dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The research leading to these results has received funding from the  European Union Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 241718 EuroBioRef. A part of that research was carried out at TCHK at  Aachen University. We also thank  Sachtleben AG  for providing the TiO 2. The authors furthermore thank  Mr. O. Gardoll ,  Mr. A. Beaurain  and  Mr. G. Cambien  for TG, TPR, XPS and BET measurements.
All known enzymes involved in chitin degradation are classified in the CAZy database (Carbohydrate Active Enzymes, http:// www. CAZy. org/, Accessed 2013 October 09)  [18]. Chitinases (EC 3. 2. 1. 14) belong to glycosyl hydrolases families GH18 and GH19 based on amino acid sequence similarity  [19] ,  [20]. Enzymes harboring carbohydrate binding modules (CAZy Auxiliary Activity enzymes AAs, former CMB33) also display lytic activities toward chitin and are known to act as ''facilitating enzymes'' acting on crystalline chitin (e. g. monooxygenases), and helping in releasing fibers for further degradation by chitinases  [21]. Another chitin degradation pathway relies on chitin deacetylases (EC 3. 5. 1. 41), belonging to the carbohydrate esterase family CE4  [22] , and chitosanases (EC 3. 2. 1.
Soil Sampling Fresh soil cores were collected from Park Grass (lat 51. 481481uN, long 0. 222231uE), Rothamsted, England (Sampling permission issued by the Rothamsted Research Center, see http:// www. rothamsted. ac. uk/for further information, Accessed 2013 October 09). The Park Grass from Rothamsted is an internationally recognized resource and is selected to be a reference for soil metagenomic studies  [32]. The soil from the ParkGrass experiment was monitored over more than 150 years for field-based experiments in order to examine the effects of fertilizers on crops. Soil samples and meteorological records were continuously accumulated since the beginning of experiments (1856), resulting in constitution of an important database on this site. The soil samples from this study are coming from the control part of the site, which has received no specific treatment since then.
Metagenomic DNA was purified on silica column according to manufacturer instructions (Illustra TM GFX TM PCR DNA and Gel Band Purification Kit, GE Healthcare). DNA was quantified by fluorometric assays (Qubit fluorometer, Invitrogen, Life technologies). Extraction reproducibility was evaluated over the 3 replicates of each condition through RISA (Ribosomic Intergenic Spacer Analysis), a bacterial community fingerprinting technique  [38]. This part of the work is presented in Supplemental Data (File S2).
A standard curve ranging from 10 4 to 10 8 molecular copies was used to quantify the 16S rRNA gene in samples (Efficiency = 0. 99, R 2 = 0. 999). Results were analyzed with the manufacturer's software (Rotor-Gene 6000 Series Software 1. 7). Because the 16S rRNA gene copy number is strongly varying depending on bacteria species  [40] , the quantification results were normalized based on DNA extraction yields per gram of soil.
Phylochip Analysis The microarray format used in this study was from Agilent Sureprint Technologies, consisting in 8 blocks of 159000 spots each, designed on a standard glass slide (25 mm675 mm). Each spot holds a 20-mer oligonucleotide probe synthesized in situ. Each oligonucleotide probe occurred at least in triplicate within each block. All blocks were identical. This format allows hybridization of eight samples per slide at the time. Probes target the 16S rRNA gene covering a wide part of the Bacteria and Archaea phylogenic tree. Probes were designed with the ARB software package and the PhylArray software  [41]. The 20-mer probes have a final melting temperature of 65uC 65uC and less than 1. 5 weighted mismatches. Our design includes oligonucleotide probes at different taxonomic levels.
This microarray covers over 400 genera and 10000 OTUs (''species'' or ''hits''). The reproducibility of the taxonomical profiles between bottle replicates was tested and validated with preliminary phylochips, as described in Supplemental Data (File S3). The bacterial 16S rRNA gene was amplified from pooled metagenomic DNA, corresponding to microcosm replicates from the original soil 060 before incubation, and chitin enriched samples from day20:0620, 1620 and 10620. The PCR reaction was performed using universal primer pA 59-TAATACGACTCACTATAGA-GAGTTTGATCCTGGCTCAG-39 and pH-T7 59-AAG-GAGGTGATCCAGCCGCA-39  [42]. 2 ml of diluted metagenomic DNA (<15 ng) was mixed with 1. 5 ml of reverse and forward primers (10 mM), 45 ml of distilled sterile water, and 1 ml Taq Polymerase (Invitrogen). PCR was conducted at 94uC for 4 mins and then with 35 cycles of 94uC for 45 s, annealing at 55uC for 45 s, and elongation at 68uC for 95 s, followed by 68uC for 5 mins.
Microarray Scanning and Data Processing An Innoscan 700 scanner (Carbonne, France) was used for scanning microarray slides based on manufacturer's instructions. Raw hybridization fluorescence signal for each spot was determined based on the signal-to-noise ratio (SNR), which was calculated by using the following formula: SNR = (signal intensity -background)/background standard deviation. Total probe fluorescence signal, including negative controls, was transformed by calculating the signal in log 2. Since at least three replicates exist for all oligonucleotide probes, outliers were eliminated when any individual spot was greater than 3 standard deviations from the average of all replicates. Analysis of variance (ANOVA) was used to evaluate positive probes. Since probes have different phylogenetic depths, the genera described here were those for which all relevant probes were positive.
Pyrosequencing and Data Analysis Up to 10 mg of metagenomic DNA corresponding to the enrichment time day 20 were extracted and purified as described in section ''Metagenomic DNA extraction'' for each condition and replicate. Based on preliminary analysis (File S2 and File S3), only two replicates were sent for further pyrosequencing investigation. Pyrosequencing replicates are indicated as: 0620a, 0620b, 1620a, 1620b, 10620a and 10620b. Metagenomic DNA was sequenced with the 454 Titanium pyrosequencing technology (Roche) at the Genoscope Sequencing Center (Paris, France). Raw data were cleaned from artificial duplicates using the CD-HIT-454 software  [45]. On average, each metagenome yielded 559671 reads (+/26. 3610 4 ), with an average read size of 392 bp (+/232) and an average GC content of 63% (+/20.
5). Metagenomic datasets were analyzed through read annotation using the MG-RAST platform for both functional and taxonomical annotations  [46]. The taxonomical affiliation of reads was done against the M5NR public database. The functional affiliation of reads was done against the SEED database  [47] , which is based on a hierarchical classification of reads into subsystems related to specific functions. The input parameters for both taxonomical and functional annotation were: 60% minimal identity, 30 bp minimal alignment length, and 1. E-05 e-value threshold. Statistical analyses were performed with Rgui  [48]  and STAMP software  [49]. Two pyrosequencing datasets corresponding to the original soil at day 0:060a and 060b were used for comparison  [33]  (Table  1 ). The reference metagenomic database generated from the Park Grass soil was used as a control to compare the different conditions, and validate the changes observed after microcosm incubation and chitin treatment  [33].
Pyrosequencing Analysis For comparison purposes, 13 pyrosequencing runs obtained from the same soil were integrated to reinforce the analysis  [33]. These metagenomes are considered as a reference metagenomic database (annotated as Roth within the text) from the Park Grass soil at Rothamsted research station (Harpenden, UK), including the actual variation imputed to seasons, depth and DNA extraction protocols (Tab. 1). All annotated metagenomes used in this study were submitted to a clusterization-based method in order to hierarchically organize the factors structuring the taxonomical profiles of the soil bacterial community (Fig. 3 ). The method used for DNA extraction is clearly responsible of the first dichotomy (Fig. 3, clusters A  and B ), with on one side metagenomes extracted by the ''indirect'' approach (bacterial cell separation from the soil matrix before lysis, cluster A) and on the other side those obtained by a direct technique (in situ lysis of cells, cluster B).
Metagenome 1620a is displaying an intermediary pattern, with higher similarities shared with 0620a/b and 1620b cluster. All the conditions used in this study, including Roth, 060, 0620 and 10620 were statistically compared together through a Welch's test, except for the 1620 metagenomes as only few differences were observed between this condition and the incubation control 0620 (Fig. 3 ). Three level of analysis were considered considering all the conditions available: (1) analysis at sensu stricto, which includes only the incubation control 0620 and the chitin enriched 10620; (2) analysis at sensu medio, including the non-treated samples 060 for investigation of the microcosm effect; and (3) analysis at sensu lato, considering all the metagenomes available in the Rothamsted database Roth.
Impact of Enrichment at the Functional Level At the functional level, differences observed are more subtle than the ones detected at the taxonomical level. In fact, the global functional profiles of metagenomes are very similar across all conditions when observed at the highest classification level. This can easily be explained by the fact that incubation and enrichment are contributing to select adapted genomes and their associated genes and functions, which are for the major part redundant when classified in an arbitrary database such as SEED. However, at a lower functional subsystem level, specific features were selected by enrichment (Fig. cosamine (NAG)'' subsystem was increased in chitin-amended metagenomes when compared to the controls, as well as many subsystems related to carbon metabolism (e.
Furthermore, most of these genera are not yet referenced in the CAZy database for having species with genes involved in chitin degradation. This reinforced the idea that chitin treatment has selected a consortium of unknown species harboring genes related to chitin degradation and utilization. Some of the secretion systems were increased in chitin 10620 treatment, including type III secretion systems (T3S) and two partner secretion pathway (TPS). T3S are present in most pathogenic Gram-negative bacteria and are involved in motility and pathogenicity  [80] , while TPS are involved in many interactions between bacteria and their habitat (e. g. aggregation and biofilm formation, iron acquisition, pathogenicity…)  [81]. Concomitantly, an unknown secreted and conserved protein referenced as DOE COG3533 was increased.
Ethical considerations Specimens and data were collected within the activities of the national public health sentinel surveillance systems and therefore this was considered to be non-research activity. Fever surveillance, including arbovirus protocols, was approved by the respective ministries of health and the National Ethics Committee of Madagascar (FWA00016900). Before taking each specimen, physicians explained the purpose of the surveillance system. Patients were then free to refuse to participate. Oral consent was documented in the patient form. This research did not cause any additional trauma and all injuries suffered by individuals were associated with routine care. The specimens used in this study were collected as part of the routine care, and this study was designed retrospectively.
We demonstrate the usefulness of this sampling method for the molecular diagnosis of Chikungunya infection. In particular, dried blood spots were very nearly as suitable as frozen serum specimens for the diagnosis of recent infection by CHIKV. region (GenBank AF369024) (Table  1 )  [28]. The Ag-Path One Step RT-PCR kit (P/N: 4387391, Ambion, Foster City, CA, USA) was used for amplification. The reaction mix, in a final volume of 25 ml, consisted of 2. 5 mL of RNA extract, primers at a final concentration of 0. 5 mM, and the CHIK probe at a final concentration of 0. 3 mM. The RT-PCR conditions were as follows: a 40 min reverse-transcription step at 50uC followed by denaturation for 10 min at 95uC and 45 cycles of denaturation at 95uC for 10 s and annealing/extension at 56uC for 60 s. Positive controls, negative controls and no template controls (NTC) were included in each series.
Statistical analysis The sensitivity and specificity of the assays were evaluated using two-by-two tables. The sensitivity and specificity of the DBFP specimens were determined by comparison with the results obtained with venous blood samples (sera) by the routine diagnostic test (real-time RT-PCR). Data were recorded and analysed statistically by R Analysis with R version 2. 7. 0 software  [29]. Results with a two-sided p value#0. 05 were scored as being significant. A non-parametric test, the Wilcoxon test, was also carried out. Receiver Operating Characteristic (ROC) plot analysis was performed to determine the best threshold value for the CHIKV RNA load by real-time RT-PCR obtained with DBFP compared with the values obtained from sera. As the mean value for the negative reference sample is expected to be smaller than the mean value for the positive reference sample, inverse transformation of the test data was used to prepare data for analysis as previously described  [30].
Determination of Ct cut-off value (Ct-off) for real-time PCR with DBFP samples The value of the Area Under Curve (AUC) was 0. 96 (95% CI:[0. 93-0. 99]. The optimal Ct cut-off for real-time RT-PCR with dried blood spot samples was 40 with an AUC = 0. 96; this value correctly classified 95. 3% of the data (sensitivity = 93. 4% and specificity = 96. 2%) (Figure  2 ). All 11 discordant cases had Ct values between 37 and 39 cycles. A second real-time RT-PCR was performed in triplicate for 8 of these 11 discordant paired samples and both concordant and discordant results were obtained with the triplicate repeats (data not shown).
Acknowledgments We are grateful to  Dr. Alain Michault  and his team for technical assistance. We also thank the Regional Public Health Director from the  Region of Vatovavy-Fitovinany  ( Dr. Albert Rasolofomanana ) and the staff of the primary health care centre in Mananjary ( Drs. Maurice Randriarison ,  Cyrille Rakotomalala  and  Jamesy Andriamanjara ). This work is dedicated to the memory of the late  Dr. Figaro  from the primary health care centre in Toamasina, who consistently supported arbovirus surveillance work and always participated actively in all our studies. Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Ministry of Health.
Excitation light and fluorescence emission were separated using a dichroic mirror (z561/658; Chroma, Bellows Falls, VT). The emitted fluorescence was selected using a long-pass filter (RU 664; Semrock, Rochester, NY). Images were recorded using an EMCCD camera (iXON, Andor, Belfast, Ireland). Cy5-DNA time series of 350 frames were recorded at 10 frames per second with 100 ms exposure time. Image analysis. DNA particle tracking was performed using Imaris 7. 2 software (Bitplane, Zurich, Switzerland). DNA positions were determined for each frame of the movie stack through the "spot objects" option, and the trajectory paths were constructed using the autoregressive motion algorithm. As a trajectory itself can exhibit parts with different modes of motion, we developed a program for the segmentation of trajectories into portions of only diffusive motion or only active transport (Supplementary Figure  S1 ).
ACKNOWLEDGMENTS We acknowledge financial support from the  Deutscher Akademischer Austauschdienst (DAAD) , the  Ministère des Affaires Etrangères (MAE) , and the  Ministère de l'Enseignement Supérieur et de la Recherche (MESR)  (program  PHC   PROCOPE 2010-2011 ). We also thank the  Sonderforschungsbereich  ( SFB 969 ) for financial support. Dominik Wöll  thanks the Zukunftskolleg and  Thorsten Rieß  thanks the  Interdisciplinary Center for Interactive Data Analysis (INCIDE)  of the  University of Konstanz  for financial support. This research was conducted within the scope of the  EBAM European-Associated Laboratory (LEA)  and the  COST Action   TD1104  (http://www. electroporation. net).
Dynamic Light Scattering-Dynamic light scattering (DLS) analyses of ND-AspRS, AdT, Hp0100, and various binary and ternary complexes were performed at 25 °C in a Zetasizer Nano S instrument (Malvern Instruments Ltd. , Worcestershire, United Kingdom). Protein samples were diluted in buffer containing 50 mM NaH 2 PO 4 and 300 mM NaCl (refractive index ϭ 1. 34) to prepare the required concentrations; 40-l samples were used for analyses. For particles that are smaller than the wavelength of incident light (), the intensity of light scattered (I) is related to the diameter of the particle (d) by the Rayleigh equation (I∞d 6 / 4 ). We used the Mie theory within the Nano S software to convert the intensity (I) versus size (d in nanometers) distribution data to volume versus size (d) distribution (supplemental Fig.
In all other cases, single predominant particles were observed (Ͼ90% of the total peak volume after volume size distribution data processing) and characterized. (All DLS spectra are provided in supplemental Fig. S4. ) By DLS, ND-AspRS alone had a hydrodynamic diameter of 9. 7 Ϯ 0. 2 nm. This diameter increased to 11. 5 Ϯ 0. 3 nm upon the addition of equimolar Hp0100, indicating binary complex formation. AdT alone had an observed hydrodynamic diameter of 10. 6 Ϯ 0. 2 nm, which increased negligibly to 11. 0 Ϯ 0. 3 nm upon the addition of Hp0100. It is unclear why this shift in particle size was statistically insignificant. The particle diameters determined by DLS represent the diameters of a perfect hard sphere. It is possible that the Hp0100-AdT complex is more tubular and, consequently, less amenable to characterization by DLS or that assembly of this complex could result in compaction such that the observed diameter is similar to AdT alone.
Molecular Analyses The left kidney of mice was excised, washed with 1X PBS and subsequently used for molecular studies. Total RNA was collected with the help of the RNeasy ß Mini Kit (Qiagen, Courtaboeuf, France) and 1 mg of total RNA was engaged in a reaction of RT-PCR (Superscript II Rnase H Reverse Transcriptase ß (Invitrogen, Villebon sur Yvette, France)). cDNA were subsequently quantified using the LightCycler Mix (Roche, Meylan, France) using the following conditions : 95uC for 5 min followed by 40 cycles (95uC for 15 secondes, 60uC for 10 secondes and 72uC for 15 secondes) and denaturation. Quantitative PCR was carried out on a LightCycler ß 480 sequence detection system. The primers were designed using Primer3 and GeneQant softwares. The efficiency of each set of primers was assessed by dilution curves and only set with efficiency higher than 95% were used.
| I out |= α(V Source , Z Source , [Z Cable ], [Z Appliance ], Z Power-grid , f ) (1) The Multiconductor Transmission Line Theory  [12]  can be applied, assuming that the height of the conductors above the ground is smaller than the shortest wavelength. The conductor dielectric insulator losses are considered negligible in this study. Based on the above physical considerations and since the ground is considered a good conductor, it can be assumed that the propagated mode is a quasi-TEM one. The conductors are randomly arranged in the raceway by defining the minimum admissible distance between wires. By using a plug-in of the CRIPTE code  [13, 14] , developed by the French Aerospace Laboratory (ONERA), named "Laplace calcul", 200 random cross-sections have been generated in order to build a significant realistic database.
It is assumed that the obtained dispersion has a mean and a standard deviation derived as follows: the phase dispersion is chosen as ± 5° and the amplitude level dispersion as ± 10% (in dB). Moreover, the open-circuit socket has been introduced in the database in order to simulate an unloaded socket. The measured and simulated loads have been integrated into the CRIPTE code. In the latter study, it is considered that the database is finally composed of 71 loads.
The CRIPTE Code One aspect of the Electromagnetic Topology theory  [13, 14]  consists in the decomposition of a non-uniform complex network into a set of connected uniform sub-networks by means of tubes and junctions  [18]. The transmission lines are the tubes and the connecting points are the junctions as well as the input and output points. An iterative application of the electromagnetic topology theory allows the compaction of complex networks; an example is depicted in Fig. 3. In order to model the interleaving of conductors in the raceway, each tube T i (i denotes the i-th tube) is the compaction of sub-networks composed of four tubes T ij of equal length characterised with the per-unit parameters obtained from random cable cross-section. Using the CRIPTE code, the cable modelling methodology has been applied and the set of characterized loads has been used in order to compute the propagation of electromagnetic interferences in a realistic network.
Application to low voltage network modelling The Monte-Carlo simulations have been applied to derive random configurations following the defined considerations. 200 cables cross-section have been generated. As a result, in our analysis 200 uniform networks can be simulated. Moreover, the model of the network is based on three one meter long tubes, thus C ! !"" =1. 3 10 6 random configurations can be generated (C refers to the binomial theorem). Concerning the factor 2 (connection state of the appliances), networks have been analysed with the following considerations: loaded (the modelled network is defined with two sockets and the database of impedances is composed of 71 appliances, thus C ! !" = = 2. 4 10 3 random configurations can be generated) and unloaded (x 2L ) by appliances. It has been verified the statistical moments (mean and standard deviation) are converging (less than 5 % of variability) respectively for a number N of experiment given as follows: N(y 1 ) = 200, N(y 2 ) = 10 4 , N(y 3 ) = 10 4 and N(y 4 ) = 10 5.
Advances in groundwater storage monitoring are crucial for water resource management and hydrological processes understanding. The evaluation of water storage changes (WSC) often involve point measurements (observation wells, moisture probes, etc. ), which may be inappropriate in heterogeneous media. Over the past few years, there has been an increasing interest in the use of gravimetry for hydrological studies. In the framework of the GHYRAF (Gravity and Hydrology in Africa) project, 3 yr of repeated absolute gravity measurements using a FG5-type gravimeter have been undertaken at Nalohou, a Sudanian site in northern Benin. Hydrological data are collected within the long-term observing system AMMA-Catch. Once corrected for solid earth tides, ocean loading, air pressure effects, polar motion contribution and non-local hydrology, seasonal gravity variations reach up to 11 µGal, equivalent to a WSC of 260-mm thick infinite layer of water.
2009; Hinderer et al. 2012). This project studies the strong seasonal monsoon signal within different aquifers (sedimentary in Niger and weathered hard rock in Benin) and climatic contexts (Sahelian and Sudanian zones). We also used the intensive hydrological monitoring that has been carried out at Nalohou site since 1992 in the frame of the AMMA-Catch longterm observing system (www. amma-catch. org; Lebel et al. 2009) , which is an observatory of RBV (Réseau des Bassins Versants), the French critical zone exploration network (rnbv. ipgp. fr). The data are available upon request via the AMMA-Catch online database (http://database. amma-international. org/). The objective of this study is to compare absolute gravity monitoring with seasonal WSC deduced from independent hydrological data (neutronic measurements and water-table levels).