Damping Analysis of Composites Used in Drilling Machine Bed

Vibrations are generally occurs during the machining process as drilling, milling etc. which is the main cause of defects in the machine tools. So vibrational damping study is very necessary for minimizing the vibrational effect on the machines bed. At present work glass fiber epoxy and glass fiber polyester are the composites used as the drilling machine bed as a base of the work piece. The purpose of the paper is to analyze the damping of sandwich composites used in this work is calculating by the energy balance approach method

Groundwater hydrochemistry of Rajnandgaon district, Chhattisgarh, Central India

The spreading of fluorosis diseases in Central India related to high concentrations of fluoride ion (F−) is a cause of major concern. In this work, the hydrochemistry of the aquifers related to Seonath River, in Rajnandgaon district, Chhattisgarh state, India, has been studied, focusing on the presence and sources of F−. Hydrochemical parameters were analyzed in the post-monsoon season in 160 wells located in nine tehsils, finding F− concentrations ranging from 0.6 to 18.5 mg L−1. Seasonal variations were also studied in Chhuikhadan tehsil, in which the highest F− values were registered, finding a noticeable enrichment in the pre-monsoon months. In many locations of the district, F− concentrations exceeded the recommended value of 1.5 mg L−1, which have led to the appearance of several health issues. Multidimensional analysis statistical methods were adopted to investigate the sources of F−, and the mineralization of bedrock elements into the groundwater was observed to be the primary source

Towards defining heterotic gene pools using SSR markers in pearl millet [Pennisetum glaucum (L.) R. Br.]

Pearl millet is a climate resilient crop and the most widely grown millet worldwide. In a maiden attempt to identify potential heterotic groups for grain yield in pearl millet, a total of 88 polymorphic SSR markers were used to genotype 343 hybrid parental lines of pearl millet. The SSR markers generated a total of 532 alleles with a mean value of 6.05 alleles per locus, mean gene diversity of 0.55, and an average PIC of 0.50. Out of 532 alleles, 443 (83.27%) alleles were contributed by B- lines with a mean of 5.03 alleles per locus. R- lines contributed 476 alleles (89.47%) with a mean of 5.41, while 441 (82.89%) alleles were shared commonly between B- and R- lines. The gene diversity and PIC were high among R- lines (0.55 and 0.50) than B- lines (0.49 and 0.44) revealed that R- lines were more diverse than B- lines. The unweighted neighbor-joining tree based on simple matching dissimilarity matrix obtained from SSR data clearly differentiated B- lines into 10 sub-clusters (B1, B2, B3, B4, B5, B6, B7, B8, B9 and B10), and Rlines into 11 sub-clusters (R1, R2, R3, R4, R5, R6, R7, R8, R9, R10 and R11). The parents, three checks and 99 hybrids generated by crossing between representative lines of each of the B- cluster with that of each of the R- cluster were evaluated in line ? tester design over three environments. Based on pooled mean performance, the cross combinations generated between clusters B1 and R3, B2 and R4, B3 and R5, B4 and undetermined cluster, B5 and 11R, B6 and R3, B8 and R4, B9 and R7 and B10 and R5 had shown higher grain yield per plant compared to their counterparts. Based on per se performance, high sca effects and standard heterosis over superior check, F1s generated from crosses between representatives of groups B3 and B10 with representative of group R5 resulted in best heterotic combinations for grain yield. These represent putative heterotic gene pools in pearl millet.publishersversionPeer reviewe

Inheritance study and stable sources of maydis leaf blight (Cochliobolus heterostrophus) resistance in tropical maize germplasm

Maydis leaf blight (MLB), a serious foliar fungal disease of maize, may cause up to 40% losses in yield. The present studies were undertaken to identify the stable sources of MLB resistance, its inheritance study, and testing of MLB resistance linked markers from diverse background in the Indian adapted tropical maize genotypes. A set of 112 inbred lines were screened under artificially created epiphytotics conditions at three hotspot locations. Analysis across multi-locations revealed significant effects of genotypes and environments, and non-significant effects due to genotypes × environment interaction on disease incidence. A total of 25 inbred lines with stable resistance were identified across multi-locations. Inheritance of resistance was studied in six F1s and two F2s of resistant and susceptible parents. The null hypothesis of segregation of resistance and susceptible for mono and digenic ratios in two F2 populations was rejected by Chi-square test. The non-significant differences among the reciprocal crosses depicted the complete control of nuclear genome for MLB resistance. Partial dominance in F1s and normal distribution pattern in F2s of resistant and susceptible parents suggested polygenic nature of MLB resistance. Correlation studies in F2 populations exhibited significant negative correlation between disease score and days to flowering. Five simple sequence repeats (SSRs) markers, found associated to MLB resistance in different studies were unable to differentiate amongst MLB resistance and susceptible parents in our study. This emphasizes the need of fine mapping for MLB resistance in Indian germplasm. The identified stable sources of resistance and information on inheritance study can be used further in strengthening of resistance breeding against MLB

Differential distribution of a SINE element in the Entamoeba histolytica and Entamoeba dispar genomes: Role of the LINE-encoded endonuclease

<p>Abstract</p> <p>Background</p> <p><it>Entamoeba histolytica </it>and <it>Entamoeba dispar </it>are closely related protistan parasites but while <it>E. histolytica </it>can be invasive, <it>E. dispar </it>is completely non pathogenic. Transposable elements constitute a significant portion of the genome in these species; there being three families of LINEs and SINEs. These elements can profoundly influence the expression of neighboring genes. Thus their genomic location can have important phenotypic consequences. A genome-wide comparison of the location of these elements in the <it>E. histolytica </it>and <it>E. dispar </it>genomes has not been carried out. It is also not known whether the retrotransposition machinery works similarly in both species. The present study was undertaken to address these issues.</p> <p>Results</p> <p>Here we extracted all genomic occurrences of full-length copies of EhSINE1 in the <it>E. histolytica </it>genome and matched them with the homologous regions in <it>E. dispar</it>, and vice versa, wherever it was possible to establish synteny. We found that only about 20% of syntenic sites were occupied by SINE1 in both species. We checked whether the different genomic location in the two species was due to differences in the activity of the LINE-encoded endonuclease which is required for nicking the target site. We found that the endonucleases of both species were essentially very similar, both in their kinetic properties and in their substrate sequence specificity. Hence the differential distribution of SINEs in these species is not likely to be influenced by the endonuclease. Further we found that the physical properties of the DNA sequences adjoining the insertion sites were similar in both species.</p> <p>Conclusions</p> <p>Our data shows that the basic retrotransposition machinery is conserved in these sibling species. SINEs may indeed have occupied all of the insertion sites in the genome of the common ancestor of <it>E. histolytica </it>and <it>E. dispar </it>but these may have been subsequently lost from some locations. Alternatively, SINE expansion took place after the divergence of the two species. The absence of SINE1 in 80% of syntenic loci could affect the phenotype of the two species, including their pathogenic properties, which needs to be explored.</p

Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments

Pearl millet [Pennisetum glaucum (L.) R. Br., syn. Cenchrus americanus (L.) Morrone], is a staple food for over 90 million poor farmers in arid and semi-arid regions of sub-Saharan Africa and South Asia. We report the ~1.79 Gb genome sequence of reference genotype Tift 23D2B1-P1-P5, which contains an estimated 38,579 genes. Resequencing analysis of 994 (963 inbreds of the highly cross-pollinated cultigen, and 31 wild accessions) provides insights into population structure, genetic diversity, evolution and domestication history. In addition we demonstrated the use of re-sequence data for establishing marker trait associations, genomic selection and prediction of hybrid performance and defining heterotic pools. The genome wide variations and abiotic stress proteome data are useful resources for pearl millet improvement through deploying modern breeding tools for accelerating genetic gains in pearl millet.publishersversionPeer reviewe

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14