Sahaspur, India
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News Article | May 4, 2017
Site: worldmaritimenews.com

Danish container shipping giant Maersk Line sent a total of seven Panamax vessels to ship recycling yards during the first quarter of this year. Four of these boxships, between 19 and 21 years old, were sent to China. They are being recycled by Jiangyin Xiagang Changjiang Ship Recycling, a representative from Maersk told World Maritime News. Jiangyin Xiagang Changjiang is a Lloyd’s Register certified facility which has agreed to full compliance with the Maersk Responsible Ship Recycling Standard (RSRS), according to Maersk. The remaining three vessels, Sea Land Charger, Sea Land Eagle and Sea Land Racer, were sold to Alang, India, during 1Q 2017. They are being scrapped by Shree Ram and Y.S. Investments also in accordance with the company’s RSRS. “In Alang, we expect Georgia and Wyoming’s dismantlement to be completed by the end of 2Q. So all in all, five Maersk Line vessels are currently being scrapped in Alang,” Maersk representative added. The demolition of the abovementioned ships comes in anticipation of 26 newbuildings that will be delivered to the company until the end of 2018. The company’s order book consists of ten 2nd generation Triple-E, nine 15,226 TEU and seven 3,596 TEU boxships.


Kumar P.,REC | Srivastava V.B.,RSRS | Khare R.,REC | Singh P.K.,RSRS | Sahaf K.A.,CSR and TI
Indian Silk | Year: 2013

In sericulture, a number of practices are taken up which involve calculation of the components of chemical fertilizers, formulation of pesticides and disinfectants at different levels and the estimation of quantity of mulberry cuttings renditta requirement of mulberry leaf etc. A software developed by the scientists which can compute these accurately, in no time and will be of great help to the stake holders.


Kumar P.,REC | Chaturvedi M.L.,DOS | Khare R.,REC | Bhat M.M.,RSRS | Khan M.A.,CSR and TI
Indian Silk | Year: 2011

Low and unsteady returns from agricultural crops caused Shri Hanuman Yadav of Gonda district in Uttar Pradesh to take to sericulture. Backed with technical intervention from REC, Gonda and support from the DOS, his returns from seri-activities increased significantly in a short span of time. The authors narrate his success story.


Bhatia N.K.,RSRS
Indian Silk | Year: 2010

Basic Seed Multiplication and Training Centers (BSMTC) at the P2 level multiply the nucleus seed into basic seed for its supply to 107 Pilot Production Centers (PPC) for multiplication into commercial seed for commercial cocoon production by tasar growers. One would agree that the PPCs in the existing set-up of seed organization system have a major role to play. Adopted PPCs have shown improvement in their multiplication ratio, but it is still to become consistent for some or the other reason. Further, the Central Silk Board, under its Catalytic Development Program (CDP), has provided intended monetary assistance to most of the tasar producing states with an aim to improve host plantation maintenance, develop chawki garden, procure rearing equipments, crop insurance and infrastructural support to ensure better seed multiplication efficiency at PPCs.


Singhal B.K.,RSRS | Khan M.A.,RSRS | Khan M.A.,Central Sericultural Research and Training Institute | Bindroo B.B.,RSRS
Indian Silk | Year: 2011

Mulberry, the sole feed for Bombyx mori, is also known for its medicinal values. Presented here is an update on its potential as an effective medicine for diabetes.


B.B. Bindroo focuses on muga cultural operations along with the schedule for different crops to ensure availability of adequate foliage for conducting rearing of increased number of dils and increased productivity. The muga plants grow luxuriantly after monsoon and during cool dry season. The plants tend to become dormant with slow growth and flushes slowly with the rise in temperature in spring. Muga silkworm is multi-voltine and 6 crops are raised in a year, of which two are commercial crops, namely Jethua in the April-May and Kotia in October-November, two seed crops, namely Chotua in February-March and Bhodia, namely August-September and the remaining pie-seed crops, namely Jarua and Aherua. The plantation under Seed crop zone would be sufficient for conducting Chotua seed crop during February-March and the same plantation after bottom pruning in April-May could be utilized for Bhodia seed crop during August-September.


Pandey R.K.,RSRS | Bindroo B.B.,RSRS | Dhar A.,RSRS | Khan M.A.,Central Sericultural Research and Training Institute
Indian Silk | Year: 2010

Research Extension Center (REC), Barnoti initiated a project to improve cocoon yield by transfer of certain new sericultural technologies in the Kandi area including introduction of new silkworm hybrids. REC, Barnoti, developed a chawki garden of early sprouting mulberry variety, S146 and conducted incubation and rearing of first and second instars at the Chawki Rearing Center by following recommended scientific methods. The new bivoltine silkworm hybrids along with conventional SH6 × NB4D2 were distributed after chawki rearing by the REC. The farmers were advised to maintain proper spacing, and feed appropriate quality and quantity of leaf during each instar. The improved mulberry varieties S146 and TR10 introduced in the Kandi belt showed 59.06 and 64.7% survival, respectively but there is also a need of drought resistant mulberry variety, which can survive moisture stress and nutritional inadequacy of the Kandi soil.


Pandey R.K.,RSRS | Bindroo B.B.,RSRS | Dhar A.,RSRS | Khan M.A.,RSRS
Indian Silk | Year: 2010

Three common oak species of sub-Himalayan region were examined for the influence of seed coat on germination, effect of nitrogen fixing bacteria on seedling growth and their growth at different locations in western Himalayan region. Seeds were soaked after removal of floating weeviled seeds for 48 hours with the moisture content of 53% of dry weight. Three combinations of rooting media were prepared; local clay soil, soil and sand in 3:1 ratio and soil and sand in 3:1 ratio inoculated with Azotobacter. The oak species Q. semecarpifolia, a late successional species is the greatest forest-forming species above 2400 AMSL in the Himalayan region. Fruit maturation was complete by late September of the second year. Seeds collected from Manipur for this study showed profuse germination and good seedling growth in different areas of Himachal Pradesh. Fruit maturation was complete by late September of the second year.


Srinivasulu Reddy P.,RSRS | Mogili T.,REC | Raju Ch.S.,RSRS
Indian Silk | Year: 2010

The concept of private chawki rearing center (CRC) is gaining popularity among farmers in Andhra Pradesh, India, as they are finding it convenient to rear the chawki silkworms in place of seeds. Central Silk Board has considered these factors and proposed to establish community CRCs under Institute Village Linkage Program (IVLP) in the state. These centers involve brushing of the silkworm eggs at one point under controlled conditions and distributing the worms, during second moult to the farmers. Research Extension Center, Venkatagiri Kota, has surveyed the area and motivated the farmers by explaining the benefits of taking the chawki worms. It has motivated one of the farmers of the area to set up a CRC to rear chawki silkworms and realize the associated benefits from them. Department of Sericulture (DOS), Kuppam and Central Silk Board, have supported the efforts by providing finance and rearing material.


News Article | August 24, 2016
Site: www.nature.com

No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. In a dedicated ancient DNA laboratory at University College Dublin, we prepared powder from 132 ancient Near Eastern samples, either by dissecting the inner ear region of the petrous bone using a sandblaster (Renfert), or by drilling using a Dremel tool and single-use drill bits and selecting the best preserved bone fragments based on anatomical criteria. These fragments were then powdered using a mixer mill (Retsch Mixer Mill 400)4. We performed all subsequent processing steps in a dedicated ancient DNA laboratory at Harvard Medical School, where we extracted DNA from the powder (usually 75 mg, range 14–81 mg) using an optimized ancient DNA extraction protocol36, but replaced the assembly of Qiagen MinElute columns and extension reservoirs from Zymo Research with a High Pure Extender Assembly from the High Pure Viral Nucleic Acid Large Volume Kit (Roche Applied Science). We built a total of 170 barcoded double-stranded Illumina sequencing libraries for these samples37, of which we treated 167 with uracil-DNA glycosylase (UDG) to remove the characteristic C-to-T errors of ancient DNA38. The UDG treatment strategy is (by–design) inefficient at removing terminal uracils, allowing the mismatch rate to the human genome at the terminal nucleotide to be used for authentication37. We updated this library preparation protocol in two ways compared to the original publication: first, we used 16U Bst2.0 Polymerase, Large Fragment (NEB) and 1× Isothermal amplification buffer (NEB) in a final volume of 25 μl fill-in reaction, and second, we used the entire inactivated 25 μl fill-in reaction in a total volume of 100 μl PCR mix with 1 μM of each primer39. We included extraction negative controls (where no sample powder was used) and library negative controls (where extract was supplemented by water) in every batch of samples processed and carried them through the entire wet laboratory processing to test for reagent contamination. We screened the libraries by hybridizing them in solution to a set of oligonucleotide probes tiling the mitochondrial genome40, using the protocol described previously7. We sequenced the enriched libraries using an Illumina NextSeq 500 instrument using 2× 76 bp reads, trimmed identifying sequences (seven base pair molecular barcodes at either end) and any trailing adapters, merged read pairs that overlapped by at least 15 base pairs, and mapped the merged sequences to the RSRS mitochondrial DNA reference genome41, using the Burrows Wheeler Aligner42 (bwa) and the command samse (v0.6.1). We enriched promising libraries for a targeted set of ~1.2 million SNPs8 as in ref. 5, and adjusted the blocking oligonucleotide and primers to be appropriate for our libraries. The specific probe sequences are given in supplementary data 2 of ref. 7. and supplementary data 1 of ref. 6. We sequenced the libraries on an Illumina NextSeq 500 using 2× 76 bp reads. We trimmed identifying sequences (molecular barcodes) and any trailing adapters, merged pairs that overlapped by at least 15 base pairs (allowing up to one mismatch), and mapped the merged sequences to hg19 using the single-ended aligner samse in bwa (v0.6.1). We removed duplicated sequences by identifying sets of sequences with the same orientation and start and end positions after alignment to hg19; we picked the highest quality sequence to represent each set. For each sample, we represented each SNP position by a randomly chosen sequence, restricting to sequences with a minimum mapping quality (MAPQ ≥ 10), sites with a minimum sequencing quality (≥20), and removing two bases at the ends of reads. We sequenced the enriched products up to the point that we estimated that generating a hundred new sequences was expected to add data on less than about one new SNP8. For each ancient DNA library, we evaluated authenticity in several ways. First, we estimated the rate of matching to the consensus sequence for mitochondrial genomes sequenced to a coverage of at least tenfold from the initial screening data. Of the 76 libraries that contributed to our dataset (coming from 45 samples), 70 had an estimated rate of sequencing matching to the consensus of >95% according to contamMix5 (the remaining libraries had estimated match rates of 75–92%, but gave no sign of being outliers in principal component analysis or X-chromosome contamination analysis so we retained them for analysis) (Supplementary Table 1). We quantified the rate of C-to-T substitution in the final nucleotide of the sequences analysed, relative to the human reference genome sequence, and found that all the libraries analysed had rates of at least 3% (ref. 37), consistent with genuine ancient DNA. For the nuclear data from males, we used the ANGSD software43 to obtain a conservative X-chromosome estimate of contamination. We determined that all libraries that passed our quality control and for which we had sufficient X-chromosome data to make an assessment, had contamination rates of 0–1.5%. Finally, we merged data for samples for which we had multiple libraries to produce an analysis dataset. We genotyped 238 present-day individuals from 17 diverse West Eurasian populations on the Affymetrix Human Origins array16, and applied quality control analyses as previously described13 (Supplementary Table 2). We merged the newly generated data with data from 2,345 individuals previously genotyped on the same array13. All individuals that were genotyped provided individual informed consent consistent with studies of population history, following protocols approved by the ethical review committees of the institutions of the researchers who collected the samples. The collection and analysis of genome-wide data on anonymized samples at Harvard Medical School for the purpose of studying population history was approved by the Harvard Human Research Protection Program, protocol 11681, re-reviewed on 12 July 2016. Anonymized aliquots of DNA from all individuals were sent to the core facility of the Center for Applied Genomics at the Children’s Hospital of Philadelphia for genotyping and data processing. For 127 of the individuals with newly reported data, the informed consent was consistent with public distribution of data, and the data can be downloaded at http://genetics.med.harvard.edu/reich/Reich_Lab/Datasets.html. To access data for the remaining 111 newly reported samples, researchers should send a signed letter to D.R. containing the following text: “(a) I will not distribute the data outside my collaboration; (b) I will not post the data publicly; (c) I will make no attempt to connect the genetic data to personal identifiers for the samples; (d) I will use the data only for studies of population history; (e) I will not use the data for any selection studies; (f) I will not use the data for medical or disease-related analyses; (g) I will not use the data for commercial purposes.” Supplementary Table 2 specifies which samples are consistent with which type of data distribution. We carried out population genetic analysis on two datasets: (i) HO includes 2,583 present-day humans genotyped on the Human Origins array13, 16 including 238 newly reported, (Supplementary Table 2; Supplementary Information, section 2), and 281 ancient individuals on a total of 592,146 autosomal SNPs. (ii) HOIll includes the 281 ancient individuals on a total of 1,055,186 autosomal SNPs, including those present in both the Human Origins and Illumina genotyping platforms, but excluding SNPs on the sex chromosomes or additional SNPs of the 1,240k capture array that were included because of their potential functional importance8. We used HO for analyses that involve both ancient and present-day individuals, and HOIll for analysis on ancient individuals alone. We also used 235 individuals from Pagani et al.30 genotyped at 418,700 autosomal SNPs to study admixture in East Africans (Supplementary Information, section 8). Ancient individuals are represented in ‘pseudo-haploid’ form by randomly choosing one allele for each position of the array. We carried out principal components analysis in the smartpca program of EIGENSOFT17, using default parameters and the lsqproject: YES13 and numoutlieriter: 0 options. We carried out PCA on the HO dataset for 991 present-day West Eurasians (Extended Data Fig. 1), and projected the 278 ancient individuals (Fig. 1b). We carried out ADMIXTURE analysis18 of the HO dataset after pruning for linkage disequilibrium in PLINK44, 45 with parameters indep-pairwise 200 25 0.4, which retained 296,309 SNPs. We performed analysis in 20 replicates with different random seeds, and retained the highest likelihood replicate for each value of K. We show the K = 11 results for the 281 ancient samples in Extended Data Fig. 2a (this is the lowest K for which components maximized in European hunter–gatherers, ancient Levant, and ancient Iran appear). We carried out analysis of f -statistics, f -ratio, and f -statistics statistics using the ADMIXTOOLS16 programs qp3Pop, qpF4ratio with default parameters, and qpDstat with f4mode: YES, and computed standard errors with a block jack-knife46. For computing f -statistics with an ancient population as a target, we set the inbreed: YES parameter. We computed f-statistics on the HOIll dataset when no present-day humans were involved and on the HO dataset when they were. We computed the statistic f (Test, Mbuti; Altai, Denisovan) in Fig. 2 on the HOIll dataset after merging with whole genome data on 3 Mbuti individuals from Panel C of the Simons Genome Diversity Project47. We computed the dendrogram of Extended Data Fig. 3 showing hierarchical clustering of populations with outgroup f -statistics using the open source heatmap.2 function of the gplots package in R. We used the lm function of R to fit a linear regression of the rate of allele sharing of a Test population with the Altai Neanderthal as measured by f (Test, Mbuti; Altai, Denisovan) as the dependent variable, and the proportion of Basal Eurasian ancestry (Supplementary Information, section 4) as the predictor variable. Extrapolating from the fitted line, we obtain the value of the statistic expected if Test is a population of 0% or 100% Basal Eurasian ancestry. We then compute the ratio of the Neanderthal ancestry estimate in Basal Eurasians relative to non-Basal Eurasians as f (100% Basal Eurasian, Mbuti; Altai, Denisovan)/ f (0% Basal Eurasian, Mbuti; Altai, Denisovan). We use a block jack-knife46, dropping one of 100 contiguous blocks of the genome at a time, to estimate the value and standard error of this quantity (9 ± 26%). We compute a 95% confidence interval based on the point estimate ± 1.96-times the standard error: −42 to 60%. We truncated to 0–60% on the assumption that Basal Eurasians had no less Neanderthal admixture than Mbuti from sub-Saharan Africa. We estimated F in smartpca17 with default parameters, inbreed: YES, and fstonly: YES. We carried out Admixture Graph modelling with the qpGraph software16 using Mbuti as an outgroup unless otherwise specified. We used the qpWave33, 48 software, described in Supplementary Information, section 10 of ref. 7, to test whether a set of ‘Left’ populations is consistent with being related via as few as N streams of ancestry to a set of ‘Right’ populations by studying statistics of the form X(u, v) = F (u , u; v , v) where u , v are basis populations chosen from the ‘Left’ and ‘Right’ sets and u, v are other populations from these sets. We use a Hotelling’s T2 test48 to evaluate whether the matrix of size (L−1)*(R−1), where L, R are the sizes of the ‘Left’ and ‘Right’ sets has rank m. If this is the case, we can conclude that the ‘Left’ set is related via at least N = m+1 streams of ancestry differently to the ‘Right’ set. We use the parameter allsnps: YES which computes each f -statistic based on the full set of SNPs with coverage among the four populations used in the statistic (without regard to whether the SNPs are covered in the other populations in the ‘Left’ and ‘Right’ sets). We used the qpAdm methodology described in Supplementary Information, section 10 of ref. 7 to estimate the proportions of ancestry in a Test population deriving from a mixture of N ‘reference’ populations by exploiting (but not explicitly modelling) shared genetic drift with a set of ‘Outgroup’ populations (Supplementary Information, section 7). We set the details: YES parameter, which reports a normally distributed Z-score estimated with a block jack-knife for the difference between the statistics f (u , Test; v , v) and f (u , Estimated Test; v , v) where Estimated Test is , the average of these f -statistics weighed by the mixture proportions α from the N reference populations. We use the allsnps: YES parameter. We model admixture from a ‘ghost’ (unobserved) population X in the specific case that X has part of its ancestry from two unobserved ancestral populations p and q. Any population X composed of the same populations p and q resides on a line defined by two observed reference populations r and r composed of the same elements p and q according to a parametric equation with real-valued parameter λ. We define and solve the optimization problem of fitting λ and obtain mixture proportions (Supplementary Information, section 10). Code implementing the newly developed method for modelling admixture from ghost populations is available on request from I.L.

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