dataesr/scientific-paragraphs-categorization huggingface dataset:
Literature review The measurement items for the performance measures were developed using an extant literature review followed by an in-depth unstructured discussion with the practitioners from the manufacturing industry. The discussions with the practitioners helped us to establish the content validity of the identified measures. Similar approaches were used in the previous studies focused on developing measurement items  (Parasuraman et al. , 1988; Peter et al. , 1982). The literature search was performed on the Scopus database using the keywords; "Smart manufacturing" and "Industry 4. 0" and "Intelligent Manufacturing" and "Digital manufacturing" in pairwise comparison with "Performance measurement" and "Performance management. " The initial search resulted in a total of 1469 papers, which was further reduced to 348 articles by limiting the search to papers published in academic journals in the subject categories: business management, operations management, decision sciences, and computer/technology management.
Exploring the underlying factors of performance measures (Phase II) In this phase, a preliminary study was conducted to establish the statistical validity of the measurement items identified from Phase I. Exploratory Factor Analysis (EFA) was performed in this phase to determine the underlying performance dimensions and finalize the measurement items for use in the final survey. The data was collected through an online survey of 210 working practitioners from 142 auto-component manufacturers in India. The questionnaire for the second phase of the study included 102 measures. Out of 102 measures, 52 were worded positively and 50 were worded negatively. A fivepoint Likert scale with the extreme values ranging from "Strongly Disagree" (1) to "Strongly Agree" (5) was developed and the respondents were asked about their agreement to what extent the measures could be used for the competitive benefits occurring from SMS investments.
Purpose -The purpose of this study is to explore South African and Italian consumers' attitude toward online wine purchasing. In detail, through the application of the technology acceptance model (TAM), this research intends to explain the antecedents of consumers actual online purchasing of wine in South Africa and Italy. Design/methodology/approach -Two questionnaire-based surveys were conducted, yielding a sample of 190 consumers in South Africa and 179 in Italy. Data were analyzed through several techniques including ttests, principal component factor analyses, and binary logistic regressions. Findings -Overall, the findings show that South African and Italian online wine consumers are more similar than the offline wine consumers. However, perceived usefulness has an impact on the use of the online channel to purchase wine in Italy but not in South Africa, whereas perceived complexity has an effect in South Africa but not in Italy.
Conclusions The purpose of this study was to explore South African and Italian consumers' attitude toward purchasing wine online and to understand the antecedents of their actual usage of wine e-commerce. Two questionnaire-based surveys were conducted, yielding a sample of 190 consumers in South Africa and 179 in Italy. Several techniques including t-tests, principal component factor analyses, and binary logistic regressions were used to analyze the data. From the data analyses, the perception of usefulness and complexity of wine e-commerce was looked at to develop two hypotheses for both South African and Italian consumers.
Sample and Procedure The student population under study comprised of students 15 to 18 years old from non-compulsory secondary education who were enrolled at teaching centers in Spain. The survey for students was carried out through a stratified sampling in educational centers of eight autonomous regions (Andalusia, Basque Country, Catalonia, Castilla and Leon, Galicia, La Rioja, Madrid, and Valencian Community). Based on data from the Ministry of Education, Culture, and Sport, we targeted 1764 students to achieve a confidence level of 95% with an error margin of 2. 3%. However, 131 questionnaires were considered null due to missing responses and therefore removed from the final sample. Consequently, the final sample of students was 1633 (92. 57% response rate). Regarding parents, 1764 questionnaires were sent to the parents of the students, and we received 839 valid responses (47.
Data Analysis Having selected the questions/variables included in the study, a code was used as an identifier of each datum, thereby yielding a data set with 1633 cases (valid student questionnaires) and 72 characteristics or measures (answers given to each of the questions or variables analyzed). The dataset was analyzed by means of principal components analysis (PCA), which is a statistical method based on reducing the dimension of the data being analyzed (reducing the number of variables), for the analysis of the results from the questionnaire. In other words, having a set of data with multiple variables, the end purpose is to reduce the number of variables in an effort to minimize information loss, as far as possible, for the new data. The new factors of principal components obtained through the redimensioning process are each the result of a linear combination of the original variables and will, in turn, be independent from each other.
Results Following the analysis of the variables based on the data obtained with the questionnaire, the PCA projection of the dataset is shown in Figure  1 , where each point is the representation of each one of the 1633 valid cases (student questionnaires) with its 72 selected characteristics (answers given to each of the questions or variables). In the analysis of the projection, we identify four groups in which the cases are distributed according to proximity and neighborhood. Clusters 1. 1 and 1. 2 correspond to the cases furthest from the part with the highest density and groups 2. 1 and 2. 2 correspond to the densest clusters (see Figure  1 ).
Results Following the analysis of the variables based on the data obtained with the questionnaire, the PCA projection of the dataset is shown in Figure  1 , where each point is the representation of each one of the 1633 valid cases (student questionnaires) with its 72 selected characteristics (answers given to each of the questions or variables). In the analysis of the projection, we identify four groups in which the cases are distributed according to proximity and neighborhood. Clusters 1. 1 and 1. 2 correspond to the cases furthest from the part with the highest density and groups 2. 1 and 2. 2 correspond to the densest clusters (see Figure  1 ). Based on the proposed work objectives, we analyzed the average scores of youth entrepreneurial interest (EI), the family's interest in the young becoming entrepreneurial (EIC), and family support (FS) for each of the clusters resulting from applying the PCA technique (see Table  2 ).
Materials and methods We analyzed the latest Nepal Demographic and Health Survey data (N = 13,436) collected between June 2016 and January 2017, using a multistage stratified sampling technique. Participants aged 15 years or older from selected households were interviewed with an overall response rate of 97%. Primary outcomes were hypertension and normal blood pressure defined by the widely used Seventh Report of the Joint National Committee (JNC7) and the American College of Cardiology/American Heart Association (ACC/AHA) 2017.
A total of 383 wards were selected altogether, 184 from urban and 199 from rural areas. Finally, a total of 11,490 households (rural-5,970 and urban-5,520) were selected for the NDHS 2016  [21]. Flowchart of the analytic sample selection process is given as a supplementary figure (S2 File). The trained interviewers collected data visiting the households. The overall response rate was approximately 97%. Blood pressure (BP) was measured among 15,163 individuals with 6,394 men and 8,769 women aged 15 years and above. In our study, a total unweighted sample was 13,371 comprising men  (5, 535)  and women  (7, 836) , after excluding participants aged <18 years and discarding the missing and extreme values. The total weighted analytic sample was 13,436 participants (men 5,646 and women 7,790) aged 18 years and above.
For examining the associations between SES and hypertension, all potential confounders for each predictor were selected using prior knowledge and directed acyclic graphs (DAGs) to avoid the 'Table  2  fallacy' in a multivariable model and to observe unbiased total effect estimates for predictors  [26, 27]. For the brevity, we have reported 'measurement-only definition' of hypertension/normal blood pressure, if not stated otherwise, especially when we assessed associations between hypertension/normal blood pressure and SES. However, similar analyses for 'medical definition' of hypertension have been provided as supplementary data (S1 File). Comparable analyses based on the new guideline of ACC/AHA 2017 have also been given as supplementary data. Two-sided P-values and 95% CIs are presented.
The veracity of our findings is contingent on replication with longitudinal data and more comprehensive assessments of SES. To the best of our knowledge, this is the first study found mediating roles of the modifiable risk factors of CVD in the SES and hypertension association using a nationally representative sample in a resource-poor setting. Our study also first time assessed the association between SES and hypertension according to standard hypertension JNC7 guideline and a new guideline recommended by the ACC/ AHA 2017. We observed sex and rural-urban differences in blood pressure outcomes by sex and urbanity stratified analysis. For instance, recent studies also emphasized to investigate the SES gradient along with sex and rural-urban differences in blood pressure outcomes in Nepal  [7, 8, 11, 37].
Seventy-two hours after incubation with antileishmanial drugs, 10 μl of PrestoBlue was added directly into existing hanging drops containing the samples and control media. The samples were incubated for an additional 60 min at 37 °C. Inhibition was determined by using a fluorescence plate reader at 560 nm excitation and 590 nm emission, and the percent of inhibition was calculated using the formula presented below: %Inhibition ¼ Absorbance control ð Þ -Absorbance sample ð Þ Absorbance control ð Þ Â 100 The percent inhibition of different drug concentrations and calculations for the IC50 value were performed using GraphPad Prism version 6 program (San Diego, USA).
Data analysis IC 50 value of promastigotes and intracellular amastigotes were calculated for the mean and standard deviation (SD) from triplicate experiments. Statistical analysis was performed using the statistical package for social sciences (SPSS) software, version 16. 0 for Windows (SPSS Inc. , Chicago, USA). The correlations between drugs and isolations were determined using one-way ANOVA. p b 0. 05 was considered to be statistically significant for differences and correlations. Differences in promastigote and intracellular amastigote forms for each drug were compared for statistical analysis using an independent t-test. A p-value b 0. 05 was regarded as indicating statistical significance. The IC 50 values of each anti-leishmanial drug and each Leishmania stage are presented in the table.
Our patient presented with persistent diarrhea (> 14 days), a course usually encountered in such immunodeficient patients  [11]. To the best of our knowledge, no cases of cryptosporidiosis associated with fingolimod have been reported in the published literature. However, we found 6 cases of cryptosporidiosis listed under fingolimod in the database Vigilyse International database (https://www. who-umc. org/vigibase/vigilyze/). There was 1 man and 5 women (mean age 42 years), among whom cryptosporidiosis occurred after a period of 7 months to 3 years following the introduction of fingolimod; a prolonged hospitalization was noted in 3 cases but no death was reported. Searching for Cryptosporidium sp. which is very small is very difficult in stools, and thus practically requires microscopic analysis with specific stains  [16].
Background: Rabies post-exposure prophylaxis (PEP) vaccination via intradermal (ID) route is common in Asia. Accumulating evidence indicates PEP can be shortened to 3 visits in 1 week without affecting persistence of antibodies or immune memory post-booster. Methods & Materials: This Phase III, mono-center, open-label randomized controlled trial [NCT01622062] in the Philippines provided data following ID simulated PEP with purified Vero cell rabies vaccine (PVRV, Verorab ® ) that supports this. Patients (600) aged ≤50 years exposed to suspected rabid animals were allocated 1:1:1 into 3 groups for ID vaccination: Group (G)1, Category II exposure, 1 week-4 site PEP regimen without purified equine rabies immunoglobulin (pERIG); G2, Category III exposure, 1 week-4 site PEP regimen with pERIG; G3, Category III exposure, Thai Red Cross (TRC) PEP regimen (2-2-2-0-2) with pERIG.
Sequence analysis ORF analysis was performed using the ORF Finder tool implemented in SnapGene (https ://www. snapg ene. com/) and reviewed manually by comparative alignment to closely related PV genotypes. Potential splicing patterns for the E1^E4 ORF were predicted using the Softberry Fsplice program (https ://www. softb erry. com/ berry. phtml ?topic =fspli ce&group =progr ams&subgr oup=gfind ) with the Capra hircus genome as a reference. Sequence similarities were calculated based on the single gene alignments. The molecular weight of the putative proteins was calculated using the ExPASy (Expert Protein Analysis System) Compute pI/Mw tool (https ://au. expas y. org/tools /pi_tool. html) [14]. Protein motifs and domains were identified manually or predicted using prosite tool (https ://prosi te.
expas y. org/)  [15, 16]. TATA Box, pA signals as well as E2 and E1 binding sites were identified manually. Potential E2 binding sites were reconfirmed by screening the TRANSFAC Database  [17]  using the Match tool (https ://gene-regul ation. com/pub/progr ams. html#match )  [18]  as described previously  [19].
Phylogenetic analysis We collected 376 full-length PV genomes from the PaVE database (pave. niaid. nih. gov, accessed 28 May 2019) and the ChPV2 genome was added to this data set (Additional file 1: Table  S6 ). The E1, E2, L2 and L1 genes were extracted from the collected genomes. Genes were aligned individually at the amino acid level using MAFFT v. 7. 310  [20] , corrected manually, and backtranslated to nucleotides using PAL2NAL v. 14  [21]. The alignments were filtered using Gblocks v. 0. 91b  [22]. The full 377 PV data set contained recombinant PVs infecting Cetaceans  [23] [24] [25] , known to have undergone a recombination event between the early and the late gene regions. Therefore initial tree construction was performed on the concatenated E1E2 and L2L1 alignments separately. Maximum Likelihood (ML) phylogenetic inference was done using RAxML v8.
2. 11  [26] , under the GTR + Γ4 model for the nucleotide alignments using six partitions (three for each gene corresponding to each codon position), or under the LG + Γ model for the amino acid alignment using two partitions (one for each gene), and using 1000 bootstrap replicates. The trees were rooted using the SaPV1 sequence. Subsequently, the recombinant and unresolved taxa were removed from the full data set, leaving us with a reduced data set of 324 PVs. The individual genes were again aligned and filtered as described above. The concatenated E1E2, L2L1, and E1E2L2L1 alignments were used to construct ML trees as described above. For the E1E2L2L1 alignment, twelve partitions were used at the nucleotide level, and four partitions were used at the amino acid level. The trees were rooted using the SaPV1 sequence.
Based on the constructed trees, the close relatives of ChPV2 were extracted from the full data set, leaving us with a reduced data set of 17 PVs. Besides E1, E2, L2, and L1, the E6 and E7 genes were extracted from these selected genomes. The individual genes were aligned without Gblocks filtering. The E6, E7, E1, E2, L2, L1, and the concatenated E1E2L2L1 alignments were used to construct ML trees for this reduced data set as described above. For the individual gene alignments, three partitions were used at the nucleotide level, and no partitions were used at the amino acid level. For the E1E2L2L1 alignment, twelve partitions were used at the nucleotide level, and four partitions were used at the amino acid level. Possible rogue taxa were identified with an algorithm implemented in RAxML. For the individual gene trees, majority rule consensus trees were constructed, and subsequently used for constructing a supernetwork using Splits Tree 4  [27].
Phylogenetic analysis In order to assess the phylogenetic relationships of ChPV2, we collected the available 376 full-length PV genomes from the PaVE database (pave. niaid. nih. gov, accessed 28 May 2019) (Additional file 1: Table  S6 ). First, we constructed ML phylogenetic trees of the concatenated early (E1E2) and late (L2L1) gene sequences at the nucleotide (Additional file 1: Figure  S2 ) and amino acid (Additional file 1: Figure  S3 ) levels. Based on these four trees, we observe that ChPV2 clusters within the Beta-XiPV crown group, and is closely related to XiPVs infecting cetartiodactyles. The position of ChPV2 is wellsupported (bootstrap support of 97 to 100) and is basal to XiPVs, 1 species (infecting bovines). After removing the recombinant and unresolved taxa, ML phylogenetic trees were constructed of the concatenated E1E2 and L2L1 alignments (Additional file 1: Figure  S4  and Additional file 1: Figure  S5 ), as well as of the concatenated E1E2L2L1 alignments at the nucleotide (Fig.
Acknowledgements We thank  Vet. Ali Haciömeroglu  for providing the clinical sample used to isolate ChPV2. We are grateful to the  Genotoul bioinformatics platform Toulouse Midi-Pyrenees (Bioinfo Genotoul)  for providing computing and storage resources. The authors acknowledge the  IRD itrop HPC (South Green Platform) at IRD Montpellier  for providing HPC resources that have contributed to the research results reported within this paper.
Funding Open Access funding enabled and organized by Projekt DEAL. Funding was provided to  Eric Ehrke-Schulz  by the " Alexander Karl-Preis 2018 " from the  Stiftung Tumorforschung Kopf-Hals. AW was supported by the  European Union   Horizon 2020 Sklodowska-Curie research and innovation program  grant ONCOGENEVOL (Contract Number  750180 ).
Preliminary experiment. The Ani_OS001 strain and the ISP phage (chosen based on its in vitro lytic activity) were assessed, respectively, for their infectivity and for their safety. Three groups (A 0 , B 0 , C 0 ) of four mice each were inoculated (50 mL) with 10 5 CFUs of Ani_OS001 (inoculum titre based on previous results, data not shown), 10 8 PFU of ISP phage and PBS (negative control),  respectively, in one experiment. One hour post-inoculation (HPI 1), all the mice were further inoculated with 50 mL of PBS. Two mice were euthanised in each group after 24 h (HPI 24) and 48 h (HPI 48) post-inoculation, respectively, their blood was collected and their mammary glands were dissected for histopathological analysis then blended with a Tissue lyser II (Qiagen, Hilden, Germany) for bacterial counts.
Statistical analysis Statistical analyses were performed on in vivo data with GraphPad Prism8, (GraphPad Software, Inc. , San Diego, CA, USA). Kaplan-Meier survival curves and log-rank (Mantel-Cox) tests were performed to analyse the G. mellonella larva survival curves. Bonferroni's multiple comparisons test was used to compare the variations of bacterial and phage titres inside G. mellonella larvae and murine mammary glands.
Genome comparison of Ani_OS001 and Ani_OS001m The draft genome of Ani_OS001 and Ani_OS001m are available from GenBank, accession numbers VXKU01000000 and VXKV01000000, respectively. The VarScan analysis revealed only two single polymorphism nucleotide (SNPs) between the two strains. One is associated with a region without any annotation according to Prokka (position 25 of contig OS001-00027 C → T). The second SNP (G → T) occurred in position 60 157 of contig OS001-00001. The Prokka annotation revealed SdrE, a gene coding for a member of the microbial surface components recognizing adhesive matrix family molecule (MSCRAMM). This mutation resulted in a G899V mutation at the protein level.
Experimental Leishmania infection Mice were infected with 1. 0 x 10 8 (intraperitoneal route) stationary L. donovani promastigotes and weight and well-being was monitored during the infection. Intraperitoneal inoculation was used given that it results in a higher homogeneity of infections between animals  [19, 20]. For GLS inhibition experiment early on infection, BPTES was administered via intraperitoneal route, at days 2, 4, 6, 8 and 10 post-infection (12. 5 mg/kg). Control animals were equally injected with vehicle (sterile corn oil and 5% DMSO). Glutamine administration was performed by oral gavage (500 mg/kg/day) throughout infection. The dose was chosen based on the previous reported data in humans  [21]  and according with the daily intake of glutamine in previous studies with rodents  [22, 23].
Reads were trimmed using Trimmomatic v0. 36 with the following options: TRAILING:30, SLIDINGWINDOW:4:20 and MINLEN:30. All other options used the default values. Quality check was performed on raw and trimmed data to ensure the quality of the reads using FastQC v0. 11. 5 and MultiQC v1. 5. The quantification was performed with Kallisto v0. 44. Differential expression analysis was performed in R v3. 5. 0 using the DESeq2 v1. 20. 0.
Flow cytometry The spleens were minced and forced through a 70-μm cell strainer (Corning Inc. ) and red blood cells were lysed with ACK lysis buffer (0. 15 M NH 4 Cl, 10 Mm KHCO3 and 0. 1 mM EDTA). The anti-mouse monoclonal antibodies used to perform this study were purchased to BioLegend (CA, USA) and shown in Supplementary S1 Table. Samples were acquired on a LSRII flow cytometer (BD Biosciences) and data analyzed using FlowJo software (FlowJo LLC).
Quantitative PCR analysis Total RNA was isolated from uninfected and L. donovani infected bone-marrow macrophages (during 6, 24 and 48 hours) with TRI reagent (Sigma), according to the manufacturer instructions. RNA concentration was determined by OD260 measurement using a NanoDrop spectrophotometer. Total RNA (10-250 ng) was reverse transcribed using the Xpert cDNA synthesis Mastermix (Grisp). Real-Time quantitative PCR (qRT-PCR) reactions were run for each sample on a Bio-Rad CFX96 Real-Time System C1000 Thermal Cycler (Bio-rad). Primer sequences were obtained from Integrated DNA technologies (USA). The RT product was expanded using the SensiFAST SYBR Hi-ROX kit (Bioline) and the results were normalized to the expression of the housekeeping gene 28s. After amplification, cycle threshold-values (Ctvalues) were calculated for all samples and gene expression changes were analyzed in the CFX Manager Software (Bio-Rad).
Statistical analysis Statistical analyses as described in figure legends were performed in GraphPad Prism 6 software. A two-way analysis of variance (two-Way ANOVA) followed by a Sidak's post-test, Mann-Whitney test of variance and Kruskal-Wallis non-parametric test followed by a Dunn's post-test were performed accordingly with the correspondent experimental design. ANOVA assumptions were analyzed through normality test (Shapiro-Wilk test, p>0,05) and homogeneity of variances evaluation. Statistically significant values are as follows: � p < 0. 05, �� p < 0. 01, ��� p < 0. 001.
Parasite viability was assessed at 96and 120-hours post-infection. A Mann-Whitney t-test was used to evaluate parasite viability in the presence of BPTES. The presented data is representative of three independent experiments and values are expressed as mean ± SD. p<0. 05; � p<0. 01; ��� p<0. 001. https://doi. org/10. 1371/journal. pntd. 0008125. g001 These results demonstrated that the inhibition of glutaminolysis impaired effective protective T cell immune response increasing L. donovani parasite burden.