growth of zno nanorods on fto glass substrate

n/

Early results after transatrial repair of RVOT obstruction including teratology of fallot

Background: Right ventricular (RV) dysfunction is a significant cause of morbidity and mortality after surgical correction of RVOT obstruction including tetralogy of Fallot (TOF). Transatrial repair avoids a ventriculotomy (in contrast to the transventricular approach) emphasizing maximal preservation of RV structure and function. We have adopted this technique as less traumatic for the right ventricle. This study evaluates the early surgical results of our approach.Methods: Between January 2005 to January 2014, 77 consecutive patients with RVOT obstruction were referred to our unit for surgical therapy. Of these, 14 were unsuitable for repair and underwent aortopulmonary shunting. In the remaining 63 patients (mean age of 2.67±0.38 years), complete transatrial/transpulmonary repair was performed. Previously placed shunts (four patients) were taken down. In all cases, subpulmonary resection and ventricular septal defect (VSD) closure were accomplished transatrially. In 51 patients, the main pulmonary artery was augmented with an autologous pericardial patch.Results: There were 7 (9%) deaths in this series. No patient required permanent pacemaker. Median ICU and hospital stay were 91 hours and 14 days, respectively. At median follow up of 54 (mean 51±12) months, all patients are asymptomatic, with no significant residual lesion.Conclusions: Transatrial/transpulmonary repair of TOF is associated with remarkably low morbidity and mortality in our early experience

Exploration of Dynamic Capabilities Needed for Digital Transformation and Business Model Innovation in the Swedish Automobile Industry.

Background: Digital transformation has become crucial for success in the global automobile industry. Emerging digital technologies are imposing new challenges and offering new opportunities to automotive firms and are fuelling the business model innovation in the global automotive sector. This research study explored the nature of business model innovation during the digital transformation process and the dynamic capabilities that automobile organizations need to build for successful transformation. Research Question: How could digital transformation-driven business model innovation be successful by building dynamic capabilities, and what key lessons could be learned from Volvo- a Swedish automobile manufacturing company? Conceptual Framework: Dynamic capabilities theory provides a theoretical basis to understand how digital transformation-led business model innovation encourages automotive firms to build their dynamic capabilities to ensure survival and dominance in the quickly changing market. Methodology: A qualitative empirical research study is conducted on chosen case organization- Volvo. The thematic analysis of 10 interviews conducted with the Volvo managers yielded some interesting insights. Conclusion: Volvo is proactive in adopting emerging digital technologies (like IoT, big data, artificial intelligence, augmented reality, etc.) to keep pace with changing world. Volvo actively builds its dynamic capabilities to invest in the emerging business model innovations fuelled by the digital transformation, which enables the firm to maintain its digital dominance. When automotive organizations build dynamic capabilities, it lays a strong foundation for business model innovations. Dynamic capability framework can be a useful guidance tool for building organizational capabilities in a digital transformation context

Exploration of Dynamic Capabilities Needed for Digital Transformation and Business Model Innovation in the Swedish Automobile Industry.

Background: Digital transformation has become crucial for success in the global automobile industry. Emerging digital technologies are imposing new challenges and offering new opportunities to automotive firms and are fuelling the business model innovation in the global automotive sector. This research study explored the nature of business model innovation during the digital transformation process and the dynamic capabilities that automobile organizations need to build for successful transformation. Research Question: How could digital transformation-driven business model innovation be successful by building dynamic capabilities, and what key lessons could be learned from Volvo- a Swedish automobile manufacturing company? Conceptual Framework: Dynamic capabilities theory provides a theoretical basis to understand how digital transformation-led business model innovation encourages automotive firms to build their dynamic capabilities to ensure survival and dominance in the quickly changing market. Methodology: A qualitative empirical research study is conducted on chosen case organization- Volvo. The thematic analysis of 10 interviews conducted with the Volvo managers yielded some interesting insights. Conclusion: Volvo is proactive in adopting emerging digital technologies (like IoT, big data, artificial intelligence, augmented reality, etc.) to keep pace with changing world. Volvo actively builds its dynamic capabilities to invest in the emerging business model innovations fuelled by the digital transformation, which enables the firm to maintain its digital dominance. When automotive organizations build dynamic capabilities, it lays a strong foundation for business model innovations. Dynamic capability framework can be a useful guidance tool for building organizational capabilities in a digital transformation context

النفس الإنسانية عند فخر الدين الرازي = Jiwa manusia apabila Fakhr al-Din al-Razi (The human soul based on the opinion of Fakhr al-Din al-Razi)

Human soul is the mystery of God's creation and His divine verse in the slaves, it is the source of knowledge and different information that is endless, it is also the source of self-evident ideas, but in the same time, it is ambiguous and vague, there are different views on the issue of soul, there are those who differentiate between the soul and the spirit, and from there the view that saw they one thing, even in previous religions and ancient philosophies and primitive beliefs, we find the belief that the self is the object which represents the part of the human rational, and despite the different naming for this wise object between these different doctrines and schools of thought, however the emphasis is on the body more than the soul, perhaps because the body is the concrete physical material, while the soul is the mysterious and invisible part of human, so the sense of its existence needs to exercise a major effort to identify and address it, therefore we can access and get knowledge of it and its illness, so that we may cure these diseases and direct it to the right path of guidance. This paper clarify the meaning of soul, which is commissioned for responsible activities, through which tends to the right and better ethics after the process of accounting, purifying and direction, to emphasize that there is moral philosophy in Islam, and not as the Westerners that it is a philosophy of Greek written in Arabic, to reach out to this result the analytical descriptive method and the comparative method, have been used, and arrived at the result that al-Razi came with several evidences to prove the existence of the human soul, al-Razi opposed the Greek ideas of the human soul transience, which is contrary to Islamic faith, the soul in the Islamic religion have the status of eternity which is not transient

Does digitisation determine financial development? Empirical evidence from Africa

AbstractAfrica is investing and recalibrating its digital infrastructure in the financial and other sectors to support economic growth and development. It is in light of this, the study seeks to examine from an empirical perspective whether digitisation has a significant role in financial development in African countries. Specifically, the study employed macroeconomic data on Africa from World Development Indicators (WDI) from the period of 2000-2021. The data covers all the 54 African countries. Bayesian Panel Vector Auto-Regressive (BPVAR) was adopted to estimate the parameters involved in the study objective. The results indicate that digitisation helps to increase financial inclusion, reduce transaction costs, and promote the development of new financial products and services, all promoting financial development and exploiting its allied opportunities. The findings also suggest that other factors such as infrastructure, financial inclusion, economic development, institutional quality, and government support are important for the development of the financial sector and should be addressed in conjunction with digital innovation. Policymakers in Africa should take note of these findings and work to create an enabling environment that supports financial sector development. Efforts to improve institutional quality, governance, and infrastructure can help to create a more conducive environment for financial development. Overall, the study suggests that digitisation has the potential to improve financial sector development in Africa, and can play a key role in mitigating financial risk, improving financial sector efficiency and harnessing the opportunities that abound in the financial sector

Prevalence, Management, and Impact of Dysmenorrhea on the Lives of Nurse and Midwife Trainees in Northern Ghana

Background. Dysmenorrhea is the most common gynecological problem affecting the majority of female students in the nursing profession today. They often experience severe pain that is not only incapacitating but also has a significant impact on their day-to-day college life, academic, and clinical performance. Aim. This study was conducted to assess the prevalence, management, and impact of dysmenorrhea on the lives of nurse and midwife trainees in northern Ghana. Methods. A descriptive cross-sectional design with a quantitative approach to data collection was employed to collect data from nurse and midwife trainees in three colleges of nursing and/or midwifery in the northern region of Ghana. A proportionate stratified random sampling technique was used to recruit 303 respondents for the study. After gaining permission from various institutions, data were collected by using a structured questionnaire from 13th September to 28th October, 2022. Stata (special edition) for Windows version 17.0 was used for the statistical analyses. Results. The study revealed a high prevalence of dysmenorrhea among female nursing students (66.7% and 95% CI: 0.611–0.720). More than half of the respondents (67.3%) experienced loss of appetite for food. The most common site of most intense pain was the pelvis and lower abdomen (98.0%). A greater proportion of students (65.8%) used antispastic drugs to reduce pain. The respondents’ concentration in the classroom was greatly affected (77.2%) as well as normal physical activities (58.4%). A multivariable logistic regression analysis revealed that the odds of dysmenorrhea are 2.67 times higher when the duration of menstruation is 4-5 days (AOR = 1.82, 95% CI = 1.13–6.28, and p = 0.024) than a duration of 1–3 days. Having urinary tract infections was associated with 3.56 times higher odds of dysmenorrhea (AOR = 3.56, 95% CI = 0.98–12.86, and p = 0.053). Again, the odds of dysmenorrhea were also four times higher among respondents with a family history of the same condition (AOR = 4.05, 95% CI = 2.16–7.61, and p = 0.001). Conclusion. The current study revealed a high prevalence of dysmenorrhea among nurse and midwife trainees in the northern part of Ghana. The majority of the respondent experienced loss of appetite and intense pain in the pelvis and lower abdomen, and their concentration during lectures was also significantly affected. The most predominant nonpharmacological method used for reducing the pain was sleep and the application of warm objects on the abdomen

Robust Benchmark for Propagandist Text Detection and Mining High-Quality Data

Social media, fake news, and different propaganda strategies have all contributed to an increase in misinformation online during the past ten years. As a result of the scarcity of high-quality data, the present datasets cannot be used to train a deep-learning model, making it impossible to establish an identification. We used a natural language processing approach to the issue in order to create a system that uses deep learning to automatically identify propaganda in news items. To assist the scholarly community in identifying propaganda in text news, this study suggested the propaganda texts (ProText) library. Truthfulness labels are assigned to ProText repositories after being manually and automatically verified with fact-checking methods. Additionally, this study proposed using a fine-tuned Robustly Optimized BERT Pre-training Approach (RoBERTa) and word embedding using multi-label multi-class text classification. Through experimentation and comparative research analysis, we address critical issues and collaborate to discover answers. We achieved an evaluation performance accuracy of 90%, 75%, 68%, and 65% on ProText, PTC, TSHP-17, and Qprop, respectively. The big-data method, particularly with deep-learning models, can assist us in filling out unsatisfactory big data in a novel text classification strategy. We urge collaboration to inspire researchers to acquire, exchange datasets, and develop a standard aimed at organizing, labeling, and fact-checking

Evaluating Knowledge, Practices, and Barriers of Paediatric Pain Management among Nurses in a Tertiary Health Facility in the Northern Region of Ghana: A Descriptive Cross-Sectional Study

Background. Pain is a major source of distress for children on admission, parents, and clinician. Hospitalized children continuously experience unrelieved pain; hence, the provision of effective pain management is an integral and important part of the nurse’s role. Adequate knowledge and positive practices of nurses regarding pain management among children are key if optimal pain management is to be achieved among paediatric cases. However, there is a paucity of published data on paediatric management among nurses in the northern part of Ghana. Aim. The current study, therefore, evaluated nurse’s knowledge and practices and identified the barriers to paediatric pain management in the Tamale Teaching Hospital, Ghana. Methodology. This was a descriptive cross-sectional facility-based study that employed a quantitative approach to data collection. A total of 180 nurses were selected conveniently from 10 selected wards of the hospital for the study. Data were collected using a questionnaire. The data were subsequently analyzed using the Statistical Package for Social Sciences version 23.0. Logistic regression analysis was done to determine the association between the dependent and independent variables of interest. Results. The findings revealed that the majority (61.1%) of all the nurses had an overall good knowledge of paediatric pain management while 57.8% demonstrated good practices of pain management. From the study, the most reported barriers to paediatric pain management by the nurses were insufficient knowledge in pain management (76.1%), inadequate paediatric pain assessment tools (73.9%), and inadequate staffing (72.2%). In further analysis, critical care nurses were 5.87 times more likely to engage in good practices of paediatric pain management than paediatric nurses (OR = 5.87 (95% CI : 1.07–32.00), p=0.041). Conclusion. The majority (61.1%) of all the respondents showed good knowledge of pain management and 57.8% demonstrated good pain management practices. Despite the high knowledge and practice, factors such as insufficient knowledge in pain management (76.1%), inadequate paediatric pain assessment tools (73.9%), and inadequate nurse staffing (72.2%) affect effective pain management. Paediatric pain management should be treated as a priority, and hence more efforts should be put in place to curtail the barriers that hinder its practice

Drug Adverse Event Detection Using Text-Based Convolutional Neural Networks (TextCNN) Technique

With the rapid advancement in healthcare, there has been exponential growth in the healthcare records stored in large databases to help researchers, clinicians, and medical practitioner’s for optimal patient care, research, and trials. Since these studies and records are lengthy and time consuming for clinicians and medical practitioners, there is a demand for new, fast, and intelligent medical information retrieval methods. The present study is a part of the project which aims to design an intelligent medical information retrieval and summarization system. The whole system comprises three main modules, namely adverse drug event classification (ADEC), medical named entity recognition (MNER), and multi-model text summarization (MMTS). In the current study, we are presenting the design of the ADEC module for classification tasks, where basic machine learning (ML) and deep learning (DL) techniques, such as logistic regression (LR), decision tree (DT), and text-based convolutional neural network (TextCNN) are employed. In order to perform the extraction of features from the text data, TF-IDF and Word2Vec models are employed. To achieve the best performance of the overall system for efficient information retrieval and summarization, an ensemble strategy is employed, where predictions of the selected base models are integrated to boost the robustness of one model. The performance results of all the models are recorded as promising. TextCNN, with an accuracy of 89%, performs better than the conventional machine learning approaches, i.e., LR and DT with accuracies of 85% and 77%, respectively. Furthermore, the proposed TextCNN outperforms the existing adverse drug event classification approaches, achieving precision, recall, and an F1 score of 87%, 91%, and 89%, respectively