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This case study explores how a group of Grade 9 students engaged in sociopolitical discourses and actions in a science class in a mostly indigenous student school in Nepal. The study used sociopolitical consciousness (SPC) as a framework to document and understand indigenous students' SPC-oriented science interactions and subsequent social change actions. We used ethnographic methods of data collection over 6 months. The study focused on the actions of 4 girls and 2 boys belonging to the indigenous Tharu group. Data were analyzed using iterative qualitative methods. The study findings show that students are capable of engaging in critical thinking, critical reflecting, and taking actions for social change. Additionally, students are competent to link their experiences with social, structural, and political discrimination to the relevant science content they learn. The study presents four thematic findings related to SPC and science teaching and learning: Fostering social justice awareness in science class, fostering structural understanding of inequities in sickle cell disease, fostering sociopolitical actions for sickle cell disease, and the teacher's activist pedagogy for SPC in science learning. Implications of the study are that culturally relevant pedagogy helps indigenous students to become sociopolitically more aware of the links between science and social change. Adding aspects of critical pedagogies in science teaching could encourage students to become more sociopolitically reflective about science learning.

In India, COVID-19 case fatality rates (CFRs) have consistently been very high in states like Punjab and Maharashtra and very low in Kerala and Assam. To investigate the discrepancy in state-wise CFRs, datasets on various factors related to demography, socio-economy, public health, and healthcare capacity have been collected to study their association with CFR. State-wise COVID-19 data was collected till April 22, 2021. The latest data on the various factors have been collected from reliable sources. Pearson correlation, two-tailed P test, Spearman rank correlation, and Artificial Neural Network (ANN) structures have been used to assess the association between various factors and CFR. Life expectancies, prevalence of overweight, COVID-19 test positive rates, and H1N1 fatality rates show a significant positive association with CFR. Human Development Index, per capita GDP, public affairs index, health expenditure per capita, availability of govt. doctors & hospital beds, prevalence of certain diseases, and comorbidities like diabetes and hypertension show insignificant association with CFR. Sex ratio, health expenditure as a percent of GSDP, and availability of govt. hospitals show a significant negative correlation with CFR. The study indicates that older people, males of younger age groups, and overweight people are at more fatality risk from COVID-19. Certain diseases and common comorbidities like diabetes and hypertension do not seem to have any significant effect on CFR. States with better COVID-19 testing rates, health expenditure, and healthcare capacity seem to perform better with regard to COVID-19 fatality rates. • Maharashtra and Punjab consistently show highest COVID-19 fatality rates in India. • Life expectancy, sex ratio and prevalence of overweight people affects COVID-19 case fatality rate (CFR). • Prevalence of cancer, diabetes, and hypertension show insignificant association with CFR. • States with better testing rates, health capacity and expenditure tend to have lower CFR. [ABSTRACT FROM AUTHOR]

Fourteen diverse genotypes of wheat including three standard check variety were evaluated under heat stress condition during rabi season 2016-17 at Agriculture Farm, Institute of Agricultural Sciences, Banaras Hindu University. Genotypes were studied for genetic variability, path analysis and diversity with the aim to identify the superior genotype with significantly satisfactory yield under very late sown condition. The data were recorded for traits viz., days to heading, days to maturity, plant height, 1000 grain weight, grain yield plot-1 and biological yield plot-1. Analysis of variance showed significant differences for all the six traits. The grain yield plot-1 ranged from 2375-3600 g. The phenotypic coefficient of variation and genotypic coefficient of variation was observed highest for grain yield plot-1. Highest broad sense heritability was observed for 1000 grain weight while genetic advance was estimated to be highest for grain yield plot-1. Diversity analysis indicates that total 14 genotypes were grouped into 5 clusters. The highest inter-cluster distance was found between cluster IV and V followed by II and V. This exhibited that genotypes included in these clusters possess wide genetic diversity. Diversity study shows that the selection of genotypes for crosses from cluster V (WR544(C)) with cluster IV(PBW778), cluster II (HD3272) and cluster I (HI11621, WH1232, PBW757, DBW251, DBW250, HD3271 and WH1233) could give maximum heterosis and prove to be good recombinants. Hence, genotypes from such diverse groups can be selected for making the crosses and selection of desirable genotype for heat tolerance and better yield. [ABSTRACT FROM AUTHOR]