dataesr/scientific-paragraphs-categorization huggingface dataset:
The importance of each item was measured according to the Index of Relative Importance (%IRI)  (Cortés, 1998). Data analysis. Additional diet information of other common taxa in the area such as Hyalella curvispina Shoemaker, 1942 (Amphipoda), the chironomids Procladius  Skuse, 1889 , Ablabesmyia Johannsen, 1905 , Pelomus Reiss, 1989 , Cladopelma Kiefer, 1921 , Chironomus Meigen, 1803 , Endotribelos Grodhaus, 1987 Phaenopsectra Kieffer, 1921 and Polypedilum Kieffer, 1912  were used from previous studies by  Saigo et al. (2009)  and  Gallizzi et al. (2012). We analyzed the patterns of niche overlap in order to verify if analyzed taxa were structured into guilds. In that case, some taxa would present high niche overlap (those belonging to the same guild) while others would show lower overlap (those of different guilds).
Our data (see Supplementary The detection limit of the analyses was 0. 01%. Saint-E ´tienne measurements: sulfur and carbon contents were determined on bulk rock powders using an Elementar Vario Micro Cube coupled, in a continuous flow mode, with an Isoprime Micromass mass spectrometer, at the Laboratoire Magmas et Volcans, Saint-Etienne (France). About 4-40 mg of bulk rock powder were weighed in tin capsules. Tungsten trioxide catalyst was added to each sample powder in the tin capsule to enhance combustion. Calibration of the carbon and sulfur contents was provided using various amounts of sulfanilic acid standard. Detection limit for reproducible carbon and sulfur contents are, respectively, of 20 and 50 p. p. m. , and relative precision of carbon and sulfur contents are within 10%. d Geochemical models.
Acknowledgements This work was supported by an  ERC   Starting Grant  (HabitablePlanet;  306655 ) and a  NERC   Deep Volatiles Consortium Grant  ( NE/M0003/1 ) awarded to H. W. H. W. and P. B. also acknowledge salary support from a  NERC Advanced Fellowship  ( NE/F014295/2 ) and  ERC   Starting Grant  ( 279828 , MASE), respectively. We thank  G. Nowell  ( Durham University ) for his assistance during isotopic analyses,  N. Riel  ( Durham University ) for instructive discussions, as well as two anonymous reviewers for their constructive and helpful comments.
9, 27, 28 The currently available data indicate that the growth factors and cytokines in TNS may help improve the clinical appearance of aged skin. A pilot study in 14 participants examined the effects of twice-daily application of TNS Recovery Complex for 60 days on photodamaged skin. 9 Physicians measured photodamage on a 9-point scale. In addition, silicone impressions were made for optical profilometry, and punch biopsies were taken to assess Grenz zone and epidermal thickness. Differences were compared using two-tailed t-tests, with p-values <0. 05 considered to indicate statistical significance. On the basis of investigators' evaluations, 11/14 participants in the study showed improvement in at least one facial area. The periorbital region, in particular, showed a statistically significant improvement in clinically assessed photodamage (p=0.
15-0. 38 mg base/ kg (9-22. 5 mg in a 60-kg adult) for a therapeutic index of 2. 5. Primaquine doses (1-20 mg) were tested using a modelled, anthropometric database of 28,138 Cambodian individuals (22,772 healthy, 4119 with malaria and 1247 with other infections); age distributions were: 0. 5-4 years (20. 0 %, n = 5640), 5-12 years (9. 1 %, n = 2559), 13-17 years (9. 1 %, n = 2550), and ≥ 18 years (61. 8 %, n = 17,389). Optimal age-dosing groups were selected according to calculated mg base/kg doses and proportions of individuals receiving a therapeutic dose. Results: Four age-dosing bands were defined: (1) 0. 5-4 years, (2) 5-9 years, (3) 10-14 years, and (4) ≥15 years to receive 2. 5, 5, 7. 5, and 15 mg of primaquine base, resulting in therapeutic doses in 97. 4 % (5494/5640), 90. 5 % (1511/1669), 97.
There is now convincing evidence that increasing treatment failures of dihydroartemisinin-piperaquine (DHAPP), the first-line ACT in Cambodia, is due to a combination of ARPf and PP resistance and that ARPf has probably contributed to the rapidly evolving ineffectiveness of this ACT  [11] [12] [13] [14]. More ACT failures can be expected in areas of ARPf and this alarming scenario underscores the urgency to eliminate falciparum malaria from the GMS. Aside from Vietnam, which uses 0. 75 mg base/kg of PQ, countries in the GMS have been slow to recommend SLDPQ, but attitudes are changing. In August 2015, Cambodia decided to deploy SLDPQ thanks, in part, to reassuring data on the use of 0. 75 mg base/kg of weekly PQ (45 mg in a 60-kg adult) in vivax-infected G6PDd patients  [15]. Moreover, a pilot study of SLDPQ is being conducted in acute uncomplicated falciparum malaria (ClinicalTrials.
gov identifier, NCT02434952) and SLDPQ is being included in antimalarial drug resistance studies (NCT02453308). When countries agree to adopt SLDPQ, one fundamental question is how the recommended dose is translated into a practical dosing regimen. No PQ dosing regimen was suggested in the 2012 recommendation. The 2015 WHO Malaria Treatment Guidelines (http:// www. who. int/malaria/publications/atoz/9789241549127/ en/) contain a weight-based regimen using whole and fractions of a 7. 5-mg PQ base tablet; it is unclear what evidence informed this regimen. Weight-based regimens that require tablet fractions are a major hassle for care providers and result in poor dosing accuracy  [16]. In Cambodia, approximately one-third of malaria patients receive treatment through Cambodia's network of village malaria workers, who do not have weighing scales (D.
Assembling the Cambodian anthropometric database After obtaining permission from the Demographic Health Survey (DHS), the 2014 DHS Cambodian database was downloaded from the DHS web site (http:// www. measuredhs. com). The database contains a broad range of data collected randomly. The data of prime interest were available in children aged < 60 months and women aged 15-45 years: (1) age (years and months for children < 60 months), (2) weight to one decimal place, (3) sex, (4) pregnancy status, (5) residential address, and (6) whether the residence was rural or urban. Other databases, obtained from colleagues at the Centre National de Malariologie and several of its collaborators, consisted of malaria patients, field surveys of individuals in malaria-endemic villages, patients with suspected central nervous system (CNS) infections, and individuals with dog bites who presented to l'Institut Pasteur du Cambodge Rabies Prevention Centre in Phnom Penh.
Modelling the weight-for-age data The raw weight-for-age data were modelled into a growth curve (Additional file 1: Figure  S1 ) by firstly excluding outlying weights for age; these were defined as values falling outside of the 1st and 99th centiles, using Box Cox power exponential model centiles. This resulted in 795 individuals being excluded from the database (Fig. 2 ). In order to obtain the weight-for-age centiles, the data were modelled using the three-parameter Box Cox power exponential distribution  [78]  and the centile growth curves smoothed using the cubic spline smoothing technique  [79]. The modelling was performed in Stata using the 'xriml' macro Stata module  [78]  with cubic spline. Although the 95th or 97. 7th percentiles  [80, 81]  are used as cut-offs for excluding overweight individuals (outliers), we used the conservative 1st and 99th percentiles for the exclusion of outliers to allow for more generalisability of the curve for PQ dosing in the South East Asian population.
Features of the anthropometric database The raw database contained 28,933 individuals aged from birth onwards. After removal of missing data and data modelling, the final database included 28,138 individuals aged ≥ 6 months; the data sources are shown in Fig. 2. The proportion of females was 65. 1 % (18,314/ 28,138); data on sex was missing for 340 individuals (1. 2 %). Children aged 0. 5-4, 5-12, and 13-17 years accounted for 20. 0 % (n = 5640), 9. 1 % (2559), and 9. 1 % (2550) of individuals, respectively, while adults accounted for 61. 8 %  (17, 389). Adults aged > 40-80 and > 50-80 years numbered 4318 (15. 3 %) and 903 (3. 2 %), respectively. Excluding the 1247 patients with CNS infections whose location could not be confirmed, the urban:rural ratio was 1:4. 1. All 5244 urban dwellers were healthy individuals, whilst 17,528 and 4119 rural dwellers were well and had malaria, respectively.
Optimal PQ dose breakdown by individual ages and sex The proportions of females who would receive a therapeutic dose ranged from 63. 2 % (age 5 years) to 100 % (Fig. 3 ); 10 % or more of individuals aged 0. 5 to < 1, 5, 6, Fig. 2  Database structure 15, and 16 years would receive supratherapeutic doses and ≤ 4 % of individuals aged 3, 4, 9, and 14 years would be under-dosed (Fig. 4 ). The proportion of males who would receive a therapeutic dose ranged from 56. 6 % (15 years) to 100 % (Fig. 3 ); 10 % or more of individuals aged 5, 10, 15, and 16 years would receive supratherapeutic doses and ≤ 9 % aged 3, 4, 9, 13, and 14 years would be under-dosed (Fig. 4 ). Statistically significant results were found for male/female comparisons for ages 0. 5 to < 1, 4, 5, 15, and ≥ 18 years. The median mg base/kg dose of PQ base ranged from 0.
Discussion This is the first, optimised, age-based regimen for SLDPQ and was developed using a substantial database of some 28,000 Cambodians across the age, sex, urban, and rural spectra. It has four dosing bands that could be adopted by the Centre National de Malariologie and, if suitable, adopted also by other malaria control programmes in the GMS as part of their urgent efforts to control and eliminate ARPf. The data were obtained from several sources and included data from the two-stage, cluster-randomised nationwide DHS survey, dog bite victims (likely also to be a random sample in Cambodia), village surveys in malaria-endemic areas (some using PCR), and malaria patients. The data from patients with suspected CNS infections are likely to be the most biased samples. However, all of the assembled data overlapped substantially and the difference in weight between urban and rural dwellers was small and not significant.
Symptomatic malaria is a rural disease in Cambodia and affects mostly young adult males who work in forests. However, there are also pools of asymptomatic, submicroscopic falciparum malaria cases (detectable by PCR) affecting all ages and both sexes across many rural regions of Cambodia  [82] [83] [84] [85]. Our weight-for-age database reflected that epidemiology, containing approximately 80 % rural dwellers, malaria patients, and asymptomatic parasiteinfected individuals. Thus, our dosing regimen is applicable to malaria patients and, if MDA becomes policy, asymptomatic malaria parasite carriers as well. Fig. 3  The proportions of females and males who would receive a therapeutic (0. 15-0. 38 mg base/kg) dose of primaquine Although our data are unsuitable as reference data to construct a weight-for-age "growth chart" for Cambodia as a whole, we did construct "growth curves" using Box Cox modelling, which enabled us to calculate the mg base/kg dose of PQ that individuals would receive.
Our weight-forage curve is similar to those of Cambodia, Laos, and Myanmar constructed by Hayes et al. [22]. These countries are also affected by ARPf and share similar G6PDd variants with Cambodia  [86]. Thus, our SLDPQ regimen is generalisable to two of Cambodia's GMS neighbours. There are some limitations to our study. Children aged < 5 years and women of child-bearing age predominated because most of these data came from the DHS survey. Previous databases have suffered from having fewer individuals aged 5-15 years  [21]  and anthropometric data from several of the databases used by Hayes et al. [22]  were also somewhat patchy. Our database had relatively fewer data in the 5-15 years age group, with individual ages numbering between 200 and 300. In common with other malaria-endemic countries, individuals often do not know their exact dates of birth but are usually able to estimate their ages reasonably well.
Acknowledgments We acknowledge with gratitude the  Demographic Health Survey of USAID  for permission to download data from their 2014 survey in Cambodia. WRJT was partly supported by  France Expertise International  through the 5 % initiative as a consultant to  Centre National de Malariologie  in operational research; he expresses "ses profonds remerciements au peuple français. "NJW is a  Wellcome Trust Principal Fellow. Data contributed by RMF were obtained from studies funded by the  Intramural Research Program  of the  US National Institute of Allergy and Infectious Diseases, National Institutes of Health.
Experiments First of all, the whole steganographic approach code is available online 1. Figure  1  presents the results of embedding data in a cover image from the BOSS contest database  (Pevný et al. , 2010)  with respect to the two second order derivative schemes presented in this work. The Ky based approach (resp. the Ko based one) corresponds to the scheme detailed in Section 3 (resp. in Section 4). The payload α is set to 0. 4 and kernels are computed with N = 4. The central column outputs the embedding result whereas the right one displays differences between the cover image and the stego one. It can be observed that pixels in smooth area (the sky, the external access steps) and pixels in clean edges (the columns, the step borders) are not modified by the approach. On the contrary, an unpredictable area (a monument for example) concentrates pixel changes.
Choice of parameters The two methods proposed in Section 3 and in Section 4 are based on kernels of size up to (2N + 1) × (2N + 1). This section aims at finding the value of the N parameter that maximizes the security level. For each approach, we have built 1,000 stego images with N = 2, 4, 6, 8, 10, 12, and 14 where the covers belong to the BOSS contest database. This set contains 10,000 grayscale 512 × 512 images in a RAW format. The security of the approach has been evaluated thanks to the Ensemble Classifier  (Kodovský et al. , 2012)  based steganalyser, which is considered as a state of the art steganalyser tool. This steganalysis process embeds the rich model (SRM) features  (Fridrich and Kodovský, 2012)  of size 34,671. For a payload α, either equal to 0. 1 or to 0. 4, average testing errors (expressed in percentages) have been studied and are summarized in Table  5.
Security Evaluation As in the previous section, the BOSS contest database has been retained. To achieve a complete comparison with other steganographic tools, the whole database of 10,000 images has been used. Ensemble Classifier with SRM features is again used to evaluate the security of the approach. We have chosen 4 different payloads, 0. 1, 0. 2, 0. 3, and 0. 4, as in many steganographic evaluations. Three values are systematically given for each experiment: the area under the ROC curve (AUC), the average testing error (ATE), and the OOB error (OOB). All the results are summarized in Table  6. Let us analyse these experimental results. The security approach is often lower than those observed with state of the art tools: for instance with payload α = 0. 1, the most secure approach is WOW with an average testing error equal to 0.
Pretreatment and de-novo assembly of metatranscriptomic data Raw paired-end Illumina data in FASTQ format were pretreated as follows (read pairs were treated together in all steps to not produce singletons): adapters were removed and each read trimmed to a minimum Phred score of 20 using cutadapt. This left 386 010 015 pairs of good-quality raw reads for the 22 samples. Ribosomal RNA reads were removed using SortMeRNA  (Kopylova et al. , 2012). The resulting non-rRNA reads (corresponding to a total of 155 022 426 pairs of raw reads binned from all samples) were used as input for de-novo transcript assembly with Trinity  (Haas et al. , 2013)  using digital normalization prior to assembly to even out kmer coverage and reduce the amount of input data. Remarkably, data reduction by digital normalization was only ∼ 35 %, hinting at a high complexity of the data set.
This complexity is not surprising regarding that the sample pool contained transcripts from 3 weeks of experiment in two locations (mesocosm vs. lagoon), yet it also means that there will be a relatively large number of transcripts with very low sequencing coverage. This study thus misses the very rare transcripts in the analyzed community. The transcript assembly led to 5 594 171 transcript contigs with an N50 of 285 nt, a median contig length of 264 nt, and an average of 326 nt. Transcript abundance estimation and normalization was done using scripts included in the Trinity package. Align_and_estimate_abundance. pl used bowtie  (Langmead, 2010)  to align all reads against all transcript contigs in paired-end mode, then ran RSEM  (Li and Dewey, 2011)  to estimate expected counts, TPM, and FPKM values for each transcript in each sample.
Only paired-end read support was taken into account. The script Abundance_estimates_to_matrix. pl was modified slightly to create a matrix with RSEM expected counts and a TMM-normalized (trimmed mean of M-values normalization method) TPM matrix (the original script uses FPKM here) using the R package edgeR. The latter matrix was used to discard transcript contigs with very low support (maxTPM > = 0. 25 and meanTPM > = 0. 02). The remaining 3 844 358 transcript contigs were classified using the Diamond tool  (Buchfink et al. , 2015)  with a blastX-like database search (BLOSUM62 scoring matrix, maximum e value 0. 001, minimum identity 10 %, minimum bit score 50) against the NCBI nonredundant protein database from October 2015. Normalized TPM values for each transcript contig were added as a weight to the query ID in the Diamond tabular output samplewise with a custom script, creating one Diamond table per sample which served as input to Megan 5.
11. 3  (Huson and Weber, 2013). Megan is an interactive tool used here to explore the distribution of blast hits within the NCBI taxonomy and KEGG hierarchy. The parameters used to import the diamond output into Megan were minimum e value 0. 01, minimum bit score 30, LCA 5 % (the transcript will be assigned to the last common ancestor of all hits with a bit score within 5 % of the best hit), minimum complexity 0. 3. During manual analysis of the top 100 transcript contigs according to their mean expression over all samples, we found 9 transcripts to be residual ribosomal RNA or internal transcribed spacer. These contigs were removed from the count and TPM matrices for all multivariate statistics analyses. Absence of these rRNA transcripts in the Diamond output was checked and verified.
Sample clustering and multivariate analysis The matrix with expected counts for each transcript contig (see Sect. 2. 2) was used as input for differential expression (DE) analysis with edgeR  (Robinson et al. , 2010)  as implemented in the Trinity package script run_DE_analysis. pl for the set of samples taken from M1 and the Nouméa lagoon, respectively. The edgeR package can compute a DE analysis without true replicates by using a user-defined dispersion value, in this case 0. 1. We are aware that significance values are highly dependent on the chosen dispersion, and thus only considered transcripts with at least a 4-fold expression change for further DE analysis. The script analyze_diff_expr. pl was used (parameters -P 1e-3 -C 2) to extract those transcripts that were at least 4-fold differentially expressed at a significance of ≤ 0.
2. 2), all matching transcripts together with their taxonomic and functional assignment were extracted and false positives discarded (i. e. , transcripts that mapped to the list of specific genes but had a different Diamond hit). The top hit for each transcript was extracted, and the protein classifications manually curated to yield one common description per function (from different annotations for the same protein in different genomes). The TMM-normalized TPM counts were added to each transcript classification, as well as the full taxonomic lineage from NCBI taxonomy. These taxonomic lineages were curated manually to align taxonomic levels per entry. The table was imported into R, all counts per sample summed up for each combination of protein and family-level taxa, and a matrix created with samples as row names and combined protein and family description as column names.
Results and discussion The metatranscriptomic data were analyzed following the strategy outlined in Fig. 1. We obtained taxonomic assignments for 37 % of all assembled transcript contigs. This reflects the fact that the genes of complex marine microbial communities, especially from infrequently sampled ocean regimes like the southwest Pacific, are still insufficiently covered by current databases. The data with taxonomic assignments thus give an overview about the gene expression processes during this mesocosm experiment. With this study, we aimed at identifying global differences in expression patterns between the mesocosm and the lagoon, as well as between the different sampling time points within the mesocosm. We further explored the expression of marker genes for N and P metabolism, and light utilization in the different taxonomic groups.
3 ). Thus, the gene expression profiles within the mesocosm were more diverse than in the lagoon waters. The comparison of the whole data set against the KEGG database (  Kanehisa et al. , 2014)  showed a major difference between M1 and the lagoon samples only in the category energy metabolism, and its subcategories photosynthesis and antenna proteins. These categories comprised 22-36, 8-16, and 2. 7-7. 5 % in the lagoon, respectively, and were in M1 (excluding day 23) constantly below 22, 7, and 4 %, respectively (the Supplement Figs. S1  and S2 ). This lower contribution of energy-related functions in M1 was detectable already at the earliest time point (day 2). Furthermore, diverging dynamics in the microbial community composition and transcriptional activity were triggered in M1 already within the first 48 h (before day 2 was sampled), indicated by the large distance between M1 and lagoon samples on day 2 (Fig.
3 ). The early timing of this effect already on day 2 suggests a rapid remodeling of the microbial community's gene expression upon confinement within the mesocosm. In addition, the DIP spike on the evening of day 4 subsequently triggered distinct ecological successions in M1. The patterns we observed here are close to the three temporal phases defined for the VAHINE experiment based on biogeochemical flux measurements (Bon-  The nonribosomal reads were mapped back onto the assembled transcripts with bowtie  (Langmead, 2010)  to infer each transcripts abundance in each sample using RSEM  (Li and Dewey, 2011). Raw abundances were used for differential expression (DE) analysis and cluster analysis with edgeR on the M1 and lagoon count matrices separately, to find transcripts which changed significantly over time.
To enable direct in-between sample comparison of transcript abundances, raw abundances were converted to TPM (transcripts per kilobase million) and TMM normalized (trimmed mean of M values) in RSEM, creating the final count matrix used for all figures showing transcript abundances. Classifications for these transcripts were generated using Diamond  (Buchfink et al. , 2015)  against the RefSeq protein database. Further, a manually curated list with specific genes involved in N and P metabolism, as well as light utilization (genes of interest, GOIs) was used to extract the corresponding transcripts, but final classifications were inferred from the Diamond output. This information was used to produce the integrated function-per-taxon heat maps. net et al. , 2016a) and nifH amplicon analysis  (Turk-Kubo et al.