Haliastur indus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA771887 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR17688966_1.fastq.gz | Fastqsanger.gz | |||
| SRR17688966_2.fastq.gz | Fastqsanger.gz |
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Project description:The Complete mitochondrial genome of the Brahminy kite (Haliastur indus)
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Project description:The genetic ancestry of modern Indus Valley populations from Northwest India
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Project description:Although no historical information exists about the Indus civilization (flourished ca. 2600-1900 B.C.), archaeologists have uncovered about 3,800 short samples of a script that was used throughout the civilization. The script remains undeciphered, despite a large number of attempts and claimed decipherments over the past 80 years. Here, we propose the use of probabilistic models to analyze the structure of the Indus script. The goal is to reveal, through probabilistic analysis, syntactic patterns that could point the way to eventual decipherment. We illustrate the approach using a simple Markov chain model to capture sequential dependencies between signs in the Indus script. The trained model allows new sample texts to be generated, revealing recurring patterns of signs that could potentially form functional subunits of a possible underlying language. The model also provides a quantitative way of testing whether a particular string belongs to the putative language as captured by the Markov model. Application of this test to Indus seals found in Mesopotamia and other sites in West Asia reveals that the script may have been used to express different content in these regions. Finally, we show how missing, ambiguous, or unreadable signs on damaged objects can be filled in with most likely predictions from the model. Taken together, our results indicate that the Indus script exhibits rich synactic structure and the ability to represent diverse content. both of which are suggestive of a linguistic writing system rather than a nonlinguistic symbol system.
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Project description:We genotyped 45 new samples from 4 populations of Northwest India and combined it with previously published data to characterize the population structure of modern Northwest Indian populations in the context of their geographic neighbors across South Asia and West Eurasia.
2018-12-05 | GSE119653 | GEO
Project description:The discharge of one of the world's largest river - Indus River was reported to be increasing that was not supported by the Karakoram (KK) glacier expansion. A major hydrometric bias was ignored, which seemed similar to the montage that the Himalayan glaciers would disappear. This study proposed a framework for quantifying the bias resulting from inaccurate data affecting hydrologic studies on the Indus. We constructed a statistical model by converting the rating curves of rivers into air temperature (T) - discharge (Q) curves from an adjacent catchment in China where flow measurement was carried out using a standard method. We found that most flow data for the Indus were much greater than the error limits of T-Q curves estimated by daily data, a greater bias occurred in recent decades when discharge increased, the higher the flow was, the larger the bias was. The estimated mean annual and maximum monthly bias was 22.5% and 210%, respectively. These biases indicated that discharge increase in the Indus probably resulted from the large errors of hydrometrics without a scientific basis. We suggested a montage bias was needed in the hydrologic science of KK's rivers that may strongly affect water resource management.
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Project description:The Indus Valley has been the backdrop for several historic and prehistoric population movements between South Asia and West Eurasia. However, the genetic structure of present-day populations from Northwest India is poorly characterized. Here we report new genome-wide genotype data for 45 modern individuals from four Northwest Indian populations, including the Ror, whose long-term occupation of the region can be traced back to the early Vedic scriptures. Our results suggest that although the genetic architecture of most Northwest Indian populations fits well on the broader North-South Indian genetic cline, culturally distinct groups such as the Ror stand out by being genetically more akin to populations living west of India; such populations include prehistorical and early historical ancient individuals from the Swat Valley near the Indus Valley. We argue that this affinity is more likely a result of genetic continuity since the Bronze Age migrations from the Steppe Belt than a result of recent admixture. The observed patterns of genetic relationships both with modern and ancient West Eurasians suggest that the Ror can be used as a proxy for a population descended from the Ancestral North Indian (ANI) population. Collectively, our results show that the Indus Valley populations are characterized by considerable genetic heterogeneity that has persisted over thousands of years.
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Project description:Intensification of smog episodes, following harvesting of paddy crops in agricultural plains of the Indus basin in the Indian subcontinent, are often attributed to farming practice of burning standing stubble during late autumn (October, November) months. Biomass burning (paddy stubble residual) is a preferred technique to clear farmlands for centuries by farmers in that basin. However, despite stable agricultural landholding and yield, smog is being increasingly associated with burning agricultural biomass, thus creating a paradox. Here, we show that the concentration of smog (NOx, PM2.5, SO2) in the ambient air exceeds the safe threshold limits throughout the entire year in the region. This study argues that agricultural biomass burning is an ephemeral event in the basin that may act as a catalyst to a deteriorated air quality in the entire region. Results further demonstrate that simultaneous saturation of air pollutants along with high ambient moisture content and low wind speeds following the monsoon season are strongly related to aggravated smog events. Findings from this study should help make holistic mitigation and intervention policies to monitor air quality for sustainability of public health in agricultural regions where farming activities are a dominant economic driver for society.
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Project description:This paper presents novel insights into the archaeology of food in ancient South Asia by using lipid residue analysis to investigate what kinds of foodstuffs were used in ceramic vessels by populations of the Indus Civilisation in northwest India. It examines how vessels were used in urban and rural Indus settlements during the Mature Harappan period (c.2600/2500-1900 BC), the relationship between vessels and the products within them, and identifies whether changes in vessel use occurred from the Mature Harappan to Late Harappan periods, particularly during climatic instability after 4.2 ka BP (c.2100 BC). Despite low lipid concentrations, which highlight challenges with conducting residue analysis in arid, seasonally-wet and alkaline environments, 71% of the vessels yielded appreciable quantities of lipid. Lipid profiles revealed the use of animal fats in vessels, and contradictory to faunal evidence, a dominance of non-ruminant fats, with limited evidence of dairy processing. The absence of local modern reference fats makes this dataset challenging to interpret, and it is possible that plant products or mixtures of plant and animal products have led to ambiguous fatty acid-specific isotopic values. At the same time, it appears that urban and rural populations processed similar types of products in vessels, with limited evidence for change in vessel use from the urban to the post-urban period. This study is a systematic investigation into pot lipid residues from multiple sites, demonstrating the potential of the method for examining ancient Indus foodways and the need for the development of further research in ancient organic residues in South Asia.
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Project description:Our understanding of the full range of natural variability in streamflow, including how modern flow compares to the past, is poorly understood for the Upper Indus Basin (UIB) because of short instrumental gauge records. To help address this challenge, we use Hierarchical Bayesian Regression (HBR) with partial pooling to develop six centuries long (1394-2008 C.E.) streamflow reconstructions at three UIB gauges (Doyian, Gilgit, and Kachora), concurrently demonstrating that HBR can be used to reconstruct short records with interspersed missing data. At one gauge (Partab Bridge), with a longer instrumental record (47 years), we develop reconstructions using both Bayesian Regression (BR) and the more conventionally used Principal Components Regression (PCR). The reconstructions produced by PCR and BR at Partab Bridge are nearly identical and yield comparable reconstruction skill statistics, highlighting that the resulting tree-ring reconstruction of streamflow is not dependent on the choice of statistical method. Reconstructions at all four reconstructions indicate flow levels in the 1990s were higher than mean flow for the past six centuries. While streamflow appears most sensitive to accumulated winter (January-March) precipitation and summer (MJJAS) temperature, with warm summers contributing to high flow through increased melt of snow and glaciers, shifts in winter precipitation and summer temperatures cannot explain the anomalously high flow during the 1990s. Regardless, the sensitivity of streamflow to summer temperatures suggests that projected warming may increase streamflow in coming decades, though long-term water risk will additionally depend on changes in snowfall and glacial mass balance.
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