bluuebunny/crossref_metadata_2025 huggingface dataset:
A 32-Year-Old Man Presented with Nephrotic Syndrome Due to Systemic Lupus Erythematosus Developed Lupus Cerebritis, Pancytopenia and Renal Failure: The Need for New Biologicals
Authors:   Professor and Head/ Senior Consultant Physician and Nephrologist, Department of Medicine/Department of Nephrology, Defence Services Medical Academy/ No. (1) Defence Services General Hospital (1000-Bedded), Yangon, Myanmar., Pyar Khin Phyu , Thant Myat Min ,   Internal Medicine Fellow, Department of Medicine, Defence Services Medical Academy, Hlaing Zin Phyo ,   Renal Pathologist, Department of Pathology, Defence Services Medical Academy, Kyaw Aung Htoo ,   Consultant Physician, No. (1) Defence Services General Hospital (1000-Bedded), Oo Kaung Myat ,   Consultant Pathologist, No. (1) Defence Services General Hospital (1000-Bedded), Htet Aung ,   Consultant Radiologist, No. (1) Defence Services General Hospital (1000-Bedded), Htet Aung Zaw ,   Consultant Nephrologist, No. (1) Defence Services General Hospital (1000-Bedded), Aung Aung ,   Consultant Hematologist, No. (1) Defence Services General Hospital (1000-Bedded), Myo Aung ,   Consultant Pulmonologist, No. (1) Defence Services General Hospital (1000-Bedded), Hlaing Soe Win ,   Senior Consultant Physician, No. (1) Defence Services General Hospital (1000-Bedded), Myint Win ,   Consultant Neurologist, No. (1) Defence Services General Hospital (1000-Bedded), Lwin Kyaw Thurein ,   Consultant Nephrologist, No. (1) Defence Services General Hospital (1000-Bedded), Phone Sai Su ,   Consultant Rheumatologist, No. (1) Defence Services General Hospital (1000-Bedded), Swe Htet Aung ,   Consultant Rheumatologist, No. (1) Defence Services General Hospital (1000-Bedded), Ko Myat ,   Nephrology Fellow, Department of Nephrology, Defence Services Medical Academy, Ya Kyaw Zay ,   Consultant Hematologist, No. (1) Defence Services General Hospital (1000-Bedded)
Published: October 2024

A 32-year-old man presented with nephrotic syndrome due to membranous nephropathy, secondary to systemic lupus erythematosus (SLE). During intensive immunosuppressive therapy with corticosteroid and cyclophosphamide, the patient developed confusion, fits (lupus cerebritis), pancytopenia and rapidly rising serum creatinine (end stage renal failure). Plasmapheresis and rituximab therapy did not make improvement. Later, the patient had gastro-intestinal bleeding, ARDS secondary to bacterial pneumonia, fits and succumbed. Multiple cerebral hemorrhages, consolidation and bilateral small kidneys were found in autopsy.
Intercondylar Fracture of the Elbow in a Pediatric Patient
Authors:   Centro Hospitalario Pereira Rossel, D Saralegui , V Teske ,   Centro Hospitalario Pereira Rossel, M Pérez ,   Centro Hospitalario Pereira Rossel
Published: October 2024

To present a case assisted at the Pereira Rossell Hospital Center of a very rare injury, its evolution, as well as an update on the diagnostic and therapeutic measures for this type of injury. Clinical case: A 12-year-old adolescent with no significant personal history who suffered a fall from a horse with direct trauma to the right elbow and no other trauma. Physical examination at the emergency room revealed a painful and swollen right elbow, no skin lesions, and no distal neurovascular alterations were found. Diagnosis was confirmed after requesting a CT scan of the elbow, which showed a supracondylar fracture. The fracture line divided the capitellum and was directed medially. A closed reduction maneuver and medial approach without arthrotomy were performed to identify the ulnar nerve. Three medial and one lateral Kirschner needles were placed. A brachypalmar splint was made. The Kirschner needles were removed at 6 weeks. Follow-up at 3 months after the injury.
The Effect of Black Cumin (Nigella sativa) on Hb and VEGF Levels in Lung Cancer Patients Undergoing Chemotherapy at Dr. Saiful Anwar General Hospital, East Java
Authors:   Department of Pulmonology and Respiratory Medicine, Faculty of Medicine, Universitas Brawijaya, Izzati Arina Aftritia , Chozin Iin Noor ,   Department of Pulmonology and Respiratory Medicine, Faculty of Medicine, Universitas Brawijaya, Pratiwi Suryanti Dwi ,   Department of Pulmonology and Respiratory Medicine, Faculty of Medicine, Universitas Brawijaya
Published: October 2024

Background: Studies show that the cytotoxic effect of black cumin seed extract and oil can reduce the viability of lung cancer cells including VEGF and increase the Hb of cancer patients. This study aims to compare Hb and VEGF levels between lung cancer patients undergoing chemotherapy with black cumin (Nigella sativa) and those undergoing standard chemotherapy. Methods: This study used a quantitative approach using the pre-post test control group design method involving 21 lung cancer patients at Dr. Saiful Anwar General Hospital, Malang, who were observed for 9 weeks between August and November 2023. The control group included patients undergoing standard chemotherapy and the treatment group included those undergoing chemotherapy with the addition of black cumin. Examination of Hb and VEGF levels used ELISA. Results: There were significant pre and post differences between the control and treatment after the 9-week study regarding their Hb and VEGF levels groups with a p-value of 0.021 and a p-value of 0.007, respectively. Conclusion: The addition of black cumin for 9 weeks plays a role in preventing the decrease in Hb values and reducing VEGF levels in cancer patients receiving standard chemotherapy.
Toxic Epidermal Necrolysis: A Clinical Case Report with Emphasis on Diagnosis, Management, and Prognostic Implications
Authors:   Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Leon, Guanajuato, Mexico. Residente de segundo año de medicina interna., Cortés Samantha Castro , Gutiérrez Karla Itzel Sánchez ,   Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Leon, Guanajuato, Mexico. Residente de segundo año de medicina interna., Castro Renata Fernanda Rodríguez ,   Clínica MAPFRE UP. Médico Interno de Pregrado, Trujillo Néstor Daniel Rodríguez ,   Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Hospital General de Querétaro.
Published: October 2024

Toxic epidermal necrolysis (TEN) is a rare, life-threatening dermatologic emergency characterized by extensive keratinocyte apoptosis, resulting in widespread epidermal detachment and mucosal involvement. Its pathogenesis is primarily linked to an immune-mediated response triggered by certain medications. This report presents a case of a 45-year-old female who developed TEN following administration of an antibiotic regimen. The patient exhibited progressive skin detachment affecting over 30% of the body surface area, with concurrent ocular and oral mucosal involvement. Despite initial delays in diagnosis, aggressive management with fluid resuscitation, prompt drug discontinuation, and systemic immunosuppressants led to stabilization and eventual recovery. This case highlights the importance of early recognition, the need for a multidisciplinary approach, and the challenges in managing complications such as secondary infections and multi-organ dysfunction. Additionally, we discuss the diagnostic criteria, therapeutic options, and the role of emerging therapies, providing a comprehensive overview for clinicians facing similar cases.
Winter is coming. De Winter Pattern
Authors:   “Instituto Mexicano del Seguro Social, Hospital General Regional 45” Internal Medicine division Guadalajara, Jal, Mexico, M.D. Assen Ognianov-Iantchoulev , M.D. Ingrid Ailyn Gonzalez Lozano ,   “Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Hospital Regional Valentín Gómez Farias” Cardiology division Guadalajara, Jal, Mexico, M.D. Jose de Jesus Valdivia Nuno ,   “Centro de neurodiagnostico Salpetriere”, Cardiology Department, Zapopan, Jal, Mexico,
Published: October 2024

The De Winters electrocardiographic pattern, which is present in only 2% of cases of acute myocardial infarction, is an electrocardiographic pattern with a high risk of complications since acute occlusion of the anterior descending artery must be considered. Early recognition and appropriate therapy are what improve the prognosis in this patients.
A Case of Intractable Shoulder Pain with Deltoid Muscle Atrophy- A Presentation of Parsonage Turner Syndrome
Authors:   Coffeyville Regional Medical Center, Coffeyville, KS, USA, Gangula Shravan
Published: October 2024

Parsonage-Turner syndrome is a rare, idiopathic plexopathy that causes severe shoulder pain followed by weakness. It is mostly unilateral, involves the brachial plexus and can present similar to several different diseases. It is ultimately a diagnosis of exclusion. Here is a case report describing the workup of a patient presenting with symptoms suspicious for Parsonage-Turner syndrome.
SPERA President's Message
Authors: Terry Emmy
Published: October 2024

A message from Emmy Terry, SPERA president.
Aguadeiros em Feira de Santana/BA
Authors: Cruz de Souza Gomes Pedro Alberto
Published: October 2024

O presente estudo objetiva analisar aspectos das relações raciais e de trabalho envolvendo os aguadeiros de Feira de Santana/BA entre 1893 e 1936. Laçamos mão de documentos como códigos de posturas, livros de matrícula, matérias de jornais e fotografias para acessar fragmentos das experiências dos aguadeiros num contexto de reordenamento do território urbano, baseado em práticas de racialização e policialização dos trabalhadores de rua. O pós-abolição aparece enquanto importante chave de leitura, contribuindo para o entendimento das diferentes posições assumidas por trabalhadores negros e elites locais no que concerne ao uso e apropriação do território urbano.
Kinematics of a humanoid robot arm with six degrees of freedom
Authors:   Al-Farabi Kazakh National University, Zh.T. Zhumasheva  , B. O. Amanov  ,   Al-Farabi Kazakh National University, S. A. Tolenov  ,   Al-Farabi Kazakh National University, B. M. Sagitzhanov  ,   Al-Farabi Kazakh National University, E. N. Zholdasov  ,   Al-Farabi Kazakh National University, A. M. Toleushova  ,   Al-Farabi Kazakh National University, N. K. Dosmagambet  ,   Al-Farabi Kazakh National University, Z. A. Rahmatulla  ,   Al-Farabi Kazakh National University
Published: October 2024

In this work, the direct and inverse kinematics of a humanoid robotic arm are solved. It is a remote controlled social robot. To study the kinematics of the robot-manipulator, the Den-with-Hartenberg transformation matrices were obtained. The position of the last performer (hand) is determined by multiplying these matrices. To study the inverse kinematics of the robotic arm, the feedback method is used to analytically determine the contact angles.
Analysis of the relevance and prospects of application of federate training
Authors:   International Information Technology University, Bektemyssova G. U. , Bakirova G. S. ,   International Information Technology University, Yermukhanbetova Sh. G. ,   International Information Technology University, Shyntore A. ,   International Information Technology University, Umutkulov D. B. ,   International Information Technology University, Mangysheva Zh. S. ,   Kazakh-British Technical University
Published: October 2024

This article examines federated learning (FOE) as an innovative approach to machine learning, different from traditional methods. In conventional machine learning (MO), data is collected on a central server to train the model. However, in the case of FO, the learning model is directed to data distributed across local devices, and learning takes place directly on these devices. In addition, the article discusses methods and algorithms of federated learning, identifies the advantages and real areas of application of federated learning. FO is used in various fields, including working with medical data and personal data of customers in sales companies. This approach is especially valuable for ensuring data confidentiality and privacy.
GPR sounding source calibration
Authors:   Manash Kozybayev North Kazakhstan university, Orman M. , Boranbayev S. A. ,   L.N. Gumilyov Eurasian National University, Kurmashev I. G. ,   Manash Kozybayev North Kazakhstan university, Karchevsky L. ,   Sobolev Insritute of Mathematics SB RAS
Published: October 2024

The paper describes the process of calibrating a GPR sounding source, provides a mathematical basis for this process, and presents the results of calibration based on data measured in a sand quarry, where the electromagnetic parameters of the probed medium are known. The obtained parameter values characterizing the behavior of the source can now be considered known and used to numerically solve inverse problems to determine unknown electromagnetic parameters of the medium using algorithms that are not built into the GPR software.
On the condition for solvability of a bundary value problem of dirichlet type for differential equations with involution
Authors:   Khoja Akhmet Yassawi Kazakh-Turkish International University, Usmanov K. I. , Nazarova K. Zh. ,   Khoja Akhmet Yassawi Kazakh-Turkish International University, Erkisheva J. S. ,   Khoja Akhmet Yassawi Kazakh-Turkish International University
Published: October 2024

This article considers a boundary value problem for a nonlocal second-order differential equation. Such problems arise when considering the solvability of boundary value and initial boundary value problems for nonlocal partial differential equations.
Relational GIS database for monitoring dams and weirs: structure and organization of data
Authors:   Astana IT University, Mukanova B. G. , Tanyrbergenova K. I. ,   National Information Technologies, Mirgalikyzy T. ,   Al-Farabi Kazakh National University, Akhmetov E. M. ,   National Center for Integrated Processing of Mineral Raw Materials
Published: October 2024

The paper is devoted to the analysis of the structure of the GIS relational database developed by the authors. The database is intended to support and document monitoring of dams located on the territory of the Republic of Kazakhstan. The paper discusses issues of organizing and recording data. The issue of data structure in the case of a “many-to-many” relationship, characteristic of many database objects, is separately considered. Various possibilities for implementing this relation in tables are shown, a compara- tive analysis of the volume of tables and the speed of execution of sampling queries is carried out.
Impact of Mother’s Profession on Academic Performance of Children: A Sociological Investigation in Gopalganj Sadar Upazila, Bangladesh
Authors: Fatema Kaniz
Published: October 2024

Each family has a mother, who serves as the cornerstone of the home. She must take on various roles, both at home and in the wider society. Mothers worldwide, whether employed or not, dedicate themselves wholeheartedly to their children. A mother’s unconditional love for her child is so profound that she would willingly sacrifice her own life. It is regrettable that working women often have to manage several obligations both at home and in the workplace. The main objective of this inquiry is to analyze the correlation between a mother’s profession and her children’s academic achievement. This research used a combination of qualitative and quantitative methods. Quantitative data was obtained via an interview schedule, while qualitative data was acquired through an in-depth interview. A total of 150 participants were selected for quantitative research, while the qualitative data included a small number of sample (10 respondents). The study investigated the correlation between a mother’s profession and her children’s academic performance, using role theory and Urie Bronfenbrenner’s ecological system theory. This research categorizes mothers’ jobs in the study region into eight distinct categories. Given the central emphasis on the correlation between a mother’s profession and her child’s academic achievement, the distribution of the mother’s time was also taken into account. The study finds that, there are statistically significant correlation between a mother’s profession and her child’s academic achievement. Parenting approaches indirectly impact children’s academic achievement by influencing their self-perception and drive.
The Use of Artificial Intelligence (AI) Translation Tools: Implications for Third Language Proficiency
Authors: Rapa Adhanawati Abdul , Ijlal Saja Ijlal Saja , Afifah Azmi Afifah Azmi
Published: October 2024

This study examines the impact of using artificial intelligence (AI)-based automatic translation tools, such as Chat GPT and DeepL, on third language proficiency among students at public universities (IPTA) in Malaysia. The primary issue discussed is the reliance of students on AI tools, which may potentially hinder language proficiency in areas such as grammar, writing, and speaking skills. The objective of this study is to evaluate the effect of AI usage on grammar and writing proficiency, analyze the relationship between students’ dependency on AI and their speaking skills, and identify the factors that drive students to use AI in learning a third language. This study employs a quantitative approach, with a questionnaire as the primary instrument, distributed to 306 students from three IPTAs in Malaysia. Correlation and regression analyses were used to examine the relationship between AI usage and language proficiency. The findings indicate a significant negative correlation between AI usage and proficiency in grammar and writing, with a correlation coefficient of r = -0.52. Additionally, reliance on AI negatively affects speaking skills, with a beta value of -0.45. Factors such as accessibility to AI, the accuracy of AI, and familiarity with technology were identified as the main contributors to AI usage. In conclusion, while AI facilitates language learning, excessive dependence on it may impair third language proficiency. Therefore, the use of AI must be balanced with innovative learning methods to ensure more comprehensive language mastery.
Assessing John Stuart Mill’s Principle of Utility: Barrier or Bridge to Equality?
Authors: Raja Komathi Muthu , Alias Mohd Syahmir
Published: October 2024

Amidst the historical and ongoing struggle for equality, this article explores the intricate relationship between the principle of utility and equality, focusing on John Stuart Mill’s views. It critically evaluates whether Mill’s version of utilitarianism serves as a barrier or a bridge to achieving equality, particularly within the context of movements like the United Nations’ 2030 Agenda, which addresses social, political, and economic inequalities. The methodology involves a comprehensive critical analysis of Mill’s utilitarianism alongside other theoretical perspectives, including Jeremy Bentham’s utilitarianism and contemporary critiques. The analysis is structured around three key areas: social, political, and economic contexts. In the social domain, Mill’s utilitarianism supports substantive equality by advocating for universal rights and access to essential resources such as education. Politically, however, utilitarian principles are critiqued for potentially justifying inequalities and infringing upon individual rights. Economically, utilitarianism’s emphasis on maximizing overall happiness suggests that resource allocation should consider marginal utility to promote equitable outcomes. The findings indicate that while Mill’s utilitarianism has the potential to foster equality in specific areas, its application is complex and context dependent. The article concludes that although Mill’s nuanced approach to utilitarianism can promote equality, it also possesses inherent limitations, necessitating careful application to avoid exacerbating inequalities and to ensure that principles of justice and individual rights are upheld.
A RELAÇÃO ENTRE ALOPECIA AREATA E FATORES VIRAIS, PARASITAS E GATILHOS EMOCIONAIS
Authors: De Paula Oliveira Ana Carolina , De Lima Bueno de Paula Aline , Nikoluk Kaffer Elizete
Published: October 2024

A alopecia areata é uma condição autoimune que resulta na perda de cabelo em áreas específicas do couro cabeludo ou do corpo. Sua etiologia exata permanece desconhecida, mas fatores virais, parasitas e gatilhos emocionais têm sido objeto de estudo como possíveis contribuintes para o desenvolvimento da doença. Este estudo tem como objetivo explorar a relação entre alopecia areata e fatores virais, parasitas e gatilhos emocionais, investigando evidências científicas e destacando sua importância para compreender a patogênese da doença. Foi realizada uma revisão da literatura científica para identificar estudos epidemiológicos, observacionais e experimentais relacionados à alopecia areata e seus possíveis fatores desencadeantes. As bases de dados PubMed, Scopus e Google Scholar foram utilizadas para a busca, com termos de pesquisa relacionados à alopecia areata, vírus, parasitas, estresse emocional e gatilhos emocionais. Os estudos revisados forneceram evidências sugestivas de uma possível associação entre alopecia areata e infecções virais, como o vírus da herpes simplex, bem como infecções parasitárias, como a infestação por ácaros Demodex. Além disso, o impacto do estresse emocional, ansiedade e depressão na alopecia areata foi amplamente reconhecido, com o estresse crônico sendo considerado um fator desencadeante importante. A alopecia areata é uma condição multifatorial, influenciada por uma combinação complexa de fatores genéticos, imunológicos, ambientais e psicossociais. Embora a relação entre alopecia areata e fatores virais, parasitas e gatilhos emocionais ainda necessite de mais investigação, evidências sugerem que esses elementos desempenham um papel significativo no desenvolvimento e progressão da doença.
The intricate relationship between job satisfaction and stress among millennials in the banking sector concerning Chennai district
Authors: Samson S. , Balamurugan J. , Kumar Arya
Published: October 2024

This study undertakes a comprehensive investigation into the intricate relationship between job satisfaction and stress among Millennials in the banking sector, a critical demographic in today’s workforce. The research employs a mixed-methods approach, integrating quantitative surveys and qualitative interviews with Millennials in diverse banking roles. This comprehensive perspective captures a complex interplay between job satisfaction and stress, significantly shaped by work-life balance, career advancement opportunities, workplace culture, and technology adoption. Key elements enhancing job satisfaction include autonomy and meaningful work, whereas elevated stress levels are attributed to heavy workloads and job insecurity. The study proposes strategies to boost job satisfaction and alleviate stress, highlighting the importance of supportive work environments, opportunities for continuous skill development, and flexible working arrangements. By providing a nuanced understanding of Millennials’ specific challenges in the banking sector, this research offers valuable insights for organizational leaders aiming to enhance employee well-being and engagement. The practical recommendations derived from this study aim to foster a more supportive and productive work environment, ultimately contributing to the overall success of banking institutions.
A study on the sustainable strategies adopted by Corporates and its impact on profitability and market value
Authors: Pathak Smriti , Shrotri Sonali S. , Fazalbhoy Sabiha , Bagchi Sadhna
Published: October 2024

Background: On the ground that there is a need to become planet-positive, the UN in 1987, introduced the concept of sustainable development which was accepted and was included in the Sustainable Development Goal (SDG) by nearly 100 nations, India is one of them. Sustainable investing has since then been driving the Corporate Social Responsibility (CSR) activities of Indian corporates. Thus the research examines the Indian corporates through the relationship between CSR, Environmental, Social and Governance (ESG) and Economic development. Purpose: The purpose of this research is to study the relationship between CSR, ESG and Gross Domestic Product (GDP) of Indian Corporates using various statistical tools and methods. The purpose is also to find how investors should evaluate the investment in ESG by developing a model. Method: This research is both quantitative and qualitative in nature and based on secondary data. Purposive sampling has been used to collect the CSR information, ESG scores and GDP prices (In billion USD) from 2015 to 2023. This study has tried to answer five research questions. First three research questions have been answered with the help of literature review and to answer the last two questions 2 hypotheses have been framed. Data has been collected for top 15 ESG fund corporations. Regression and Correlation analysis is done using SPSS 16 to check the relationship between ESG with Market value and ESG with profitability. Conclusion: The results indicated that there is a linear relationship between CSR, ESG and GDP and there is positive correlation between the three. The sustainable development goal can be achieved if the investors keep increasing and investing in ESG funds and there is ROI for both the stakeholders. The findings also show that ESG effect is positive on market value of ESG fund corporations. This paper suggests that high ESG performance is rewarded with higher market valuation and high GDP as well.
Exploring Hydrogen Storage Options
Authors: Muhamad Hisham Sakinah , Sazali Norazlianie , Kamarulzaman Mohd Kamal bin
Published: October 2024

Hydrogen is a major facilitator of the clean energy transition as the globe shifts to renewable energy utilization. Being an environmentally benign fuel, hydrogen exhibits great potential due to its clean burning into water and high gravimetric energy density. However, achieving the goal of a hydrogen economy is still hampered by ineffective storage technology. The most recent research on hydrogen storage, including gaseous, liquid, and solid-state material storage modalities, is examined in this study. Cryogenic liquefaction provides density even though it wastes energy whereas underground storage provides seasonal capacity but battles leakage. Reversible solid-state materials with favorable kinetics and shielding, such as metal hydrides, are particularly attractive, notwithstanding their capacity limitations. Substantial scientific discoveries are interspersed throughout the performed assessment, ranging from materials that absorb hydrogen 900 times their volume to the excavation of salt caverns in Romania. The present paper also explains how storage requirements for fixed and mobile applications differ significantly. Whether a person is a scientist, an engineer, or a policy maker, this review aims to pique the interest of anybody who wishes to comprehend the limitless potential of hydrogen by providing a thorough yet easily readable overview of the state-of-the-art storage technology, along with opportunities and obstacles.
An Optimal Controller for an Active Damping System based on Hedge Algebra and PSO Algorithm
Authors: Hoang Viet Nguyen , Nguyen Tien Duy , Deng Feiqi
Published: October 2024

The theory of Hedge Algebra (HA) has attracted the attention of numerous scientists, who have conducted extensive research into it. The capacity to calculate the semantic value of linguistic terms in HA enables the resolution of fuzzy inference issues and the development of fuzzy controllers based on HA (Hedge Algebra Controller – HAC). This paper presents a newly proposed methodology for the design of HAC to control an active damping system. The objective of the controller optimization is to adjust the fuzziness parameters of the hedge algebra structure. The optimization technique adopted in this study is the Particle Swarm Optimization algorithm (PSO), which is a popular and effective algorithm for optimizing multi-parameter systems. The optimal HAC was used to control the active damping system. Simulation results demonstrate that the HAC functions effectively in the presence of varying road disturbances.
Detection of Depression in Social Media Posts using Emotional Intensity Analysis
Authors: Myee M. Kiran , Rebekah R. Deepthi Crestose , Deepa T. , Zion G. Divya , Lokesh K.
Published: October 2024

Tapping into digital footprints on social media, this research focuses on providing new insights into detecting depression through textual analysis. Initially, emotional raw data found in social media posts, aimed particularly at the expressions of anger, fear, joy, and sadness, were collected and analyzed. These emotions, each scored by their intensity, offer a quantifiable view into the users' mental state, serving as possible depression markers. Central to the methodological framework adopted is the binary classification system, which classifies texts into depressive or non-depressive states, well founded by the patterns unearthed from the data. The proposed model rigorously trains Artificial Intelligence/Machine Learing (AI/ML) models to traverse through the complexities of natural language, concentrating on noticing delicate indications that signal depression. The introduced models are tested and measured with accuracy, precision, recall, and F1-score. RoBERTa, DistilBERT, and Electra are the transformer-based models emphasized in this research. Their performance is critically evaluated, with the results denoting particular capabilities in understanding and contextualizing language, which is the key advantage in the early identification of mental health issues. This research stands at the intersection of technology and mental health, revolutionizing mental health monitoring and intervention.
Radar Quantitative Precipitation Estimation (QPE) Calibration Methods: A Systematic Literature Review
Authors: Osman Noor Shazwani , Tahir Wardah
Published: October 2024

High-quality Quantitative Precipitation Estimation (QPE) beyond a sizable area with high spatial and temporal precision is important for many hydrological and meteorological applications. The development of the weather radar over the past 60 years has made it possible for QPE to effectively identify the rainfall location and has enabled the former’s use in actual hydrometeorological processes such as flood forecasting. These capabilities are made possible by the radar QPE's exceptionally high temporal and spatial resolutions. Through the enhancement of radar QPE for rainfall estimation, this research contributes to the field by offering critical analysis and assessment of the focus studies. The current study takes into account publications from reputable internet search libraries published between 2010 and 2023. The former will help academics analyze the most recent work on radar QPE, adopting the most advanced and improved techniques, and provide a baseline for future comparisons and directions.
Analysis of Rainfall Distribution in Malaysia through the Employment of Hydro-Estimator Data
Authors: Aminudin Nur Auni Izzati , Mohd Yunus Noor Hidayah , Basarudin Hafiz , Ramli Aizat Faiz , Mohd Nadzir Mohd Shahrul , Sampe Jahariah , Hasan Nurhayati
Published: October 2024

Rain rate influenced by atmospheric factors is related to rainfall patterns affected by climate change. Attenuation and signal losses due to rain are crucial constraints in communication systems such as 5G, microwave radio links and communication satellite systems. These communication systems have deteriorated from signal fading and distortion when exposed to rain. Signal fading by hydrometeor particles in the atmosphere may occur during wireless signal transmissions at frequencies higher than 10 GHz. In this paper, Hydro-Estimator data for Peninsular Malaysia, Sabah and Sarawak from the years 2011 to 2022 are extracted to determine the rain rate distribution, which is a crucial parameter for simulating and analyzing rain fade. Climate change affects rainfall distribution when signal transmission with higher frequency carries more data, thus resulting in a higher chance of signal losses and degradation. Long-term forecasts of the signal performance in 5G systems and high-frequency radio links frequencies due to hydrometeor can be developed by analyzing the effects of climate change based on the rainfall rate and the rain fade distribution.
An Improved Pre-Exploitation Detection Model for Android Malware Attacks
Authors: Al Besher Hamad Saleh , Bin Rohani Mohd Fo’ad , Saleh Al-rimy Bander Ali
Published: October 2024

This paper presents an innovative approach to the early detection of Android malware, focusing on a dynamic pre-exploitation phase identification system. Traditional methods often rely on static thresholding to delineate the pre-exploitation phase of malware attacks, which can be insufficient due to the diverse behaviors exhibited by various malware families. This study introduces the Dynamic Pre-exploitation Boundary Definition and Feature Extraction (DPED-FE) system to address these limitations, which utilizes entropy for change detection, thus enabling more accurate and timely identification of potential threats before they reach the exploitation phase. A comprehensive analysis of the system's methodology is provided, including the use of vector space models with Kullback-Leibler divergence for dynamic boundary detection and advanced feature extraction techniques such as Weighted Term Frequency-Inverse Document Frequency (WF-IDF) to enhance its predictive capabilities. The experimental results demonstrate the superior performance of DPED-FE compared to traditional methods, highlighting its effectiveness in real-world scenarios.
Enhancing Emotion Detection in Textual Data: A Comparative Analysis of Machine Learning Models and Feature Extraction Techniques
Authors: Saif Wedad Q. A. , Alshammari Majid Khalaf , Mohammed Badiea Abdulkarem , Sallam Amer A.
Published: October 2024

The digital age has resulted in a massive increase in the amount of available textual data, including articles, comments, texts, and updates on social networks. The value of analyzing such a large volume of data extends to many other industries and applications, as it provides important insights into the perspectives of customers, strategic decision-making, and market demands. Detecting emotions in texts faces challenges due to linguistic patterns and cultural nuances. This study proposes a system capable of accurately identifying emotions expressed in text using a variety of machine learning models, including logistic regression, extra randomized tree, voting, SGD, and LinearSVC. It also employs different feature extraction techniques, such as TF-IDF, Bag-of-Words, and N-grams, comparing their performance in these models. An evaluation was carried out using two English emotion datasets, namely ISEAR and AIT-2018, using F1 score, accuracy, recall, and precision. The findings demonstrate the ability and effectiveness of the system to detect emotions conveyed within texts. The LinearSVC model with N-grams achieved the highest accuracy of 88.63% on the ISEAR dataset, while the extra randomized tree classifier with N-grams achieved 89.14% accuracy on the AIT-2018 dataset. Furthermore, the SGD model with TF-IDF achieved 88.18% and 84.54% accuracy on the ISEAR and the AIT-2018 datasets, respectively.
Challenges of BIM Technology and Lean Theory in the Construction Industry in Vietnam
Authors: Ngoc Nguyen Minh , Dung Nguyen Anh , Hung Tran Duy , Thang Tran Ngoc
Published: October 2024

Vietnam's construction industry is in the development stage. Construction problems and especially the issue of construction quality are considered and analyzed from numerous aspects. Currently, building information modeling (BIM) technology plays a major role in the development of the construction industry. Companies, governments, experts, and training providers aim for the widespread adoption of BIM. BIM development stages are being continually edited and oriented to suit each development point. Moreover, lean construction philosophies are gradually being applied to construction implementation based on BIM technology. This philosophy helps ensure construction quality and enhances BIM processes in construction projects. The current study has initially analyzed construction quality needs with the lean philosophy applied in BIM technology. The basic challenges are identified and management solutions are proposed for construction projects to meet customer needs.
Face Mask Detection using CNN: A Fusion of Cryptography and Blockchain
Authors: Hagui Imen , Msolli Amina , Helali Abdelhamid , Fredj Hassen
Published: October 2024

The global COVID-19 pandemic has led to an urgent need for government intervention to prevent its spread. Scientific evidence has confirmed the effectiveness of mask-wearing in reducing virus spread. However, enforcing mask mandates in public spaces presents notable monitoring hurdles, particularly as facial recognition technology is impeded by face coverings. With many organizations relying on facial recognition for employee authentication, security and authentication become critical, especially for IoT systems. This article uses a Convolutional Neural Network (CNN) model to accurately identify mask-wearing individuals and introduces a secure user authentication mechanism between the node and the access point. This authentication mechanism consists of three phases. (i) Identification Phase at the Access Point Level: A novel hybrid biometric pattern, merging password and image features, is employed to strengthen user authentication security through a fusion approach. (ii) Secure Communication: Utilizing blockchain technology and AES cryptography ensures the secure transmission of these patterns between the node and the access point. (iii) Matching Phase at the Node Level: A newly proposed method verifies authenticity by comparing the combined image and password features with database records during the development phase. The experimental results demonstrate its outstanding performance, achieving 99% accuracy, 99% recall, 100% precision, and 98.9% F1 score. These results suggest that the proposed approach holds promise as an effective and secure solution for identifying individuals wearing masks while ensuring reliable authentication in various environments.
A Robust Hybrid Machine and Deep Learning-based Model for Classification and Identification of Chest X-ray Images
Authors: Mohammed Rana Jassim , Ghrabat Mudhafar Jalil Jassim , Abduljabbar Zaid Ameen , Nyangaresi Vincent Omollo , Abduljaleel Iman Qays , Ali Ali Hasan , Honi Dhafer G. , Neamah Husam A.
Published: October 2024

Successful medical treatment for patients with COVID-19 requires rapid and accurate diagnosis. Fighting the COVID-19 pandemic requires an automated system to diagnose the virus on Chest X-Ray (CXR) images. CXR images are frequently used in healthcare as they offer the potential for rapid and accurate disease diagnosis. SARS-CoV-2 targets the respiratory system, resulting in pneumonia with additional symptoms, such as dry cough, fatigue, and fever, which could be misdiagnosed as pneumonia, TB, or lung cancer. There is difficulty in differentiating the features of COVID-19 from other diseases that have similarities in CXR images. Automated Computer-Aided Diagnosis (CAD) systems incorporate machine or deep learning methods to improve efficiency and accuracy. CNNs are among the most widely used methods, as they have shown encouraging accuracy in identifying COVID-19 in CXR images. This study presents a hybrid deep learning model to provide faster diagnosis of COVID-19 infection using CXR images. The Densenet201 model was used for feature extraction and a Multi-Layer Perceptron (MLP) was used for classification. The proposed method achieved 98.82% accuracy and similar sensitivity, specificity, precision, recall, and F1 score. These results are promising when compared to other DL models trained in similar datasets.
Enhancing Co-Benefits and reducing Flood Risks through Nature-based Solutions and Assessments: A Case Study in the Dead Sea Region of Jordan
Authors: Gokcekus Huseyin , Kassem Youssef , Alijl Nour
Published: October 2024

The integration of Nature-Based Solutions (NBS) with Sustainable Development Goals (SDGs) is a crucial step in the restoration of ecosystems and the mitigation of the effects of urbanization and climate-induced flooding. Moreover, National Statistical Policies (NSP) and SDGs have notably diminished flood and hydrogeological risk in developed countries. Nevertheless, developing countries like Jordan have encountered difficulties in implementing NSP and SDG. Accordingly, the objective of the present study was to evaluate the feasibility of implementing NBS in the Jordanian Dead Sea (DS) area for the first time. To this end, a novel approach was proposed, integrating the NBS and SDGs with the SA-GIS and Fuzzy Analytical Hierarchy Process (FAHP) approaches, with the objective of addressing the severe issue of urban floods in the DS area. Furthermore, a life-cycle cost-benefit analysis was employed to comprehensively assess costs and benefits over a specified time frame, utilizing key indicators such as Net Present Value (NPV) and the Benefit-Cost Ratio (BCR). The findings revealed that detention ponds, vegetated swales, rain gardens, and rainwater harvesting have BCR values exceeding one, suggesting that incorporating co-benefits into economic assessments significantly enhances the economic efficiency and viability of NBS. In conclusion, the proposed method can be applied globally and serves as a viable strategy for advancing sustainable urban growth and reducing the risk of disasters in developing countries like Jordan.
A Novel Methodological Approach to assessing Deformation and Force in Barrette Walls using FEM and ANOVA
Authors: Vo Luan Nhat , Dang Truong Xuan , Nguyen Phuong Tuan , Tran Hoa Van Vu , Nguyen Tuan Anh
Published: October 2024

This research advances the understanding of deep excavation impacts by integrating a refined Finite Element Method (FEM) analysis with empirical data, specifically examining the behavior of retaining structures in urban environments. Unlike prior studies that predominantly relied on theoretical models, this paper combines FEM with statistical methods, particularly ANOVA, to identify critical factors affecting the performance of barrette walls during excavation. The primary objective of this study is to analyze the deformation and force behaviors at various depths, thereby enhancing the predictive capabilities of existing models. The findings highlight significant variations in horizontal displacements (Uy) and vertical displacements (Uz) across different excavation stages, with notable mean differences ranging from 0.000529420 m to 0.000700240 m for Uy and -0.017563652 m for Uz. Axial forces (N1) also show significant increases with depth, reaching a mean difference of 516.137991 kN/m. These results underscore the importance of adaptive design strategies in deep excavation projects. However, the study is limited by the specific geological conditions and the scope of empirical data used for model validation. Practical recommendations include enhancing real-time monitoring systems and applying refined methodologies.
Integration of Scanning Technology for Tool Wear Analysis in the Electrical Discharge Machining Process
Authors: Sabbar Osama Sameer , Khleif Ali Abbar , Albaghdadi Baraa M. H. , Abdulhameed Nader
Published: October 2024

There is a direct correlation between surface roughness and electrode tool status in the Electrical Discharge Machining (EDM) process. The quality of the machined surface of workpieces is becoming even more critical in recent industries. In general, electrode wear evaluation plays a vital role in the EDM process, affecting the operation cost and the accuracy of the required dimensions and geometric shape. This study presents a new method to evaluate the copper electrode wear during machining AISI 1005 carbon steel in the EDM process using a 3D laser scanner that measures the lost volume of the electrode. The results of the proposed method were compared with those of the conventional method. Laser technology was used to accurately measure the dimensions and surface characteristics of the electrode by scanning the electrode surface and the electrode view topology before and after the machining process. The processed data was saved on a computer connected to the laser scan device, converted to STL files, and sent to a 3D system (Geomagic Control X software). This software utilizes accurate mathematical algorithms to determine the available volumetric differences in the electrode. The experiments used Design-Expert 13 software, selecting three machining parameters: Current (Ip), pulse on time (Ton), and pulse off time (Toff). The results showed that the Tool Wear Rate (TWR) obtained by the two methods showed a mean absolute deviation of 3.6%, with an insignificant error on the effect of the machining parameters on TWR (1.01% for Ip, 1.92% for Ton, and 2.29% for Toff).
A New Approach for Enhancing Friction Welding Joint Strength
Authors: Abbas Naseer Malik , Hassoni Safaa M. , Mohammed Ali Ghusoon Ridha
Published: October 2024

The current research provides a new approach for enhancing the mechanical characteristics of friction welding joints for AA 6061 T6. Friction welding depends on the contact surface area between the two parts that need to be welded to generate the frictional heat necessary for the welding process. The frictional area is increased by modifying the contact area from flat circles on both sides of the joint to three different design configurations: a truncated cone, a half sphere, and a cylinder along with their opposite cavity. Mechanical characteristics and microstructural behavior for the new joints are studied. It was elucidated that the conical design configuration is the only one that succeeded through specimen manufacturing, welding, and testing procedures. The results show an improvement in the tensile strength of the truncated cone by 12% compared to the basic flat circle configuration. Bending and Vickers Micro-Hardness (HV) also increased in the joint cross-section by 10% and 7%, respectively. The results are consistent with the microstructure tests where the cone design configuration exhibited a finer grain structure than that of the flat circle. This proves that the generated heat is greater in the new design configuration. Thus, it can be said that the current study provides a promising approach for the improvement of friction welding joint strength.
Classification of Coral Reef Species using Computer Vision and Deep Learning Techniques
Authors: Alshahrani Amal , Ali Hanouf , Saif Esra , Alsayed Maha , Alshareef Fatimah
Published: October 2024

Coral reefs are among the most diverse and productive ecosystems, teeming with life and providing many benefits to marine life and human communities. Coral reef classification is popular for many important reasons, such as assessing biodiversity, prioritizing conservation actions to protect vulnerable species and their habitats, and many other objectives related to scientific research and interdisciplinary studies on marine ecosystems. Classifying images of coral reefs is challenging due to their great diversity and subtle differences in morphology. Manually classifying them is a time-consuming process, especially when dealing with large datasets. This can limit the scalability and efficiency of scientific research and conservation efforts. This study proposes an automated classification approach using computer vision and deep learning techniques to address these challenges, employing models such as YOLOv5l, YOLOv8l, and VGG16 to classify images of coral reefs. The dataset, comprising 1,187 images of five coral species, was augmented for robustness. YOLOv8l demonstrated superior performance with an accuracy of 97.8%, significantly outperforming the other models in terms of speed and accuracy. These results demonstrate the potential of advanced deep-learning models to improve coral reef monitoring and conservation efforts. This approach aims to streamline classification processes, improving the efficiency and scalability of coral reef research and conservation initiatives worldwide.