Cosmos Scholars Publishing House: Journals Management System
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Key Factors Impacting Business Performance an Investigation of Firms in Vietnam
Full text linkThis study examines factors affecting company performance on the Ho Chi Minh Stock Exchange from 2008 to 2020, analyzing internal and external variables, including the Covid-19 pandemic's impact. Using data from 40 firms and macroeconomic indicators, advanced econometric models identify key determinants of Return on Assets (ROA). Findings suggest financial leverage and operating leverage enhance ROA, while asset size and consumer inflation have mixed effects. Industrial production positively correlates with ROA, whereas the pandemic negatively impacts corporate performance. These insights inform strategic management and policy-making for economic resilience
Assessing Deep Learning Models in Breast Cancer Molecular Marker Prediction: A Systematic Review and Meta-Analysis
No full textThe advancements in artificial intelligence (AI) and its incorporation into clinical care have improved the prognosis, diagnosis and treatment to an extent. Whole slide imaging and multi-omics data analysis sum up into a promising new sub-specialty of computation pathology. Pathology of cancer need quick diagnosis to initiate intervention and AI has gained much importance in this field. This paper aimed to evaluate the diagnostic accuracy of different deep learning models for predicting molecular markers of breast cancer. This study was conducted by following the Preferred Reporting Items for Systematic Review and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines. We searched the research articles according to research aims from PubMed, EMBASE and Ovid MEDLINE. For assessment of risk bias, “Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2)” was used that collect application concerns in different areas. The RevMan version 5.4.0 was used for pooled analysis. Sensitivity and specificity were calculated with 95% confidence interval (CIs) for pooling the effect size. The included 9 studies have data of specificity and sensitivity for diagnostic method that help in the detection or interpretation of breast cancer risk or biomarkers through DP model (CNN). The deep learning model showed a generally good accuracy scores for detection of breast cancer through imaging. The area under the SROC curve was 0.940. In contrast to the general detection, DL seems to be more sensitive and specified in diagnosing key molecular biomarkers (PR, ER, HER2 and Ki67) among BC patients. Also, the paper provides links to functional code repositories and ends with the exploration of limitations and potential of deep learning-based diagnostic systems. 
A Study on Enhancing the Properties of Geopolymer Concrete Using Hybrid Fibers
Full text linkAlkali is present in significant quantities in geopolymer concretes. Due of this, their ductility and flexural strength are also low. The flexural strength of concrete is enhanced by the addition of fibers. Flexural strength has been a challenge for geopolymer concretes, thus researchers have tried using fibers to strengthen them. On the other hand, geopolymer concretes have never before utilized hybrid fibers. This study is an effort to incorporate hybrid fibers in geopolymer concrete to prevent its brittle fracture. Experiments are conducted to learn more about the geopolymer concrete's different mechanical characteristics, and then the settings are fine-tuned. Mechanical qualities of geopolymer concrete are improved by determining the optimal molarity of sodium hydroxide, the optimal ratio of sodium silicate to sodium hydroxide, and the optimal proportion of addition of fibers
Assessment Of Risk Factors for Polycystic Ovarian Syndrome Among Women of Reproductive Age in Lahore
No full textPolycystic ovarian syndrome (PCOs) is the most common hormonal disease of present era among the women of reproductive age. It has prevalence of 5-15% worldwide and in Pakistan its prevalence is approx. 52%. Which can be due to multiple risk factors and can cause multiple symptoms. However, no study in past showed exact cause of PCOs. The objective of the study was to access the risk factors for polycystic ovarian syndrome among women of reproductive age in Lahore. We conducted a Case-Control study. Cases were defined as women diagnosed with PCOS, while controls were age-matched women without a PCOS diagnosis. We emphasis more on dietary factors, socioeconomic status and BMI. Data on diet, health, and physical activity were collected from the questionnaire and analyzed using SPSS version 21. Odd ratio and Chi-square test was used to determine statistical significance with p-value < 0.05. The total of 68 cases and 68 controls were included in the study. We found that the most of the participants were young, mean age of the participants was 26.34 ± 6.63 years. There were significant differences between cases and controls in their income status (p=0.075), BMI (p=0.013), Family history (OR=2.826), conception difficulty (p=0.012), infertility treatment (p=0.011), irregular menstrual problems (OR=12.536), hirsutism (OR=10.086), U/S diagnosis (OR=33.970) and dietary factors including sweets/deserts (p=0.004) and dairy products (p=0.006). Our study concluded that socioeconomic status, BMI, reproductive health factors and diet are associated with PCOS in women in Lahore. Key factors such as family history, menstrual irregularities, hirsutism, and specific dietary habits were notably associated with higher risk. So, these results can be important for early detection and treatment of PCOS
Geochemical Behaviour of Heavy Metals in the Sondong Region of Bacgiang, Vietnam: A Comprehensive Case Study
No full textCharacterizing geochemistry is crucial for identifying pollutant sources and providing a scientific basis for environmental control and management. This study aimed to determine the geochemistry of stream water and sediment and metal sources for environmental management of the Luc Nam River basin in the Son Dong area, Bac Giang province, Vietnam. The results revealed geochemical background (GB) and minimum anomalies (MA) of Cu, Pb, Zn, Hg, and pH in water and Cd, Hg, and Cu in sediment. The highest anomalies in stream water were pH (4.2), Zn (63.7MA), Cu (5.7MA), Mo (3.7MA), Hg (3.4MA), Sb (2.0MA), Pb (1.2MA) and As (1.6MA). The highest anomalies in sediment were Pb (1.6MA), Cd (1.2MA), Cu (1.1MA), Ni (1.6MA), Hg (1.9MA) and Co (1.1MA). Based on the geochemistry of water and sediment, three zones were characterized: (1) Zone I: a natural source with recognized copper mines (Lang Lan, Giao Liem, An Lap, and Yen Dinh) and possible unrecognized mines; (2) Zone II: natural and anthropogenic sources from exploited mines (i.e. Khuon Muoi, Dong Bua, and Bien Dong) and deposits that have not been exploited (Phu Nhuan and Tan Thanh copper deposits, Lang Vai gold deposit); and (3) Zone III: natural source with possible unrecognized mines. These findings contribute to understanding the behavior of elements in response to governance changes in the environmental composition of water and sediments, which can affect ecosystems and communities beyond just the environmental standards and regulations of the government.  
Analysis of Road Infrastructure Problems in Urban City, Karachi
Full text linkRoad infrastructure is a significant part of the economic development of countries. Better performance of road communication system is significant part of all over the world. Developed countries make a significant effort for designing a well-managed traffic arrangement for the individuals. Furthermore, an efficient transport system is the key element for improving the country's economic conditions. Sustainable and efficient traffic management system is the backbone for humanizing the economic growth of developing countries. In case of Pakistan, Karachi is the main industrial hub for whole country's economy and accommodates enormous number of migrants. Due to this reason the population of city is increasing day by day. This paper presents the current situation of road infrastructure troubles in Karachi. The urban city is facing several numbers of issues that were already documented by researchers such as traffic congestion and road safety problems. On an urgent basis an efficient mass transit system is required to reduce the traffic jam conditions. The transport system of Karachi requires instant proper management rules and designed transport facilities. The aim of the paper is to identify the main traffic problems of the large urban city, Karachi, which is faced by the people in their daily life and to suggest recommendations for reducing the current situation related to traffic management strategies. The research methodology for this paper will be based on qualitative analysis of the road infrastructure troubles that are identified by the individuals through interviews and detailed group meetings
Effect Of the Disclosure of Corporate Social Responsibility Practices on The Financial Value of The Companies Listed on The Colombian Stock Exchange
Full text linkThis research project intends to analyze the financial effects caused by the implementation of Corporate Social Responsibility (CSR) in companies, and the shareholders’ perspective regarding the disclosure of these practices in the stock market. The Colombian Stock Exchange (BVC) market’s reaction was studied, using as a reference 20 companies included in the COLCAP index. The influence of this CSR-type announcements published in important local newspapers was analyzed. The results show that the social practices developed by the Colombian companies listed on the BVC have a positive relationship with financial performance; this fact is evidenced by the change in the share price
Analysis of Multi-modal Data Through Deep Learning Techniques to Diagnose CVDs: A Review
Full text linkIn cardiology, there has been a surge in artificial intelligence (AI), machine learning, and deep learning techniques. Artificial intelligence (AI) and electronic health records have the potential to advance our knowledge of disease states and enable personalized cardiac care in the era of modern medicine. With its latest data fusion techniques of non-imaging and imaging data (including cardiac magnetic resonance imaging, echocardiography, and cardiac computed tomography), the field of cardiac medicine is evolving, leading the revolution in precision cardiology. Although these data were previously used in isolation, new developments in deep learning (DL) and machine learning (ML) allow these data sources to be integrated to generate multimodal insights. There is growing interest in the application of data fusion, which uses ML and DL techniques to integrate data from multiple modalities into cardiac care. We review the most advanced research in this paper, emphasizing how the new methods of data fusion are delivering clinical and scientific insights uniquely to the field of cardiovascular medicine. Although multi-modal deep learning yields more reliable estimations than multi-modal machine learning and unimodal techniques, it suffers from limitations related to scalability and the time-consuming nature of concatenating information
Mapping the Regulatory Framework for Telemedicine in Zambia: A Content Analysis
Full text linkThis paper explores the regulatory framework for telemedicine in Zambia. Telemedicine, involving remote clinical services using technology, is a rapidly evolving field intersecting with legal, ethical, and professional domains. The primary aim is to understand Zambia's telemedicine regulatory framework through an analysis of key documents namely the Zambia E-Government Interoperability Standard (eGIF), Zambia Digital Health Strategy 2022-2026, HPCZ Guidelines for the Quality Assurance of Telemedicine Services, and Statutory Instrument 43 of 2023 (SI 43 of 2023). The study addresses the challenge of comprehensively understanding and effectively implementing telemedicine in Zambia, considering the evolving nature of technology and healthcare services. Mapping the regulatory framework is a critical exercise for ensuring legal compliance, maintaining high standards of service, protecting patients, and making informed strategic decisions in the telemedicine sector. The study conducts a detailed exploration and content analysis of the aforementioned documents. This includes examination of their contributions to establishing a strong telemedicine landscape in Zambia, focusing on aspects like interoperability, data security, and healthcare service delivery. Findings reveal each document's significant, yet varied, contributions to the telemedicine framework in Zambia. The eGIF ensures integrated, standardized, and secure digital telemedicine services. The Zambia Digital Health Strategy 2022-2026 promotes telemedicine via digital technology and global alignment, while the HPCZ Guidelines provide a detailed framework focusing on ethical and legal standards. SI. 43 of 2023 emphasizes data security, quality assurance, and collaboration in telemedicine. Comparatively, Zambia's framework, as shaped by the four documents, aligns with global standards but differs in its centralized regulation and strategic focus, lacking extensive coverage on medical device regulations and reimbursement issues seen in other countries. The study suggests the need for a unified approach to telemedicine, emphasizing standardization, legal compliance, accessibility, and inclusivity. Recommendations include improving interoperability, ensuring data security, and fostering user-centric telemedicine services for enhanced healthcare outcomes
Green Synthesis of Guilandina bonduc Seed Extract Mediated Silver Nanoparticles and Its Anti-Inflammatory Activity
Full text linkGreen synthesis is a promising approach for the synthesis of silver nanoparticles (AgNPs) that is environmentally friendly and sustainable. In this study, we report a green method for the synthesis of AgNPs using Guilandina bonduc seed extract. The seed extract was used as a reducing and capping agent for the synthesis of AgNPs. The prepared nanoparticles were evaluated for its anti-inflammatory activity using Bovine serum albumin denaturation assay and Egg albumin denaturation assay. The AgNPs also showed significant anti-inflammatory activity in vitro. The results show that the green synthesised silver nanoparticles have excellent anti-inflammatory activity. The results of this study suggest that the green synthesised AgNPs have potential application in the treatment of inflammation. These findings also highlight the potential of Guilandina bonduc seed extract as a source of natural compounds for the green synthesis of AgNPs with biological activity