dataesr/scientific-paragraphs-categorization huggingface dataset:
8 such features, a standard error on the mean of 0. 2 and standard deviation of 1. 8. The large standard deviation for the matched noise cubes is the result of the small initial search area about the source centre. The mean number of matched peaks implies that with the data in hand there is, on average, a 50% chance of detecting spatially and spectrally correlated ≥3. 8σ noise peaks in both the Band 4 and 6 data. However, given the standard deviation, the likelihood is consistent with 100%. We found that the number of matched noise peaks drops sharply with S/N. The number of jointly detected noise peaks drops to 0 at a S/N threshold of ∼4. 4. Thus, at S /N > 4. 4 two matched positive features in the Band 4 and 6 data are certain to be real whereas at S /N > 3. 8 they are fully consistent with both being noise peaks.
Consistency between the SED fits and line upper limits We explored whether the upper limits on the line luminosities covered by the Band 4 and 6 data are consistent with the three redshift solutions inferred previously from the photometry. For this, we used the mean rms per 50 km s -1 channel, excluding the channels at the outskirts of the SPW, which is 0. 319 mJy beam -1 for the Band 6 data and 0. 096 mJy beam -1 for the Band 4 data. In each of the three cases, we assumed a line width of 200 km s -1 , applied a S/N threshold of 4, and assumed that the source is unresolved for both the Band 4 and 6 beam. The last assumption is motivated by the fact the maximum radius of the emission seen in the VISTA K s image is 0. 7, which is equivalent to the beam size of the Band 6 data and significantly smaller than the beam of the Band 4 data.
Low-redshift dwarf-galaxy scenario We first explored the z ∼ 0. 2-0. 3 scenario, which corresponds to a dust-rich but barely star-forming (SFR ∼ 10 -2 M yr -1 ) dwarf galaxy. In this case, a high visual extinction of A V ∼ 7. 5 is required to explain the SED. For this scenario, the Band 6 observations would cover the frequency of HCN(3-2) for z = 0. 06-0. 20 and CO(3-2) for z = 0. 38-0. 56 whereas the Band 4 observations cover HCN(2-1) for z = 0. 32-0. 34. Since HCN is typically far fainter than CO (e. g. Vanzi et al. 2009) , we first tested whether we could have detected CO(3-2), for a dwarf galaxy at z ∼ 0. 4. The ALMA data provide an upper limit on the CO(3-2) line luminosity of 11. 7 × 10 7 K km s -1 pc 2. A29, page 10 of 13 The dust mass predicted by the MAGPHYS fit is M dust ∼ 10 5. 8 M.
Thus, we find that even with the addition of the ALMA Band 4 upper limits, the existing data cannot be used to constrain the redshift of HD1. Determining the redshift and properties of HD1 will require at least one of the following: (1) deep, sub-arcsecond resolution photometry at ∼100 µm (as the upper limits provided by Herschel provide too little constraining power), (2) 10× deeper observations at submillimetre wavelengths, or, (3) spectra covering the apparent break at ∼2 µm and flux bluewards of the break. For (1), there is currently no suitable observational facility and (2) may require significantly more ALMA time (∼500 h). Thus, option (3) using deep JWST/NIRSpec observations, will likely be the most feasible way to determine the nature of HD1. Indeed, recently four z > 10 galaxies have been confirmed in this way (Curtis-Lake et al.
Acknowledgements. We thank the referee for a constructive report that helped improve the analysis and discussion of the likely redshift of HD1. We also thank  Dr. Elisabete da Cunha  and  Dr. Leindert Boogaard  for helpful discussions that greatly improved the quality of the analysis and interpretation of the data herein. Our thanks also to the creators of the publicly available codes used herein; thanks to  Dr. Elisabete da Cunha  for MAGPHYS,  Dr. Adam Carnall  for  Bagpipes  and  Drs. Mladen Novak ,  Leindert Boogaard  and  Romain Meyer  for Interferopy. This paper makes use of the following ALMA data: ADS/JAO. ALMA#2021. A. 00008. S. ALMA is a partnership of  ESO  (representing its member states),  NSF (USA)  and  NINS (Japan) , together with  NRC (Canada) ,  MOST  and  ASIAA (Taiwan) , and  KASI ( Republic of Korea) , in cooperation with the  Republic of Chile.
The  Joint ALMA Observatory  is operated by  ESO ,  AUI/NRAO  and  NAOJ. Calibrated measurement sets were provided by the  European ALMA Regional Centre  network (Hatziminaoglou et al. 2015) through the calMS service (Petry et al. 2020). L. D. M. is supported by the  ERC-StG 'ClustersXCosmo ' grant agreement  716762. AtLAST has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No. 951815.
Indeed, the literature review conducted by  Stanelle et al. (2014)  concluded that the change of the today's total dust emissions attributable to human activities was comprised between -20 % and 60 %. As an example, using the same observational dataset (dust storm frequency data to constrain global dust model outputs),  Tegen et al. (2004)  concluded that the contribution of dust from agricultural areas to the global dust load was less than 10 %, whereas  Mahowald et al. (2004)  found that this contribution ranged between 0 and 50 %. More recently, using the dust optical depth Deep Blue product derived from the measurements of Moderate Resolution Imaging Spectroradiometer (MODIS) in conjunction with other data sets including land use,  Ginoux et al. (2012)  estimated that anthropogenic (primarily agricultural) sources accounted for 25 % of the global dust emissions.
This study aims at documenting the impact of a crop cycle on wind erosion and at disentangling the respective roles played by meteorology, surface properties, and human practices. To do so, an experimental field campaign was conducted in southern Tunisia during agricultural year 2015-2016 on a barley field with a traditional land management. Meteorological parameters, in particular wind speed and direction and precipitation, as well as surface characteristics (including barley growth), and horizontal fluxes of aeolian sediments were measured. This data set is used to understand what controls wind erosion in the region and to propose possible improvements in the land management. In the future, this data set could also be used to improve wind erosion modeling in traditional cultivated areas of southern Tunisia so that the contribution of these areas to total dust emission could be estimated in this region.
Meteorological parameters A mast equipped with 7 cup anemometers (A100R Vector Instru-ment®; resolution = ± 0. 1 m s -1 ) was set up at the eastern edge of the plot (Fig. 1a ) to measure at 0. 1 Hz the wind speed vertical profile. Data were acquired using a CR1000 data logger (Campbell® Scientific company), with a nominal data acquisition time of 1-min. The 7 anemometers were respectively set at 0. 285 m, 0. 825 m, 1. 395 m, 1. 920 m, 2. 965 m, 4. 060 m, and 5. 005 m above ground level (AGL). These measurements allowed estimating the aerodynamic roughness length, z 0 (see §2. 2. 2. ). Additional wind speed and direction as well as rainfall measurements were continuously performed using a meteorological station located 10 m north of the meteorological mast. Wind speed and direction were measured there at 2 m AGL using a 2 dimensional (2D) sonic anemometer (WindSonic TM Gill Instruments ltd), and rainfall using an ARG100 Tipping Bucket rain gauge (Campbell® Scientific company).
Data were acquired using a CR200X data logger (Campbell® Scientific company), with a nominal data acquisition time of 5-min for all parameters measured with a frequency of 0. 1 Hz. Given the high variability of both wind speed and direction on a 5-min time step, the maximum and mean values of wind speed, and the mean and standard deviation of wind direction measured over this interval were recorded. 5-min rainfall measurement corresponds to the accumulated bucket tippings over this interval with one tipping corresponding to 0. 2 mm of rainfall.
Vegetation monitoring Five plots of 2. 0 m × 1. 5 m were delimited in the field to weekly follow the barley height and cover rate using photographs and eye estimates. Barley height was measured using a meter tape. The mean maximum height of the barley tufts was measured for each plot. The barley cover rate was always estimated by the same observer on site. When barley was green, its cover rate was also estimated following  Mougin et al. (2014)  by a numerical treatment (CAN-EYE© software) to corroborate eye estimates. Vertical and horizontal photographs were used to check the estimates.
Acknowledgements The authors would like to thank: (i)  Houcine Khatteli , Director of the  Institut des Régions Arides (IRA) of Médenine , for the constant support of  IRA  in all research related to wind erosion, and in particular for giving us access to the Dar Dhaoui's experimental range and for the IRA's logistic help during the whole experiment to ensure the success of the campaign, (ii) the watchmen of the experimental station ( Noureddine Boukhli ,  Mokhtar Elghoul  and  Mousbah Elghoul ) for their constant help.
This was achieved by introducing additional linguistic context, namely, (1) two special words rather than one and (2) two ambiguous pronouns instead of one. Consequently, we obtained more observables and more measurement contexts, leading to a scenario that resembles the Bell-CHSH scenario. The above outlines the first contribution of this paper. Our second contribution lies in the instantiation of our generalized Winograd Schema and the collection of human judgments via a crowdsourcing platform. This allowed us to calculate the violation of the Bell-CHSH inequality and thereby establish the contextuality of our model, which was constructed based on human judgments. We also modelled the data using the Contextuality-by-Default (CbD) framework of contextuality and calculated a corresponding CbD degree of contextuality.
Submit Figure  2 : A screenshot of the template of the questionnaire. The placement holders ${word1} and ${word2} are instantiated with the two special words or the alternate words of the generalised Winograd Schema. In this example, ${word1} can be either cannibalistic or herbivorous and ${word2} can be either hungry or alive. Four versions of the questionnaire were created, each corresponding to one of the four contexts in the generalised WS scenario. Note that the story contains several incorrect uses of English. Unfortunately, we did not notice these until a reviewer pointed them out, after data collection. Since each referring phrase can be interpreted in two ways, there are 4 possible combinations of interpretations, (A, A), (A, B), (B, A), (B, B), of the two referring phrases. The symmetry between A and B in the example ensures that the combinations (A, A) and (B, B) are equally plausible and (A, B) and (B, A) are also equally plausible.
Therefore we asked the respondents to pick two out of the four combinations. This design choice also allows the detection of invalid answers, that is, those that do not and 100 each were to the rest of the three contexts. Out of all the responses, 348 were valid, i. e. their responses respected the symmetry between A and B. The respondents were each financially rewarded USD 1. 00, regardless of the validity of their responses. The collected valid data were used to build an estimated probability distribution for each of the four contexts. The resulting empirical model is shown in Table  1. The model violates the Bell-CHSH inequality by 0. 192 with a standard deviation of 0. 176. Since the model is symmetric in the outcomes by construction, it is non-signalling and thus the measure of contextuality CNT 1 in the CbD framework coincides with the degree of violation  [25].
The symmetry in the outcomes also allows the violation to saturate the bound defined by CF in sheaf-theoretic framework  [1] , i. e. the following equality is attained max 0, 1 2 violation of Bell-CHSH inequality = CF. Thus, our model is considered contextual in both the sheaf-theoretic framework and the CbD framework. To establish the significance of the contextuality result, we conducted bootstrap resampling to estimate the spread of the violation to the Bell-CHSH inequality. Simulated datasets were generated by random sampling with replacement from the original dataset. The resulting distribution of violations is depicted in Figure  3. Among the resampled datasets, 87% of them exhibited a positive violation, indicating that our experimental model demonstrates contextuality with a significance level of 87%.
Both approaches analyse mononucleotides derived from selected tRNAs and are based on already reported sequences. The exact position of the modified nucleotide was thus inferred from available information on tRNA sequences and modification profiles database  (Jühling et al, 2009; Chan & Lowe, 2016; Boccaletto et al, 2018). Recently, a new method called Ribo-MethSeq was established and allows the identification of Nm sites in a complete unbiased manner, based on the protection conferred by the ribose methylation to alkaline digestion  (Marchand et al, 2016 (Marchand et al, , 2017)). This offers the possibility to identify every Nm site regulated by a particular enzyme, especially when investigating abundant RNAs, such as tRNAs. In this study, we took advantage of this novel approach to identify the full set of FTSJ1's tRNA targets in humans.
FTSJ1 mutation perturbates the silencing activity of miR-181a-5p miRNA As some of the FTSJ1-deregulated miRNAs and mRNAs were implicated in similar biological processes such as cancer and brain function, we wondered whether there were some miRNA::mRNA pairs that could be involved in these commonly deregulated processes. Using miRNet 2. 0  (Chang et al, 2020) , we performed a bioinformatics cross-analysis of the small RNA-seq and mRNA-seq datasets. We found a subset of FTSJ1-deregulated miRNAs that were previously shown to modulate some of the FTSJ1-deregulated mRNAs. For instance, the SPARC mRNA is an experimentally confirmed target of miR-10a-5p  (Bryant et al, 2012; Wang et al, 2020). This result thus suggests that SPARC mRNA down-regulation observed in FTSJ1 mutants may be due to its increased silencing by the up-regulated miR-10a-5p.
Consistently with the posttranscriptional regulatory role of miRNAs, we also found through mRNA-seq an enrichment of brain morphogenesis-related mRNAs differentially expressed in FTSJ1 loss of function when compared to control LCLs. Interestingly, a cross-analysis of these two RNAsequencing experiments revealed potential miRNA::target mRNA couples among the deregulated RNA populations. This is indicative of possible miRNA silencing changes in the absence of FTSJ1, similar to what we report earlier in Drosophila FTSJ1 mutant orthologs. The predicted miRNA::mRNA couples need to be further validated individually in neuronal tissues, although their report from miRnet database  (Chang et al, 2020 ) already includes experimental evidence on the miRNA::mRNA regulation, particularly for BTBD3 and SPARC mRNAs  (Bryant et al, 2012; He et al, 2015; Wang et al, 2020).
PCR products were sequenced using the Sanger method with a forward primer hybridizing in exon 5: 59-CCACTGCCAAGGAGATCA-39 (Fig  S1A ). Sequences are available upon request. Briefly, this variant causes a skipping of the entire exon 6 in the mRNA leading to a frameshift and a premature stop codon, thus undergoing nonsense-mediated mRNA decay as shown in Fig S1C. Consequently, a strong decrease of the corresponding mRNA steady-state level is observed (Fig  S1B ). This MM variant was deposited in the ClinVar database (VCV000981372. 1).
RNA fragments were converted to library using NEBNext Small RNA Library Kit (ref. E7330S; New England Biolabs) following the manufacturer's instructions. DNA library quality was assessed using a High Sensitivity DNA chip on Bioanalyzer 2100. Library sequencing was performed on Illumina HiSeq 1000 in a single-read mode for 50 nt. Primary analysis of sequencing quality was performed with RTA 2. 12 software, to ensure > Q30 quality score for >95% of obtained sequences. After SR50 sequencing run, demultiplexing was performed with BclToFastq v2. 4, and reads not passing quality filter were removed. Raw reads after demultiplexing were trimmed with Trimmomatic v0. 32  (Bolger et al, 2014). Alignment to the reference tDNA sequences was performed with bowtie 2 ver2. 2. 4  (Langmead et al, 2009)  in end-to-end mode.
This reduced collection contains 43 tRNA species and was validated by analysis of several experimentally obtained RiboMethSeq datasets  (Pichot et al, 2021). Alignment of RiboMethSeq reads obtained in this study also confirmed low content in ambiguously mapped reads. In order to establish a reliable map of Nm positions in the human tRNA anticodon loop, RiboMethSeq cleavage profiles were used to calculate detection scores (Mean and ScoreA2)  (Pichot et al, 2020). However, this scoring strategy shows its limits in the case of short and highly structured RNAs (like tRNAs), because the cleavage profile is highly irregular. In addition, because these scores are calculated for two neighbouring nucleotides, the simultaneous loss of two closely located Nm residues (e. g. , Cm 32 and Gm 34 in tRNA Phe ) makes analysis of raw score misleading  (Angelova et al, 2020).
Moreover, the presence of multiple RT-arresting modifications  (Anreiter et al, 2021)  in the same tRNAs (m 1 A, m 1 G, m 2 2 G, m 3 C, etc. ) reduces coverage in the upstream regions. Considering all these limitations, visual inspection of raw cleavage profiles revealed to be the most appropriate, because changes in protection of a given nucleotide represent modulation of its Nm methylation status. Analysis of alignment statistics demonstrated that most of the human tRNAs are well represented in the analysed datasets and proportion of uniquely mapped reads were >90% for all tRNA sequences, except the tRNA Leu_CCA family, composed of three highly similar species. Only limited coverage of totally mapped reads <7,500 reads/tRNA (~100 reads/position) was obtained for five tRNAs (Arg_TCG, Leu_CAA2, Ser_CGA_TGA1, Thr_CGT, and Tyr_ATA).
9× to remove adapter dimer contamination. Quality of the libraries was verified by HS DNA Chip on Bioanalyzer 2100 (Agilent Technologies) and quantification done by Qubit 2. 0 with an appropriate RNA quantification kit. Sequencing was performed on HiSeq 1000 (Illumina) in single-read SR50 mode. About 50 million of raw sequencing reads was obtained for each sample. Adapters were trimmed by Trimmomatic v0. 32  (Bolger et al, 2014)  and the resulting sequencing reads aligned in sensitive-local mode by Bowtie 2 v2. 2. 4  (Langmead & Salzberg, 2012)  to hg19 build of human genome. Differential expression was analysed using *. bam files in the DESeq2 package  (Love et al, 2014)  under R environment. Analysis of KEGG and gene ontology pathways for differentially expressed genes was done under R environment.
For small RNA data analysis, adapters were trimmed from total reads using FASTX_Toolkit (http://hannonlab. cshl. edu/fastx_toolkit/). Only trimmed reads with a length between 15 and 40 nucleotides were kept for further analysis. Data analysis was performed according to the published pipeline ncPRO-seq  (Chen et al, 2012). Briefly, reads were mapped onto the human genome assembly hg19 with Bowtie v1. 0. 0. The annotations for miRNAs were done with miRBase v21. The normalization and comparisons of interest were performed using the test for differential expression, proposed by  Love et al (2014)  and implemented in the Bioconductor package DESeq2 v1. 22. 2 (http://bioconductor. org/). MicroRNA target prediction was performed using miRNet 2. 0  (Chang et al, 2020).
After 5 d, third instar larvae were dissected and subjected to NMJ staining. Images from muscles 6-7 (segments A2-A3) were acquired with a Zeiss LSM 710 confocal microscope. Serial optical sections at 1,024 × 1,024 pixels with 0. 4 μm thickness were obtained with the ×40 objective. Bouton number was quantified using Imaris 9 software. ImageJ software was used to measure the muscle area and the NMJ axon length and branching. Statistical tests were performed in GraphPad (Prism 8).
8 litres⋅min -1. Flies were given 1 min in complete darkness to freely move within the T-maze. Flies were then collected from each arm and counted; an avoidance index was calculated as (N air -N odour )/(N air + N odour ). The side of the T-maze with odorant-interlaced air was alternated between experimental replicates. Quantification and statistical analysis All data are presented as the mean ± SEM. Performances from different groups (mutant and control) were statistically compared using one-way ANOVA followed by Tukey's post hoc pairwise comparison between the mutant genotypes and the control group.
Val121Glyfs*51) (Fig S1A). Part of the transcripts undergo nonsense-mediated mRNA decay (Fig S1C). Consequently, a strong decrease of the corresponding mRNA steady-state level is observed (Fig S1B). This variant was deposited in the ClinVar database (VCV000981372. 1). The research on LCL-MM was performed according to a research protocol approved by a local ethics committee (Comit é Consultatif de Protection des Personnes dans la Recherche Biom édicale-CCPPRB). Written informed consent was obtained from the patient and his legal representatives.
Acknowledgements We thank the patients and their families for their participation in the study. We also thank  Christelle Thibaut-Charpentier  from the GenomEast sequencing platform in Strasbourg, a member of the " France G énomique" consortium  ( ANR-10-INBS-0009 ), the  Institut de G én étique M édicale d'Alsace , for their technical support, and  Myriam Bronner  from  Nancy University Hospital  for the establishment of the LCL-MM line. We thank  Johann Schor  and  Laura Gu  édon for their help with behavioural experiments. Human NPC work was carried out at ICM's CELIS core facility and NPC imaging at the  ICM Quant facility. We thank  Dr. Bernard Moss  ( NIAID/NIH ) for providing FTSJ1 KO HeLa cells. We thank the members of the  TErBio laboratory  for helpful discussions and reading of the article.
C Carr é received financial support from the  CNRS ,  Sorbonne Universit é (Emergence 2021_RNA-Mod-Diag) , the  Fondation Maladies Rares  (Genomics-2018 # 11809  and Genomics-2020 # 12824 ), the  IBPS-2020 Action Incitative , the  Ligue National contre le cancer Île de France  ( RS21/76-29 ), and  ANR  ( ANR-21-CE12-0022-01 #BiopiC ). Work in the  BA Hassan laboratory  was supported by the  Investissements d'Avenir programme.
Data Availability The RNA-sequencing and small RNA-sequencing data discussed in this publication are deposited and fully accessible, either in NCBI's Gene Expression Omnibus accessible through GEO Series accession number GSE179384 for small RNA-seq or at the European Nucleotide Archive at EMBL-EBI under accession number PRJEB46400 for the RiboMethSeq and PRJEB46399 for RNA-seq.
Overall aims of the core protocol are to collect safety, tolerability, and e cacy data for treatment assessment and marketing authorization. Methods: To develop the core protocol, the VWM Consortium designated a committee, including clinician members of the VWM consortium, family and patient group advocates, and experts in statistics, clinical trial design and alliancing with industries. We drafted three age-speci c protocols, to stratify into more homogeneous patient groups, of ages ≥18 years, ≥6 to <18 years and <6 years. We chose double-blind, randomized, placebo-controlled design for patients aged ≥6 years; and open-label non-randomized natural-history-controlled design for patients <6 years. The protocol describes study populations, agespeci c endpoints, inclusion and exclusion criteria, study schedules, sample size determinations, and statistical considerations.