG welds, although slag was remained on the weld beads after the pickling process to remove heat tints of the A-TIG welds. However, the slag on the bead of A-TIG welds had no correlation with pitting corrosion.
Effect of Welding Heat Input on the Simulated Heat-Affected-Zone Toughness for Yield Strength 390MPa Class TMCP Steel Plate
Authors: Sim Ho-Seop , Kim Ki-Hyuk , Sung Joon-Ho , Ha Ryeo-Sun , Lim Kyeong-Taek , Kim Do-Hyung , Hong Hyun-Uk
Published: June 2024

In this study, the influence of heat input on the microstructure and toughness of the simulated heat-affected zone (HAZ) of YP390 MPa grade steel with a thickness of 80 mm was investigated. The weld coarse-grained HAZ was simulated using a Gleeble 3500 simulator, with heat input levels ranging from 30 to 650 kJ/cm. Following the HAZ simulation test, the microstructures and Charpy impact properties were examined. For heat inputs ranging from 30 to 50 kJ/cm, the microstructure consisted of bainitic ferrite/acicular ferrite, resulting in an impact toughness exceeding 200 J at -20 ℃. Conversely, in the higher heat input range of 130 to 650 kJ/cm, the simulated HAZ exhibited a lower impact toughness value due to the formation of coarse grain boundary ferrite. A high proportion of acicular ferrite with minimal grain growth was found to be the key metallurgical factor contributing to the improvement of impact toughness.
“Matayo is what in English?” On experiences of English medium instruction in rural Ugandan classrooms
Authors: Ssentanda Medadi E.
Published: June 2024

The question of using English as a language of learning and teaching (LoLT) has been around for some time, but limited studies have been conducted in Africa’s multilingual context to understand the challenges involved. In this paper, I attempt to demonstrate the difficulties in the classroom interactions between teachers and learners in four rural primary schools in which the mother tongue is the LoLT for the first three years of primary school, followed by a transition to English as the LoLT during the fourth year and English only from the fifth year onwards. Based on fieldwork conducted in two private and two public schools in Kyotera District, Uganda, this paper investigates classroom practices related to the use of English as the LoLT. Data were collected through questionnaires, classroom observations and interviews and were analysed using a triangulation approach to determine disparities between what the teachers report in the questionnaires and interviews and what the language policy and curriculum require of their classroom practice. The findings demonstrate that both teachers and learners struggle with the English language in negotiating learning. Moreover, learners are mostly comfortable responding to questions posed to them in English in their mother tongue. Teachers’ involvement of learners in the learning process is largely by cues, calling for only a word in English—an indication of learners’ inefficiency in the language. The paper discusses the implications of these findings. Key words: Mother tongue education, transition, classroom practices, English medium education, Luganda, Uganda
Performance of L1 and L2 grade 6 South African learners on an assessment of core academic language skills
Authors: MacFarlane Marco
Published: June 2024

This study investigates the relationship between the linguistic background/s of South African Grade 6 learners and an instrument measuring Core Academic Language Skills (CALS). The learners’ (n = 89) results were divided into two groups based on their most commonly spoken language (either English, L1 or a language other than English, L2). All learners in the study (and indeed the overwhelming majority of South African learners) attend school in an English language immersion setting, where English is the sole language of learning and teaching. The groups were assessed on the CALS-I-ZA, an instrument developed to measure CALS that has been validated in the South African context. This study found that in both the L1 and L2 groups, the CALS-I-ZA showed a strong association with both the provincial Maths Common Examination (r = 0.642) and the provincial Natural Sciences and Technology Examination (r = 0.650). Surprisingly, the home language variable either does not correlate or correlates only very weakly with the other variables, suggesting that L1 or L2 status alone is a weak or increasingly irrelevant predictor of academic success. This research concludes that the strong association between CALS and schooling results remains robust, regardless of L1 or L2 status, and thus, there is compelling evidence to begin deploying the construct as an instructional tool in South African classrooms.
The application of language games in teaching and learning the English language in lower secondary schools: a case of the Meru district council (Tanzania)
Authors: MGECHA PERIDA
Published: June 2024

Language games are one of the significant techniques appropriate for teaching and learning a foreign language. This paper examines how language games are applied in teaching and learning the English language in lower secondary schools: a case of Meru District Council (Tanzania). The paper is guided by the Communicative Language Teaching Approach. This study was qualitative; hence, data were collected from eight secondary schools through interviews and observations and then analysed thematically. Thirteen English language teachers were involved in data collection. The findings show that the majority of English language teachers do not use language games in language classes. The reasons for this are that many such teachers have had little exposure to a variety of games and lack awareness of language game instruction being among the techniques for teaching and learning the English language; hence, they lack the knowledge, skills, and competencies to apply such games in the language class. This study recommends that capacity building for English language teachers is needed, particularly in the language games technique.
Food security as a catalyst for innovative food products industry in MENA region
Authors: Будрин А.Г. , Кузнецов А.А.
Published: June 2024

данная статья исследует фактор продовольственной безопасности при продвижении инновационных пищевых продуктов в регионе Ближнего Востока и Северной Африки (MENA). В статье анализируется влияние ряда факторов, оказывающих воздействие на продовольственную безопасность региона и возможность использования данных факторов в контексте социально-ориентированного маркетинга. В статье также обсуждаются стратегии и механизмы, используемые для обеспечения продовольственной безопасности в регионе MENA и их влияние на стимулирование инноваций в сфере питания. Результаты исследования могут быть полезны для понимания динамики развития пищевой промышленности в регионе, а также при разработке стратегии продвижения инновационных пищевых продуктов в регионе MENA на основе концепции социально-ответственного маркетинга.

this article explores the role of food security as a catalyst that contributes to the development of the innovative food industry in the Middle East and North Africa (MENA) region. The article analyzes the impact of a number of factors affecting food security in the region. The article also discusses the strategies and mechanisms used to ensure food security in the MENA region and their impact on fostering food innovation. The results of the study may be useful for understanding the dynamics of the food industry in the region and developing policies to stimulate innovation and ensure food security.
The mainstream use of artificial intelligence in sports
Authors: Димитров И.Л. , Садыкова А.И.
Published: June 2024

в статье рассматривается применение искусственного интеллекта (ИИ) в фитнес индустрии и в спорте высших достижений. Работа демонстрирует возможности в совместной деятельности менеджера и искусственного интеллекта, а также минусы работы каждого из них по-отдельности. Основываясь на текущее состояние ИИ и изученные материалы, предлагаются варианты, которые помогут быстрее внедрить цифровые разработки. Целью работы является изучение состояния на данный момент искусственного интеллекта в сфере спорта и составление рекомендаций по ускорению процесса внедрения ИИ. Задачи: 1. Рассмотреть и определить влияние искусственного интеллекта на спортивную жизнь с разных ракурсов 2. Анализировать сильные и слабые стороны как управленца, так и ИИ, чтобы сформулировать преимущества их объединения 3. Провести кейс-исследование спортивных ассоциаций боевых искусств, хоккея на льду и футбола. Методы: данная статья написана с помощью анализа литературы информационных, государственных источников и статистических данных, включенного метода наблюдения, метода обобщения. Выводы: в настоящее время ИИ является движущей силой для достижения спортивных побед и для поддержания здорового образа жизни нации, о необходимости стремительного развития цифровых технологий.

the article discusses the use of artificial intelligence (AI) in the fitness industry and in high-performance sports all. The work demonstrates the possibilities in the joint activities of the manager and artificial intelligence, as well as the disadvantages of each of them working separately. Based on the current state of AI and the materials studied, options are offered that will help to implement digital developments faster. The purpose of the work is to study the current state of artificial intelligence in the field of sports and make recommendations to accelerate the process of AI implementation. Tasks: 1. To study and determine the impact of artificial intelligence on sports life from different angles 2. To analyze the strengths and weaknesses of both the manager and the AI in order to formulate the advantages of combining them 3. To conduct a case study of sports associations of martial arts, ice hockey and football. Methods: this article is written using the analysis of the literature of information, government sources and statistical data, the included method of observation, the method of generalization. Conclusions: currently, AI is the driving force for achieving sports victories and for maintaining a healthy lifestyle of the nation, about the need for rapid development of digital technologies.
The impact of digital transformation on the modernization of industrial production: the potential of smart contracts
Authors: Жагловская А.В.
Published: June 2024

развитие цифровых технологий существенно трансформирует различные сферы экономики, в том числе и промышленное производство. Одним из перспективных направлений в данном контексте является внедрение смарт-контрактов, способных значительно оптимизировать бизнес-процессы. Цель данного исследования заключается в анализе потенциала смарт-контрактов в контексте модернизации промышленного производства. Методологическая база работы включает в себя системный подход, методы сравнительного анализа, синтеза и обобщения. Эмпирической основой исследования послужили статистические данные, отражающие динамику внедрения смарт-контрактов в различных отраслях промышленности, а также результаты экспертных интервью с представителями бизнес-сообщества. В ходе исследования выявлено, что использование смарт-контрактов способствует сокращению транзакционных издержек на 15-20%, ускорению процессов согласования условий сделок в 2-3 раза, а также минимизации рисков, связанных с человеческим фактором. Так, по данным компании Deloitte, внедрение смарт-контрактов в сфере логистики позволяет сократить время обработки документов на 80% и снизить затраты на 90%. При этом в машиностроении использование смарт-контрактов обеспечивает повышение эффективности управления цепочками поставок на 30-35%.

the development of digital technologies is significantly transforming various sectors of the economy, including industrial production. One of the promising areas in this context is the introduction of smart contracts that can significantly optimize business processes. The purpose of this study is to analyze the potential of smart contracts in the context of modernization of industrial production. The methodological basis of the work includes a systematic approach, methods of comparative analysis, synthesis and generalization. The empirical basis of the study was statistical data reflecting the dynamics of the introduction of smart contracts in various industries, as well as the results of expert interviews with representatives of the business community. The study revealed that the use of smart contracts helps to reduce transaction costs by 15-20%, accelerate the processes of agreeing on terms of transactions by 2-3 times, as well as minimize the risks associated with the human factor. Thus, according to Deloitte, the introduction of smart contracts in the field of logistics can reduce document processing time by 80% and reduce costs by 90%. At the same time, in mechanical engineering, the use of smart contracts provides an increase in the efficiency of supply chain management by 30-35%.
Formation of the institutional mechanism for sustainable development of the national economy of Russia
Authors: Калмыков К.А.
Published: June 2024

для обеспечения устойчивого инновационного развития промышленности России необходимо существенное увеличение объемов инвестиций в НИОКР – с текущих 1,1% ВВП до 2,5-3% ВВП к 2030 году. При этом оптимальная структура инвестиций предполагает приоритетное финансирование исследований и разработок в области информационно-коммуникационных технологий, биотехнологий, новых материалов, робототехники и искусственного интеллекта. Например, в сфере ИКТ объем инвестиций в НИОКР должен возрасти с 67 млрд руб. в 2020 г. до 450-500 млрд руб. в 2030 г., в биотехнологиях – с 18 млрд руб. до 200-250 млрд руб., в сфере новых материалов – с 43 млрд руб. до 300-350 млрд руб. соответственно. Предложенная модель позволяет также определить оптимальные пропорции между государственным и частным финансированием НИОКР в различных отраслях промышленности. В частности, в наукоемких отраслях, связанных с реализацией крупных инфраструктурных проектов (авиакосмическая промышленность, энергетическое машиностроение и др.), доля государственных инвестиций должна составлять не менее 50-60%, тогда как в отраслях, ориентированных на потребительский рынок (пищевая промышленность, легкая промышленность и др.), основной объем инвестиций должен обеспечиваться за счет частного сектора.

to ensure sustainable innovative development of the Russian industry, a significant increase in R&D investment is necessary – from the current 1.1% of GDP to 2.5-3% of GDP by 2030. The optimal investment structure implies priority financing for research and development in the fields of information and communication technologies, biotechnologies, new materials, robotics, and artificial intelligence. For instance, in the ICT sector, R&D investment should increase from 67 billion rubles in 2020 to 450-500 billion rubles in 2030, in biotechnologies – from 18 billion rubles to 200-250 billion rubles, and in the field of new materials – from 43 billion rubles to 300-350 billion rubles, respectively. The proposed model also allows determining the optimal proportions between public and private R&D financing in various industrial sectors. In particular, in science-intensive sectors associated with the implementation of large infrastructure projects (aerospace industry, power engineering, etc.), the share of government investments should be at least 50-60%, whereas in sectors oriented towards the consumer market (food industry, light industry, etc.), the main volume of investments should be provided by the private sector.
Problems of effectiveness of systems for assigning credit ratings to companies and bonds
Authors: Сотников А.А.
Published: June 2024

объектом исследования являются системы присвоения кредитных рейтингов компаниям и облигациям. Предметом исследования является оценка эффективности систем присвоения рейтингов специализированными агентствами. Данный вопрос широко представлен в академической литературе и многие исследователи приводят в пример прежде всего необъективность рейтингов структурированных финансовых продуктов, что являлось одной из причин мирового финансового кризиса 2007–2008 г.г. Автор рассматривает процедуры присвоения рейтингов, а также их влияние на кредитоспособность эмитентов. По результатам работы автором сделаны выводы, что действующие рейтинговые системы с одной стороны наделены положительными свойствами быстрого и легко интерпретируемого индикатора состояния эмитента (его долговых инструментов), а с другой стороны, присвоение рейтингов и их пересмотр сопряжены с возможными конфликтами интересов, а также с проблемой нахождения баланса между своевременностью и точностью рейтинговых прогнозов, которую тяжело преодолеть в практической деятельности.

the object of the study is systems for assigning credit ratings to companies and bonds. The subject of the study is to assess the effectiveness of rating systems by specialized agencies. This issue is widely represented in the academic literature and many researchers cite as an example primarily the bias in ratings of structured financial products, which was one of the reasons for the global financial crisis of 2007–2008. The author examines the procedures for assigning ratings, as well as their impact on the creditworthiness of issuers. Based on the results of the work, the author concluded that the current rating systems, on the one hand, are endowed with the positive properties of a quick and easily interpreted indicator of the condition of the issuer (its debt instruments), and on the other hand, the assignment of ratings and their revision are associated with possible conflicts of interest, as well as the problem finding a balance between the timeliness and accuracy of rating forecasts, which is difficult to overcome in practice.