Prevalence and Determinants of Food Insecurity and Association with Malnutrition of under Five Children in Aligarh

Background: Food security has always been a major determinant behind development of malnutrition among the under 5 children of India. Even after sustained efforts to alleviate this problem, we are still way behind in achieving our targets. Aims and Objectives: To assess the prevalence and determinants of food security, and find association of food security with stunting and wasting of children less than five years of age. Materials and Methods: This study among under five children was conducted in field practice areas of Department of Community Medicine, Jawaharlal Nehru Medical College, Aligarh Muslim University, Aligarh. Food security was assessed through Household Food Insecurity Access Scale (HFIAS) while stunting and wasting were assessed by parameters defined by World Health Organization. Statistical Analysis: Done using IBM SPSS 20.0 version. Results: 41.1% children were found to have low food security and among these 1.8% children have very low food security. Overall, statistically significant association was found between food security and malnutrition among the children (p<0.05). Significant association was also found between place of residence, caste, type of family, father’s education, father’s occupation and mother’s education. Conclusion: New health policies should be introduced, and already existing programs need to reinforce to curb this menace

Performance Variation with time of Apparel Sewing Workers: A Case Study

The purposes of this case study is to analyze and identify the variation of sewing workers’ performance of the apparel industry with respect to working hours in a day and different working days; and find out possible solutions to overcome these variations. Data was collected following the theory of work study and then statistical hypothesis test such as two-way ANOVA was done to uncover the variations within the work station relative to working hours and working days and the variations were occurred in around 70% work stations whereas 53% stations faced variation in hourly only. Furthermore, the findings were analyzed by Delphi technique with a group of experts to identify the causes and the corresponding solutions. The Delphi experts group used a cause and effect diagram to identify the causes and finally suggested short-term and long-term solutions

Frequency and associated factors for anxiety and depression in pregnant women: a hospital-based cross-sectional study.

Antepartum anxiety and/or depression is a major public health problem globally. The aim of this study was to estimate the frequency of antepartum anxiety and/or depression among pregnant women. This was a cross-sectional study conducted in a tertiary care hospital among pregnant women. A total of 165 pregnant women were interviewed by a clinical psychologist using HADS for assessing anxiety and/or depression and also collected information regarding sociodemographic, obstetric, family relationships, and home environment. Out of the total of 165 pregnant women about 70 percent of them were either anxious and/or depressed. The increasing age of women (P-value = 0.073), not having any live birth (P-value = 0.036), adverse pregnancy outcome in past including death of a child, stillbirth or abortion (P-value = 0.013), participant\u27s role in household decision making (P-value = 0.013), and domestic violence (verbal or physical abuse towards mother or children by any family member) (P-value = 0.123). Our study highlights that anxiety and/or depression is quite common among pregnant women. Therefore, there is a need to incorporate screening for anxiety and depression in the existing antenatal programs and development of strategies to provide practical support to those identified

DESIGN AND OPERATION OF MICROGRID

The need for new generation systems has motivated the development of microgrids. This new concept may provide significant benefits such as losses compensation, achieving high degree of efficiency and reliability to the transmission and distribution networks. This novel idea provides more advantages about Microgrids like general structure and different topologies. Also an original methodology for facilitating its design is proposed. Finally Simulink model of Microgrid is designed and then analyzed.Â

Adaptive Body Area Networks Using Kinematics and Biosignals

The increasing penetration of wearable and implantable devices necessitates energy-efficient and robust ways of connecting them to each other and to the cloud. However, the wireless channel around the human body poses unique challenges such as a high and variable path-loss caused by frequent changes in the relative node positions as well as the surrounding environment. An adaptive wireless body area network (WBAN) scheme is presented that reconfigures the network by learning from body kinematics and biosignals. It has very low overhead since these signals are already captured by the WBAN sensor nodes to support their basic functionality. Periodic channel fluctuations in activities like walking can be exploited by reusing accelerometer data and scheduling packet transmissions at optimal times. Network states can be predicted based on changes in observed biosignals to reconfigure the network parameters in real time. A realistic body channel emulator that evaluates the path-loss for everyday human activities was developed to assess the efficacy of the proposed techniques. Simulation results show up to 41% improvement in packet delivery ratio (PDR) and up to 27% reduction in power consumption by intelligent scheduling at lower transmission power levels. Moreover, experimental results on a custom test-bed demonstrate an average PDR increase of 20% and 18% when using our adaptive EMG- and heart-rate-based transmission power control methods, respectively. The channel emulator and simulation code is made publicly available at https://github.com/a-moin/wban-pathloss.Comment: Accepted for publication in IEEE Journal of Biomedical and Health Informatic

An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier

EMG-based gesture recognition shows promise for human-machine interaction. Systems are often afflicted by signal and electrode variability which degrades performance over time. We present an end-to-end system combating this variability using a large-area, high-density sensor array and a robust classification algorithm. EMG electrodes are fabricated on a flexible substrate and interfaced to a custom wireless device for 64-channel signal acquisition and streaming. We use brain-inspired high-dimensional (HD) computing for processing EMG features in one-shot learning. The HD algorithm is tolerant to noise and electrode misplacement and can quickly learn from few gestures without gradient descent or back-propagation. We achieve an average classification accuracy of 96.64% for five gestures, with only 7% degradation when training and testing across different days. Our system maintains this accuracy when trained with only three trials of gestures; it also demonstrates comparable accuracy with the state-of-the-art when trained with one trial

The Salient Motives for Malaysia Aviation Industry Sustainability: An Explorative Study on Business, Management and Technology Components in Aviation Management Program in Malaysia

The purpose of this research is to develop a comprehensive evaluation framework of three important elements, namely business, management, and technology embedded in the newly developed Master of Science program in aviation management. A Focus group interview has been adopted in this study with the involvement of aviation management faculty members and also panel members from the Board of Studies (BOS). Two prominent aviation practitioners and two leading academicians with aviation background were called for a focus group discussion and the meeting held for six (6) hours. Alignments of the course offered need to be formed to link with the aviation industry 4.0 and aviation industry 5.0. This study reveals the critical needs and issues at the industry perspective and drives new areas for an academician to focus on the syllabus and research. This study bridges the gap between industry and academicians by keeping scholars and practitioners abreast of the timeliest industry-academician framework. It elevated the current thinking necessary for better performance of the industry, as well as the quality of the new proposed master program. This study clearly shows both academic and industry players related needs to establish a new program by consolidating both theoretical development and industry career. Recommendation to all academicians, practitioners, and policymaker are also highlighted in this study

DESIGN AND OPERATION OF MICROGRID

The need for new generation systems has motivated the development of microgrids. This new concept may provide significant benefits such as losses compensation, achieving high degree of efficiency and reliability to the transmission and distribution networks. This novel idea provides more advantages about Microgrids like general structure and different topologies. Also an original methodology for facilitating its design is proposed. Finally Simulink model of Microgrid is designed and then analyzed.

A Remarkable Case of Acute Motor-Sensory Axonal Polyneuropathy (AMSAN) Variant of Guillain Barré Syndrome, in a Diabetic Patient Infected With COVID-19: A Case Report and Review of the Literature

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease- 2019 (COVID-19), has been a global epidemic in our healthcare system. SARS-CoV-2 primarily affects the respiratory system, but neurological involvement has also been reported, including Guillain–Barré syndrome (GBS) development.Case PresentationA 58-year-old male with known co-morbid hypertension and type 2 diabetes mellitus presented to the emergency room with complaints of worsening shortness of breath, dry cough, and fever for the past 10 days. On day 20 of hospitalization, he developed neurological symptoms after being tested positive for COVID-19. A neuroelectrophysiology study was conducted to evaluate neurological symptoms and suggested that the patient suffers from acute motor-sensory axonal polyneuropathy (AMSAN). CSF analysis showed elevated protein levels that confirmed the diagnosis of GBS. He was subsequently treated with oral prednisolone and IVIG, which improved neurological symptoms.ConclusionEver since the emergence of COVID-19, GBS has surfaced as to its potentially dangerous outcome. Healthcare professionals should be mindful of GBS and should rule it out in anyone having sensory symptoms or weakness during or after a COVID-19 infection. Its early detection and treatment can result in improved clinical outcomes