Modeling the Impact of Process Variation on Resistive Bridge Defects

Recent research has shown that tests generated without taking process variation into account may lead to loss of test quality. At present there is no efficient device-level modeling technique that models the effect of process variation on resistive bridges. This paper presents a fast and accurate technique to model the effect of process variation on resistive bridge defects. The proposed model is implemented in two stages: firstly, it employs an accurate transistor model (BSIM4) to calculate the critical resistance of a bridge; secondly, the effect of process variation is incorporated in this model by using three transistor parameters: gate length (L), threshold voltage (V) and effective mobility (ueff) where each follow Gaussian distribution. Experiments are conducted on a 65-nm gate library (for illustration purposes), and results show that on average the proposed modeling technique is more than 7 times faster and in the worst case, error in bridge critical resistance is 0.8% when compared with HSPICE

Prevalence of and factors associated with childhood diarrhoeal disease and acute respiratory infection in Bangladesh: an analysis of a nationwide cross-sectional survey

Objectives This study aimed to estimate the prevalence of childhood diarrhoeal diseases (CDDs) and acute respiratory infections (ARIs) and also to determine the factors associated with these conditions at the population level in Bangladesh. Setting: The study entailed an analysis of nationally representative cross-sectional secondary data from the most recent Bangladesh Demographic and Health Survey conducted in 2017–2018. Participants: A total of 7222 children aged below 5 years for CDDs and 7215 children aged below 5 years for ARIs during the survey from mothers aged between 15 and 49 years were the participants of this study. In the bivariate and multivariable analyses, we used Pearson χ2 test and binary logistic regression, respectively, for both outcomes. Results: The overall prevalence of CDD and ARI among children aged below 5 years was found to be 4.91% and 3.03%, respectively. Younger children were more likely to develop both CDDs and ARIs compared with their older counterparts. Children belonging to households classified as poorest and with unimproved floor materials had a higher prevalence of diarrhoea than those from households identified as richest and with improved floor material, respectively. Stunted children had 40.8% higher odds of diarrhoea than normal children. Being male and having mothers aged below 20 years were 48.9% and two times more likely to develop ARI than female counterparts and children of mothers aged 20–34 years, respectively. Children whose mothers had no formal education or had primary and secondary education had higher odds of ARI compared with children of mothers having higher education. Conclusion: This study found that children aged below 24 months were at higher risk of having CDDs and ARIs. Thus, programmes targeting these groups should be designed and emphasis should be given to those from poorest wealth quintile to reduce CDDs and ARIs

Rational synthesis of ternary PtIrNi nanocrystals with enhanced poisoning tolerance for electrochemical ethanol oxidation

The development of highly efficient and durable anode materials for ethanol electro-oxidation remains a challenge. Herein, we report the synthesis of Pt1−x−yIrxNiy nanocrystals via one-step procedure by ultrasonic-assisted co-reduction of the metal precursors using ascorbic acid as a mild reducing agent and pluronic F127 as a structure directing agent. The catalytic performance of this ternary catalyst towards electrochemical oxidation of ethanol was examined and compared to its mono and binary Pt counterparts (Pt, Pt1−xIrx, and Pt1−yNiy) that are synthesized by the same method. TEM analysis showed a porous nanodendritic structure for the synthesized ternary electrocatalyst with an average size of 20 ± 1 nm. The electrochemical measurements revealed an electrochemically active surface area, ECSA, of 73 m2 g−1. The as-synthesized ternary electrocatalyst showed an improved catalytic activity towards ethanol oxidation in 1 M KOH with a measured mass activity of 3.8 A mg−1 which is 1.7, 2.0, and 3.2 times higher than that of Pt1−xIrx, Pt1−yNiy, and Pt, respectively. Additionally, the Pt1−x−yIrxNiy nanocrystals expressed high poisoning tolerance (jf/jb = 4.5) and high durability compared to its mono and binary counterparts.Scopu

Factors influencing and changes in childhood vaccination coverage over time in Bangladesh: a multilevel mixed-effects analysis

Introduction: This study aimed to investigate the associated factors and changes in childhood vaccination coverage over time in Bangladesh. Methods: Bangladesh’s Demographic and Health Surveys from 2011, 2014, and 2017-18 provided data for this study on vaccination coverage among children aged 12 to 35 months. For three survey periods, multilevel binary logistic regression models were employed. Results: The overall prevalence (weighted) of full vaccination among children aged 12–35 months were 86.17% in 2011, 85.13% in 2014, and 89.23% in 2017-18. Children from families with high wealth index, mothers with higher education, and over the age of 24 and who sought at least four ANC visits, as well as children from urban areas were more likely to receive full vaccination. Rangpur division had the highest change rate of vaccination coverage from 2011 to 2014 (2.26%), whereas Sylhet division had the highest change rate from 2014 to 2017-18 (34.34%). Conclusion: To improve immunization coverage for Bangladeshi children, policymakers must integrate vaccine programs, paying special attention to mothers without at least a high school education and families with low wealth index. Increased antenatal care visits may also aid in increasing the immunization coverage of their children

MENTAL HEALTH OUTCOMES OF ADULTS WITH COMORBIDITY AND CHRONIC DISEASES DURING THE COVID-19 PANDEMIC: A MATCHED CASE-CONTROL STUDY

Background: Individuals with certain pre-existing chronic health conditions have been identified as a high-risk group for fatalities of COVID-19. Therefore, it is likely that individuals with chronic diseases may worry during this pandemic to the detriment of their mental health. This study compares the mental health of Bangladeshi adults affected by chronic disease to a healthy, matched control group during the COVID-19 pandemic. Subjects and methods: A matched case-control analysis was performed with data collected from 395 respondents with chronic diseases and 395 controls matched for age, gender, and residence. Inclusion criteria for cases were respondents who self reported having asthma, cardiovascular disease symptoms and/or diabetes. Respondents were recruited using an online survey, which included the DASS-21 measure to assess symptoms of stress, anxiety, and depression. Chi-square test, t-test, Fisher’s exact test and a conditional logistic regression were performed to examine associations among variables. Results: The prevalence of anxiety symptoms and depression symptoms and the level of stress were significantly higher among cases (59%; 71.6%; 73.7%, respectively) than among controls (25.6%; 31.1%; 43.3%, respectively). Chi-square and t-test showed significant associations and differences between having chronic diseases and mental health outcomes. A conditional logistic regression showed that respondents with asthma, diabetes, cardiovascular disease symptoms, or any combination of these diseases had higher odds of exhibiting symptoms of stress, anxiety, and depression than healthy individuals. Conclusion: These results underscore a subpopulation vulnerable to mental health consequences during this pandemic and indicate the need for additional mental health resources to be available to those with chronic diseases

Technology-Circuit-Algorithm Tri-Design for Processing-in-Pixel-in-Memory (P2M)

The massive amounts of data generated by camera sensors motivate data processing inside pixel arrays, i.e., at the extreme-edge. Several critical developments have fueled recent interest in the processing-in-pixel-in-memory paradigm for a wide range of visual machine intelligence tasks, including (1) advances in 3D integration technology to enable complex processing inside each pixel in a 3D integrated manner while maintaining pixel density, (2) analog processing circuit techniques for massively parallel low-energy in-pixel computations, and (3) algorithmic techniques to mitigate non-idealities associated with analog processing through hardware-aware training schemes. This article presents a comprehensive technology-circuit-algorithm landscape that connects technology capabilities, circuit design strategies, and algorithmic optimizations to power, performance, area, bandwidth reduction, and application-level accuracy metrics. We present our results using a comprehensive co-design framework incorporating hardware and algorithmic optimizations for various complex real-life visual intelligence tasks mapped onto our P2M paradigm

Factors associated with food safety knowledge and practices among meat handlers in Bangladesh: a cross-sectional study.

Background Food handlers can play a vital role into reducing foodborne diseases by adopting appropriate food handling and sanitation practices in working plants. This study aimed to assess the factors associated with food safety knowledge and practices among meat handlers who work at butcher shops in Bangladesh. Methods A cross-sectional study was conducted among 300 meat handlers from January to March, 2021. Data were collected through in-person interviews using a structured questionnaire. The questionnaire consisted of three parts; socio-demographic characteristics, assessments of food safety knowledge, and food safety practices. A multiple logistic regression model was used to identify the factors associated with food safety knowledge and practices. Results Only 20% [95% confidence interval, (CI) 15.7–24.7] and 16.3% (95% CI 12.3–20.7) of the respondents demonstrated good levels of food safety knowledge and practices, respectively. The factors associated with good levels of food safety knowledge were: having a higher secondary education [adjusted odds ratio (AOR) = 4.57, 95% CI 1.11–18.76], income above 25,000 BDT/month (AOR = 10.52, 95% CI 3.43–32.26), work experience of > 10 years (AOR = 9.31, 95% CI 1.92–45.09), ≥ 8 h per day of work (AOR = 6.14, 95% CI 2.69–13.10), employed on a daily basis (AOR = 4.05, 95% CI 1.16–14.14), and having food safety training (AOR = 8.98 95% CI 2.16–37.32). Good food safety knowledge (AOR = 5.68, 95% CI 2.33–13.87) and working ≥ 8 h per day (AOR = 8.44, 95% CI 3.11–22.91) were significantly associated with a good level of food safety practice. Conclusions Poor knowledge and practices regarding food safety were found among Bangladeshi meat handlers. Findings may help public health professionals and practitioners develop targeted strategies to improve food safety knowledge and practices among this population. Such strategies may include education and sensitization on good food safety practices

Acoustic emission based damage localization in composites structures using Bayesian identification

Acoustic emission based damage detection in composite structures is based on detection of ultra high frequency packets of acoustic waves emitted from damage sources (such as fibre breakage, fatigue fracture, amongst others) with a network of distributed sensors. This non-destructive monitoring scheme requires solving an inverse problem where the measured signals are linked back to the location of the source. This in turn enables rapid deployment of mitigative measures. The presence of significant amount of uncertainty associated with the operating conditions and measurements makes the problem of damage identification quite challenging. The uncertainties stem from the fact that the measured signals are affected by the irregular geometries, manufacturing imprecision, imperfect boundary conditions, existing damages/structural degradation, amongst others. This work aims to tackle these uncertainties within a framework of automated probabilistic damage detection. The method trains a probabilistic model of the parametrized input and output model of the acoustic emission system with experimental data to give probabilistic descriptors of damage locations. A response surface modelling the acoustic emission as a function of parametrized damage signals collected from sensors would be calibrated with a training dataset using Bayesian inference. This is used to deduce damage locations in the online monitoring phase. During online monitoring, the spatially correlated time data is utilized in conjunction with the calibrated acoustic emissions model to infer the probabilistic description of the acoustic emission source within a hierarchical Bayesian inference framework. The methodology is tested on a composite structure consisting of carbon fibre panel with stiffeners and damage source behaviour has been experimentally simulated using standard H-N sources. The methodology presented in this study would be applicable in the current form to structural damage detection under varying operational loads and would be investigated in future studies

(E,E)-1,2-Bis[3-meth­oxy-4-(prop-2-yn-1-yl­oxy)benzyl­idene]hydrazine

The complete mol­ecule in the title compound, C22H20N2O4, is generated by the application of an inversion centre. With the exception of the terminal acetyl­ene groups [C—O—C—C = −78.02 (17)°], the remaining atoms constituting the mol­ecule are essentially coplanar. The configuration around the C=N bond [1.282 (2) Å] is E. The formation of supra­molecular chains mediated by C—H⋯O inter­actions, occurring between methyl­ene H and meth­oxy O atoms, is the most notable feature of the crystal packing