Pub Date : 2024-07-30DOI: 10.30574/wjarr.2024.23.1.2160
Busola Sulaimon
Breast implants are often used in restorative and cosmetic surgeries. However, the materials used for implants today could be better regarding biocompatibility and mechanical strength. It is possible to make composite biomaterials out of nanomaterials with better mechanical qualities than common implant materials like silicone elastomers and saline-filled shells. Researchers have found that adding carbon nanotubes, graphene, and hydroxyapatite nanoparticles to the shells of metal and silicone implants makes them much stronger, more flexible, and less likely to break. Researchers are also looking into polymer nanocomposites made of polycaprolactone and polylactic acid to see if they can break down better and integrate better with tissues. Changing the surface of implants at the nanoscale level can make them more biocompatible by controlling how proteins stick to the material and how cells interact with it. Animal tests with nanocoatings of polyacrylate, chitosan, and hyaluronic acid showed that they lowered the formation of capsules and inflammation. Antimicrobial nanoparticles, such as silver, zinc oxide, and antibiotics, are attached to the surfaces of implants to protect against infections and release drugs locally. Nanocontrast agents are used in high-resolution MRI and ultrasound images of implant shell integrity to get new imaging and diagnosis tools. By tracking biomarkers, nanostructured sensors could be used to find seromas, ruptures, and device failures with little to no damage. Much work has been done to show that different nanotechnologies can help breast implants in a pre-clinical setting. However, problems with regulation and standardization still need to be fixed before the implants can be used in people and made in large quantities. The process needs to be improved even more to make a lot of nanocomposite and etched surfaces. To make sure patients are safe, it is also important to do long-term biocompatibility and nanotoxicology tests. Nanotechnology has a lot of promise to change the way breast implants are made so that they look better and improve people's quality of life. This review examines nanotechnology's emerging applications for enhancing breast implants' durability and performance.
{"title":"Nanotechnology applications in breast implant manufacturing for improved durability and functionality","authors":"Busola Sulaimon","doi":"10.30574/wjarr.2024.23.1.2160","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.2160","url":null,"abstract":"Breast implants are often used in restorative and cosmetic surgeries. However, the materials used for implants today could be better regarding biocompatibility and mechanical strength. It is possible to make composite biomaterials out of nanomaterials with better mechanical qualities than common implant materials like silicone elastomers and saline-filled shells. Researchers have found that adding carbon nanotubes, graphene, and hydroxyapatite nanoparticles to the shells of metal and silicone implants makes them much stronger, more flexible, and less likely to break. Researchers are also looking into polymer nanocomposites made of polycaprolactone and polylactic acid to see if they can break down better and integrate better with tissues. Changing the surface of implants at the nanoscale level can make them more biocompatible by controlling how proteins stick to the material and how cells interact with it. Animal tests with nanocoatings of polyacrylate, chitosan, and hyaluronic acid showed that they lowered the formation of capsules and inflammation. Antimicrobial nanoparticles, such as silver, zinc oxide, and antibiotics, are attached to the surfaces of implants to protect against infections and release drugs locally. Nanocontrast agents are used in high-resolution MRI and ultrasound images of implant shell integrity to get new imaging and diagnosis tools. By tracking biomarkers, nanostructured sensors could be used to find seromas, ruptures, and device failures with little to no damage. Much work has been done to show that different nanotechnologies can help breast implants in a pre-clinical setting. However, problems with regulation and standardization still need to be fixed before the implants can be used in people and made in large quantities. The process needs to be improved even more to make a lot of nanocomposite and etched surfaces. To make sure patients are safe, it is also important to do long-term biocompatibility and nanotoxicology tests. Nanotechnology has a lot of promise to change the way breast implants are made so that they look better and improve people's quality of life. This review examines nanotechnology's emerging applications for enhancing breast implants' durability and performance.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"3 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/wjarr.2024.23.1.2183
Md Nurul Raihen, Sultana Akter
Twitter, a platform for micro-blogging, has contained as a novel information architecture. Everyday People worldwide publish about 200 million status messages, known as tweets. Twitter users express their opinions by posting concise text messages. Twitter data is useful for sentiment analysis and consumer feedback tweets. This study employed multi-class sentiment analysis to analyze tweets from 6 major US airlines (American, United, US Airways, Southwest, Delta and Virgin America). Airlines are essential for travel, and this study has helped people choose the best ones. Classification model with the lowest error rate could help airline companies improve their business by figuring out why information is being misclassified. This analysis of airline evaluations can help us identify good airlines and apply this model to our own journeys. This helps the airline identify its weaknesses so they can improve them. A technique of natural language processing (NLP) known as sentiment analysis (or opinion mining) classifies the tone of data as positive, negative, or neutral. The analysis was conducted with seven distinct classification strategies: Linear Discriminant Analysis, Quadratic Discriminant Analysis, Decision Tree, Random Forest, K-Nearest Neighbors, Gradient Boosting, and AdaBoost to utilize the split validation (80% as train data set, 20% as test data set) and 10 folds cross validation process. The suggested model demonstrates superior accuracy and efficiency compared to all others, achieving an accuracy score of 90.13% for the Random Forest with 10 folds cross validation approach. The project aims to utilize machine learning techniques to estimate the reasons for misclassified information since the lowest error rate means the airline sentiment provides less wrong prediction.
{"title":"Sentiment analysis of passenger feedback on U.S. airlines using machine learning classification methods","authors":"Md Nurul Raihen, Sultana Akter","doi":"10.30574/wjarr.2024.23.1.2183","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.2183","url":null,"abstract":"Twitter, a platform for micro-blogging, has contained as a novel information architecture. Everyday People worldwide publish about 200 million status messages, known as tweets. Twitter users express their opinions by posting concise text messages. Twitter data is useful for sentiment analysis and consumer feedback tweets. This study employed multi-class sentiment analysis to analyze tweets from 6 major US airlines (American, United, US Airways, Southwest, Delta and Virgin America). Airlines are essential for travel, and this study has helped people choose the best ones. Classification model with the lowest error rate could help airline companies improve their business by figuring out why information is being misclassified. This analysis of airline evaluations can help us identify good airlines and apply this model to our own journeys. This helps the airline identify its weaknesses so they can improve them. A technique of natural language processing (NLP) known as sentiment analysis (or opinion mining) classifies the tone of data as positive, negative, or neutral. The analysis was conducted with seven distinct classification strategies: Linear Discriminant Analysis, Quadratic Discriminant Analysis, Decision Tree, Random Forest, K-Nearest Neighbors, Gradient Boosting, and AdaBoost to utilize the split validation (80% as train data set, 20% as test data set) and 10 folds cross validation process. The suggested model demonstrates superior accuracy and efficiency compared to all others, achieving an accuracy score of 90.13% for the Random Forest with 10 folds cross validation approach. The project aims to utilize machine learning techniques to estimate the reasons for misclassified information since the lowest error rate means the airline sentiment provides less wrong prediction.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"10 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/wjarr.2024.23.1.1968
Muhammad Isnaini, M. Yamin, Desi Aryani
This research aims to determine the public's perception of The Zafarm Agrotourism. The sample of respondents in this study used an accidental sampling technique, which was calculated using the Slovin formula so that the number of respondents was 72 people. The analytical method used is qualitative descriptive analysis. Data was collected using questionnaires both directly and online via Google Drive links and barcodes. The results of this research show that the public's perception of The Zafarm Agrotourism in terms of the dimensions of attractions, accessibility and amenities is in agreement, where the public's perception of The Zafarm Agrotourism object in terms of the attractions dimension has a total score of 1.501, which is in the score range of 1.224–1.511 according to the criteria agree, the public's perception of The Zafarm Agrotourism object in terms of the accessibility dimension has a total score of 579, which is in the score range 489–603 with the criteria of agree, the public's perception of The Zafarm Agrotourism object, which is viewed from the amenity dimension, has a total score of 578, which is in the score range of 489 –603 with agree criteria. This means that The Zafarm Agrotourism object is well received by the community. The natural beauty, unique experiences in learning about agricultural cultivation with the cultural nuances of Palembang City, the availability of infrastructure, affordable road access, and other supporting facilities such as learning media for the visiting public are the attractions of The Zafarm Agrotourism.
{"title":"Analysis of public perceptions towards agrotourism (Case Study of The Zafarm Agrotourism in Palembang City)","authors":"Muhammad Isnaini, M. Yamin, Desi Aryani","doi":"10.30574/wjarr.2024.23.1.1968","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.1968","url":null,"abstract":"This research aims to determine the public's perception of The Zafarm Agrotourism. The sample of respondents in this study used an accidental sampling technique, which was calculated using the Slovin formula so that the number of respondents was 72 people. The analytical method used is qualitative descriptive analysis. Data was collected using questionnaires both directly and online via Google Drive links and barcodes. The results of this research show that the public's perception of The Zafarm Agrotourism in terms of the dimensions of attractions, accessibility and amenities is in agreement, where the public's perception of The Zafarm Agrotourism object in terms of the attractions dimension has a total score of 1.501, which is in the score range of 1.224–1.511 according to the criteria agree, the public's perception of The Zafarm Agrotourism object in terms of the accessibility dimension has a total score of 579, which is in the score range 489–603 with the criteria of agree, the public's perception of The Zafarm Agrotourism object, which is viewed from the amenity dimension, has a total score of 578, which is in the score range of 489 –603 with agree criteria. This means that The Zafarm Agrotourism object is well received by the community. The natural beauty, unique experiences in learning about agricultural cultivation with the cultural nuances of Palembang City, the availability of infrastructure, affordable road access, and other supporting facilities such as learning media for the visiting public are the attractions of The Zafarm Agrotourism.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"2 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper explores the application of Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks for stock price prediction over a 10-day horizon. The study aims to compare the predictive performance of these two deep learning architectures within the context of financial forecasting. Utilizing historical stock data from the CAC40 dataset, which represents a capitalization-weighted measure of the 40 most significant stocks on the Euronext Paris, we train and evaluate RNN and LSTM models to forecast future stock prices. Our results demonstrate the superior performance of LSTM networks in capturing the intricate temporal dependencies inherent in stock price data. Compared to standard RNNs, LSTM models exhibit higher accuracy and provide more reliable forecasts over the 10-day prediction period. The specialized memory cells and gating mechanisms in LSTM networks enable them to effectively identify both short-term changes and long-term patterns in stock prices, thus outperforming traditional RNN architectures. This enhanced ability to model the complex dynamics of stock market data underscores the potential of LSTM networks to improve investment decision-making, risk management, and the overall efficiency of financial markets. The insights gained from this study contribute to the growing body of knowledge on the application of deep learning in finance and investment, offering valuable guidance for practitioners and researchers seeking to harness the power of advanced algorithms for stock market prediction and optimization.
{"title":"Enhancing stock market prediction accuracy with recurrent deep learning models: A case study on the CAC40 index","authors":"Arash Tashakkori, Niloufar Erfanibehrouz, Shahin Mirshekari, Abolfazl Sodagartojgi, Vatsal Gupta","doi":"10.30574/wjarr.2024.23.1.2156","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.2156","url":null,"abstract":"This paper explores the application of Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks for stock price prediction over a 10-day horizon. The study aims to compare the predictive performance of these two deep learning architectures within the context of financial forecasting. Utilizing historical stock data from the CAC40 dataset, which represents a capitalization-weighted measure of the 40 most significant stocks on the Euronext Paris, we train and evaluate RNN and LSTM models to forecast future stock prices. Our results demonstrate the superior performance of LSTM networks in capturing the intricate temporal dependencies inherent in stock price data. Compared to standard RNNs, LSTM models exhibit higher accuracy and provide more reliable forecasts over the 10-day prediction period. The specialized memory cells and gating mechanisms in LSTM networks enable them to effectively identify both short-term changes and long-term patterns in stock prices, thus outperforming traditional RNN architectures. This enhanced ability to model the complex dynamics of stock market data underscores the potential of LSTM networks to improve investment decision-making, risk management, and the overall efficiency of financial markets. The insights gained from this study contribute to the growing body of knowledge on the application of deep learning in finance and investment, offering valuable guidance for practitioners and researchers seeking to harness the power of advanced algorithms for stock market prediction and optimization.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"11 26","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Some disorders can cause concomitant kidney dysfunction with lung involvement. The diagnosis of diffuse alveolar hemorrhage (DAH) is considered in patients who develop progressive dyspnea with alveolar opacities on chest imaging and acute renal failure with proteinuria and hematuria occurs due to rapidly progressive glomerulonephritis (RPGN). These syndromes are caused by variable disorders the most frequent are ANCA associated vascularitis or goodpasture syndrome. DAH diagnosed by the presence of blood on bronchoscopic alveolar lavage, and RPGN by the presence of specific glomerular lesions on the renal biospy. Treatment should target the underlying disorder. Here, we describe in detail the clinical manifestations, diagnostic approach, and treatment of DHA in a 39-year-old male who presented an alveolar hemorrhage, with acute renal failure. Treatment involved the use of high-dose corticosteroids to suppress the autoimmune response. Finally, we discuss the striking response to corticosteroid treatment and emphasize the importance of early initiation of treatment.
有些疾病可在肺部受累的同时引起肾功能障碍。如果患者出现进行性呼吸困难，胸部影像学检查显示肺泡不通透，并且由于快速进展性肾小球肾炎（RPGN）而出现伴有蛋白尿和血尿的急性肾功能衰竭，则应考虑诊断为弥漫性肺泡出血（DAH）。这些综合征由不同的疾病引起，最常见的是 ANCA 相关血管炎或 Goodpasture 综合征。DAH 的诊断依据是支气管镜肺泡灌洗液中出现血迹，而 RPGN 的诊断依据是肾脏活组织检查中出现特定的肾小球病变。治疗应针对潜在的疾病。在此，我们详细描述了一名出现肺泡出血并伴有急性肾功能衰竭的 39 岁男性 DHA 患者的临床表现、诊断方法和治疗。治疗包括使用大剂量皮质类固醇来抑制自身免疫反应。最后，我们讨论了患者对皮质类固醇治疗的显著反应，并强调了尽早开始治疗的重要性。
{"title":"A rare clinical course of seronegative of diffuse alveolar hemorrhage coexisting with extra-capillary glomerular","authors":"Hajar Benaziz, Maryem Hindi, Hasna Yasine, Mohamed Ijim, Oussama Fikri, Lamyae Amro","doi":"10.30574/wjarr.2024.23.1.1755","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.1755","url":null,"abstract":"Some disorders can cause concomitant kidney dysfunction with lung involvement. The diagnosis of diffuse alveolar hemorrhage (DAH) is considered in patients who develop progressive dyspnea with alveolar opacities on chest imaging and acute renal failure with proteinuria and hematuria occurs due to rapidly progressive glomerulonephritis (RPGN). These syndromes are caused by variable disorders the most frequent are ANCA associated vascularitis or goodpasture syndrome. DAH diagnosed by the presence of blood on bronchoscopic alveolar lavage, and RPGN by the presence of specific glomerular lesions on the renal biospy. Treatment should target the underlying disorder. Here, we describe in detail the clinical manifestations, diagnostic approach, and treatment of DHA in a 39-year-old male who presented an alveolar hemorrhage, with acute renal failure. Treatment involved the use of high-dose corticosteroids to suppress the autoimmune response. Finally, we discuss the striking response to corticosteroid treatment and emphasize the importance of early initiation of treatment.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"9 33","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/wjarr.2024.23.1.2177
Charles Guandaru Kamau, Christine Kanana Murori
Creative accounting has become a widespread practice in financial reporting. It involves manipulating financial data to paint a more positive picture of a company's financial performance or position. This paper aims to provide a comprehensive exploration of creative accounting. It will delve into its underlying factors, characteristics, different forms, and associated Implications. By reviewing existing literature, we will examine the complex relationship between creative accounting and factors such as ethics, quality of disclosure, internal control, and ownership structure. The discussion will shed light on the double-edged nature of creative accounting, acknowledging its potential for innovation in accounting practices while also recognizing its negative consequences for stakeholders when used unethically. Various forms of creative accounting, including earnings management, income smoothing, and big bath accounting, will be examined in detail, with a focus on their impact on financial reporting transparency and stakeholder perceptions. Additionally, this paper will discuss the precautions associated with creative accounting, emphasizing the need for careful consideration in financial decision-making and the importance of
{"title":"Characteristics of creative accounting: A Multifaceted Literature Analysis","authors":"Charles Guandaru Kamau, Christine Kanana Murori","doi":"10.30574/wjarr.2024.23.1.2177","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.2177","url":null,"abstract":"Creative accounting has become a widespread practice in financial reporting. It involves manipulating financial data to paint a more positive picture of a company's financial performance or position. This paper aims to provide a comprehensive exploration of creative accounting. It will delve into its underlying factors, characteristics, different forms, and associated Implications. By reviewing existing literature, we will examine the complex relationship between creative accounting and factors such as ethics, quality of disclosure, internal control, and ownership structure. The discussion will shed light on the double-edged nature of creative accounting, acknowledging its potential for innovation in accounting practices while also recognizing its negative consequences for stakeholders when used unethically. Various forms of creative accounting, including earnings management, income smoothing, and big bath accounting, will be examined in detail, with a focus on their impact on financial reporting transparency and stakeholder perceptions. Additionally, this paper will discuss the precautions associated with creative accounting, emphasizing the need for careful consideration in financial decision-making and the importance of","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: In our hospitals, nursing-related accidents are frequent. It is not uncommon for minor incidents and near misses to occur before a serious accident occurs. The main aims of this study are to explore the experience of healthcare professionals of nursing-related accidents; to determine what to do about nursing-related accidents; and to analyze the attitudes of healthcare professionals to nursing-related accidents. Methods: We conducted a qualitative, phenomenological study based on free, face-to-face interviews. It involved 3 care providers working at the Makiso General Referral Hospital from March 2 to 31, 2024. Results: In terms of experience, respondents identified risk factors, managing emotions during the accident and the consequences of a nursing-related accident. In terms of what to do in the event of a care-related accident, the subjects identified teamwork to prevent care-related accidents, taking precautions before administering care and ensuring patient safety. Finally, with regard to the attitude of nursing staff to accidents attributable to care, respondents expressed their views on reassuring patients that their health would be restored in the event of an accident attributable to nursing care, identifying problems linked to the accident and ways of preventing accidents attributable to care. Conclusion: To prevent nursing-related accidents, it is necessary to put into practice preventive measures that should be taken to reduce the frequency and severity of accidents attributable to nursing care. Nurses should regularly undergo medical training to prevent nursing-related accidents
{"title":"Experience of healthcare professionals at the Makiso General Reference Hospital on nursing-related accidents","authors":"Joseph Kasereka Kyakwa, Nicole Kahindo Vagheni, Marie Otshudi Ndjeka, Gaspard Lisongomi Lotiyo, Marthe Bumba Basiatiwe, Jean-Marc Aninge Memeyo, Gustave Shungu Bernard, Bienvenu Lomande Atambanaka","doi":"10.30574/wjarr.2024.23.1.1426","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.1426","url":null,"abstract":"Introduction: In our hospitals, nursing-related accidents are frequent. It is not uncommon for minor incidents and near misses to occur before a serious accident occurs. The main aims of this study are to explore the experience of healthcare professionals of nursing-related accidents; to determine what to do about nursing-related accidents; and to analyze the attitudes of healthcare professionals to nursing-related accidents. Methods: We conducted a qualitative, phenomenological study based on free, face-to-face interviews. It involved 3 care providers working at the Makiso General Referral Hospital from March 2 to 31, 2024. Results: In terms of experience, respondents identified risk factors, managing emotions during the accident and the consequences of a nursing-related accident. In terms of what to do in the event of a care-related accident, the subjects identified teamwork to prevent care-related accidents, taking precautions before administering care and ensuring patient safety. Finally, with regard to the attitude of nursing staff to accidents attributable to care, respondents expressed their views on reassuring patients that their health would be restored in the event of an accident attributable to nursing care, identifying problems linked to the accident and ways of preventing accidents attributable to care. Conclusion: To prevent nursing-related accidents, it is necessary to put into practice preventive measures that should be taken to reduce the frequency and severity of accidents attributable to nursing care. Nurses should regularly undergo medical training to prevent nursing-related accidents","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"3 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/wjarr.2024.23.1.2170
Bukola Jane David, David Opeyemi Adebayo, Monday Florence Anabel, Zariat Yetunde Ayoade, Obianwa Faith Ogechi, Dike Ndidi Pauline, Olanase Sarah Oluwadamilola, Akabuogu Elochukwu Lynda
This research focuses on gender stereotypes in selected African literary text. The way in which some African writers view gender inequalities and stereotypes in their characters is explored. We will also be able to see who is involved and affected by these gender inequalities and how. What determines beliefs about the ability and appropriate role of women? An overwhelming majority of men and women born early in the 20th century thought women should not work; a majority now believes that work is appropriate for both genders. Betty Friedan (1963) postulated that beliefs about gender were formed by consumer goods producers, but a simple model suggests that such firms would only have the incentive to supply error, when mass persuasion is cheap, when their products complement women’s time in the household, and when individual producers have significant market power (1). Such conditions seem unlikely to be universal, or even common, but gender stereotypes have a long history. To explain that history, we turn to a second model where parents perpetuate beliefs out of a desire to encourage the production of grandchildren. Undersupply of female education will encourage daughters’ fertility, directly by reducing the opportunity cost of their time and indirectly by leading daughters to believe that they are less capable. Children will be particularly susceptible to persuasion if they overestimate their parents’ altruism toward themselves. The supply of persuasion will diminish if women work before childbearing, which may explain why gender-related beliefs changed radically among generations born in the 1940s.
{"title":"Gender stereotypes in Lola Shoneyin’s the secret lives of baba Segi’s wives","authors":"Bukola Jane David, David Opeyemi Adebayo, Monday Florence Anabel, Zariat Yetunde Ayoade, Obianwa Faith Ogechi, Dike Ndidi Pauline, Olanase Sarah Oluwadamilola, Akabuogu Elochukwu Lynda","doi":"10.30574/wjarr.2024.23.1.2170","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.2170","url":null,"abstract":"This research focuses on gender stereotypes in selected African literary text. The way in which some African writers view gender inequalities and stereotypes in their characters is explored. We will also be able to see who is involved and affected by these gender inequalities and how. What determines beliefs about the ability and appropriate role of women? An overwhelming majority of men and women born early in the 20th century thought women should not work; a majority now believes that work is appropriate for both genders. Betty Friedan (1963) postulated that beliefs about gender were formed by consumer goods producers, but a simple model suggests that such firms would only have the incentive to supply error, when mass persuasion is cheap, when their products complement women’s time in the household, and when individual producers have significant market power (1). Such conditions seem unlikely to be universal, or even common, but gender stereotypes have a long history. To explain that history, we turn to a second model where parents perpetuate beliefs out of a desire to encourage the production of grandchildren. Undersupply of female education will encourage daughters’ fertility, directly by reducing the opportunity cost of their time and indirectly by leading daughters to believe that they are less capable. Children will be particularly susceptible to persuasion if they overestimate their parents’ altruism toward themselves. The supply of persuasion will diminish if women work before childbearing, which may explain why gender-related beliefs changed radically among generations born in the 1940s.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Financial compliance is a critical aspect of business management, particularly for Small and Medium-Sized Enterprises (SMEs). These enterprises play a vital role in economic development, yet they face unique challenges in adhering to financial regulations. This review explores the importance of financial compliance for SMEs, the common obstacles they encounter, and effective strategies to overcome these hurdles. SMEs often struggle with the complexity of regulatory requirements, limited resources, and the high cost of compliance. Additionally, the lack of standardized regulations across regions and industries, coupled with rapid technological advancements and cyber threats, further complicates compliance efforts. The significance of financial compliance for SMEs cannot be overstated, as it ensures legal conformity, builds stakeholder trust, promotes sound financial management, and facilitates international expansion. By maintaining compliance, SMEs can avoid legal penalties, attract investment, and achieve sustainable growth. However, the path to compliance is fraught with challenges that require innovative and practical solutions. This review outlines several strategies to help SMEs navigate financial compliance effectively. These include leveraging technology to automate compliance processes, investing in staff training to enhance regulatory knowledge, and seeking external expertise when necessary. Additionally, adopting a proactive approach to financial management, such as implementing robust internal controls and regular audits, can significantly enhance compliance efforts. The discussion emphasizes the need for a supportive regulatory environment that considers the unique constraints of SMEs and provides tailored guidance to aid their compliance journey. By addressing these aspects, this review aims to empower SMEs to overcome compliance challenges and implement effective solutions, ultimately contributing to their growth and the broader economic landscape.
{"title":"Navigating Financial Compliance in Small and Medium-Sized Enterprises (SMEs): Overcoming challenges and implementing effective solutions","authors":"Halima Oluwabunmi Bello, Toluwalase Vanessa Iyelolu","doi":"10.30574/wjarr.2024.23.1.1984","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.1984","url":null,"abstract":"Financial compliance is a critical aspect of business management, particularly for Small and Medium-Sized Enterprises (SMEs). These enterprises play a vital role in economic development, yet they face unique challenges in adhering to financial regulations. This review explores the importance of financial compliance for SMEs, the common obstacles they encounter, and effective strategies to overcome these hurdles. SMEs often struggle with the complexity of regulatory requirements, limited resources, and the high cost of compliance. Additionally, the lack of standardized regulations across regions and industries, coupled with rapid technological advancements and cyber threats, further complicates compliance efforts. The significance of financial compliance for SMEs cannot be overstated, as it ensures legal conformity, builds stakeholder trust, promotes sound financial management, and facilitates international expansion. By maintaining compliance, SMEs can avoid legal penalties, attract investment, and achieve sustainable growth. However, the path to compliance is fraught with challenges that require innovative and practical solutions. This review outlines several strategies to help SMEs navigate financial compliance effectively. These include leveraging technology to automate compliance processes, investing in staff training to enhance regulatory knowledge, and seeking external expertise when necessary. Additionally, adopting a proactive approach to financial management, such as implementing robust internal controls and regular audits, can significantly enhance compliance efforts. The discussion emphasizes the need for a supportive regulatory environment that considers the unique constraints of SMEs and provides tailored guidance to aid their compliance journey. By addressing these aspects, this review aims to empower SMEs to overcome compliance challenges and implement effective solutions, ultimately contributing to their growth and the broader economic landscape.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"9 51","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.30574/wjarr.2024.23.1.2005
Pradeep Kumar Panda, Rahul Sharma
Artificial intelligence (AI) signifies advanced computer systems adept at tasks traditionally within the purview of human intelligence. This paper explores the transformative landscape of AI applications in healthcare, with a specific focus on risk assessment, predictive modeling, and remote monitoring to proactively address high-risk pregnancies. Aligned with Sustainable Development Goal (SDG) 3.1, our investigation underscores AI's pivotal role in advancing maternal outcomes, encapsulating recent research across domains such as complication prediction, healthcare access enhancement, clinical decision support systems, and fertility treatments. AI-driven models demonstrate efficacy in predicting preterm birth, gestational diabetes, preeclampsia, and other adverse outcomes through meticulous analysis of maternal health data, enabling timely interventions. In underserved regions, AI acts as a catalyst, enhancing accessibility to vital services like prenatal ultrasounds and health education through telemedicine platforms. The integration of AI decision support systems empowers healthcare providers with real-time, patient-specific assessments and recommendations derived from population data analysis. Within fertility medicine, AI proves instrumental in refining genetic screening, embryo viability selection, and optimizing in vitro fertilization success rates. Despite these advancements, challenges persist in regulatory policy, privacy safeguards, accuracy, and seamless integration into clinical workflows, necessitating prudent consideration before widespread implementation. So, ethically applied AI emerges as a transformative force, offering substantial opportunities to advance maternal healthcare significantly. By averting complications, broadening access, informing sound decisions, and optimizing fertility outcomes, AI stands as a promising ally. This comprehensive review encapsulates pivotal applications of this burgeoning technology, outlining potential directions for future research, thereby contributing to the realization of SDG 3.1.
{"title":"Transforming maternal healthcare: Harnessing the power of artificial intelligence for improved outcomes and access","authors":"Pradeep Kumar Panda, Rahul Sharma","doi":"10.30574/wjarr.2024.23.1.2005","DOIUrl":"https://doi.org/10.30574/wjarr.2024.23.1.2005","url":null,"abstract":"Artificial intelligence (AI) signifies advanced computer systems adept at tasks traditionally within the purview of human intelligence. This paper explores the transformative landscape of AI applications in healthcare, with a specific focus on risk assessment, predictive modeling, and remote monitoring to proactively address high-risk pregnancies. Aligned with Sustainable Development Goal (SDG) 3.1, our investigation underscores AI's pivotal role in advancing maternal outcomes, encapsulating recent research across domains such as complication prediction, healthcare access enhancement, clinical decision support systems, and fertility treatments. AI-driven models demonstrate efficacy in predicting preterm birth, gestational diabetes, preeclampsia, and other adverse outcomes through meticulous analysis of maternal health data, enabling timely interventions. In underserved regions, AI acts as a catalyst, enhancing accessibility to vital services like prenatal ultrasounds and health education through telemedicine platforms. The integration of AI decision support systems empowers healthcare providers with real-time, patient-specific assessments and recommendations derived from population data analysis. Within fertility medicine, AI proves instrumental in refining genetic screening, embryo viability selection, and optimizing in vitro fertilization success rates. Despite these advancements, challenges persist in regulatory policy, privacy safeguards, accuracy, and seamless integration into clinical workflows, necessitating prudent consideration before widespread implementation. So, ethically applied AI emerges as a transformative force, offering substantial opportunities to advance maternal healthcare significantly. By averting complications, broadening access, informing sound decisions, and optimizing fertility outcomes, AI stands as a promising ally. This comprehensive review encapsulates pivotal applications of this burgeoning technology, outlining potential directions for future research, thereby contributing to the realization of SDG 3.1.","PeriodicalId":23739,"journal":{"name":"World Journal of Advanced Research and Reviews","volume":"6 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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