bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the prevalence and risk factors of burnout syndrome among healthcare workers: A cross-sectional study
Authors: Mohamed Nur Adam , Mohamed Yusuf Abdirisak , Haji Mohamud Rahma Yusuf , Gabow Adan Ali
Published: January 2025

BACKGROUND

Burnout syndrome is a significant issue among healthcare professionals worldwide, marked by depersonalization, emotional exhaustion, and a reduced sense of personal achievement. This psychological and physical burden profoundly affects healthcare professionals' quality of care and overall well-being. In Somalia, where the healthcare system faces numerous challenges, the escalating demand for medical services and inadequate resources, coupled with overwhelming workloads, long hours, and high-stress levels, make healthcare providers particularly vulnerable to burnout syndrome. This, in turn, affects both the mental health of healthcare personnel and the quality of care they provide.

AIM

To examine the prevalence and determinants of burnout syndrome among healthcare practitioners in Mogadishu, Somalia.

METHODS

This cross-sectional prospective study was performed among 246 healthcare providers employed at a tertiary care hospital in Mogadishu, Somalia, who were recruited via random sampling. Data were collected using questionnaires that covered sociodemographic, psychological, work-related characteristics, and burnout syndrome. Bivariate and multivariate logistic regression analyses were performed to identify the variables that correlated with burnout syndrome. The results were presented using adjusted odds ratios (AORs), 95%CIs, and P values, with a cutoff of 0.05 for identifying significant associations.

RESULTS

Among the participants, 24% (95%CI: 18.8%–29.8%) exhibited symptoms of burnout syndrome. Factors associated with burnout included female gender (AOR = 6.60; 95%CI: 2.29-19.04), being married (AOR = 3.07; 95%CI: 1.14-8.28), being divorced or widowed (AOR = 5.84; 95%CI: 1.35-25.35), working more than 7 night shifts (AOR = 3.19; 95%CI: 1.30–7.82), having less than 5 years of job experience (AOR = 5.28; 95%CI: 1.29-21.65), experiencing poor sleep quality (AOR = 5.29; 95%CI: 1.88-14.89), and exhibiting depressive (AOR = 4.46; 95%CI: 1.59-12.53) and anxiety symptoms (AOR = 7.34; 95%CI: 2.49-21.60).

CONCLUSION

This study found that nearly one in four healthcare professionals suffers from burnout syndrome. Improving sleep quality, monitoring, and providing mental health support could enhance their well-being and patient care.
GIÁ TRỊ CỦA THANG ĐIỂM ASPECTS TIÊN LƯỢNG HỒI PHỤC BỆNH NHÂN NHỒI MÁU NÃO CẤP TUẦN HOÀN TRƯỚC ĐƯỢC LẤY HUYẾT KHỐI CƠ HỌC
Authors: Nguyễn Thanh Tâm , Vũ Đăng Lưu , Trần Anh Tuấn , Lê Hoàng Kiên , Nguyễn Quang Anh , Trần Cường
Published: January 2025

Mục tiêu: So sánh giá trị của thang điểm ASPECTS trong tiên lượng hồi phục bệnh nhân nhồi máu não cấp tuần hoàn trước được lấy huyết khối với tiêu chuẩn so sánh là chụp tưới máu trước can thiệp.
Phương pháp nghiên cứu: Nghiên cứu mô tả cắt ngang hồi cứu kết hợp với tiến cứu 60 trường hợp được chụp CLVT không tiêm thuốc, CTA, CTP, sử dụng phần mềm RAPID tính giá trị core, penumbra và lấy huyết khối cơ học trong 6-24 giờ kể từ thời điểm khởi phát tại trung tâm Điện Quang, bệnh viện Bạch Mai từ. Dự hậu đột quỵ tốt (0-2 điểm) và xấu (3-6 điểm) được đánh giá tại thời điểm sau 3 tháng bởi thang điểm hồi phục chức năng Rankin hiệu chỉnh (mRS). Sử dụng đường cong ROC và giá trị AUC để so sánh giá trị tiên lượng dự hậu đột quỵ tốt và xấu của ASPECTS và các giá trị core, penumbra, mismatch ratio.
Kết quả: Từ tháng 1/2023 đến tháng 1/2024, có 60 bệnh nhân được đưa vào nghiên cứu. Tại thời điểm 90 ngày, tỷ lệ kết cục độc lập chức năng mRS tốt (0-2) là 58%, mRS xấu (3-6) là 42%. Đường cong ROC đã chỉ ra rằng, trong các chỉ số ASPECTS, core, penumbra và mismatch ratio, chỉ có ASPECTS có khả năng tiên lượng tốt dự hậu đột quỵ (p = 0.001<0.05), diện tích dưới đường cong là 0.727 với chỉ số điểm cắt J – point tại ngưỡng ASPECTS = 6 với độ nhạy 91.4% và độ đặc hiệu 48%
Kết luận: ASPECTS ≥ 6 có khả năng tiên lượng dự hậu hồi phục chức năng tốt sau đột quỵ ở những bệnh nhân nhồi máu não cấp tuần hoàn trước được lấy huyết khối tại cửa sổ mở rộng. Từ đó có thể xem xét đến việc sử dụng ASPECTS ≥ 6 để thay thế cho CTP lựa chọn bệnh để lấy huyết khối cơ học tại những cơ sở y tế không có các phương tiện chẩn đoán hình ảnh nâng cao.
Từ khóa: đột quỵ sau 6 giờ, lấy huyết khối cơ học, ASPECTS, core, penumbra, mismatch ratio.
BẤT THƯỜNG HỒI LƯU TĨNH MẠCH PHỔI BÁN PHẦN VÀ BIẾN THỂ GIẢI PHẪU ĐỘNG MẠCH NGỰC TRONG PHẢI: BÁO CÁO TRƯỜNG HỢP LÂM SÀNG VÀ TRA CỨU Y VĂN
Authors: Nguyễn Thanh Nam , Trần Thị Thanh Thủy , Nguyễn Hữu Xuân
Published: January 2025

Chúng tôi báo cáo một trường hợp bệnh nhân nữ 56 tuổi có bất thường tĩnh mạch phổi bán phần bên phải đổ về tĩnh mạch chủ dưới kết hợp với biến thể giải phẫu của động mạch ngực trong phải có chia nhánh tới thùy dưới phổi phải và vách liên thất sau; được chụp X quang phổi và Cắt lớp vi tính lồng ngực có tiêm thuốc cản quang tĩnh mạch tại khoa Chẩn đoán hình ảnh, bệnh viện Vinmec Đà Nẵng. Qua trường hợp này chúng tôi bàn luận về bất thường hồi lưu tĩnh mạch phổi bán phần kết hợp với biến thể giải phẫu của động mạch ngực trong phải và tra cứu y văn.
“BREAST CHECK” - GIẢI PHÁP SÀNG LỌC UNG THƯ VÚ CÁ THỂ HOÁ CHO PHỤ NỮ VIỆT NAM
Authors: Hoàng Trung Hiếu , Hà Thị Hiền , Văn Nữ Thuỳ Linh , Nguyễn Thị Thanh Nhi , Nguyễn Vũ Quốc Huy , HOANG THI NGOC HA
Published: January 2025

Ung thư vú là loại ung thư phổ biến nhất ở phụ nữ, tỷ lệ mắc trên toàn thế giới hiện tại là 23,8%, tỷ lệ tử vong là 15,4%. Ở Việt Nam, ung thư vú chiếm 28,9% tổng số ca ung thư ở nữ giới và chiếm 13,6% tổng số ca ung thư ở cả hai giới theo GLOBOCAN 2022.  Tỷ lệ phát hiện sớm ung thư vú ở Việt Nam còn khá thấp, dẫn đến tỷ lệ tử vong cao (8,3%). Sàng lọc và dự phòng chuyên sâu ung thư vú đóng vai trò quan trọng trong việc phát hiện sớm ung thư vú, tăng khả năng điều trị thành công và giảm tỷ lệ tử vong. Với bối cảnh thực tế của Việt Nam và đặc điểm về nhân chủng học, thói quen đi kiểm tra sức khoẻ và khả năng tiếp cận các phương pháp sàng lọc, nhóm nghiên cứu của chúng tôi đề xuất giải pháp cá thể hoá trong sàng lọc ung thư vú cho phụ nữ Việt Nam thông qua gói sàng lọc “Breast Check”. Mục đích của bài viết này là để xây dựng một chương trình sàng lọc ung thư vú dễ thực hiện, khả thi và hiệu quả nhất cho phụ nữ Việt Nam.
Can thiệp nội mạch 2 trường hợp giả phình mạch khổng lồ trong dò động mạch cảnh xoang hang
Authors: Nguyễn Huỳnh Nhật Tuấn , Nguyễn Văn Tiến Bảo , Phạm Đăng Tú , LÊ VĂN KHOA
Published: January 2025

TÓM TẮT
Giới thiệu ca bệnh: Dò động mạch cảnh xoang hang (DĐMCXH ) kèm giả phình mạch khổng lồ rất hiếm gặp theo y văn trên thế giới. Chúng tôi báo 2 ca bệnh đặc biệt của dò động mạch cảnh xoang hang với sự giãn lớn giả phình mạch khổng lồ vùng xoang hang, được điều trị can thiệp nội mạch (CTNM) thành công tại Bệnh viện Chợ Rẫy. Ca 1 là bệnh nhân nam 38 tuổi, tiền sử chấn thương 20 năm vào viện vì đau đầu cấp, hình ảnh CT/DSA là DĐMCXH phải với giãn dạng khổng lồ giả phình vùng xoang hang KT# 61,9x57,8x56,7 mm, giãn lớn tĩnh mạch vỏ não, và điều đặc biệt là lỗ dò cấp máu qua động mạch thông trước và thông sau đối bên, trong khi đó động mạch cảnh trong phải tắc mạn tính tại gốc. CTNM tiếp cận lỗ dò từ động mạch đốt sống qua động mạch thông sau phải vào lỗ dò, tắc hoàn toàn lỗ dò bằng coils, bảo tồn động mạch cảnh trong trên lỗ dò. Ca 2 là bệnh nhân trẻ nam 20 tuổi, tiền sử chấn thương 1 năm, vào viện vì chảy máu mũi lượng nhiều. Hình ảnh MRI/DSA là DĐMCXH phải với giãn dạng khổng lồ giả phình vùng xoang hang hàm mặt phải KT# 98,8x87,7x96,7 mm, kèm giả phình nhỏ cạnh vị trí lỗ dò, với huyết khối chiếm phần lớn bên trong giả phình. Làm test tắc động mạch cảnh cùng bên giả phình ghi nhận bàng hệ động mạch thông trước và thông sau tốt. CTNM  tiếp cận tắc vị trí ngay lỗ dò và động mạch cảnh vị trí tương ứng bằng coils. Cả hai ca bệnh có diễn tiến sau can thiệp tốt và xuất viện sau đó 3 ngày. Từ khóa: giả phình mạch, can thiệp nội mạch, dò động mạch cảnh xoang hang.
The Perception and Approach of Bangladeshi Ready-made Garment Factory in the Current Context of Digital Marketing
Authors: Zannat Meheraz , Iqbal Tareq , Tasnim Tamanna
Published: January 2025

As a catalyst, digital marketing promotes consumer interaction, recognition of the brand, and broadening company growth. Since the Bangladesh Ready-made garment sector makes a significant contribution to the economy of the country and engagement in the international market, the primary purposes of the study-the current scenario and perception of textile factories regarding digital marketing were analyzed using convenience sampling in a mixed-method approach and a self-made questionnaire, data from 29 factories. Descriptive statistics explored the factory's full consciousness of the effectiveness of digital marketing, but implementation and updates were slow and had limited benefits. It also attempts to develop hypotheses to observe which variables have a relationship with the factory’s initiative in digital marketing, and the Fisher exact test was applied. The odds ratio had helped for better interpretation, and most of the factories accepted that investment in digital marketing was worthy due to its cost effectiveness. Now the capabilities of digitalization are a matter of consideration, though sometimes factories are offered digital marketing from their suppliers, and then it’s easy to apply it to their buyers. Ultimately, building partnerships with technically sound companies and developing diversified items can help managers, owners, and stakeholders prosper in their worldwide business growth.
Yield Available for Tourism from Short-Term Investments: Evidence from Angola
Authors: Sanches-António Luzolo , Fernando Miguel
Published: January 2025

The present study aimed to contribute to a more informed view of the investment alternatives available in the Angolan financial market, which allow the realization of yields that can be channeled to consumer expenses such as those incurred in the context of tourism. To this end, a survey was carried out of the main valid alternatives for the investment of funds in the Angolan financial market, considering two possible alternatives: term deposits, with maturity of up to one year, and the purchase of securities: bonds and shares, also with maturity of up to one year. The main results indicate that in the short term, the alternatives that can provide the highest expected returns to potential tourists, who wish to use them for expenses related to tourism activities, are: term bank deposits at BIC, at an annual effective interest rate of 11.54% considering a daily capitalization period, and the purchase of shares in BODIVA.
تحرير المقاصد والقيم الأخلاقية في تحريم الرّبا وأهميته لترشيد الفتاوى المالية المعاصرة
Authors: Abozaid Abdulazeem
Published: January 2025

إنّ الربا بنوعيه ربا الدين والبيع من أهم مسبّبات فساد العقود، وأكثر أحكام الشريعة المالية ترتدّ إليه. وتحرير مقاصد الشريعة وقيمها الأخلاقية في تحريم الربا أمر ضروري لمعرفة علل الأحكام والإفادة منها في الاجتهادات الفقهية المعاصرة، لا سيما ربا البيع، بيد أنّ مقاصد تحريمه لم تُحرر على النحو الذي يرفع الَّلبس في فهم أحكامه ويعين على ربط المسائل المعاصرة بها. ويبدو أنّ التطورات التي طرأت على المعاملات المالية في عصرنا الحديث قد أعانت على الكشف عن مقاصد بعض هذه الأحكام، ربما لم تكن هذه الحِكم باديةً لفقهاء السلف، وهو ما أورث اضطراب اجتهاداتهم في بعض المسائل. يأتي هذا البحث محاولةً لتحرير مقاصد الشريعة وقيمها الأخلاقية في تحريم الربا بالإفادة من التجارب المالية المعاصرة، بغيةَ إجلاء محاسن التشريع الإسلامي وترشيد الاجتهاد الفقهي المعاصر الذي أنتج أحكاماً تتجرد عن مقاصد التشريع أو قيمه الأخلاقية في بعض المسائل ذات الصلة، وهذا ما يشكل مشكلة البحث. ويعتمد البحث المنهج الاستقرائي التحليلي، ومن أهم نتائجه أنّ تحريم الربا له مقاصد شرعية جزئية محددة وأن الفتاوى المعاصرة لم تراع في بعض الأحوال هذه المقاصد، فتنبغي مراجعتها.
ASSESSMENT OF SUBSTANCE USE RELATED EXPERIENCE OF MEDICAL STUDENTS IN A PUBLIC MEDICAL UNIVERSITY
Authors: Imtiaz Kashaf , Ammar Ahmad  , Adnan Rashid  , Nighat Haider
Published: January 2025

Background: Substance use affects all aspects of life of an individual. Males typically have higher tendency. Youth is particularly at risk. Curiosity, peer pressure, lack of knowledge and easy availability are major risk factors. Increasing trends of substance use are seen in medical students despite the fact that they are well aware of adverse effects of addiction. Study of consequences faced by medical students due to substance use is the main aim of research so these effects can be identified early and help can be provided in time. Methods: This was a descriptive cross-sectional study conducted among the students of a public sector Medical University situated in one of the main cities of Pakistan from 15th January to 15th April 2023. A total of 1038 students were recruited to the study using non-probability convenient sampling method. Data were entered & analyzed using SPSS version 26. Results: Only 1.4% (n=15) admitted substance use when direct question was asked and 2.02% (n=21) admitted when asked indirectly. 3.6% (n=38) experienced withdrawal symptoms. Feelings of guilt were observed in 18.5% (n=191), majority of which were first year students (n=51). Families of 3.3% (n=34) were worried due to substance use disorder. 0.3% (n=3) admitted being involved in criminal activity to obtain drugs of abuse. Conclusions: A considerable fraction of medical students were involved in substance use and majority of them faced consequences like medical effects, family issues and being involved in illegal activities.
Automating Rock Classification: A Vision Transformer Approach in Brazil's Ornamental Stone
Authors: Douglas Fiório Dias  , Karin Satie Komati  , Kelly Assis de Souza Gazolli
Published: January 2025

The ornamental stone sector in Brazil is renowned for its diverse array of rock types. However, the classification of these rocks largely relies on subjective assessments and the specialized expertise of professionals. This dependence has spurred interest in employing artificial intelligence (AI) to enhance the image classification process in this field. This study establishes a comprehensive labeled database of ornamental rock images, containing 1,798 images divided into 12 distinct classes, and makes this database publicly available. Additionally, it proposes the use of a Vision Transformer network, specifically the SI-ViT (Shuffle Instance-based Vision Transformer), which was originally developed for the automated classification of pancreatic cancer images, for this task. In comparative evaluations, the SI-ViT network demonstrated superior performance, outperforming established models such as Vgg16, Vgg19, Resnet50, Resnet101, Xception, and Inception v3, with an impressive accuracy rate of 99.68%.
Checking the Status of High Voltage Disconnection Switches Using Siamese Convolutional Neural Networks
Authors: Celso Soares Godoy  , Marcelo Denadai Marcon  , Gustavo Maia de Almeida  , Daniel Cruz Cavalieri  , Cassius Zanetti Resende
Published: January 2025

A high voltage power substation is an electrical installation made up of equipment responsible for transmission and distribution of energy for voltages above 69kV and below 230kV. Necessary to keeping our homes and industries running, a substation has various power equipment such as circuits breakers, power transformers and disconnection switches that guarantee its operation. These devices can be controlled locally or remotely way, either through control systems or manually by a human operator.One of the fundamental pieces of equipment to guarantee the operation of a substation is a disconnection switch. Disconnection switches are electromechanical equipment composed by moving parts, in a conventional substation. This equipment is subject to mechanical efforts, vibration and temperature. The wrong functioning of a disconnection switch can cause major losses for the company, from equipment downtime to a complete lack of power to the plant.With the aim of contributing to avoiding failures in the operation of an industrial substation, this work proposes the use of artificial intelligence (AI) and machine learning techniques, through computer vision based on the Siamese convolutional neural network to verify the disconnection switches opened and closed status of a power substation in a steel industry.
Collection and Processing of Data from Articles in Scientific Events
Authors: Thiago Magela Rodrigues Dias  , Guilherme Mascarenhas Dias  , Fernanda Coimbra  , Patrícia Mascarenhas  , Guilherme Mascarenhas Dias
Published: January 2025

Several studies focus on exploring the behavior of scientific evolution. For this reason, one of the main means of scientific communication today is events, in which diverse and valuable works are generated, also enabling fast communication and possibilities for argumentation. However, most works that evaluate scientific production in scientific events generally have specific repositories as a data source, often restricted to some areas of knowledge. Although such works present interesting results, no studies were found that encompass events in general, with a large number of publications or that address different areas. In this context, this work aims to analyze the scientific production published in the annals of events of the group of physicians who have CVs registered on the Lattes Platform. The data used were extracted from the Lattes Platform in January 2021, so that all the selection and processing of the data of interest could be carried out. Therefore, this work has the general objective of analyzing the scientific production published in events, understanding how Brazilian scientific production occurs in this means of dissemination, using bibliometric metrics in the data extracted from the curricula registered in the Lattes Platform.
Intelligent analysis system and automatic conference of train formations at EFVM using computation vision
Authors: Diogo Henrique da Silva  , Gustavo Maia de Almeida
Published: January 2025

Every wagon and locomotive has an alphanumeric code on each of its longitudinal faces that identifies and distinguishes it from any other railway vehicle on the Brazilian network. The train formation process consists of joining one or more sets of wagons and locomotives, which will be used to transport ore, and is an inherent step in the railway logistics process, where resources (wagons and locomotives) are joined or separated due to physical limitations of ore loading terminals. At the end of a formation we have a sequence of vehicles ordered and sequenced by their codes, and from this we are able to identify the characteristics of the ore being transported. The activity of forming trains is very important in railway operations, and requires attention and care, as they involve operational, fiscal and commercial risks, which, if not mitigated, can bring irreparable negative results. Such results range from fines imposed by government agencies and even potentially catastrophic accidents, thus putting the lives of employees, communities, partners and the environment at risk. As an example, we have the possibility of an ore composition being delivered with the wrong wagon sequence to a customer, and it entering the production line of a steel mill, which could cause an explosion due to the use of a type of ore wrongly added to a mixture in the blast furnace. Faced with such high risks, the activity of checking the trains after the maneuvers to separate and join the wagons becomes even more important. Making a cut in the Iron Ore circuit on the Vitória a Minas Railway, around 7,800 wagons are allocated daily per train, making checking all formations/compositions a very laborious task. The present work consists of the development of an intelligent system, based on Computer Vision, which automatically checks the alphanumeric codes of train compositions, aiming to guarantee the correct sequence of wagons in each formation of ore trains in the Tubarão yard in Vitória a Minas Railway.
Invisible Colleges and Technical Production: A Study of Patents in Brazil
Authors: Thiago Magela Rodrigues Dias  , Patrícia Mascarenhas Dias  , Felipe Campos
Published: January 2025

Analyzes of scientific collaboration networks have been extensively explored in research from different areas of knowledge, in view of their ability to identify how groups of researchers have carried out their work collectively. Such studies make it possible to identify how collaboration between individuals occurs through analyzes based on social network metrics. In this context, new studies have been proposed in order to analyze collaboration in the development of technical products, with data on patents being studied in most studies. This type of analysis is relevant because it makes it possible to understand the collaboration process in the proposal of new inventions. In this work, initially a general characterization of the group of individuals analyzed is presented, and afterwards, a global and temporal analysis of the collaboration network is performed in the proposal of patents of Brazilian individuals with curricula registered in the Lattes Platform. For that, all the patents registered in the curricula of these individuals were used for the identification and characterization of the collaboration networks. As a result, it is possible to see how collaboration in the proposed inventions of the analyzed set has been intensified over the years, with an emphasis on the institutions and areas of expertise of each inventor.
Socioeconomic Analysis of students who took the Enem between 2019 and 2022 using Machine Learning
Authors: Bruno da Silva Macêdo  , Pablo da Silva Macêdo  , Bruno Henrique Groenner Barbosa  , Cristina Maria Valadares de Lima  , Patrícia Mascarenhas Dias  , Camila Martins Saporetti  , Leonardo Goliatt
Published: January 2025

The National Secondary Education Examination (Enem) is the exam that allows students, through the results obtained, to enter higher education institutions. Socioeconomic analysis is the means that evaluates the economic relationship with a portion of society. Through this analysis, which is carried out through socioeconomic questionnaires carried out in Enem, it is possible to analyze the factors that impact student performance. In this context, the objective of this work is to carry out a socioeconomic analysis of Enem from 2019 to 2022, aiming to identify possible social inequalities and factors that may influence students' performance in Enem. With socioeconomic analysis, it is possible to define a target audience in which public measures are needed to avoid social inequalities, seeking to promote more opportunities and equal access to education and higher education. Due to the size of the Enem databases from 2019 to 2022, the Knowledge Discovery in Databases(KDD) steps were adopted to carry out the analyses, which consist of: selection, pre-processing, transformation, data mining and interpretation of data through discovered knowledge. Furthermore, in the development of the KDD stages, the programming language Python. As a result, between 2019 and 2022, two groups were divided for each year, a group of students with good performance and one of students who did not perform as expected. The group of students with good performance, the vast majority are from private schools, white color/race, with a computer at home, southeast and northeast region, monthly family income in class C where the minimum wage is 4 to 10, class D in that the minimum wage is 2 to 4, and class E of up to 2 minimum wages. Furthermore, of the students who did not perform as expected, the vast majority are from public schools, brown color/race, do not have a computer at home, are from the southeast and northeast regions, have a monthly family income of class E, which is up to 2 salaries minimums.
Study of the Temporal Propagation of Arboviruses in the Region of Recife-PE: Analysis of Climatic Influence using the SIR Model and Recurrent Neural Networks
Authors: Guilherme Lopes de Campos  , Rita de Cássia de Vasconcelos Pedrosa  , Cláudio Tadeu Cristiano
Published: January 2025

The occurrence of disease outbreaks, especially Dengue, Zika and Chikungunya, is on the increase throughout Brazil, and is currently a significant concern for the Recife-PE region due to the high temperatures. This directly affects public health and the population's quality of life, as well as the city's economy and education. To deal with this challenge, public policies are being implemented, such as awareness campaigns, inspections, and case reports. However, underreporting is a common problem due to the lack of demand for health services and difficulties in accessing medical care, which is reflected in official municipal data. In addition, there are gaps in the treatment of the specificity and cause of the problem and its mitigation. To overcome this inaccuracy, dynamic models such as the SIR model have been widely used in epidemiology. This model, which is based on differential equations, describes the temporal evolution of the susceptible, infected, and recovered classes. In Recife, the ambient temperature shows a strong positive correlation with the infection rates of cases of the diseases, which leads to the intensification of prevention campaigns during the summer. A study carried out in 2022 used data from the National Institute of Meteorology (INMET) to adjust a trigonometric function and analyse the seasonal influence of climate on infection rates, applying the SIR model. In addition, monthly iterations were carried out using the Runge Kutta numerical method in Simulink software. To improve the prediction and qualification of endemic disease cases, long-term memory modelling was used with a Recurrent Neural Network (RNN), validated based on available epidemiological data, obtaining an RMSE error metric of around 0.8 for the three diseases assessed.
Technical Decisions Influences on Dynamics and Results in Football: An Analytical Approach Based-On Graph Theory
Authors: Felipe Werneck de Oliveira Mendes  , Thiago Magela Rodrigues Dias  , Alisson Marques da Silva  , André L. Maravilha  , Michel Pires da Silva
Published: January 2025

Soccer players are meticulously and continuously observed and evaluated during games based on their roles, positions, and characteristics. In a scenario of great tactical complexity, it becomes essential to identify variations in athletes' performance, a dynamic that directly impacts the quality of the team during each competition. In this context, relevant challenges emerge and require meticulous analysis of the teams and their behavior during the game. Among these challenges, evaluating the player's performance is an important aspect that is deeply influenced by the strategic approach adopted by the coach. In this paper, we explore the issue of individual player performance, given the different philosophies and strategies that coaches use during each match. In this context, we introduced an analysis approach based on graph theory, aiming to evaluate the relationships between players, the quality of assistance in the match, and the coaches' strategies to develop a model capable of identifying the different impacts of strategic composition in individual gameplay. The results show that training strategies adopted can considerably influence gameplay quality and, consequently, the player's performance during a match.
The Relationship between Occupation, Sleep Disorders, and Health Impacts: an Analysis Based on Maximum Spanning Tree
Authors: Letícia de Oliveira Silva  , Thiago Magela Rodrigues Dias  , Alisson Marques da Silva  , André Luis Maravilha Silva  , Michel Pires da Silva
Published: January 2025

The health challenges of sleep quality disorders are notable, especially in certain occupational groups and their interactions with the professional job environment. The adversities in such a professional atmosphere can compromise the excellence of activities, the quality of life, and, consequently, physical and mental health. The present study proposes an analysis model to investigate the relationship between health and job occupation in developing sleep disorders. The objective is to identify the professional groups most susceptible to these problems, thus highlighting the predominant characteristics in the manifestation of such disorders. In this context, based on Kruskal's algorithm, we adopt the maximum spanning tree strategy to investigate the sleep quality datasets available on the Kaggle platform. The results show a broad relationship between hereditary conditions, such as high blood pressure, with the professional occupation and several sleep quality disorders, such as insomnia and apnea. With these results, we hope to amplify the discussions and evidence that certain occupational groups, due to high levels of occupational stress, tend to suffer considerable influence on indicators such as increased blood pressure and sleep quality disorders, having relevant impacts on the lives of these individuals.
Shell Analysis Using a Solid-Shell Approach
Authors: Pedro Ygor Rodrigues Mesquita  , Evandro Parente Junior  , João Batista Marques de Sousa Junior  , Elias Saraiva Barroso
Published: January 2025

Shells are curved three-dimensional structures whose thickness is much smaller than their other two dimensions. They can be found in various sectors, such as aerospace, energy, naval and civil engineering. There are several structural theories in the literature to deal with this type of structure, such as Kirchhoff-Love, Reissner-Mindlin and Higher-order theories. However, these theories are based on assumptions that require rotational degrees of freedom in their kinematic description, making the problem complex, especially for geometrically nonlinear analysis, since large 3D rotations are not additive. Furthermore, in shell theories, it is usually assumed that there is no thickness stretching. In other words, the normal transversal strain is neglected, so it is not possible to use full 3D constitutive models for the analysis. With this in mind, the structural modeling in this work will be based on the solid-shell approach, which uses a 3D mesh with only one element through the thickness and does not require rotational degrees of freedom in the kinematic description, like in solid elements, but with a lower computational cost. Its formulation considers the general stress state, so a complete 3D constitutive relation is assumed. The use of this theory in structural problems results in partial differential equations whose analytical solutions are very complex or impossible to obtain, thus requiring the use of numerical methods to obtain approximate results. The presented formulation can be applied to develop isoparametric and isogeometric solid-shell elements. The performance of linear and quadratic elements is assessed using numerical examples.
Comparative Study of Intelligent and Classical MPPT Techniques Applied to Solar Battery Charger
Authors: Mario Henrique Bigai  , Lucas Santana de Freitas  , Matheus Tauffer de Paula  , Eloi Agostini Jr  , Fernanda Cristina Corrêa
Published: January 2025

Renewable solar energy is an excellent alternative to conventional energy sources and, recently, it has shown remarkable growth on electrical power grid in various countries around the world. Maximum power point tracking (MPPT) has critical importance in solar energy generation since it increases the system's efficiency in many scenarios. Photovoltaic modules (PV) are influenced by environmental factors such as temperature and solar irradiation density, changing the amount of energy generated throughout the day. In order to extract the maximum available power from a PV, its necessary to use the MPPT technique, which considers the systems nonlinearities. Maximum power tracking (MPP) is done by tuning the duty cycle of the DC-DC converter, so that the PV's terminal voltage is modulated to match the environmental conditions. This tuning, generally, is dependent on sensor readings. Normally, only the modules voltage and current sensors are used, due to the low cost and ease of acquisition of these signals. However, intelligent techniques demand the usage of temperature and irradiation sensors, increasing the complexity of the systems implementation. The use of intelligent control techniques applied to the energy generation system has had a notable presence in recent publications. The high efficiency obtained from its application demonstrates that the use of intelligent systems in the decision-making process is a useful tool in obtaining maximum generation power. The objective of the present study is the development and simulation via MATLAB/SIMULINK of a battery charging system with solar energy, which consists of a PV, a Buck converter, a 12V battery, and the MPPT controller. The intelligent fuzzy logic MPPT technique (FLS) and the classical incremental conductance technique (INC) will be compared, both techniques using only voltage and current measurements.
Computational Simulation of a Plane Channel with Spalart-Allmaras Turbulence Model and Fourier Pseudo-Spectral Method
Authors: Laura Augusta Vasconcelos de Albuquerque
Published: January 2025

The majority of fluid flows encountered in nature and practical applications are turbulent, characterized primarily by a broad range of scales, from large structures influenced by flow geometry to small structures determined by fluid viscosity. Turbulence is a topic of significant relevance in engineering across various sectors. For instance, airflow over terrestrial surfaces, where roughness varies considerably, is critical for predicting the potential and sizing of wind turbines and wind farms.In this context, this study proposes extending the IMERSPEC methodology to conduct simulations of turbulent flows based on Reynolds-averaged Navier-Stokes equations, utilizing the Spalart-Allmaras turbulence model. The IMERSPEC methodology integrates the Fourier Pseudo-Spectral Method with the Immersed Boundary Method, offering excellent numerical accuracy and computational efficiency compared to other high-order techniques, attributed to the efficient use of Fast Fourier Transform (FFT) and the pressure term projection method in Fourier space.The numerical results obtained through this approach are validated against experimental data and Direct Numerical Simulations (DNS) for flow in a flat channel at a Reynolds number of 40,000. This comparative analysis will facilitate assessing the effectiveness and precision of the proposed method in capturing turbulent flow characteristics, with potential applications in aerodynamic and fluid dynamic engineering studies.
Discussion on bending-torsion behavior of long wind turbine blades
Authors: Gabriel Vicentin Pereira Lapa  , Alfredo Gay Neto
Published: January 2025

In recent years there has been a tendency to increase the size of wind turbine rotors, particularly when considering offshore applications, leading to more capacity for energy extraction from wind. However, there are many engineering challenges to that. Blades become very long, surpassing lengths of 100 meters, and are usually very flexible, which claims a geometrically nonlinear model for evaluation of their structural behavior. In this context, the present work employs an enhanced structural solver to evaluate the behavior of very flexible wind turbine blades. The blades are modeled as beams. Large displacements and finite rotations are assumed to model the kinematics by employing the geometrically-exact theory. To establish a relationship between generalized internal loads and generalized strains we adopt a linear constitutive model such that one can take results from BECAS, directly. This can handle torsion-bending constitutive coupling for a general position of the beam axis, conveniently. The developed solver was used to study general operational conditions, assuming distinct pitch angles for the blade considering the scenario of the wind turbine. The present work brings discussions on the structural behavior, such as internal loads distributions along the blade spam in numerical simulations. The focus is given to the analysis of bending and torsion moments, discussing their aspects when considering such a long and flexible blade in operational conditions.
Estimation of wind energy potential through experimental investigation of boundary layer in small wind tunnel
Authors: Felipe Pamplona Mariano  , Cássia Silva de Azevedo Maia  , Andreia Aoyagui Nascimento  , Marlipe Garcia Fagundes Neto
Published: January 2025

In Brazil, the persistent increase in electricity consumption, primarily propelled by economic and technological advancements, can exceed the capacity of generation and distribution, underscoring the imperative for alternative energy sources. Given the compromised state of hydroelectric power and the environmental ramifications of thermoelectric plants, wind energy emerges as a promising and sustainable solution. Research in this domain encompasses turbine efficiency and analysis of local wind potential. Precise determination of this potential is pivotal to ensure project viability and efficacy, directly impacting decisions of electrical generation companies. Tests for assessing wind potential can be conducted in situ or employing techniques such as Fluid Dynamics, crucial for large-scale projects. Experimental investigations, particularly those conducted in wind tunnels, assume a foundational role in research and development in this field. The distribution of wind velocity across the test section stands as a critical parameter, with accurate simulation of the atmospheric boundary layer being indispensable for dependable outcomes. The boundary layer, an area adjacent to the surface influenced by friction between solid and fluid, holds a crucial role in drag and heat transfer. Various techniques have been devised to simulate and control the boundary layer in wind tunnels, representing a burgeoning area of inquiry. The present study advocates for the utilization of the 'boundary layer plate with flap device' to examine how different flap angles and Reynolds numbers impact boundary layer height, employing experimental design with factorial planning for result analysis. Subsequently, the obtained results indicate that flap angle significantly alters the boundary layer height within a given range of Reynolds numbers, thereby enabling the simulation of diverse boundary layer heights within a small wind tunnel, facilitating experiments related to wind flow and atmospheric boundary layer. Consequently, this research contributes to the estimation of wind potential and propels the efficient utilization of wind energy as a clean and renewable source.
Soil-structure interaction effects on modal analysis of a 3D reticulated structure supporting plane rectangular shells
Authors: Patrick de Oliveira Batista da Costa  , Lucas P. de Souza  , Dhionata W. M. Santos  , Daniel C. de M. Candido  , Paulo de O. Weinhardt
Published: January 2025

This paper aims to verify the interference of soil-structure interaction (SSI) on the natural frequencies and on the respective vibration modes of a 3D reticulated structure supporting plane rectangular shells. This is done through a computational linear elastic 3D finite element model using EulerBernoulli frame elements, biquadratic Lagrangian thin shell elements and elastic translation springs for the soil at columns bases (representing pile embedded length). A convergence analysis is performed to determine the maximum mesh size and mass participation factors are measured to establish the number of considered vibration modes. Chosen elastic spring coefficients are extracted using polynomial linear regression applied to the results of experimental compressive and horizontal load tests of steel piles embedded in a silty clay soil. Using these parameters, nine models are processed via an eigen solver and obtained frequencies and some mode shapes are presented. It is found that, for the adopted approach and for the evaluated structure, there are not significant changes in modal response induced by SSI, being the mass distribution more important than soil stiffness in this case. Despite the results, this study indicates the need of further investigation to provide better measures about the interference of SSI on modal response of structures as the one analyzed in this research.
Structured Model for Hydrothermal System Operation and Optimization
Authors: Guilherme Sanches da Silva  , Patricia Teixeira Leite Asano  , Roberto Asano Junior  , Thales Cunha da Paixão
Published: January 2025

This paper presents an analysis for optimizing hydrothermal system operation within the Brazilian energy sector.In the last years, researchers at the Laboratory of Bio-Inspired Technologies and Solutions from Federal University of ABC (LabBITS - UFABC) have been implementing a platform for accessing the information of this Brazilian electric power generation system from a SQL (Structured Query Language) database, regularly updated from the ONSs provided package of files. The database is accessed by the laboratory researchers via a REST (Representational State Transfer) API (Application Programming Interface) which is used to supply the parameters of the energy system models used in the energy operation planning calculations.In 2024, utilizing Java object models for hydroelectric power plants, a structured approach was developed, organizing plants into power plant systems to capture the interdependencies between flow data and storage of water in reservoirs throughout a cascade and across time.The simulation technique of genetic algorithms was then applied to test the structure for optimal operating schedules. Different populations of solutions were tested, considering the maximization of energy generation.
Aerodynamic and structural optimization of wind turbine blade considering natural of frequencies of vibration
Authors: Patricia Habib Hallak  , Júlia Cássia da Silva Kunsch  , Nicolas Lima Oliveira
Published: January 2025

In recent years, wind energy has garnered significant global attention due to its immense energy and environmental potential, leading to a substantial increase in both capacity and size of wind turbines, evolving from a nominal power of 75kW to 7.5MW and a rotor diameter of 17m to over 125m. However, this scaling-up has introduced new challenges related to instability caused by the aeroelastic effect, which stems from the interplay between wind loads and the structural deformation of wind turbine blades. Consequently, an effective model necessitates well-defined aerodynamic and structural components. Yet, the complex geometric shapes of turbines demand extensive computational resources for analysis, particularly given their composite materials and intricate configurations.Various research institutions, including NREL, DTU, and ECN, have developed aeroelastic tools for wind turbine studies, integrating structural and aerodynamic modules. The prevalent approach employs the BEMT (Blade Element Moment Theory) model for aerodynamic simulation and FEM models for structural dynamic analysis. The BEMT model partitions the blade into elements to evaluate aerodynamic loads based on local characteristics. This amalgamation offers an efficient solution for predicting element performance parameters. Additionally, the BEM model provides a computationally economical alternative to more intricate models, making it a cost-effective choice for wind turbine analysis and a cheaper tool compared to robust methods, like CFD.This work proposes an aerodynamic optimization method constrained by the structural model, focusing on the natural vibration frequencies of wind turbine blades. The methodology comprises three phases: defining the aerodynamic model using the CCBlade code in Julia Language, implementing the structural analysis method via FEM for rotating Timoshenko beams in MATLAB, and integrating the aerodynamic and structural models on a multi-objective optimization platform. Evolutionary algorithms were employed to enhance wind turbine energetic efficiency and avoid structural instabilities within this study. By leveraging advancements in modeling and optimization techniques, the aim is to contribute to the development of more efficient and reliable wind turbines, further promoting the transition to clean and sustainable energy sources.
Analysis of optimization algorithm models for the design of prestressed steel beams
Authors: Lucas Sena da Cruz  , Élcio C. Alves  , Elisabeth J. Laure
Published: January 2025

Prestressing in steel beams offers significant benefits in terms of structural efficiency and material savings. The aim of this study is to present a comparative analysis of the design results of prestressed steel beams obtained through three optimization algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and its variant, including a craziness operator for performance enhancement (CRPSO). These algorithms were used to minimize CO2 emissions and cost in the structural design process, while adhering to the constraints imposed by ABNT NBR 8800:2008. The implementation was carried out using MATLAB (2016). The validation of the methodology was conducted using examples from the literature, comparing the CO2 emissions and cost values obtained from experimental work and those derived from GA, PSO, and CRPSO. The results indicate that, although the Genetic Algorithm is widely used in optimization, more optimized results are achieved using PSO. Furthermore, the improvement obtained by CRPSO showed no significant deviation from those obtained by PSO, nor did it affect the convergence speeds of the results. It was also observed that all three implemented models yielded more optimized values of emissions and costs compared to those reported in the literature.
Backcalculation of asphalt pavement materials moduli considering absolute and relative errors
Authors: Evandro Parente Junior  , Lia Beatriz Gomes Furtado  , Elias Saraiva Barroso  , Samuel de Almeida Torquato e Silva  , Juceline Batista dos Santos Bastos  , Lucas Feitosa de Albuquerque Lima Babadopulos
Published: January 2025

Backcalculation is a procedure used to estimate the material properties of pavement layers from the results of non-destructive tests, such as the Falling Weight Deflectometer (FWD). This procedure is important to assess the quality of a pavement structure during its construction and/or to monitor its condition during its lifespan. The Finite Element Method (FEM) can be used to evaluate the pavement deflections, provided that the loading, geometry, and material properties of each pavement layer are known. Thus, assuming a linear elastic behavior and known Poissons ratios and layer thicknesses, the backcalculation procedure consists of the determination of the set of elastic moduli that minimize the differences between the simulated (FEM) and measured (FWD) deflections. Different error measures can be adopted to assess the quality of the model fitting. The resulting Nonlinear Least Squares (NLS) problem can be solved using classical algorithms, such as Gauss-Newton and LevenbergMarquardt methods. However, these algorithms present convergence problems for NLS with large errors. In this case, it can be necessary to use of hybrid algorithms based on a combination of Gauss-Newton and BFGS methods. The robustness, accuracy, and computational efficiency of classical and hybrid algorithms are compared in the backcalculation of asphalt pavements.