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Advance prediction about bearing remaining useful life (RUL) is a major activity which aims at scheduling proper future actions to avoid catastrophic events. However, the reliability of bearing life prediction models is subject to processes, such as construction of a robust bearing degradation health index, monotonicity and trendability of health index, uncertainty in construction of a failure threshold etc. Therefore, to achieve reliable bearing RUL estimates, this study proposes a fundamental framework wherein several data driven models are trained adaptively corresponding to the different bearing health states. The core idea is to selectively identify effective bearings from the training set of bearings whose failure patterns match closely with the evolving failure pattern of a bearing under operation. In each bearing, the locations of all health state change points are identified and then the training bearings are clustered into groups having similar failure trajectories using a K-means approach and developed similarity index. The proposed approach utilizes only partial data from the test bearing for RUL prediction and eliminates the need to manually predefine a failure threshold limit. The prediction estimates are updated with every incoming data point acquired on the test bearing until failure. A cumulative function is proposed to make the trend of the adopted health indicator (HI) into being monotonic and trendable, which is then used as an input to the data driven model. A confidence value (CV) parameter is proposed to map the inputs of the data driven model, such the CV varies in a fixed range. Both simulated data and run-to-failure experimental data (IEEE PHM 2012 bearing data) have been used to demonstrate the effectiveness of the proposed method. The test results from the proposed methodology have been benchmarked with other approaches, further validating its generic character and robustness.

Barley spot blotch (SB) caused by Cochliobolus sativus is one of the major constrains to barley production in warmer regions worldwide. The study was undertaken to identify and estimate effects of loci underlying quantitative resistance to SB at the seedling and adult plant stages. A panel of 261 high input (HI-AM) barley genotypes consisting of released cultivars, advanced breeding lines, and landraces, was screened for resistance to SB. The seedling resistance screening was conducted using two virulent isolates from Morocco (ICSB3 and SB54) while the adult plant stage resistance was evaluated at two hot spot locations, Faizabad and Varanasi, in India under artificial inoculation using a mixture of prevalent virulent isolates. The HI-AM panel was genotyped using DArT-Seq high-throughput genotyping platform. Genome wide association mapping (GWAM) was conducted using 13,182 PAV and 6,311 SNP markers, for seedling and adult plant resistance. Both GLM and MLM model were employed in TASSEL (v 5.0) using principal component analysis and Kinship Matrix as covariates. Final disease rating and Area Under Disease Progress Curve (AUDPC) were used for the evaluation of adult stage plant resistance. The GWAM analysis indicated 23 QTL at the seedling stage (14 for isolate ICSB3 and 9 for isolate SB54), while 15 QTL were detected at the adult plant stage resistance (6 at Faizabad and 9 at Varanasi) and 5 for AUDPC based resistance at Varanasi. Common QTL at seedling and adult plant stages were found across all barley chromosomes. Seedling stage QTL explained together 73.24% of the variance for seedling resistance to isolate ICSB3 and 49.26% for isolate SB54, whereas, QTL for adult plant stage resistance explained together 38.32%, 44.09% and 26.42% of the variance at Faizabad and Varanasi and AUDPC at Varanasi, respectively. Several QTL identified in this study were also reported in previous studies using bi-parental and association mapping populations, corroborating our results. The promising QTL detected at both stages, once validated, can be used for marker assisted selection (MAS) in SB resistance barley breeding program.

Purpose The study aims to assess the journal packing density (JPD) of the research journals published across different subject discipline at the global level. The concept of JPD is aimed to compute the average number of research articles published per volume or per issue of a research journal in any given subject discipline. The study also discusses about the leading research journals publishing countries and continents across the world and their average JPD. An attempt has also been made to identify the leading research counties having maximum JPD in any given subject discipline. Design/methodology/approach The study covers 27 major research subject disciplines widely popular all across the globe. To undertake the present study, data were retrieved from SCImago Journal and Country Ranking. Findings In all, 36,081 research journals were indexed by Scopus across 27 major subject disciplines at the global level till 2015. During the period 2013-2015, 11,023,122 research articles were published in 36,081 research journals across 27 major subject disciplines at the global level at an average of 101.84 research articles per journal per volume. This means the average JPD of the research journals at the global level is 101.84 research articles per journal per volume. Chemistry, physics and astronomy and multidisciplinary journals are the three leading subject disciplines to have the maximum JPD, namely, 266.66, 253.92 and 242.53 research articles per journal per volume. JPD of research journals published in the sciences is higher than the JPD of research journals published in the social sciences and humanities. Business, management and accounting, social sciences and arts and humanities are three subject disciplines having lowest JPD, namely, 44.26, 35.68 and 32.66 research articles per journal per volume, respectively. China, Ireland and The Netherlands recorded the highest average JPD in the research journals published from these counties, namely, 213.39, 178.44 and 135.31 research articles per journal per volume, respectively. Research limitations/implications Countries from where a lesser number of research journals are indexed by the popular indexes, such as Scopus, Web of Science, etc., face greater pressure of publishing. To ooze out this pressure, there is need to index more and more research journals from these countries and that can be done only by improving and maintaining the research standard over a period. Originality/value The study is original and the first of its kind undertaken at the global level across all the major subject disciplines.