dataesr/scientific-paragraphs-categorization huggingface dataset:
In the grid, each algorithm tuning parameter can be specified as a vector of possible values. These vectors are combined to define all the possible combinations to try. As previously mentioned, different models such as RF, ELM, ANN and SVM have been used to design VFA soft sensors. Each of these models has its own parameters that must be tuned to generate an accurate model. Table  6  shows the final tuning parameters obtained with the grid search. No major parameters need to be tuned for the GP model implemented in the Eureqa Formulize software package. The NRMSE and R 2 are estimated based on the training and validation sets for each model. The results obtained using different techniques are shown in Table  7. The lowest validation error was achieved by the model developed with the GP algorithm; thus, it should be considered as the final, ready-to-use model.
The GP optimal soft sensor model generated by the Eureqa package is given as a coefficient in Table  8. The GP was trained based on the full input vector; however, Table  8  shows that the final model contains four variables. This is in accordance with the result obtained by the fscaret method. In addition, to check the prediction ability of each model, the final models were tested using the whole data set without sampling. Figure  6  shows the prediction result of each model. It can be seen that the performance of all models is satisfactory except for the RF model.
0018 kmol•m -3 respectively. To evaluate the robustness of each model, new data sets were generated by the BSM2 simulation with modified biochemical parameters. Then, each trained model was tested based on the newly obtained data set. Figure  7  shows the results of the robustness evaluation for each model. As the RF soft sensor failed, it is not considered for the robustness evaluation. to changing process states. This change in soft sensor accuracy may cause some issues in the process operation, including increasing the maintenance cost and decreasing the quality of final products. Therefore, it is very beneficial to examine how this accuracy degradation affects the final prediction. To do this, we selected three important biochemical parameters of anaerobic digestion: the hydrolysis rate of carbohydrates (khyd,ch), the maximum uptake rate of acetate (km,ac), and the ammonia inhibition constant (kI,NH3).
SEM Analysis Some chemical and physical properties of drugs are related to the characteristics of the particle size, shape, and morphology. Such characteristics influence the formulation homogeneity, dissolution rate, and bioavailability of bioactive compounds, which are tested for the performance study of the desired intermediate and final products  [16]. Table  1  shows the averages of the number of particles calculated by the ImageJ ® software (ImageJ ® 64-bit Java 1. 8. 0_112 for Windows, Bethesda, MD, USA). Samples 08 and 09 did not result in a sample retained in the collector. Cyclone sample 07 cannot be viewed in the SEM, as it has degraded before analysis due to high hygroscopicity. SEM images show that there is no uniformity in the particle sizes, as represented in Figure  1. They presented amorphous characteristics, some spherical surfaces, and they are prone to agglomeration.
UHPLC Analysis Total flavonoids analysis were carried out by Ultra-High Performance Liquid Chromatography (Shimadzu ® , Kyoto, Japan) consisting of the following modules: diode array detector (SPD-M20A), column oven (CTO-20A), auto injector (SIL-20A), degasser mobile phase controller (DGU-20A5), controller system (CBM-20A), quaternary pump (LC-20AT), and LC-Solution data system (software). The data obtained were exported in. txt files and processed in Origin ® OriginPro 2019b Trial software (version 9. 65, Northampton, MA, USA) for the better visualization and overlapping of chromatograms. The chromatographic analysis was suited by the methodology developed by Zeirak et al. [22] , who quantified the total flavonoids in Passiflora edulis fruit pulp by HPLC-DAD. In our work, we transferred this methodology to a UHPLC-DAD system, in a lower scale, as described: the dried extract was reconstituted by diluting 3 mg of each sample into the mobile phase consisting of 0.
NIR Analysis A Near Infrared Spectrophotometer (FT-NIR), MPA ® model (Bruker ® , Bremen, Germany), equipped with an integrating sphere, with liquid sample compartment and probe and OPUS ® Spectroscopy Software (version 7. 0, Bremen, Germany) was used. The method of choice for obtaining the spectra was through the 32-scan background solids probe, 32-scan analysis, and 32-scan resolution in the 12500 to 4000 cm -1 wavelength range. Then, the wavelength data (800 to 2500 nm) were converted for data processing. Analyses were performed in triplicate readings for each sample. The calculations were performed using the PLS-toolbox of the MATLAB version 6. 5 (The Math-Works, Natick, MA, USA). The calculated NIR spectra were log 1/R transformed in the first step, followed by the average spectra for each sample.
The present study is a first attempt to investigate at global scale whether the loss and gain of forest cover can promote outbreaks of vector-borne and zoonotic diseases. Here, we examine the global trends between changes in forest cover in recent decades and epidemics of human infectious diseases, using the GIDEON global database, which is the best available dataset on infectious diseases that has already been used in several studies  (2, (19) (20) (21). We also examine the global pattern between increasing areas of oil palm and epidemics of human infectious diseases. We hypothesize that zoonotic and vector-borne diseases should be favored both by deforestation and by the increase of commodity plantations like oil palm, taking into account the concomitant increase in the size of the human population.
MATERIALS AND METHODS Data on forest cover (in share of total land area) by country from 1990 to 2016 were extracted from the World Bank (https://www. worldbank. org/). Data on oil palm harvested area by country were extracted from the FAOSTAT (http://www. fao. org/faostat/) of the Food and Agricultural Organization (FAO) of the United Nations. Data on population demography by country were also extracted from the World Bank (https://www. worldbank. org/). Data on human infectious diseases were obtained from GIDEON (www. gideononline. com), which contains information on the occurrence of epidemics of human infectious diseases in each nation [see  (2) ]. In the GIDEON database, an outbreak follows the general definition of the WHO as any grouping of cases, including family clusters and epidemics.
We used the classification of vector-borne and zoonotic diseases provided by Smith et al. (20). The 1990-2016 extracted dataset contains 3,884 outbreaks of 116 zoonotic diseases and 1,996 outbreaks of 69 vector-borne infectious diseases. General additive modeling (GAM), an extension of the generalized linear models, was used to investigate the relationships between outbreaks of infectious diseases and forest cover or oil palm areas taking into account both the spatial autocorrelation and the temporal autocorrelation. The model assumes that the response variable is dependent on the univariate smooth-terms of independent variables  (22). All models were fitted using the "MGCV" package  (23). We used the function gam. check to choose the basis dimension for each predictor according to estimated degrees of freedom value in the main effect.
RESULTS Because of the time limitation of the datasets, analyses were narrowed to the period from 1990 to 2016 for disease outbreaks (GIDEON), share of forest cover and area of oil palm (FAOSTAT) by country. Globally, the number outbreaks of zoonotic diseases increased from the period 1990-2016 (Spearman Rho = 0. 99, P < 0. 00001, n = 27, Figure  1A ), as well as the number of outbreaks of vector-borne diseases (Spearman Rho = 0. 94, P < 0. 00001, n = 27, Figure  1B ). In the same period of time, the forest cover slightly but significantly decreased worldwide (Spearman Rho = 0. 91, P < 0. 00001, n = 27, Figure  1C ), while the total area of oil palm dramatically increased (Spearman Rho = 0. 98, P < 0. 00001, n = 27, Figure  1D ). The above global trends resulted in significant increases in both zoonotic diseases outbreaks (Spearman Rho = 0.
Identification of FgH2A. Z as a single H2A variant in F. graminearum We scanned the entire proteome of F. graminearum PH-1 for the presence of proteins carrying a domain characteristic of the C-terminal end of histone H2A, and found the accessions FGRAMPH1_01T26109 and FGRAMPH1_01T03973 as candidates for histone H2A and one variant. We putatively assigned FGRAMPH1_01T26109 as H2A and FGRAMPH1_01T03973 as H2A. Z by protein sequence similarity (see blastp  [55]  reports in S1 File and S2 File). FgH2A and FgH2A. Z are found on chromosomes 1 and 4, respectively. Gene models supported by transcriptomics data  [56] [57] [58]  show that both genes possess two introns, the first one being much larger in FgH2A. Z than FgH2A for which the second exon is larger (S1A Fig). As a point of comparison, the other sordariomycete Neurospora crassa was shown to also possess two introns in its H2A gene  [59]  whereas the eurotiomycete Aspergillus nidulans was shown to possess three ones  [60].
The fact that four mutant strains originating from the same parental strain INRA156 exhibit different phenotypes suggests that the suppressor mutations rather than the influence of the We investigated the occurrence of potential compensatory mutations in all ΔH2A. Z strains in both INRA156 and PH-1 background, similarly to the analysis we performed for INRA349 and its derived mutants. Putative compensatory mutations were detected in the two genes previously identified, namely FGRAMPH1_01G23597 and FGRAMPH1_01G18675, plus eight other genes in the five ΔH2A. Z mutants obtained in INRA156 and PH-1 backgrounds (Table  1 ). Strikingly, most genes are annotated as to encode proteins directly involved in chromatin remodeling in the reference functional database FungiDB  [81, 82]. In three instances, the same gene is affected in two ΔH2A.
Identification of FgH2A. Z We used a Hidden Markov Model-based approach  [110]  to identify proteins carrying a domain characteristic of the C-terminal end of histone H2A (PFAM accession number PF16211) in the reference proteome of F. graminearum PH-1  [78] [79] [80]  available at FungiDB  [81, 82]. Putative identification was then assigned by sequence similarity with the reference protein database (ref_seq_protein_v5) at NCBI using BLASTP  [55, 111]. Genes structures and sequences, protein sequences, and transcript levels were retrieved from FungiDB  [81, 82]. Protein alignment was performed and displayed with CLC Workbench 10. 0.
Sexual reproduction assays Self-fertilization were performed on carrot agar plates as previously described  [120]. Perithecia were observed under microscope two days after sexual induction. Ascospores were harvested by placing the carrot agar plates upside down and allowing the mature perithecia to discharge ascospores on petri dish covers. Ascospores were collected by adding 1 mL of sterile MilliQ water and observed under microscope. A volume of 10 μL of each suspension was inoculated in liquid CM to check whether ascospores could grow or not. Experiments were done in triplicate. (C). Protein alignment of FgH2A and FgH2A. Z. Residues were colored according to Rasmol scheme. Red boxes indicate domains essential for H2A. Z function (vs. H2A) according to Suto et al. [2]. All datasets can be viewed at FungiDB  [3, 4].
Z::H2A. Z (S6A Fig). More surprising, we discovered in I349ΔH2A. Z one mutation elsewhere in the genome (S6B Fig) and a second one in I349ΔH2A. Z::H2A. Z (S6C Fig; verified by Sanger sequencing, S7 Fig), which we hypothesized to be compensatory mutations considered to have beneficial effects on fitness when a deleterious mutation is present [68]. The mutation discovered in I349ΔH2A. Z is a deletion of a single nucleotide A in position 2015 of its CDS (S5B Fig), causing a frameshift mutation (Ile673fs) in the ORF of FGRAMPH1_01G23597, annotated in the FungiDB database as an essential subunit of the histone deacetylase Rpd3S complex. FGRAMPH1_01G23597 encodes a 1225 amino acid-long protein predicted to contain two PHD-type domains (one of the TNG2 superfamily and one PHD2_PHF12_Rco1 particularly found in the yeast Rpd3s component Rco1p) including their zinc and histone H3 binding sites (Fig 4A) using the NCBI CD-Search [69,70].
Work was funded by  Agence Nationale de la Recherche  (www. anr. fr)Grant  ANR-18-CE91-0006  to N. P. , and by  FWF  (https://www. fwf. ac. at/ en/) Grant I  3911-B29  to L. S. Z. C. held a doctoral fellowship from the  China Scholarship Council. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
SfM photogrammetry and orthophotograph/DSM production A standard SfM photogrammetry pipeline  (Lucieer et al. , 2014; Turner et al. , 2014) , using Agisoft © Photoscan Professional program version 1. 2. 6 (Table  2  & Fig. 2 ), was used to build the 3D model and export the end-products. After selection of the non-redundant and good-quality pictures, we initiated the aerial triangulation in a first step named "image alignment" which consisted in: (1) extraction of the key points on each image using a Scale Invariant Feature Transform-like (SIFT) algorithm  (Lowe, 2004; Turner et al. , 2014) ; (2) finding all matching tie points in image pairs; (3) processing the self-calibration starting from a basic camera model using the Exchangeable image file format (Exif) information and refining it using the tie points; (4) calculating the relative orientation of cameras using bundle-blocks adjustment.
Surface sediment colour from orthophotographs A supervised classification of the visible colour of surficial mudflat areas was realised from the orthophotgraph in order to assign to each pixel its appropriate and homogeneous colour classes. The Orfeo Toolbox package and its graphical interface MonteVerdi, developed by the French National Centre for Space Studies (CNES), were used for this operation. Four classes of surface facies, each of which corresponds to an intensity of biofilm development on the mudflat, were identified on the orthophotographs (Fig. 4 ): facies 1 (F1) -dark green surfaces attributed to well-developed benthic biofilm; facies 2 (F2) -light green surfaces corresponding to moderately developed biofilm; facies 3 (F3)ochre surfaces corresponding to soft mud with poorly developed biofilm; and facies 4 (F4) -grey surfaces corresponding to bare dry and wet mud without biofilm or with small patchy biofilm.
Before processing the classification, water surfaces were masked since they were highly turbid and thus induced confusion with bare mud surfaces. Continuous mangrove stands, which can be confused with F1 and F2 facies because of their canopy colour, were also masked by manual digitisation and removed from the analysis. However, the locations of individual mangrove trees, and small sparse patches of mangroves, as distinct from continuous stands, were included in the figures in order to give a visual idea of the stage of mangrove colonisation of the mudflat. The colour-reconnaissance was made from a single Red-Green-Blue (RGB) image, and using the machine-learning "random forest" algorithm which is known to be rapid and efficient with high-resolution datasets  (Inglada et al. , 2015) , and easy to tune compared to other more difficult methods such as Support Vector Machine (SVM).
Acknowledgements This work was supported by the  French National Agency  under the programmes " Young Researcher " ( BIOMANGO :  ANR-12-JSV7-0012-01 ), " Investissements d'Avenir" (LabexMER :  ANR-10-LABX-19 ), and the  Belmont Forum-ANR  Project ' BF-Deltas :  ANR-13-JCLI-0004 , and by the  "Pépinière Interdisciplinaire de Guyane" (PIG CNRS ) and by the  FEDER ECOCOT. The project is a contribution of the  French GDR LIGA researcher network. We thank the two anonymous reviewers for their salient remarks and suggestions for improvement.
C, the cells were then subsequently fixed and stained for actin to observe cell perimeter. Quantification of cell area was done using ImageJ software (n = 3). D, the cells were subsequently fixed and stained for actin (phalloidin in cyan) and paxillin (green). All images are fully representative of three independent experiments. Scale bars, 10 mm. (36). If paxillin is maintained in the dephosphorylated state (Tyr 31/ Tyr 118 ), as for example in the Y31F/Tyr 118 F mutant, stress fibers and elongated FAs are found (71) (Fig. 7B ), suggesting that the regulation of paxillin phosphorylation and its association with FAK is critical to maintain low levels of insulin secretion (Fig. 2B ). How IGF1R signaling regulates adhesion proteins to maintain proper adhesion morphology and insulin secretion is still unclear.
Statistical analysis Statistical significance for differences between experimental conditions was determined using GraphPad Prim 5 software by one-way analysis of variance (for all experiments which compared more than two conditions) or two-way analysis of variance (for insulin secretion experiments that compared basal and stimulated conditions) with Tukey post hoc test for multiple comparison analysis or by Student's t test (when only two conditions were compared). The data are means 6 S. E. , independent experiments, and P values less than 0. 05 were considered significant (ns, nonsignificant; *, p , 0. 05; **, p , 0. 01; ***, p , 0. 001).
The cells were cultured in 2. 8 mM glucose for 4 h in the presence or absence of Rho activator (RhoAc, 0. 25 mg/ml). C, the cells were then subsequently fixed and stained for actin to observe cell perimeter. Quantification of cell area was done using ImageJ software (n = 3). D, the cells were subsequently fixed and stained for actin (phalloidin in cyan) and paxillin (green). All images are fully representative of three independent experiments. Scale bars, 10 mm.
Acknowledgments-We thank  Nicole Aebischer  for punctual and expert technical assistance. Author contributions-C. A. conceptualization; C. A. , K. B. , and B. W. -H. resources; C. A. software; C. A. and K. R. formal analysis; C. A. , K. B. , and B. W. -H. supervision; C. A. , K. B. , and B. W. -H. funding acquisition; C. A. , M. L. M. , and K. B. validation; C. A. and K. B. investigation; C. A. methodology; C. A. writing-original draft; C. A. , M. L. M. , MP, K. B. , and B. W. -H. writing-review and editing; M. L. M. visualization; K. R. data curation; B. W. -H. project administration. Funding and additional information-This work was supported by  European Foundation for the Study of Diabetes/Lilly   Research Fellowship Programme 95057 , the  Gertrude Von Meissner Foundation , and the  Bo & Kerstin Hjelt Foundation.
Notes: a. The option "--scarnapair" instructs MAFFT to use MXSCARNA to perform pairwise structural alignments, which is the default option. To use the LaRA aligner instead, invoke the pair of options "--larapair --laraparams parameter_file", where "parameter_file" is a file with LaRA configuration parameters. A template file "lara. params" is provided with the LaRA software. To use the FOLDALIGN aligner, invoke the option "--foldalignlocalpair" or "-foldalignglobalpair" to perform local or global pairwise alignment, respectively. In benchmarking comparisons  (Katoh and Toh, 2008).
Data analysis The protocol described here has been used to examine the covariation within metastable regions in a structural alignment of 107 mRNAs of type I toxin-antitoxin systems from bacteria of the genus Helicobacter (Masachis et al. , 2019, Figure  8 , figure supplement 1 and 2 therein). All files including the unaligned sequences (in FASTA format), the unedited alignment produced by MAFFT (run with the "--scarnapair" option; in FASTA format), the manually-edited alignment (in FASTA format), the reference secondary structure (in dot-bracket/Vienna format), and the covariation-annotated alignment drawn by R-chie (in PDF format) for both datasets (metastable 1 and 2) analyzed in  Masachis et al. (2019)  are included as supplementary material, to allow the user to learn and reproduce the analyses.
and Windows systems. For Windows, a terminal or Tourasse and Darfeuille, (2020). Structural Alignment and Covariation Analysis of RNA Sequences,Bio-protocol 10 (3): e3511. DOI: 10. 21769/BioProtoc. 3511. Procedure 1. Prepare a set of related (homologous) RNA sequences to analyze, either using local sequences or by downloading sequences from a database. Sequences can be retrieved via keyword searches from general-purpose databases such as NCBI GenBank/RefSeq (https://www. ncbi. nlm. nih. gov/), ENA (https://www. ebi. ac. uk/ena), or Ensembl (http://www. ensembl. org/), or from specialized RNA databases such as SILVA (https://www. arb- silva. de/), ncRNA databases (https://ncrnadatabases. org/), RNAcentral (https://rnacentral. org/), the Comparative RNA Website (http://www. rna. icmb. utexas.
edu/), or Rfam (https://rfam. org/; e. g. , see the Nucleic Acids Research website for a non-exhaustive listing of RNA sequence databases; http://www. oxfordjournals. org/nar/database/cat/2). Some of the RNA databases (e. g. , SILVA, Rfam, Comparative RNA Website) provide sequences that are already aligned in the form of structure-aware multiple alignments. Homologs of RNA sequences of interest can Linux emulator such as Cygwin (http://www. cygwin. com/) or Ubuntu (Yao et al. , 2006), 2013)m/store/p/ubuntu/9nblggh4msv6) is needed. In any case, familiarity with the use of command-line-driven applications is required. Software 1. MAFFT (Katoh and Toh, 2008, https://mafft. cbrc. jp/alignment/software/source. html) 2. R (R Development Core Team, 2018, http://www. R-project. org/) 3. R-chie (Lai et al.
31 and 1. 32 frequently abort. Please cite this article as: also be identified by sequence similarity search, e. g. , using the well-known BLASTN tool. All general databases and some of the RNA databases provide a BLAST service. One can also search for related RNA sequences at the structural level with the help of covariance models using INFERNAL(Nawrocki and Eddy, 2013)or CMfinder(Yao et al. , 2006).
Trial Eligibility HR-NBL1/SIOPEN, an international, randomised, multiarm, open-label, phase 3 trial for high-risk neuroblastoma, opened on 24 June 2002 and is registered with ClinTrials. gov, number NCT01704716, and EudraCT, number 2006-001489-17. All randomisations of the HR-NBL1/SIOPEN trial are closed, and three have been published  [5, 6, 12]. SIOPEN institutions recruited patients after approval of the trial by national regulatory authorities and ethical committees. Parents/guardians and patients provided written informed consent or assent, when applicable. The International Neuroblastoma Staging System criteria (INSS) and International Neuroblastoma Response Criteria (INRC)  [16]  were used to classify the disease and to evaluate responses to therapy. Untreated patients with INSS stage 4 metastatic neuroblastoma aged 1-20 years or INSS stage 2-4 neuroblastoma with MYCN amplification, as determined in SIOPEN reference laboratories  [17] , any age up to 20 years, were eligible.
Acknowledgments: Re-cloning and production of the ch14. 18monoclonal antibody was done at Polymun, Vienna, Austria and was enabled by a SIOPEN fundraising effort in 2001. APEIRON provided additional products at a later stage. Neither Polymun nor APEIRON had a role in the study design or analysis. The authors express their gratitude and appreciation to SIOPEN investigators, treating physicians, clinical research and care teams and most importantly to patients and families facing high-risk neuroblastoma for their committed participation in the trial. The authors are indebted to  Ingrid Pribill  for her important technical assistance in trial management and to  Mag. Claudia Zeiner-Koglin  for editorial assistance.