Microstructure quality control of steels using deep learning

In quality control, microstructures are investigated rigorously to ensure structural integrity, exclude the presence of critical volume defects, and validate the formation of the target microstructure. For quenched, hierarchically-structured steels, the morphology of the bainitic and martensitic microstructures are of major concern to guarantee the reliability of the material under service conditions. Therefore, industries conduct small sample-size inspections of materials cross-sections through metallographers to validate the needle morphology of such microstructures. We demonstrate round-robin test results revealing that this visual grading is afflicted by pronounced subjectivity despite the thorough training of personnel. Instead, we propose a deep learning image classification approach that distinguishes steels based on their microstructure type and classifies their needle length alluding to the ISO 643 grain size assessment standard. This classification approach facilitates the reliable, objective, and automated classification of hierarchically structured steels. Specifically, an accuracy of 96% and roughly 91% is attained for the distinction of martensite/bainite subtypes and needle length, respectively. This is achieved on an image dataset that contains significant variance and labeling noise as it is acquired over more than 10 years from multiple plants, alloys, etchant applications, and light optical microscopes by many metallographers (raters). Interpretability analysis gives insights into the decision-making of these models and allows for estimating their generalization capability

Policy Recommendations for Meeting the Grand Challenge to Reduce Extreme Economic Inequality

This brief was created forSocial Innovation for America’s Renewal, a policy conference organized by the Center for Social Development in collaboration with the American Academy of Social Work & Social Welfare, which is leading theGrand Challenges for Social Work initiative to champion social progress. The conference site includes links to speeches, presentations, and a full list of the policy briefs

Work-Based Antipoverty Programs for Parents Can Enhance the School Performance and Social Behavior of Children

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65246/1/1467-8624.00281.pd

Co-resident Parents and Young People Aged 15–34: Who Does What Housework?

Young adults are now more likely to co-reside with their parents than previous generations, but domestic work patterns among this family type are largely unexplored. This study addresses this issue using Australian Bureau of Statistics Time Use Surveys (1992, 1997, 2006) and Poisson–Gamma regression analyses. It examines patterns in and correlates of domestic labor in two-generation households in which young people aged 15–34 co-reside with their parents (n = 1,946 households comprised of 2,806 young people and 5,129 parents). It differentiates between routine indoor tasks (cooking, cleaning, laundry), non-routine tasks (outdoor work, household management and maintenance, car care) and grocery shopping. Predictors of more time in some domestic activities by young people include being in neither employment nor education/training (NEET), being older, having a single parent and being in a non-English speaking household (young women). Young people being NEET, or female, are associated with less cooking time for mothers, but in the main when young people do perform domestic activities, they do not relieve their parents of those same activities, suggesting more time is spent by the household in total

Siblings of children with autism:The Siblings Embedded Systems Framework

Purpose of review: a range of interacting factors/mechanisms at the individual, family, and wider systems levels influences siblings living in families where one sibling has autism. We introduce the Sibling Embedded Systems Framework which aims to contextualise siblings’ experience and characterise the multiple and interacting factors influencing family and, in particular, sibling outcomes.Recent findings: findings from studies that have reported outcomes for siblings of children with autism are equivocal, ranging from negative impact, no difference, to positive experience. This is likely due to the complex nature of understanding the sibling experience. We focus on particular elements of the framework and review recent novel literature to help guide future directions for research and practice including the influence of culture, methodological considerations, and wider participatory methods.Summary: the Siblings Embedded System Framework can be used to understand interactive factors that affect sibling adjustment and to develop clinically, educationally and empirically based work that aims to enhance and support sibling adjustment, relationships, and well-being in families of children with autism.<br/