Experimental Analysis of Friction Stir Welding of Dissimilar Aluminium Alloys by Machine Learning

This research focusses on joining of dissimilar materials on AA5083 and AA6082 using friction stir welding process. Tool rotation speed, welding speed and tool tilt angle are optimized using L27 Orthogonal design of experiments with tensile strength as the response. To evaluate potential of sophisticated machine learning methodologies, random forest regressor and artificial neural network algorithms are utilized for predicting the joint strength of friction stir welded dissimilar plates of AA5083 and AA6082. These models are used to investigate discrepancies between experimental and predicted results. Of the available results, 21 readings are chosen for training the model while remaining are used for testing the model. Random forest regressor and artificial neural network techniques were formed using the data associated with the experiment. Moreover, results of the analysis of variances are compared to the machine learning predicted results to determine the variances

Multiple Genome Wide Association Mapping Models Identify Quantitative Trait Nucleotides for Brown Planthopper (Nilaparvata lugens) Resistance in MAGIC Indica Population of Rice

Brown planthopper (BPH), one of the most important pests of the rice (Oryza sativa) crop, becomes catastrophic under severe infestations and causes up to 60% yield loss. The highly disastrous BPH biotype in the Indian sub-continent is Biotype 4, which also known as the South Asian Biotype. Though many resistance genes were mapped until now, the utility of the resistance genes in the breeding programs is limited due to the breakdown of resistance and emergence of new biotypes. Hence, to identify the resistance genes for this economically important pest, we have used a multi-parent advanced generation intercross (MAGIC) panel consisting of 391 lines developed from eight indica founder parents. The panel was phenotyped at the controlled conditions for two consecutive years. A set of 27,041 cured polymorphic single nucleotide polymorphism (SNPs) and across-year phenotypic data were used for the identification of marker–trait associations. Genome-wide association analysis was performed to find out consistent associations by employing four single and two multi-locus models. Sixty-one SNPs were consistently detected by all six models. A set of 190 significant marker-associations identified by fixed and random model circulating probability unification (FarmCPU) were considered for searching resistance candidate genes. The highest number of annotated genes were found in chromosome 6 followed by 5 and 1. Ninety-two annotated genes identified across chromosomes of which 13 genes are associated BPH resistance including NB-ARC (nucleotide binding in APAF-1, R gene products, and CED-4) domain-containing protein, NHL repeat-containing protein, LRR containing protein, and WRKY70. The significant SNPs and resistant lines identified from our study could be used for an accelerated breeding program to develop new BPH resistant cultivars

Alcohol use and burden for 195 countries and territories, 1990-2016 : a systematic analysis for the Global Burden of Disease Study 2016

Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.Peer reviewe

Allocation of optimal energy from storage systems using solar energy

In order to reduce carbon emissions, a growing reliance on renewable energy sources such as solar energy is required. As a result of their ability to store excess solar electricity that may be used at a later time to reduce waste and increase utility profits, battery energy storage systems (BESSs) have emerged as a factor for power systems that integrates solar power system. BESSs are traditionally put on buses in solar farms, allowing extra electricity via solar to be stored instantaneously and transmission line losses to be kept to an absolute minimum. According to this placement strategy, BESS is exclusively built in the proximity of solar power plants. In this way, deployment of BESS without network topology consideration, and collaboration among BESSs is limited with capacity pooling to store excess electricity from photo voltaic (PV) panels. In this paper, we develop an optimal deployment of BESSs and it is associated with the estimation of the capacity using a multi-objective constraint modelling. The soft margin classifier minimize the curtailment associated with solar energy that considers both the power flow constraint and network topology. The results of entire model shows that the proposed soft margin classifier is efficient in storing the surplus power in the batter devices than other methods

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Not AvailableBacterial blight (BB) and fungal blast diseases are the major biotic constraints that limit rice productivity. To sustain yield improvement in rice, it is necessary to developed yield potential of the rice varieties by incorporation of biotic stress resistance genes. Tellahamsa is a well-adapted popular high yielding rice variety in Telangana state, India. However, the variety is highly susceptible to BB and blast. In this study, simultaneous stepwise transfer of genes through marker-assisted backcross breeding (MABB) strategy was used to introgress two major BB (Xa21 and xa13) and two major blast resistance genes (Pi54 and Pi1) into Tellahamsa. In each generation (from F1 to ICF3) foreground selection was done using gene-specific markers viz., pTA248 (Xa21), xa13prom (xa13), Pi54MAS (Pi54) and RM224 (Pi1). Two independent BC2F1 lines of Tellahamsa/ISM (Cross-I) and Tellahamsa/NLR145 (Cross-II) possessing 92% and 94% recurrent parent genome (RPG) respectively were intercrossed to develop ICF1—ICF3 generations. These gene pyramided lines were evaluated for key agro-morphological traits, quality, and resistance against blast at three different hotspot locations as well as BB at two locations. Two ICF3 gene pyramided lines viz., TH-625-159 and TH-625-491 possessing four genes exhibited a high level of resistance to BB and blast. In the future, these improved Tellahamsa lines could be developed as mega varieties for different agro-climatic zones and also as potential donors for different pre-breeding rice research.Department of Biotechnology, Government of India grant # BT/ PR11705/AGR/02/646/200