dataesr/scientific-paragraphs-categorization huggingface dataset:
An additional 294 (~13%) were cycling in both saline-and cocaine-treated mice and, notably, 863 (~37%) de novo oscillating transcripts were identified upon cocaine challenge (Fig. 2a ). The phases of oscillation of genes diurnal in both conditions were similar (Fig. 2b, c ). The newly cocaine-induced oscillating transcripts display a peak at around ZT7, which is absent in saline condition. Moreover, 13% of the common oscillating genes showed a decrease in amplitude, while 35% displayed an increase upon cocaine treatment with respect to saline conditions (Fig. 2d ). Thus, the circadian program of cycling    genes in the NAcc is profoundly modified upon acute cocaine administration. Pathway analyses were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) (Fig.
Data was collected using Minimitter Vital View v5. 0 data acquisition software and analyzed through Matlab R2013a v9. 7. 0. 1296695 software and Clocklab software v2. 72. Quantitative RT-PCR. Striatum samples were homogenized in TRIzol lysis reagent (Thermo Fisher) following manufacturer's instructions. Total RNA was reverse-transcribed using iScript Reverse Transcription Supermix (Biorad Cat. N. 1708840). Gene expression was analyzed by Real-Time PCR (BIO-RAD Real-Time System; BIO-RAD CFX Manager Software v3. 1) using SsoAdvanced Universal SYBR Green Supermix (Biorad Cat. N. 172-5270). The sequences of the primers used for RT-PCR are Kcnd1 Forward: 5′-TCCGTTTGGCAAAGAGTGGT-3′, Kcnd1 Reverse: 5′-AGCTCGTCTGTGAACTCGTG-3′; Gabrd Forward: 5′-GGC GCCAGGGCAATGAAT-3′, Gabrd Reverse: 5′-GTCAATGCTGGCCACCTCTA-3′; Adora2a Forward: 5′-TTCATCGCCTGCTTTGTCCT-3′, Adora2a Reverse: 5′-AATGATGCCCTTCGCCTTCA-3′; Bmal1 Forward: 5′-GCAGTGCCACTGAC TACCAAGA-3′, Bmal1 Reverse: 5′-TCCTGGACATTGCATTGCAT-3′; Per1 Forward: 5′-ACCAGCGTGTCATGATGACATA-3′, Per1 Reverse: 5′-GTGCACA GCACCCAGTTCCC-3′; Dbp Forward: 5′-AATGACCTTTGAACCTGATCCCG CT-3′, Dbp Reverse: 5′-GCTCCAGTACTTCTCATCCTTCTGT-3′; Cry1 Forward: 5′-CAGACTCACTCACTCAAGCAAGG-3′, Cry1 Reverse5′-TCAGT-TACTGCTCTGCCGCTGGAC-3′.
The resulting libraries were validated by qPCR and sized by Agilent Bioanalyzer DNA high sensitivity chip. The concentrations for the libraries were normalized and then multiplexed together. The multiplexed libraries were sequenced on four lanes using single end 100 cycles chemistry on the HiSeq 2500. The version of HiSeq control software was HCS 2. 2. 58 with real time analysis software, RTA v1. 18. 64. Sequence alignment was performed using TopHat v2. 1. 1 while assembly and expression estimation was done using Cufflinks v0. 12. 1  79. Reads were mapped to the mouse genome mm10 and expression values were estimated as FPKM. DETAILS: FASTQ files were obtained from the sequencing facility and processed through the standard Tuxedo protocol  79. Reads were then aligned to the UCSC mm10 mouse reference genome using TopHat and Bowtie2 v2.
3. 4. Assembled transcripts were obtained via Cufflinks with the mm10 reference annotation file. Genome assembly was obtained using Cuffmerge and expression levels (summarized to genes) were calculated using Cuffquant and then normalized via Cuffnorm to FPKM values. For each condition, 24 h time series data from six time points with three replicates each were collected. In total, expression levels of 24138 unique genes were considered for further analysis. Data was further split to pairwise time series format for comparative analysis (e. g. WT Saline vs WT Cocaine treatment, KO Saline vs KO Cocaine treatment etc). Bioinformatics and pathway analysis. Bioinformatics analysis was performed on RNA-seq data using JTK_CYCLE 37 v3. 1 and pipelines for CircadiOmics (circadiomics. ics. uci. edu)  80.
Pathway analysis was performed using DAVID  81  and Reactome 82,83 software. Details: Statistical and bioinformatics analyses were performed based on pairwise comparisons, where the effect of cocaine treatment was analyzed while controlling the genotype or the difference between genotypes (WT or KO) were compared while controlling the treatment. Dixon's test was performed on replicates of transcriptomic data to reduce outlier effects, filtering out up to 1 outlier replicate from each time point. For transcriptomic data, genes with consistently low expression values (FPKM < 1) were filtered out from further analysis to reduce noise. Time series data was then used to determine circadian behavior of genes using JTK_CYCLE, including the p-value for whether the time series is considered circadian, its periodicity (between 20-28 h), amplitude and phase.
A gene is considered circadian if its JTK_CYCLE p-value passed the cutoff of 0. 01. Heatmaps of circadian transcripts were generated using the R package gplots v3. 0. 3, where the values on each row were normalized and rows were sorted by the JTK_CYCLE phase. The Database for Annotation, Visualization and Integrated Discovery (DAVID) pathway and Reactome analysis tools were used to identify enriched KEGG pathways for circadian genes in each condition. Pathways were ranked by the number of genes found annotated with the pathway information or with the negative natural log of p-values for enrichment, which behave similarly to z-scores where larger values indicate higher confidence. Putative TFBS information from MotifMap  39  were used to determine the enriched TFs in each condition. Fisher's test was conducted comparing the relative abundance of binding sites in the promoter regions (-10000 bps to +2000 bps of transcription start site) of circadian genes in each condition, as opposed to the genomic background (defined as all 24138 genes from the RNAseq data with FPKM > 0 at any time point).
In addition, a filtering parameter of BBLS > 1, FDR < 0. 25 was used to obtain high quality binding sites while TFs with motifs that are too short or degenerate (more than 50000 binding sites under the filtering criteria) were removed as they tend to be unreliable. TFs were ranked by the negative log of their Fisher p-values. Enrichment results from different pairwise comparisons were also compared in a meta-analysis to identify condition-specific TFs, in particular PPARγ which was found to be exclusively enriched in WT-Cocaine condition. PPARγ targeted genes were filtered using a combination of MotifMap data and ChIP-Seq data from GSE64458  84. Binding sites were searched within a smaller promoter region of -3000 bps to +1000 bps of the TSS while filtering parameters for MotifMap were kept the same as mentioned above.
Other visualization and statistical analyses were performed in R or in python using pandas and scikit-learn. Metabolomics analysis. Metabolomic analyses were performed using p180 from the Biocrates facility (Innsbruck, Austria). Metabolite levels were measured at ZT7 after an intraperitoneal injection of saline or cocaine at a dose of 20 mg kg -1 at ZT3, 5 replicates each. Statistical and bioinformatics analyses were performed based on pairwise comparisons, where the effect of cocaine treatment was analyzed while controlling the genotype or the difference between genotypes (WT or KO) were compared while controlling the treatment. Dixon's test was performed to reduce outlier effects, filtering out up to 1 outlier replicate from each condition. Heatmaps for the metabolite profiles were generated using the RStudio software.
Row z-scores are displayed and were calculated using the 'heatmap. 2' function of the gplots package. Immunohistochemistry and fluorescent in situ hybridization analysis. Single immunostaining was performed on vibratome sections as described previously  85  using anti-PPARγ antibody (1:1000; Novus Biotechnologies Cat. #NB120-19481). Nuclei staining was obtained using Draq7 (Biostatus, Cat# DR70250). For quantifications, frames of 375×375 µm/image (n = 4) were analyzed. ROIs were drawn around individual cells using LASX software v3. 7. 0 (Leica); mean gray values/cell were obtained and background subtracted. Double immunohistochemistry/in situ hybridization staining were obtained using striatal sections which were hybridized with digoxigenin (DIG)-Enkephalin or (DIG)-D1R riboprobes (RNA labeling mix; Roche, Cat# 11277073910)  29.
Acknowledgements We thank all the members of the  Sassone-Corsi and Borrelli laboratories for scientific discussion  and technical assistance. We also thank  Siwei Chen  for computational assistance. We greatly appreciate  Melanie Oakes ,  Christophe Magnan ,  Seung-Ah Chung  and  Valentina Ciobanu  at the  UCI Genomics High-Throughput Facility. RGL was supported by the  University of California, Irvine School of Medicine Dean's Fellowship  and the  Dr. Lorna Carlin Scholar Award. MC was supported by predoctoral fellowships from the  National Institutes of Health (NIH)  ( GM117942 ) and the  American Heart Association  ( 17PRE33410952 ). PT by  Human Frontier Science Program   LT 000576/2013. This work was supported by grants from  NIH  ( DA 035600  to EB and PSC) and by the  French Institut National de la Santé et de la Recherche Médicale (INSERM).
Data availability The GEO accession number for the RNA-seq data set reported in this paper is GSE142657. RNA-seq data was used for Figs. 2 3 4 , and Supplementary Figs. 1 2 3 4. UCSC mm10 mouse reference genome was used for alignment. All the transcriptomic data associated with this work is publicly available on the resource circadiomics. ics. uci. edu. PPARγ ChIP-seq data used for Fig. 4  was downloaded from GEO, accession number GSE64458  84. Source data are provided with this paper.
Food consumption data and nutrient composition Data from the dietary survey INCA2 conducted in 2006-2007 on a representative sample of the French population  (Dubuisson et al. 2010)  were used for this study. In terms of ethics of human subject participation, this survey was approved by the CNIL, the French Data Protection Authority (CNIL: 'Commission Nationale Informatique et Libert es' No. 2003X727AU) and the CNIS, the French National Council for Statistical Information (CNIS: 'Conseil National de l'Information Statistique'). Verbal informed consent was obtained from all participants and formally recorded. Participants completed a food diary for 7 consecutive days. After exclusion of under-reporters identified using Black equations  (Black 2000) , only data from adults aged 18 years and over having reported all 7 days were kept.
The final sample contained 1863 individuals which reported, as a whole, the consumption of 1300 foods. Since FBDGs deliver recommendations on relatively broad categories of foods and not on specific foods, and since our aim was to simulate the fulfilment of FBDGs, we decided to work with a short food database of food items, named the SUSTABLE database  (Gazan et al. 2018b) , which provides the nutritional composition of 206 food composite items commonly consumed in France. As previously described  (Gazan et al. 2018b) , each food declared as consumed in the INCA2 survey was linked with one food item in the SUSTABLE database, and the nutrient content of each food item in the SUSTABLE database was the average nutrient content of one or several related foods in the INCA2 food database, weighted by the level of intakes of the related foods in the population.
The percentage of inadequacy to the nutritional recommendation was calculated for each nutrient. Under the assumption of a Gaussian distribution of nutritional requirements in a given population, the estimated average requirement (EAR) is the value for which it is assumed that half of the individuals in the population are meeting their needs. When there is insufficient data to estimate the distribution of individual needs (and therefore the EAR) for a nutrient, the recommended value, called Adequate Intake (AI), is the average daily intake of a population (or subgroup) for which the nutritional status is considered satisfactory. For each nutrient, the percentage of inadequacy compared to the nutritional recommendation was obtained by calculating the percentage of diets not reaching, either the AI (for thiamin, riboflavin, vitamin B6, vitamin B12, magnesium, phosphorus, selenium, iodine, essential fatty acids and fibre) or the EAR (for the other nutrients)  (Carriquiry 1999 ).
The nutritional recommendations (i. e. the AI and EAR values) used by the French Food Safety Agency in their report providing the scientific basis for the development of the new FBDGs were also used to calculate the MAR and the MER (ANSES 2016a). The quantities of the PHF groups, the nutritional characteristics of the diets and the percentages of inadequacy to the nutritional recommendations were compared between observed and DP2 and DP3 modelled diets using paired tests based on a general linear model adjusted for energy, gender and age. The SAS 9. 4 software was used to conduct Individual diet optimisation models and statistical analyses. It was possible to optimise diets (i. e. simultaneous compliance with all the constraints was mathematically achievable) with both the DP2 and DP3 models for a total of 1847 individuals, representing more than 98% of the sample.
9 portions/day)  (Dehghan et al. 2018). Finally, it is noticeable that dairy products are part of the French food culture and they are relatively inexpensive sources of essential nutrients  (Maillot et al. 2007) , two fundamental dimensions to be considered when establishing national food guides (Joint FAO/ WHO Consultation 1998). This study is subject to limitations. Like all studies based on dietary surveys, the results are subject to various biases (e. g. reporting bias) and depend on the quality of data used. For instance, in this study we used dietary data (food intakes and nutrient content of food items) that were 13-14 years old. Nevertheless, these limitations have less impact in this study since the objective was not to analyse the observed diets per se but to compare them to the modelled diets.
Acknowledgements M. M. and N. D. designed the study, interpreted the results, wrote the manuscript and were responsible for the final content of the manuscript. M. M. performed the modelling and statistical analysis. Both authors read and approved the final version of the manuscript. This research was funded by the  CNIEL  ( Centre National Interprofessionnel de l'Economie Laiti ere: National Interprofessional Center for the Dairy Economy ).
Cross-sectional survey Based on the census, a random selection of households was drawn oversampling small villages to ensure sufficient coverage (Additional file 1: Table  ST1 ). Selected households were visited from mid-December 2017 until mid-April 2018 and all household members aged 2-80 years who had resided in the study area for at least 3 months were invited to participate in the survey. Upon informed consent, a questionnaire on household variables was administered to the head of household or another adult household member by trained interviewers. A questionnaire on individual-level variables was administered to each consenting household member. Children were interviewed assisted by a parent (or rarely another caregiver in the absence of the parents). Data were collected on tablets and run through automated data quality checks within days after the interview.
In case of missing data or discrepancies, the field team was informed for immediate resolution if possible. Fingerprick blood samples were collected as thick and thin film slides and in K + EDTA-microtainers. Participants were screened for symptoms, i. e. feeling sick or feverish on the day of interview, having felt feverish over the preceding two days, or having an axillary body temperature of at least 37. 5 °C. Upon any indication, the participant was administered a standard malaria RDT (Malaria Ag P. f/P. v, Standard Diagnostics Inc. , South Korea) and referred to a local health care provider for treatment if positive.
Funding This study is part of the  International Centers of Excellence for Malaria Research programme  "Understanding, tracking and eliminating malaria transmission in the  Asia-Pacific Region ", funded by the  National Institutes of Health, MD, US  (grant  1U19AI129392-01 ) and received additional funding by  NHMRC (Australia ,  GNT1092789 ). IM is supported by an  NHMRC   Principal Research Fellowship  ( GNT1155075 ). LJR is supported by an  NHMRC   Career Development Fellowship  ( GNT1161627 ). MS is part of the PhD programme of the doctoral school ED393 Pierre Louis de santé publique and supported by the  Sorbonne Université  (contract  n°2695/2017 ). AP is supported by the  Pasteur Institute International Network PhD fellowship programme "Calmette & Yersin". The funding bodies had no role in the design of the study, the collection, analysis, and interpretation of data, and in writing the manuscript.
It is intended as a reference for the instrument suite, and can be considered as a partial update to the TDR. It covers both the scientific scope and technical performance of each of the 15 user instruments, as well as a test beamline for characterising the moderator performance. The instruments all pass through a series of project phases, and at the time of writing, all of them have passed from preliminary to detailed engineering design. Their scope and performance have thus been fixed and form the basis of the descriptions in this paper. For all instruments, their design has been optimised and their performance thoroughly evaluated using both analytical calculations and Monte-Carlo ray-tracing simulations by means of the established software packages McStas  [19]  and VITESS  [20]. Many instruments have well-identified upgrade paths to expand their day-one scope, often involving an increase in detector coverage.
NMX expected performance Scientific performance is a very complex and intrinsically subjective quantity to measure and depends on many other factors than the purely technical performance of the instrument and its components. The assessment below tries to address those aspects of the technical performance that affect the data collection time. The principal technical challenges are the limited crystal size and the high background. The data collection time depends strongly on the crystal size and other crystal properties such as symmetry, mosaicity, hydrogen content and the background from the surrounding mother liquor. The other relevant variables are the beam brilliance and the solid angle subtended by the detectors. The neutronic performance was evaluated by ray-tracing Monte Carlo simulations using the McStas package.
One upgrade option at ODIN foresees to complement the instrument with diffraction detectors, while imaging will be one of the day-one configurations available at BEER. Tomography-driven diffraction experiments, i. e. locating regions within a sample of complex geometry by 3D-imaging that should be investigated in more detail by engineering diffraction, will be another common application where synergies between instruments in this class can be expected. The strategy to centralise software and data management (including analysis) for all instruments at the ESS Data Management and Software Centre will enable an even more efficient toolbox for investigating samples using more than one instrument. Both BEER and ODIN will provide ample space in the sample area to allow not only for large and complex samples but also for bulky sample environments.
Acknowledgements Some of the work described here is part of projects that have received funding from the  European Union 's  Horizon 2020 research programme: SINE 2020  under grant agreement number  654000 ,  Bright-nESS  under grant agreement number  676548 , and  SoNDe  under grant agreement number  654124. Financial support for the fast-shutter upgrade for FREIA from  Swedish Research Council VR , grant no  2018-05013 , is acknowledged. The VESPA team gratefully acknowledges the  Science & Technology Facilities Council (STFC)  and the  CNR , within the  CNR-STFC  Agreement ( 2014-2020 ) No. 3420. The MIRACLES team wishes to thank the IN16B team ( Bernhard Frick  and  Tilo Seydel ), the  BASIS  team ( Kenneth W. Herwig ,  Eugene Mamontov  and  Niina Jalarvo ), the DNA team ( Kaoru Shibata  and  Yukinobu Kawakita ), and the  IRIS/OSIRIS team  ( M.
Only a small fraction of glitches correspond to a motion of the SEIS package as a whole caused by minuscule tilts of either the instrument or the ground. In this study, we focus on the analysis of the glitch+spike phenomenon and present how these signals can be automatically detected and removed from SEIS's raw data. As glitches affect many standard seismological analysis methods such as receiver functions, spectral decomposition and source inversions, we anticipate that studies of the Martian seismicity as well as studies of Mars' internal structure should benefit from deglitched seismic data.
Introduction InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) landed successfully on Mars on 26 November 2018 (Sol 0, a sol is a Martian day with around 24 hr 40 min). Since 9 February 2019 (Sol 73), InSight's main scientific instrument SEIS (Seismic Experiment for Internal Structure) is recording seismic data in its operational configuration  (Banerdt et al. , 2020). The SEIS package  (Lognonné et al. , 2019) , which is located at 135. 6234°E and 4. 5023°N in Elysium Planitia  (Golombek et al. , 2020)  and whose network and station code for the scientific data is XB. ELYSE, consists of 2 three-component seismometers; one being very broadband (VBB) with a corner period of 16 s, and one being short-period (SP) with a corner period of 35 s. The noise floor of the two instruments is equivalent only above 5 Hz while it is about ∼30 dB lower for the VBB at frequencies below 0.
1 Hz. It is this frequency dependence of the seismometers' self-noise that determines their names as established for the InSight project  (Lognonné et al. , 2019) , even though the naming convention does not follow terrestrial standards (e. g. ,  Ahern et al. , 2012). Due to their different noise floors, the VBB is the main instrument to detect distant marsquakes, while the SP is used to cover the frequency range of ∼5-50 Hz for more detailed analysis of regional events and lander-induced signals. Both seismometers have nonorthogonal sensor orientations (Figures  1a  and 1c ). To date, all six seismic components as well as the acquisition system have functioned nominally, exceeded mission requirements, and delivered unprecedented seismic data from the surface of Mars (InSight Mars SEIS Data Service, 2019).
This obviously represents no valid option for the seismic data returned from Mars, hence the correct treatment of the glitches is of upmost importance for the scientific analyses. Within the InSight team, four groups therefore independently investigated the glitch phenomenon to ensure redundancy of the effort, reproducibility of the outcomes, and convergence toward a complete understanding. To some extent these efforts also reflect the scientific objectives across the different groups as well as institutional responsibilities within the InSight project. The present study is the current culmination of this teamwork and focuses on the detection, analysis, and removal of glitches. It extends Supplement V of  Lognonné et al. (2020).
Glitch Detection To automatically detect glitches on SEIS's VBB and SP raw data, several groups (MPS, ISAE, UCLA, and IPGP) independently developed algorithms in the Python and MATLAB programming languages. The group acronyms stand for the affiliation of the group's leading analyst, that is, Max-Planck-Institute for Solar System Research (MPS), Institut Supérieur de l'Aéronautique et de l'Espace SUPAERO (ISAE), Department of Earth, Planetary, and Space Sciences, University of California Los Angeles (UCLA), and Université de Paris, Institut de physique du Globe de Paris (IPGP). We describe each approach in the following. The common detection idea and working hypothesis of this study is that glitches in the raw data represent steps in acceleration convolved with the seismometer's instrument response, while spikes represent steps in displacement convolved with the seismometer's instrument response.