Dry sliding wear studies of aluminum matrix hybrid composites

In the present work, hybrid composites are fabricated with self-lubricating characteristics to make them as resource-efficient materials. AA6061-10 wt. % B4C-MoS2 hybrid composites reinforced with 2.5, 5 and 7.5 wt. % concentration of MoS2 particles are produced using stir casting technique, and mechanical and tribological properties are evaluated. Microstructural characterization of the hybrid composites revealed the uniform distribution of reinforcement (B4C and MoS2) particles in the matrix material. Hardness and fracture toughness of the hybrid composites are decreased monotonously with an increase in the addition of MoS2 particles. Dry sliding tribological studies conducted using a pin-on-disk tribotester under atmospheric conditions revealed the formation of MoS2-lubricated tribolayer on the worn pin surface which significantly influenced the tribological properties. The addition of MoS2 particles decreased the friction coefficient and wear rate of the hybrid composites. Delamination and abrasion are observed to be the controlling wear mechanisms and material in the form of platelet-shaped debris, and flow-type chip debris is formed, and a long and shallow crater on the worn pin surface of the hybrid composite is also observed

Molecular characterization and assessment of genetic diversity of sorghum inbred lines

Selecting parents of diverse genetic base with contrasting phenotype is an important step in developing mapping populations for quantitative trait loci (QTL) detection and marker-assisted selection. We studied genetic diversity in 31 sorghum parents using 413 sorghum simple sequence repeats (SSR) markers. The polymorphism information content (PIC), a measure of gene diversity, varied from 0 to 0.92 with an average of 0.53 and was significantly correlated with number of alleles. The primers IS10215, IS10270 and IS10333 could differentiate all the 31 lines conclusively. Clustering analysis based on the genetic dissimilarity grouped the 31 parents into eight clusters and grouping was in good agreement with pedigree, race and geographic origin. Diverse pairs of sorghum parents were identified with contrast phenotype for various biotic and abiotic stresses with higher genetic diversity for developing recombinant inbred line (RIL) mapping populations to identify QTLs/genes for important traits in sorghum. One of the mapping populations resulted in the identification of QTLs for resistance to sorghum shoot fly and these QTL results were validated in a second mapping population.Key words: Simple sequence repeats (SSR) markers, genetic diversity, sorghum, mapping parents

Assessing the genetic diversity of Indian Kharif sorghum landraces through agro-morphological characterization (Sorghum bicolor L. Moench)

The agro-morphological characterization of local germplasm provides insight into existing diversity, enables the identification of desirable traits, and enhances crop improvement. The present study evaluated 96 kharif sorghum (Sorghum bicolor L. Moench) landraces and 6 checks using 20 agro-morphological traits at two locations, ICAR-IIMR in Hyderabad and Experimental Farm at Annamalai University in Annamalai Nagar, using alpha lattice design with 2 replications during 2021 kharif to assess genetic diversity. Results showed significant genetic variability among the 20 traits (P<0.01), providing opportunities for improvement. The high genotypic (GCV) and phenotypic components of variance (PCV) exhibited among the traits indicated their genetic determination and potential for improvement through breeding programs. High heritability and genetic advance also indicated the presence of additive genes, offering reliable improvement through trait selection. The correlation analysis showed a strong positive relationship between grain yield and several desirable traits, including panicle length, width, primary branch length, hundred seed weight, number of leaves, and total tillers per plant, indicating that grain yield can be improved by selecting accessions with desirable characteristics for these traits. The Cluster analysis using Euclidean distance revealed (four distinct clusters), with Cluster I being the most differentiated. These clusters may serve as valuable resources for hybridization programs. The PCA analysis indicated that the first three PCs accounted for 43.26% of the total variation and highlighted the key agro-morphological traits driving diversity. The results of this study demonstrated the significant genetic diversity among kharif sorghum landraces, providing a promising opportunity for varietal development programs.

Grey Relational Analysis and Anova to Determine the Optimum Process Parameters for Friction Stir Welding of Ti and Mg Alloys

The welding of Magnesium and Titanium and its alloys has continuously depicted a good challenge for designers and technologists. Ti and Mg alloys, particularly heat-treatable alloys, are difficult to join by fusion fastening techniques. The welding of dissimilar alloy such as Ti (Grade 2) and Mg (AZ91D) Alloy is an important problem during Friction Stir Welding (FSW). In this paper, the influence of Rotation speed (Rpm), Travel Speed (mm/min), Bottom Diameter Tool Pins (mm) and Tool Profiles of Ti and Mg alloy during FSW was investigated by Grey Relational Analysis and Anova was used to work out the foremost important Travel speed and feed rate affecting the Response. The primary and cooperation impact of the information factors on the normal reactions are examined. The expected values and measured values are genuinely close

Multifunctional ZnO nanorod-reduced graphene oxide hybrids nanocomposites for effective water remediation: Effective sunlight driven degradation of organic dyes and rapid heavy metal adsorption

We demonstrate the multi-functionality engineering on nanocomposite by combining one dimensional (1D) ZnO nanorod (NR) and two dimensional (2D) reduced graphene oxide (rGO) for efficient water remediation. Nano-engineered ZnO NR-rGO nanocomposites show efficient water remediation in terms of degradation of organic dyes and removal of heavy metal ions. Herein, we report on the fabrication of ZnO NR-rGO nanocomposite via a facile template-free hydrothermal route with an aim to improve the visible photocatalytic efficiency of the ZnO NR based nanocomposites. The structural and morphological features reveal that the rGO sheets are attached on the ZnO NRs and form a hybrid composite assembly. The surface enabled ZnO NR-rGO nanocomposites were used to degrade organic dye molecules (methylene blue (MB), methyl orange (MO) and rhodamine B (RhB)) under visible irradiation and adsorb Cu (II) and Co (II) ions from water through an adsorption process. The nanocomposite containing 7.5 wt% rGO and ZnO NRs shows a 4-fold enhancement in the visible photocatalytic activity and effective removal of Cu (II) and Co (II) ions from aqueous solution respectively. The photocatalytic performance is discussed in detail with respect to interaction between ZnO NRs and rGO sheets, light-harvesting properties of the nanocomposites. The effective experimental adsorption data also fit very well with the pseudo-second-order model which reveals the surface adsorption of metal ions. The results provide insight into a new method utilize for both visible photo degradation and adsorption for the removal of various wastewater pollutants. Construction of hybrid form of nanostructures delivers the effective catalytic properties with tunable functionalities for the water remediation. © 2017 Elsevier B.V

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

Background Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil–lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population. Methods The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR. Results We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28–2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70–2.94). Both age and HbA1c were found to modulate the association between NLR and the risk of DR. Conclusions The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

Background: Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil–lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population.Methods: The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR.Results: We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28–2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70–2.94). Both age and HbA 1c were found to modulate the association between NLR and the risk of DR.Conclusions: The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status.</p

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Not AvailableHybrids are commercially successful in many crops, including sorghum. Development of hybrids through the exploitation of heterosis involves evaluation of hundreds of test crosses in the field, making it input and resource intensive. Therefore, plant breeders are interested in methods that can forecast the potential parental combinations so that only limited test crosses can be evaluated for heterosis. The availability of genomic tools such as DNA markers and gene expression platforms has encouraged research groups globally to work toward the prediction of heterosis. Once DNA markers for the prediction of heterosis are identified, potential parental combinations can be predicted by DNA marker-based analysis, thereby increasing the speed of hybrid development without large-scale field evaluation. Whole transcriptome and metabolome analyses will help in dissecting the genes or metabolic networks involved in heterosis. Advanced genomic tools along with mathematical modeling offer excellent opportunities for the development of simple and reliable methods for the prediction of heterosis. This chapter critically discusses the different methods of heterosis prediction, recent trends, factors affecting heterosis prediction and the impact of prediction in the development of hybrids.Not Availabl

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Not AvailableAnalysis of synteny is an integral part of comparative genomics inasmuch as it helps us to understand the structures and functions of genes in the related genomes in relation to genome evolution and their roles in gene expression. The identification of synteny blocks, the basic unit of genome synteny, may provide insights into the gene structure and regulation that are essential for biological processes. During earlier days, synteny blocks were identified through ad hoc methods that were slow, lacked reproducibility, ignored the conservation of gene order and orientation, and were not suitable for general applications. However, during the last decade, concerted efforts by several researchers have led to the development of a large volume of genomic data as well as computational resources that allow comparative genomic analysis between genomes of interest with high resolution. Comparative analysis of map-based genomic sequences led to the identification of shared intragenomic duplications, which provide important clues on the evolution of crop genomes from common ancestors. Recent studies in synteny analysis involve transcriptomic synteny to understand the functional conservation of orthologous genes and paleogenomic synteny to understand the role of whole-genome duplications on genome evolution. This chapter discusses the role of synteny analysis in comparative genomics; various computational tools employed for synteny analysis; synteny of sorghum with allied and model genomes with reference to molecular maps, markers, and the whole genome; emerging trends in synteny analysis; and future prospects.Not Availabl

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Not AvailableAvailability of molecular markers is essential for various genetic and breeding applications such as assessment of genetic diversity, construction of linkage map, genetic purity testing, QTL mapping, and marker-assisted selection. Prior to in silico approaches, DNA markers were developed through experimental approaches, which were skill oriented, time consuming, and expensive. Moreover, it resulted in the development of few hundred markers involving a substantial amount of time. The advent of nextgeneration sequencing technologies has led to the sequencing of whole nuclear as well as organellar genomes and the transcriptome projects have resulted in the accumulation of huge amounts of expressed sequence tags (ESTs) and/or cDNA sequences. Such an ocean of DNA sequence information, including genome survey sequences (GSS), expressed sequence tags (ESTs), full-length cDNAs, and complete nuclear and organellar genome sequences, serves as a vital resource for the identifi cation of target motifs such as simple sequence repeats (SSRs), insertionsdeletions (In-Dels), and single-nucleotide polymorphisms (SNPs) through in silico approaches leading to the rapid development of DNA-based markers, which otherwise would be time consuming through conventional experimental approaches. This review discusses the development of DNA markers such as SSR, SNP, In-Del, and intron length polymorphisms using various bioinformatic tools.Not Availabl