Complex-valued sliding mode controllers for doubly-fed induction motors

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis article presents two algorithms to control the speed of doubly-fed induction motors. The controllers are designed using the complex-valued sliding mode methodology to track either the rotor or the stator current. An outer loop controls the mechanical speed. The control schemes are validated experimentally and compared in a laboratory setup.Peer ReviewedPostprint (author's final draft

Review of Agri-Food Chain Interventions Aimed at Enhancing Consumption of Nutritious Food by the Poor: Bangladesh

Bangladesh is primarily an agrarian nation. Most of the people of the country directly or indirectly depend on agriculture. Rural people are more involved in this sector compared to urban people. Agriculture is the single largest producing sector of the economy. The performance of this sector has an overwhelming impact on major macroeconomic objectives like employment generation, poverty alleviation, human resources development and food security. The acceleration in economic and agricultural growth has made a positive impact on the diversity of food intake, away from the rice- and vegetable-based diet in favour of quality food. However, nearly 20 per cent of the population is still calorie deficient and the gender disparity in calorie intake still persists. Bangladesh has made significant progress in reducing under nutrition of children. However, progress in reducing stunting, the indicator of chronic malnutrition, shows a less encouraging picture. A review on existing agriculture value chain-based interventions that focus on enhancing the availability, affordability, acceptability and/or consumption of nutritious foods in households beyond the farm gate in Bangladesh has been undertaken. This review covers: interventions focused on foods that are naturally nutrient-dense interventions focused on enhancing the nutritional value of foods, including staples and prepared foods, whether directed at particular nutritional uses or for consumption by the general population food distribution programmes that might incorporate foods in either of the preceding categorie

Serum zinc status of neonates with seizure

Background: Seizure is a common neurological disorder in neonatal age group!. Primary metabolic derangement is one of the important reason behind this convulsion during this period. Among primary metabolic derangement hypoglycemia, is most common followed by bypocalcaemia, hypomagnesaemia, low zinc status etc. As causes of many cases of convul­sion remain unknown in neonate. Objectives: To see the zinc status in the sera of neonate with convulsion. So that if needed early intervention can be taken up and thereby prevent complications. Method: A total of 50 neonates (1-28 days) who had convulsion with no apparent reasons of convulsion were enrolled as cases and 50 healthy age and sex matched neonates were enrolled as controls. After a quick clinical evaluation serum zinc status was estimated from venous blood by atomic absorption method in Chemistry Division, Atomic Energy Centre. Low zinc was considered if serum value was <0.7mg/L. Results: Among a total of 50 cases 6% had low zinc value & 2% of controls also had low zinc level. The mean serwu zinc level of cases and controls were 1.57±0.95 and 2.37±1.06 mmol/1 respectively (p<0.01). Conclusion: From the study it is seen that low zinc value is an important cause of neonatal seizure due to primary metabolic abnormalities. So early recognition and treatment could save these babies from long term neurological sequelies

Double burden of malnutrition in children aged 24 to 59 months by socioeconomic status in five South Asian countries: evidence from demographic and health surveys

Objectives We aimed to investigate the socioeconomic inequalities in the burden of underweight and overweight among children in South Asia. We also examined other factors that were associated with these outcomes independently of household’s socioeconomic status. Design Nationally-representative surveys. Settings Demographic and Health Surveys from Bangladesh, India, Pakistan, Maldives and Nepal, which were conducted between 2009 and 2016. Participants Children aged 24 to 59 months with valid measurement for height and weight (n=146 996). Primary exposure and outcome measures Primary exposures were household’s wealth index and level of education. Underweight and overweight were defined according to the WHO and International Obesity Task Force definitions, respectively. Results Underweight prevalence was 37% in Bangladesh, 38% in India, 19% in Maldives, 29% in Nepal and 28% in Pakistan. Bangladesh, India and Nepal had similar overweight prevalence (between 2% and 4%) whereas Pakistan (7%) and Maldives (9%) had higher prevalence. Households with higher wealth index or education had lower odds of having underweight children. Adjusted ORs of underweight for richest versus poorest households were 0.4 (95% CI: 0.3 to 0.5), 0.5 (95% CI: 0.5 to 0.6), 0.5 (95% CI: 0.2 to 1.4), 0.5 (95% CI: 0.3 to 0.8) and 0.7 (95% CI: 0.5 to 1.1) for Bangladesh, India, Maldives, Nepal and Pakistan, respectively. Compared with poorest households, richest households were more likely to have overweight children in all countries except Pakistan, but such associations were not significant after adjustment for other factors. There were higher odds of having overweight children in households with higher education in Bangladesh (OR 2.1 (95% CI: 1.3 to 3.5)), India (OR 1.2 (95% CI: 1.2 to 1.3)) and Pakistan (OR 1.8 (95% CI: 1.1 to 2.9)) when compared with households with no education. Maternal nutritional status was consistently associated with children’s nutritional outcomes after adjustments for socioeconomic status. Conclusions Our study provides evidence for socioeconomic inequalities for childhood underweight and overweight in South Asian countries, although the directions of associations for underweight and overweight might be different

Machine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications

The concept of small modular reactor has changed the outlook for tackling future energy crises. This new reactor technology is very promising considering its lower investment requirements, modularity, design simplicity, and enhanced safety features. The application of artificial intelligence-driven multi-scale modeling (neutronics, thermal hydraulics, fuel performance, etc.) incorporating Digital Twin and associated uncertainties in the research of small modular reactors is a recent concept. In this work, a comprehensive study is conducted on the multiscale modeling of accident-tolerant fuels. The application of these fuels in the light water-based small modular reactors is explored. This chapter also focuses on the application of machine learning and artificial intelligence in the design optimization, control, and monitoring of small modular reactors. Finally, a brief assessment of the research gap on the application of artificial intelligence to the development of high burnup composite accident-tolerant fuels is provided. Necessary actions to fulfill these gaps are also discussed

Accelerating progress towards the Zero Hunger Goal in cross-boundary climate change hotspots

The most recent 2017 United Nations’ Sustainable Development Goals progress report highlighted the need to accelerate the pace of progress in order for the Sustainable Development Goals to be fully achieved. Responding to these concerns, the present commen tary proposes four distinct, but interrelated approaches to accelerate the Zero Hunger G oal in transboundary climate change hotspots, regions which suffer from multiple stressors and vulnerabilities, and in which prevalence of food insecurity and malnutrition often remains disproportionately high. These conceptual, programmatic and policy approaches are discussed drawing from a newly developed conceptual framework and referring to specific examples from climate change hotspots around the world

Association between Infant- and Child-feeding Index and Nutritional Status: Results from a Cross-sectional Study among Children Attending an Urban Hospital in Bangladesh

Integration of infant- and child-feeding index (ICFI) addressing the multidimensional child-feeding practices into one age-specific summary index is gaining importance. This cross-sectional study was aimed at understanding the association between the ICFI and the nutritional status of 259 children, aged 6-23 months, who attended the paediatric outpatient department of the Dhaka Medical College Hospital in Bangladesh. The mean length-for-age z-score (LAZ) of children aged 12-23 months was significantly (p<0.05) higher among those who were at the upper ICFI tercile compared to those who were at the middle or lower ICFI tercile (-2.01 and -3.20 respectively). A significant correlation was found between the ICFI and the LAZ (r=0.24, p=0.01 and r=0.29, p=0.01) in children aged 6-8-months and 12-23-months. Multivariable analysis, after adjusting for potential confounders, also found a significant association between the ICFI and the LAZ (\u3b2=0.13, p=0.03). The predictive capability of the proposed ICFI on nutritional status of children, especially length-for-age, needs to be further evaluated prospectively among healthy children in the community

The impact of COVID-19 pandemic on mental health & wellbeing among home-quarantined Bangladeshi students: A cross-sectional pilot study.

BACKGROUND:COVID-19 is imposing threat both on physical and mental health since its outbreak. Bangladesh adopted lockdown strategy with potential consequences on day to day life, mental and physical health and this study aims to explore the impact of COVID-19 on mental health and wellbeing among Bangladeshi students. METHODS:A cross-sectional study was conducted between 9th and 23rd April 2020 among 505 college and university students. Data was collected by using online questionnaire including DASS 21 and IES. Descriptive analysis and bivariate linear regression were performed to examine the association of variables. RESULTS:28.5 % of the respondents had stress, 33.3% anxiety, 46.92% depression from mild to extremely severe, according to DASS 21 and 69.31% had event-specific distress from mild to severe in terms of severity according to IES. Perceiving physical symptoms as COVID-19 was significantly associated with DASS stress subscale (B = 3.71, 95% CI: 1.01 to 6.40), DASS anxiety subscale (B = 3.95, 95% CI: 1.95 to 5.96), DASS depression subscale (B = 3.82, 95% CI: 0.97 to 6.67) and IES scale (B = 7.52, 95% CI: 3.58 to 11.45). Additionally, fear of infection, financial uncertainty, inadequate food supply, absence of physical exercise and limited or no recreational activity had significant association with stress, anxiety, depression and post-traumatic symptoms. CONCLUSION:This COVID-19 outbreak imposes psychological consequences on people to a great extent which requires attention from the concerned authorities to cope with this situation mentally. The perception about the outbreak can also play a big role in psychological impact

Construction of copy number variation landscape and characterization of associated genes in a Bangladeshi cohort of neurodevelopmental disorders

Introduction: Copy number variations (CNVs) play a critical role in the pathogenesis of neurodevelopmental disorders (NDD) among children. In this study, we aim to identify clinically relevant CNVs, genes and their phenotypic characteristics in an ethnically underrepresented homogenous population of Bangladesh. Methods: We have conducted chromosomal microarray analysis (CMA) for 212 NDD patients with male to female ratio of 2.2:1.0 to identify rare CNVs. To identify candidate genes within the rare CNVs, gene constraint metrics [i.e., “Critical-Exon Genes (CEGs)”] were applied to the population data. Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) was followed in a subset of 95 NDD patients to assess the severity of autism and all statistical tests were performed using the R package. Results: Of all the samples assayed, 12.26% (26/212) and 57.08% (121/212) patients carried pathogenic and variant of uncertain significance (VOUS) CNVs, respectively. While 2.83% (6/212) patients’ pathogenic CNVs were found to be located in the subtelomeric regions. Further burden test identified females are significant carriers of pathogenic CNVs compared to males (OR = 4.2; p = 0.0007). We have observed an increased number of Loss of heterozygosity (LOH) within cases with 23.85% (26/109) consanguineous parents. Our analyses on imprinting genes show, 36 LOH variants disrupting 69 unique imprinted genes and classified these variants as VOUS. ADOS-2 subset shows severe social communication deficit (p = 0.014) and overall ASD symptoms severity (p = 0.026) among the patients carrying duplication CNV compared to the CNV negative group. Candidate gene analysis identified 153 unique CEGs in pathogenic CNVs and 31 in VOUS. Of the unique genes, 18 genes were found to be in smaller (<1 MB) focal CNVs in our NDD cohort and we identified PSMC3 gene as a strong candidate gene for Autism Spectrum Disorder (ASD). Moreover, we hypothesized that KMT2B gene duplication might be associated with intellectual disability. Conclusion: Our results show the utility of CMA for precise genetic diagnosis and its integration into the diagnosis, therapy and management of NDD patients

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world’s highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%.Peer ReviewedPostprint (published version