Abstract Food preservation involves different food processing steps to maintain food quality at a desired level so that maximum benefits and nutrition values can be achieved. Food preservation ...methods include growing, harvesting, processing, packaging, and distribution of foods. The key objectives of food preservation are to overcome inappropriate planning in agriculture, to produce value-added products, and to provide variation in diet. Food spoilage could be caused by a wide range of chemical and biochemical reactions. To impede chemical and microbial deterioration of foods, conventional and primitive techniques of preserving foods like drying, chilling, freezing, and pasteurization have been fostered. In recent years, the techniques to combat these spoilages are becoming sophisticated and have gradually altered to a highly interdisciplinary science. Highly advanced technologies like irradiation, high-pressure technology, and hurdle technology are used to preserve food items. This review article presents and discusses the mechanisms, application conditions, and advantages and disadvantages of different food preservation techniques. This article also presents different food categories and elucidates different physical, chemical, and microbial factors responsible for food spoilage. Furthermore, the market economy of preserved and processed foods has been analyzed in this article.
Skin cancer is a prevalent form of malignancy globally, and its early and accurate diagnosis is critical for patient survival. Clinical evaluation of skin lesions is essential, but it faces ...challenges such as long waiting times and subjective interpretations. Deep learning techniques have been developed to tackle these challenges and assist dermatologists in making more accurate diagnoses. Prompt treatment of skin cancer is vital to prevent its progression and potentially life-threatening consequences. The use of deep learning algorithms can improve the speed and accuracy of diagnosis, leading to earlier detection and treatment. Additionally, it can reduce the workload for healthcare professionals, allowing them to concentrate on more complex cases. The goal of this study was to develop reliable deep learning (DL) prediction models for skin cancer classification; (i) deal with a typical severe class imbalance problem, which arises because the skin-affected patients' class is significantly smaller than the healthy class; and (ii) interpret the model output to better understand the decision-making mechanism (iii) Propose an End-to-End smart healthcare system through an android application. In a comparison examination with six well-known classifiers, the effectiveness of the proposed DL technique was explored in terms of metrics relating to both generalization capability and classification accuracy. A study used the HAM10000 dataset and an optimized CNN to identify the seven forms of skin cancer. The model was trained using two optimization functions (Adam and RMSprop) and three activation functions (Relu, Swish, and Tanh). Furthermore, an XAI-based skin lesion classification system was developed, incorporating Grad-CAM and Grad-CAM++ to explain the model's decisions. This system can help doctors make informed skin cancer diagnoses in their early stages, with an 82% classification accuracy and 0.47% loss accuracy.
Stroke is a dangerous medical disorder that occurs when blood flow to the brain is disrupted, resulting in neurological impairment. It is a big worldwide threat with serious health and economic ...implications. To solve this, researchers are developing automated stroke prediction algorithms, which would allow for early intervention and perhaps save lives. The number of people at risk for stroke is growing as the population ages, making precise and effective prediction systems increasingly critical. wo In a comparison examination with six well-known classifiers, the effectiveness of the proposed ML technique was explored in terms of metrics relating to both generalization capability and prediction accuracy. To give insight into the black-box machine learning models, we also studied two kinds of explainable techniques, namely SHAP and LIME, in this study. SHAP (Shapley Additive Explanations) and LIME (Local Interpretable Model-agnostic Explanations) are well-established and reliable approaches for explaining model decision-making, particularly in the medical industry. The findings of the experiment revealed that more complicated models outperformed simpler ones, with the top model obtaining almost 91% accuracy and the other models achieving 83-91% accuracy. The proposed framework, which includes global and local explainable methodologies, can aid in standardizing complicated models and gaining insight into their decision-making, which can enhance stroke care and treatment.
Epilepsy is a neurological disorder that affects millions of people worldwide, characterized by recurring seizures that can vary in frequency, duration, and intensity. Accurate classification of ...seizures is critical for effective diagnosis and treatment. Machine learning (ML) algorithms have shown great potential in recent years for analyzing EEG recordings and classifying epileptic seizures. This research project investigates the classification of epilepsy seizures using ML algorithms and explainable AI. A publicly available dataset of EEG recordings from 500 individuals is used, with each recording consisting of 4097 data points sampled over 23.6 seconds. The data is preprocessed by dividing it into 23 chunks of 178 data points each, and labels are assigned to each recording based on whether the individual had an epileptic seizure (class 1) or not (classes 2-5). Various classification algorithms are evaluated, including Logistic Regression, K-nearest neighbors, Support Vector Machine, Naive Bayes Classifier, Random Forest Classifier, and Gradient Boosting. Accuracy, precision, recall, f1-score, and specificity are measured for all algorithms using confusion metrics. The best accuracy of 96.1% is achieved using the Random Forest algorithm. Additionally, SHAP and LIME techniques are employed to explain the models and gain insights into their decision-making processes. The findings demonstrate the potential of ML algorithms to accurately classify epilepsy seizures and the value of explainable AI for enhancing the interpretability and understanding of these models.
PurposeThe study explores the existing Shariah audit practice of Islamic banks (IBs) in Bangladesh aiming at providing suggestions for improvements on the detected shortfalls in the relevant ...areas.Design/methodology/approachThis research applied a qualitative method, and data were collected through conducting semi-structured interviews in Bangladesh. A total of 17 interviews were conducted for accomplishing the research objectives.FindingsThe study finds that there is no comprehensive Shariah audit manual in the current operation for IBs in Bangladesh, and as such, the requirements of their Shariah compliance remain a big question. Although the Shariah audit is conducted within IBs, and the Shariah audit officers or Shariah officers inspect necessary documents while conducting the Shariah audit, they only cover 10–20% of total investments and transactions. Based on the findings of this study, it is recommended that the Shariah auditing tasks should broadly cover at least 80% of the investment portfolios, documents and financial contracts and activities.Research limitations/implicationsThe findings of this research are expected to significantly contribute to the regulatory authorities concerned in Bangladesh and beyond, which include the suggestions that IBs can adopt to strengthen their Shariah governance system. The study also pinpoints that in the current system, Shariah auditors' roles are somehow limited in examining and checking the investment sides with a minimal portion (10–20%), for which they are unable to perform their responsibilities in a befitting manner to provide assurance services and overall Shariah compliance of IBs activities.Practical implicationsThis study explores the current Shariah audit systems and provides recommendations to improve the existing systems which will be beneficial for Islamic banks of Bangladesh.Originality/valueTo the researchers' knowledge, perhaps this is the first research of its kind which seeks to explore the current Shariah audit practice in Bangladesh qualitatively, and it provides some practical suggestions for making the necessary developments of the current audit process of IBs. In addition, there are no empirical studies in the entire Emerald insight publishers and Scopus database regarding Shariah audit practices. The study contributes to the agency, stakeholder and legitimacy theories by exploring the Shariah audit of IBs.
Background: Clear vision is crucial for effective learning among preschool children. Hence, early detection of vision impairment and prompt treatment are required to improve prognosis. Currently, ...limited information is available, and no program exists to screen for vision impairment among preschoolers in Bangladesh. This study aimed to validate the KieVision™ Preschool Vision Screening Kit, translated into the Bengali language, to improve vision impairment detection among preschool children.
Methods: In this prospective case–control study, 60 preschool teachers from Chittagong were randomly selected. The study group was trained to conduct vision screening among preschool children using the translated kit, whereas the control group was trained using the Chittagong Eye Infirmary and Training Complex (CEITC) School Teachers’ Training Module. Fifteen preschool children aged 4–6 years were screened by each preschool teacher and again by the optometrist.
Results: Sixty preschool teachers screened 900 children. The results showed a higher validity of vision screening findings by the preschool teachers in the study group (sensitivity, 68.00%; specificity, 92.75%) than in the control group (sensitivity 47.37%, specificity 70.39%). The level of agreement between the preschool teachers and optometrists was high for all tests (first-order agreement coefficient AC1 ? 0.80 in the study group). The sensitivity and specificity of the visual acuity test for the study group were 59.65% and 94.15%, respectively, while in the control group it was 13.33% and 62.54%, respectively. A similar trend was noted in the general observation component and Hirschberg’s test.
Conclusions: The Bengali Language KieVision™ Preschool Vision Screening Kit can be used effectively by preschool teachers in vision screening programs to improve the identification of vision impairment among preschool children in Bangladesh.
Public debt is intended to bridge the gap between domestic savings and investment. This paper examines the effect of public debt on economic growth in Bangladesh in the short run and the long run. It ...finds a significant positive relationship to exist between public debt and economic growth in the short-run while a significant rise in the public debt in Bangladesh appears to be a burden for the economic growth in the long run controlling for other determinants of growth. This suggests that funds have not been utilized in the productive economic avenues which might have improved the economic growth scenario in Bangladesh. Also, the adverse effect exerted by public debt may further be responsible for a reduction in investment and slower growth of capital stock, which eventually can hamper labour productivity growth in the country in the long run.
Bangladesh Atomic Energy Commission TRIGA Research Reactor (BTRR) is a MK II type nuclear research reactor with a maximum thermal output power of 3 MW. Nuclear research/test reactors are designed for ...the development of nuclear science and technology including all necessary safety features. Safety issues are the prime concern for nuclear reactors to protect the nuclear accidents. BTRR has several passive and engineered safety features against any accidental failure of its control mechanisms leading to the meltdown of the reactor core or any other nuclear incident/accident. The nuclear percent power channel (NPP-1000) is one of the vital parts of the safety systems of the BTRR. Suddenly, the Instrumentation and Control (I&C) system of BTRR is tripped with a system SCRAM message “NPP HV Low”. As a safety system, it is very compulsory to resolve the occurred uncertain issue before going to further reactor operation. To solve that kind of unwanted problem, effective troubleshooting steps were taken very carefully. Circuit analysis showed that a fault transistor was found inside the “HV trip circuit”. By replacing this transistor with a good one, the corresponding relay is now functioning successfully and the “NPP HV low trip” condition as well as the "trip alarm" have been removed from the I&C system. Several types of experiments, research and training are now going on using this Bangladesh Atomic Energy Commission (BAEC) TRIGA Research Reactor facility by ensuring proper safety. Different troubleshooting experiences provide various strategies which are helpful for resolving many upcoming problems and also enrich the problem analyzing ability for further known or unknown tasks".
Background: The predominant cause of giant left atrium (GLA) is rheumatic mitral valvular disease. GLA is commonly defined echocardiographically by measuring the left atrial diameter (LAD). In the ...context of changing epidemiology of rheumatic heart disease (RHD) globally, and introduction of left atrial volume index (LAVI), the aetiology of GLA and utility of LAVI for defining GLA may be necessary.
Methods: The prospective observational study was carried out at a dedicated tertiary care cardiac centre of a developing country to know the aetiology and clinical pattern of GLA over 8 years. GLA was defined echocardiographically as a left atrium (LA) having a diameter ≥80 mm in the left parasternal long-axis view. Follow-up was made over the telephone.
Results: Thirty cases of GLA were diagnosed over 8 years from 2013 to 2021. Twenty two were due to rheumatic heart disease (RHD), 7 due to MVP, and 1 due to flail anterior mitral leaflet. Mean LAD was 92.13 ± 16.72 mm, and the mean LAVI was 288.77 ± 134.40 ml/m2. LA thrombus was present in 5 patients, 6 had spontaneous echo contrast (SEC) in LA, 2 had both LA thrombus and SEC. Mean follow-up was 0.99 ± 1.06 years. Out of 15 patients, 5 died, while 10 were alive. Mean survival was 1.8 ± 1.17 years, ranging from less than 1 year to 4 years.
Conclusion: RHD continues to be the predominant cause of GLA; however, MVP is also important. The cut-off value of LAVI for defining GLA needs further study.
Cardiovasc j 2023; 15(2): 151-158
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