dataesr/scientific-paragraphs-categorization huggingface dataset:
RESULTS AND DISCUSSION VaRank was successfully applied in various human genetics studies both in diagnostics and research. In total, more than 800 patients from several datasets of increasing complexity including the Cockayne syndrome (10 genes tested, manuscript in preparation), Bardet-Biedl syndrome (30 genes  (Redin et al. , 2012) ), ataxias (60 genes), leucodystrophies (70 genes, manuscript in preparation), congenital myopathies (142 genes  (Vasli et al. , 2012)  and 275 genes, manuscript in preparation), intellectual disability (217 genes,  Redin et al. , 2014)  and exome sequencing  (Scheidecker et al. , 2014)  have been analyzed to highlight potential pathogenic variants. In the following sections, we will provide insight into several datasets analyzed by VaRank and that were used to validate the tool and to highlight its effectiveness.
Bardet-Biedl syndrome (BBS) dataset The Bardet-Biedl syndrome (BBS; OMIM# 209900) is a pleiotropic recessive disorder, part of the ciliopathies, characterized by extensive genetic heterogeneity counting to date 19 genes  (Aldahmesh et al. , 2014; Scheidecker et al. , 2014). We applied targeted highthroughput sequencing for 30 ciliopathy related genes to 52 patients with clinical features compatible with BBS  (Redin et al. , 2012). VaRank was used to annotate and rank the variants identified in those patients. Thirty-two cases could be solved by this approach leading to frameshift, missense and splice site mutations all validated by Sanger sequencing (we excluded Copy Number Variations). Sequencing data from the 32 positive samples have been reanalyzed using Alamut Batch version 1. 1. 11 and PolyPhen-2 v2.
Intellectual disability (ID) dataset Intellectual disability is a common neurodevelopmental disorder (∼2% of children and adolescents)  (Ellison, Rosenfeld & Shaffer, 2013)  that can be initiated by either environmental, genetic or multifactorial causes. The monogenic forms are very heterogeneous genetically, with several hundred genes identified so far. We present here the results of 203 patients affected with moderate to severe intellectual disability. A first cohort of 107 patients was already analyzed by VaRank  (Redin et al. , 2014)  and led to the identification of 25 causal mutations (Table  4A ). A second cohort of 96 additional patients is reported here for which 12 causative mutations could be identified (Table  4B ). The identified mutations were all validated by Sanger sequencing (we excluded pathogenic CNV).
High-throughput sequencing data of protein-coding exons of 217 genes (first cohort) and 275 genes (second cohort) (either on the X-chromosome or associated to autosomal dominant or recessive forms of ID) were collected for the 25 positive known Table  3  Analysis of 32 patients with Bardet-Biedl syndrome. From the BBS dataset, mutations and ranking for 32 patients sequenced for 30 genes. The ranking for each mutation has been obtained from the "filteredVariants" output. Mutations in italics are predicted to affect splicing. Notes.
Patient a The second mutation of the patient, a complete heterozygous deletion of exon 8 and 9 (c. (592-?) (830+?)del) is a pathogenic CNV that cannot be ranked by VaRank. b Parent of BBS patients, a single heterozygous mutations is expected. c This validated mutation was filtered out in the "filteredVariants" results due to low sequencing quality (only 7 reads supported the variant) but ranked at the second position in the non-filtered results. patients and the 96 additional ones. A total of 8,388 non redundant variants have been reannotated by VaRank using Alamut Batch version 1. 1. 11 and PolyPhen-2 v2. 2. 2, resulting on average into 1,129 (±189) private variants per sample. Each sample has been reanalyzed and a summary of the ranking results using the default filtration strategy for this dataset defined by the biologists (frequency in dbSNP or EVS >1% and presence in <3 samples) is available in Table  4.
Whole Exome Sequencing (WES) dataset WES of a single patient with a clear BBS phenotype from a consanguineous Italian family  (Scheidecker et al. , 2014)  revealed for the first time mutations in the BBIP1 gene counting since as the 18th BBS gene. A total of 50,569 non redundant variants have been annotated by VaRank using Alamut Batch version 1. 1. 11 and PolyPhen-2 v2. 2. 2. The nonsense mutation c. 173T>G (p. Leu58*) in BBIP1 has been ranked at the 50th position/50569 in the "allVariants. rankingByVar" file. Applying the default filtration strategy (i. e. , frequency in dbSNP or EVS >1% and sequence quality filters) changed the ranking to the 6th position/4,908 ("filteredVariants. rankingByVar" file). This exome sequencing dataset was analyzed together with 29 other exomes from unrelated patients and pathologies for a BBS patient for which we could further filter variations using for example the barcode.
Given that the most frequent known disease causing mutation in BBS is the c. 1169T>G (p. M390R) mutation in BBS1  (Mykytyn et al. , 2002) , found in EVS at the frequency of 26/12,694 (0. 2%) at the heterozygous state, we used the barcode statistics to further reduce the total number of variations. Being very tolerant, we kept variants present less than four times at the heterozygous state or two times at the homozygous state out of 29 samples. The final ranking placed the mutation at the forth position (and first homozygous) out of 3,493 remaining variants. The integration of these three datasets of increasing complexity (BBS with 30 genes consolidated on 188 patients, ID with more than 200 genes in 121 patients and the WES data consolidated for 35 samples) highlights major directions for further developments.
Considering the distribution of the non-redundant variation by functional category, one can first observe, despite a different gene composition, that the distribution of the categories is similar among the datasets (Fig. 5 ). The vast majority of the identified and annotated variations are either intronic or synonymous. Those categories contain known variations in dbSNP (∼85% have an rs#) and are either polymorphisms or rare variant. Thus they are often considered as non-pathogenic. Nevertheless, some of these could potentially affect the correct splicing of the closest gene. Although efforts are being taken to enhance the predictions on splicing especially for the consensus sequences  (Houdayer et al. , 2012; Jian, Boerwinkle & Liu, 2014) , little is done in more distant regions including enhancers sequences, branch point or even promoter regions.
CONCLUSION The rationale behind VaRank is to provide a simple yet powerful tool for biologists and researchers aiming to discover new human disease causing variants (i. e. , mutations) from DNA sequencing projects. VaRank is a comprehensive workflow for annotating and ranking SNVs and indels that aims at collecting the major annotation sources. The program is currently compatible with two annotation software namely Alamut Batch and SnpEff. This could further expanded to other annotation solutions such as Annovar  (Wang, Li & Hakonarson, 2010)  or VEP  (McLaren et al. , 2010). It stands out from other solutions by being able to provide a summarized overview of the presence/absence status of each variant within all patients (e. g. , barcode and family barcode) and allowing users to easily test several disease transmission hypothesis (recessive, dominant.
). The barcode counts can serve as an internal frequency database in order to filter out known and unknown frequent variants together with annotation errors and recurrent sequencing errors. Moreover, a specific ranking for each gene is particularly appropriate in the case of recessive diseases. Finally, as a command line tool it can easily be integrated into existing bioinformatics pipelines and accelerate identification of causal variants. The manual and a tutorial together with changelogs and various use cases are available via our dedicated website at http://www. lbgi. fr/VaRank.
ACKNOWLEDGEMENTS We thank  Ngoc-Hoan Nguyen  for his help in the bioinformatics setup,  Osorio Lopes Abath Neto  and  Nathalie Drouot  for their comments, our collaborators for validating our analysis ( Valérie Biancalana ,  Nadège Calmels, Bénédicte Gérard ) and all the clinical colleagues who addressed patients for diagnostic or research purpose.
9. The muon spectrometer has one barrel and two endcap air-core toroid magnets. Three layers of precision tracking stations provide muon momentum measurements over the range |η| < 2. 7. The ATLAS trigger system consists of three levels of event selection: a first level implemented using custommade electronics, which selects events at a design rate of at most 75 kHz, followed by two successive softwarebased levels. The level-2 trigger uses fast online algorithms, and the final trigger stage, Event Filter (EF), uses reconstruction software with algorithms similar to the offline versions.
Each event in the data and in the MC simulation is counted n times, where n is sampled from a Poisson distribution with a mean of one. A fluctuated transfer matrix and efficiency corrections are calculated as the average over these pseudo-experiments in MC simulation. Then, each resulting pseudo-experiment of the data spectrum is unfolded using the fluctuated transfer matrix and efficiency corrections. Finally, the covariance matrix between bins of measured m jjj cross-section is calculated using the set of unfolded pseudo-experiments of the data. The random numbers for the pseudo-experiments are generated using unique seeds. The dijet [6] and inclusive jet [5] cross-section measurements use the same unique seeds to evaluate the statistical uncertainties. In this way, the statistical uncertainty and bin-to-bin correlations in both the data and the MC simulation are encoded in the covariance matrix and the statistical correlation between different measurements can be taken into account in combined fits.
Fixed-order predictions The fixed-order QCD calculations are performed with the NLOJET++ program interfaced to APPLgrid  [48]  for fast convolution with various PDF sets. The renormalisation (Q R ) and factorisation (Q F ) scales are set to the mass of the three-jet system, Q = Q R = Q F = m jjj. The following proton PDF sets are considered for the theoretical predictions: CT 10 [49], GJR 08  [50] , MSTW 2008  [51] , NNPDF 2. 3  [52] , HERAPDF 1. 5  [53] , and ABM 11  [54]. To estimate the uncertainty due to missing higherorder terms in the fixed-order perturbative expansion, the renormalisation scale is varied up and down by a factor of two. The uncertainty due to the dependence of the theoretical predictions on the factorisation scale, which specifies the separation between the shortdistance hard scattering and long-distance non-perturbative dynamics, is estimated by varying the factorisation scale up and down by a factor of two.
All permutations of these two scale choices are considered, except the cases where the scales are shifted in opposite directions. The maximum deviations from the nominal prediction are taken as the scale uncertainty. The scale uncertainty is generally 10-20% depending on the m jjj. The multiple uncorrelated uncertainty components of each PDF set, as provided by the various PDF analyses, are also propagated through the theoretical calculations. The PDF groups generally derive these from the experimental uncertainties in the data used in the fits. For the results shown in Sect. 9, the standard Hessian sum in quadrature  [55]  of the various independent components is calculated taking into account asymmetries of the uncertainty components. The NNPDF 2. 3 PDF set is an exception, where uncertainties are expressed in terms of replicas instead of independent components.
These replicas represent a collection of equally likely PDF sets, where the data used in the PDF fit were fluctuated within their experimental uncertainties. For the plots shown in Sect. 9, the uncertainties in the NNPDF 2. 3 PDF set are evaluated as the RMS of the replicas in each bin of m jjj , producing equivalent PDF uncertainties in the theoretical predictions. These uncertainties are symmetric by construction. Where needed, the uncertainties of PDF sets are rescaled to the 68% confidence level (CL). HERAPDF provides three types of uncertainties: experimental, model and parameterisation. The three uncertainty sources are added in quadrature to get a total PDF uncertainty. The uncertainties in the cross-sections due to the strong coupling, α s , are estimated using two additional proton PDF sets, for which different values of α s are assumed in the fits, such that the effect of the strong coupling value on the PDFs is included.
Cross-section results Measurements of the double-differential three-jet crosssections as a function of the three-jet mass in various ranges of |Y * | are shown in Figs. 3  and 4  for anti-k t jets with values of the radius parameter R = 0. 4 and R = 0. 6, respectively. The cross-section decreases rapidly as a function of the three-jet mass. The NLO QCD calculations using NLOJET++ with the CT 10 PDF set corrected for non-perturbative effects are compared to the measured cross-sections. Good agreement between the data and the theoretical predictions is found over the full kinematic range, covering almost seven orders of magnitude in the measured cross-section values. The ratios of the theoretical predictions calculated with various PDF sets to the measured cross-sections are presented in Figs.
5  and 6  for R = 0. 4 jets and in Figs. 7  and 8  for R = 0. 6 jets. Theoretical calculations that use CT 10, MSTW 2008 and GJR 08 PDFs are compared to data in Figs. 5  and 7  and comparisons to other global PDFs, namely NNPDF 2. 3, ABM 11 and HERAPDF 1. 5. are presented in Figs. 6  and 8. The three-jet cross-sections are well described by the calculations that use CT 10, NNPDF 2. 3, GJR 08, MSTW 2008 and HERAPDF 1. 5 PDFs. Disagreement between data and the predictions using ABM 11 PDFs is observed for most of the cross-sections measured with both jet radius parameters. For all PDF sets, the predictions for anti-k t R = 0. 4 jets agree well with measured cross-sections, while the calculations that use the ABM 11 PDF set are systematically below all other theory curves. Theory predictions for anti-k t R = 0.
Conclusions Cross-section measurements of three-jet production in pp collisions at 7 TeV centre-of-mass energy as a function of the three-jet mass, in bins of the sum of the absolute rapidity separations between the three leading jets are presented. Jets are reconstructed with the antik t algorithm using two values of the radius parameter, R = 0. 4 and R = 0. 6. The measurements are based on the full data set collected with the ATLAS detector during 2011 data-taking at the LHC, corresponding to an integrated luminosity of 4. 51 fb -1. The measurements are corrected for detector effects and reported at the particle level. The total experimental uncertainty in these measurements is dominated by the jet energy scale calibration uncertainty. The measurement uncertainties are smaller than, or similar to, those in the theoretical predictions.
The measurements probe three-jet masses up to ∼ 5 TeV and are well described by perturbative QCD at NLO accuracy across the full m jjj -|Y * | plane. The comparison of NLO QCD predictions corrected for nonperturbative effects to the measured cross-sections is performed using several modern PDF sets. The data are well described by the theoretical predictions when using CT 10, NNPDF 2. 3, HERAPDF 1. 5, GJR 08 and MSTW 2008 PDFs. The theoretical calculations based on the ABM 11 PDFs are systematically below all the other predictions. Comparison of measured cross-sections to theoretical predictions for two different jet radius parameters shows good agreement for R = 0. 4 jets but shifted theory-to-data ratios for R = 0. 6 jets. This shift is covered by the experimental and theoretical uncertainty bands and it has only a minor dependence on the PDF set used.
We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We Table  1  Measured double-differential three-jet cross-section, σ, for R = 0. 4 jets and |Y * | < 2, along with uncertainties in the measurement. All uncertainties are given in %, where δ data stat (δ MC stat ) are the statistical uncertainties in the data (MC simulation). The γ components are the uncertainty in the jet energy calibration from the in situ, the pileup, the close-by jet, and flavour components. The u components show the uncertainty for the jet energy and angular resolution, the unfolding, the quality selection, and the luminosity. While all columns are uncorrelated with each other, the in situ, pileup, and flavour uncertainties shown here are the sum in quadrature of multiple uncorrelated components.
, 2006; Taylor et al. , 2006 Taylor et al. , , 2007;; Peplowski et al. , 2011 Peplowski et al. , , 2012)) , and of the Earth through laboratory analysis of crustal rocks. Pulse height spectra measured by GRaND's BGO sensor during the first few weeks of LAMO were examined to determine whether K and Th concentrations could be extracted. Thorium was not detected and K was reported to be present in concentrations less than 1000 lg/g  (Prettyman et al. , 2012). While this result is consistent with low concentrations of K and Th in HEDs, greater precision and accuracy are needed to determine whether Vesta's K-Th content is similar to the HEDs or other meteorites (e. g. Wasson, 2013). In this study, we return to the problem of measuring K and Th using the full data set acquired during 5 months of LAMO and improved data reduction and analysis methods.
Data reduction During the Vesta encounter, a time-series of gamma-ray pulse height spectra was acquired by GRaND's BGO scintillator during 15 months spanning approach through departure. Accumulated spectra were recorded every 210 s during approach and every 70 s during LAMO. Experimental data records (EDR) are archived at the NASA Planetary Data System (PDS) Small Bodies Node (SBN). The EDR were subjected to corrections to produce a data set suitable for scientific analysis. The reduced data records (RDR) and a description of detailed processing steps can be found at the PDS SBN (http://sbn. pds. nasa. gov/). RDR processing removed corrupted data and spectra acquired during solar energetic particle events. Only spectra acquired during quiet Sun conditions were analyzed. Under these conditions, galactic cosmic ray (GCR) interactions steadily produce gamma rays and neutrons within Vesta's regolith.
Digitization artifacts were removed from the remaining spectra, and gain/offset corrections put each 1024-channel pulse height spectrum onto a common energy scale (8. 9 keV/channel). Gain corrections accounted for small, short-term variations in gain due to changes in temperature and other environmental factors. Reduction in gain over larger time scales (e. g. from accrued radiation damage resulting in a gradual darkening of the BGO crystal) was also corrected. Ancillary data including the spacecraft position and pointing, the solid angle subtended by Vesta at the spacecraft, measurement live time and a proxy for the interaction rate for galactic cosmic rays (GCR) were reported for each archived accumulation interval. The resulting data set contains over 300,000 spectra.
A background spectrum was obtained by summing 33,000 spectra acquired during Vesta approach with a total live time of 6 million seconds. For LAMO, a global average spectrum was determined along with averages for four broad regions, including the poles, Vesta's ''dark'' hemisphere and its complement. To ensure consistent measurement geometry, the LAMO spectra were filtered to remove data not pointed within 5°of Vesta body center. The resulting global average LAMO spectrum was determined from 68,000 spectra with a total live time of 4 million seconds. The LAMO and approach spectra are shown in Fig. 1. The 7. 6 MeV Fe capture gamma rays are clearly visible in LAMO. At lower energies, differences between the LAMO and approach spectrum are difficult to discern prior to subtraction. In order to minimize the introduction of artifacts, the LAMO and approach spectra must have the same energy calibration and pulse height resolution.
Acknowledgments This work was carried out under contract with the  NASA Jet Propulsion Laboratory , which is operated by the  California Institute of Technology in Pasadena, California. The Dawn mission is led by the  University of California, Los Angeles  under the auspices of the  NASA Discovery Program. GRaND is managed by the  Planetary Science Institute. Funding for D. W. M. and R. C. R. was provided by the  NASA   Dawn at Vesta Participating Scientist Program. We greatly appreciate comments by  Larry R. Nittler  and an anonymous reviewer, which helped improve the manuscript.
Cochrane Database of Systematic Reviews There was su icient evidence to suggest that several stand-alone tests o en used to assess dehydration in older people (including fluid intake, urine specific gravity, urine colour, urine volume, heart rate, dry mouth, feeling thirsty and BIA assessment of intracellular water or extracellular water) are not useful, and should not be relied on individually as ways of assessing presence or absence of dehydration in older people. No tests were found consistently useful in diagnosing current water-loss dehydration.
Library Trusted evidence. Informed decisions. Better health. Cochrane Database of Systematic Reviews live in care homes or long-stay hospitals; rising to 21% of those aged 85 years and over  (National Care Homes 2007). Research in Norfolk (UK) care homes found that on a single assessment of 56 residents (from six institutions), 17 (30%) residents were dehydrated (with a furrowed tongue). A year later rates were lower (21%) and the risk of being dehydrated at the second visit did not relate to hydration status at first visit (Kenkmann 2010). More recently a cross-sectional study of 186 older people living in 56 Norfolk and Su olk care homes measured dehydration using serum osmolality and found that 46% had water-loss dehydration (including 19% with current dehydration, and a further 27% with impending dehydration, Siervo 2014).
Cochrane Database of Systematic Reviews TBW can be estimated by deuterium oxide dilution and therefore change in TBW can be assessed over time  (Schloerb 1950). A fall in body water of 2% or more could be considered to constitute dehydration, however due to the variance in assessment of TBW (1% to 2%), this will not be used as a reference standard. A single measure of TBW has not been correlated with hydration status in older people, so cannot be used as a reference standard on its own. In summary, we accepted the use of the following reference standards for dehydration: 1. serum or plasma osmolality 2. serum or plasma osmolarity 3. change in body weight over seven days Where more than one of these was available in any one study we always used osmolality for preference, followed by osmolarity.
Types of studies Diagnostic studies that compared an index test with a reference standard for water-loss dehydration in older people were included. We also considered cohort and cross-sectional studies that had not analysed diagnostic accuracy, but where at least one reference standard and at least one index test were measured in at least 10 participants aged 65 years or over and with at least two participants with water-loss dehydration and at least two participants without water-loss dehydration. These studies were included where the authors were able to provide a relevant 2 x 2 table comparing a reference with an index test, or a dataset from which relevant 2 x 2 tables could be calculated. Where we had access to the full study dataset we excluded any participants who did not receive both the index test and the reference standard.