dataesr/scientific-paragraphs-categorization huggingface dataset:
In order to test hypotheses 3 and 4, we use the recently developed PROCESS macro for SPSS  (Hayes, 2013)  with 5000 bootstrap samples as recommended by  (MacKinnon et al. , 2012). This macro is both useful and appropriate for calculating the interaction effects  (Hayes, 2013). Hypothesis 3 states that employees' calling orientation moderates the positive relationship between external CSR and perceived external prestige, such that the higher the calling orientation, the stronger will be the relationship, and vice versa. Table  4  shows that the interaction term (external CSR × calling orientation) has a significant effect on perceived external prestige. This implies that the effect of external CSR on perceived external prestige increases in tandem with calling orientation. The results, therefore, support the Hypothesis.
, 2003). Since all the constructs were measured using a cross-sectional design, a single-factor model was also analyzed. This showed a poor fit to the data, implying that no single factor explains the bulk of the variance. Thus, common method variance was not a serious concern in our dataset. In future, we suggest using a longitudinal design to address any concerns relating to causal relationships and cross-sectional data. The use of a more sophisticated design will provide robust evidence of this mediating relationship  (Aguinis and Glavas, 2012). We also propose including the behavioral outcomes of organizational identification (e. g. , task and contextual performance, actual turnover), which can be measured using objective data. This would strengthen the research design and enhance the reliability of the results.
Tests of Hypotheses The hypotheses were tested using Hayes' (  2013 ) "process" macro in SPSS. 21. This approach to mediation is preferred to more traditional approaches to mediation (e. g. Baron and Kenny, 1986) , as it does not require a normal sampling distribution. The approach draws on ordinary least squares regression to estimate direct and indirect effects of mediation and uses 1000 bias corrected bootstraps. Since our theoretical model implies that the two mediators are not interchangeable, we estimated two parallel dual mediator models to test the hypotheses, with job involvement and work overload modelled as mediators. Tables  3  and 4  present the results of the hypotheses testing. The results of Table  3  show that HRM-performance attributions is positively related to job involvement, but not work overload, and job involvement is negatively related to emotional exhaustion.
Limitations Although our cross-lagged design is a methodological strength, there are limitations associated with its use. For instance, not all participants completed the survey at both time points. Further, we used shortened versions of some scales, and all variables were derived from self-report measures, raising concerns of common method variance. However, established recommendations for controlling for the influence of common method bias were followed  (Podsakoff et al. , 2003)  and the statistical analyses revealed that common method variance did not wholly explain the associations in the data. Future research should employ the full items from established scales, and use non self-report data to mitigate these concerns. Another potential limitation is our ability to generalise to the broader organisation from which the sample was drawn.
In order to understand the strategic alliances management, it isn't enough to realize an investigation or having a database general study. They may reveal and confirme only explicit knowledge. For understanding and shed light on tacit knowledge, it is imperative to do a research action study, or at least a longitudinal study. This method led us to delve deeply on the machinery of alliances management. The authors of this article elaborate managed Two Erasmus European project in ordre to transfer competences on innovation. This projects are between universities from UE and Maghreb. Hyp 2: the alliance success depend on cooperation/coordination quality process Hyp 3: to achieve the goals of the alliance, it is necessary that the coordination/cooperation cycle goes through the different hierarchical levels of the various organizations involved in the relationship.
The volume of data to be processed can be considerable. For example, billions of lines published every day on supermarket receipts are valuable masses of information, but so are big data extracted and processed from operational systems. One specificity of business intelligence tools is their remoteness and independence from operational systems. These are tools that affect the strategic level of the organization. This separation is to avoid penalizing operational systems asking them to ensure heavy processing  (sorting, extraction, computing). It also helps protect operational data by authorizing a posteriori analysis. It is therefore necessary to extract information from massive operational systems to inject into specific tools for "data warehousing" into multidimensional databases. The frequency of these extractions should be adapted to the analytical (daily, weekly, monthly) needs.
It was explained by five criteria: a. Data quality: measured the correspondence between needs and the available data, it also measured the exactness of these available data by using BI tools and the quality of data at a level of detail suitable for the tasks. b. Localization of data: measured the ease of determining the availability and the exact sense of data (the existence in due course and under the deliberate size of public information). c. Authorization of access: measured the accessibility of data (ease of connection and ease of extraction of public information). d. Data compatibility: between the various sources of data. e. Relevance of the system: making sure that BI tools did not raise unexpected problems or difficulty of use. Variable IV: The dimension "intensity of BI tool use" was explained by: The intensity or frequency of use: it was a subjective appreciation of the increase or the decrease of the degree of use.
RESULTS AND DISCUSSION Descriptive statistics have been used in order to show population characteristics. We have used SPSS. 19 to treat data. In total, 60. 4% of respondents were male and 39. 6% were female. Furthermore, 17. 2% of respondents were 23 years or less, 30. 6% were between the ages of 23-26 years, 24. 6% were between the ages of 27-35 years and 27. 6% were 36 years or older. Finally, our sample of users was composed of 58. 2% students and 41. 8% professionals (Table  1 ). According to Table  2 , about 36% of respondents used general tools such as search engines and other free tools (such as Google search, Google alert and Netvibes), while 45% used specialized tools like databases of patents or sector studies (such as Espacenet, Patenscope and Xerfi), and a final 19. 4% used platforms to monitor the competitive environment and social networks (such as Cognos, Business Objects, SAS, Sindup and Digimind).
Beta-2-microglobulin (B2M) is a component of the HLA class I complex at the cell surface, and should theoretically be upregulated when there are more HLA-molecules on the cell surface. However, the B2M gene is located on a different chromosome (15q21). HLA-C was not analyzed, as it has a tenfold-lower expression at the protein level than HLA-A and -B  [32, 33]. As the peptide-loading machinery is needed to get a functional HLA class I molecule expressed at the cell surface, we looked at several of these genes. In cases where Illumina provided multiple probes for the same gene, the mean value of these probes was used for further analysis. One of four probes for HLA-A (ILMN_2165753) was omitted because of discordancy with the values of the other three HLA-A probes. The Illumina array data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus  [34]  and are accessible through GEO Series accession number GSE84976 (https://www.
Validation Quantitative polymerase chain reaction (qPCR) was performed, as described previously  [35] , in duplicate on the selected genes for HLA and HLA-regulation activators, as a validation of the results found with gene-expression profiling. In short, RNA was extracted from the fresh frozen primary tumors using an RNeasy Mini Kit (Qiagen). Complementary DNA (cDNA) was synthesized with the iScript cDNA synthesis kit (Bio-Rad). Beacon Designer (Biosoft) was used for primer design. Primers for ACTB (βactin; OMIM 102630), GAPDH (OMIM 138400), RPL13 (OMIM 113703), and RSP11 (OMIM 180471) were included for selecting suitable reference genes. Gene expression was calculated by normalizing the C-value of each marker to the reference genes. Reference genes were selected based on their stable expression in the tissue, which was measured with the geNorm Software  [36].
Statistics Data analysis of the material obtained at the LUMC in Leiden was performed with the statistical programming language R version 3. 0. 1 (R: A Language and Environment for Statistical Computing, R Core Team, R foundation for Statistical Computing, Vienna, Austria, 2014, http://www. R-project. org), supplemented with specialized packages for SNP and RNA analysis. The main package used for SNP analysis was aroma. affymetrix [43] [44] [45] , supported by 'DNAcopy' (Venkatraman E. Seshan and Adam Olshen, DNAcopy: DNA copy number data analysis. R package version 1. 34. 0), 'sfit' (Henrik Bengtsson and Pratyaksha Wirapati (2013), sfit: Multidimensional simplex fitting. R package version 0. 3. 0/r185, http://R-Forge. R-project. org/ projects/matrixstats/), and 'R. utils' (Henrik Bengtsson (2014), R.
utils: Various programming utilities, R package version 1. 29. 8, http://CRAN. R-project. org/package=R. utils). Data of eightyfour healthy controls served as reference set, obtained with the same Affymetrix 250K Nsp chip (Affymetrix, Santa Clara, CA, USA) by the Department of Human Genetics at our center. The ' Aroma. Affymetrix' package made it possible to use these SNP microarrays to determine copy number values  [43] [44] [45]  The packages used for RNA microarray analysis were 'limma' version 3. 16. 8 and the specific packages for Illumina microarrays: 'lumi' version 2. 12. 0, 'annotate' (R. Gentleman, annotate: Annotation for microarrays, R package version 1. 38. 0), and 'illuminaHu-manv4. db' (Mark Dunning, Andy Lynch and Matthew Eldridge, illuminaHumanv4. db: Illumina HumanHT12v4 annotation data (chip illuminaHumanv4), R package version 1.
18. 0). Data of the xenografts and corresponding original human tumors were analyzed at the Institut Curie (Paris, France) with R software (version 2. 12) at gene level using custom Brain array Chip Description Files (CDF) based on Entrez Gene database (version 13) as described in detail by Laurent et al. [42]. For this study, a paired sub-analysis was made at the Institut Curie with regard to the genes of our interest. All other statistical analysis was performed with SPSS 20. 0. 1 (IBM SPSS Statistics, IBM Corporation, Armonk, NY, US). Cumulative survival was calculated with Kaplan-Meier and its significance analyzed with the log rank test. Hazards ratios (HR) were measured with Univariate Cox regression models. Associations for clinical categorical variables with gene expression were determined using the Mann-Whitney U test (Wilcoxon rank sum test) for non-parametric analysis.
The genes that code for the HLA class I and II antigens are located on chromosome 6p, which has prognostic importance in UM. In order to determine whether the level of HLA class I and II antigens was influenced by a gene-dosage effect, we determined the presence of chromosome 6 by SNP array, and compared HLA and B2M gene expression levels with chromosome dosage. Additionally, we examined the gene-dose effect of chromosome 3, as a previous study from our laboratory had indicated an association between loss of chromosome 3 and increased HLA expression levels on primary UM  (8). An overview of the clinical, chromosomal, gene expression, and histological data is provided in S4 Table.
W e report on markedly different frequencies of genetic lesions within subsets of chronic lymphocytic leukemia patients carrying mutated or unmutated stereotyped B-cell receptor immunoglobulins in the largest cohort (n=565) studied for this purpose. By combining data on recurrent gene mutations (BIRC3, MYD88, NOTCH1, SF3B1 and TP53) and cytogenetic aberrations, we reveal a subset-biased acquisition of gene mutations. More specifically, the frequency of NOTCH1 mutations was found to be enriched in subsets expressing unmutated immunoglobulin genes, i. e. #1, #6, #8 and #59 (22-34%), often in association with trisomy 12, and was significantly different (P<0. 001) to the frequency observed in subset #2 (4%, aggressive disease, variable somatic hypermutation status) and subset #4 (1%, indolent disease, mutated immunoglobulin genes).
Cytogenetic and SNP-array studies Interphase fluorescence in situ hybridization (FISH) for the 13q14, 13q34, 11q22, 17p13 chromosomal regions and the centromere of chromosome 12 was performed as previously described. 30 For 30 cases recurrent genomic aberration data was obtained using the Affymetrix 250K SNP Array. 31.
Sequence analysis of IGHV-IGHD-IGHJ rearrangements PCR amplification, sequence analysis and interpretation of IGHV-IGHD-IGHJ rearrangements were performed following established international guidelines and using the IMGT® database and the IMGT/V-QUEST tool, as previously reported. 2, 7, 8, 10 lonotypic IGHV gene sequences were defined as either mutated or unmutated based on the clinically relevant 98% cutoff value for identity to the closest germline gene. 4, 5 ssignment of cases to specific stereotyped subsets was performed following established guidelines and based on the following stringent criteria: the IG sequences must: (i) have ≥ 50% amino acid identity and 70% similarity within the variable heavy complementarity-determining region 3 (VH CDR3); (ii) have the same VH CDR3 length and the shared amino acid patterns must occur at identical codon positions; and (iii) utilize IGHV genes belonging to the same phylogenetic clan.
Funding The authors would like to thank the  Swedish Cancer Society , the  Swedish Research Council , The Lion 's  Cancer Research Foundation and Selander's Foundation, Uppsala ; the  ENosAI  project (code  09SYN-13-880 ) co-funded by the  EU  and the  General Secretariat for Research and Technology of Greece ; the KRIPIS action, funded by the  General Secretariat for Research and Technology of Greece ; the  AIRC Special Program Molecular Clinical Oncology , 5 x 1000, # 9965  and  10007  and  Investigator grant ,  Milano, Italy) ;  Ricerca Finalizzata 2010 -Ministero della Salute, Roma, Italy ;  Leukaemia and Lymphoma Research, Kay Kendall Leukaemia Fund, UK ; the  Spanish ICGC-CLL   Genome  Project funded by the  Instituto de Salud Carlos III (ISCIII) ; The  Danish Cancer Society ; the research grants  IGA  MZ  CR NT13493-4/2012  and  MSMT CR VaVPI  project  CZ.
1. 05/1. 1. 00/02. 0068(CEITEC) ;  H2020  " AEGLE, An analytics framework for integrated and personalized healthcare services in Europe" , and  H2020  " MEDGENET, Medical Genomics and Epigenomics Network " (No. 692298 ), both funded by the  European Commission , for their financial support; and also  Barbara Kantorova  and  Veronika Navrkalova  for their technical help with NOTCH1 and SF3B1 sequencing analysis of the Czech cohort. L. -A. Sutton et al. 966 haematologica | 2016; 101(8).
A custom tool was used for the comparative processing of the results. SNPs were called with a minimal coverage of 5-fold and a minimal frequency of 90% for the SNP allele. Problematic sites as identified by  Morelli et al. (2010) , genomic non-core regions as defined by  Cui et al. (2013)  as well as annotated repeat regions, rRNAs, tRNAs and tmRNAs were excluded from the SNP analysis. SNPs were annotated using SnpEff  (Cingolani et al. , 2012)  with default parameters. The upstream and downstream region size was set to 100 nt. At McMaster University, raw reads were trimmed and merged using SeqPrep (https://github. com/jstjohn/Seq-Prep), requiring a minimum overlap of 11 base pairs to merge. Reads shorter than 24 base pairs were filtered out using SeqPrep. Merged reads and unmerged forward reads were concatenated and mapped to the CO92 reference sequence (NC_003143) using the Burrows-Wheeler Aligner (BWA) version 0.
Acknowledgements We acknowledge The Director of the  Regional Department of Archeology (DRAC-PACA / Aix-en-Provence, France)  for granting us access to the Observance skeletal collection ( 4422-17/09/2009 ). Funding was provided by  European Research Council  starting grant APGREID (to JK, KIB and AH),  Social Sciences and Humanities Research Council of Canada postdoctoral fellowship  grant  756-2011-501  (to KIB),  National Health and Medical Research Council (NHMRC)  grant (to ECH and HNP), and an  NHMRC   Australia Fellowship  to ECH, as well as a  Canada Research Chair  and  NSERC  discovery research grant to HNP. We thank  M Green  and  SN DeWitte  for providing us with the corrected date for 6330. HNP thanks former and current members of the  McMaster aDNA Centre  for their help with this study.
After repeatedly pipetting to detach the adherent amoebae, a 250-µl fraction of each specimen was fixed in paraformaldehyde (4%) then transferred to a suitable tube for flow cytometric analysis on the BD LSRFortessa (BD Biosciences) at 0, 24, and 48 h after infection. Data acquisition was performed using log scales for instrument scatter parameters, forward scatter (FSC) and side scatter (SSC), respectively associated with size and internal complexity of the event analyzed. Protocol threshold was adjusted on FSC parameter. Acquisition and analysis were performed using "BD FACSDiva Software. " The number of collected events was fixed for all specimens. We gated our amoeba population using the density plot representation SSC versus FSC. We performed serial dilutions from 10 6 to 10 1 amoebae/ml to calibrate the analyzer, to determine the reliability of the counts and to establish the limit sensitivity of detection of the flow cytometer to choose a lysis threshold that corresponds to the loss of amoebae.
, 2013; Yoosuf et al. , 2014). For our technique, we conducted three blind co-cultures as an enrichment step; primoculture, sub-culture, and final culture without any microscopic observation. Data acquisition on the flow cytometer was performed 24 and 48 h following the final enrichment step. The number of collected events was fixed for all samples. Uninfected amoebae were used as a negative control. They were analyzed first and used to gate the population of amoebae according to the parameters defined above. The percentage of live and dead cells was evaluated. Moreover, the presence and percentage of debris characterizing amoebal lysis was also evaluated in the FSC SSC plot. All data from LSR Fortessa were analyzed using kaluza software (Beckman Coulter). An arbitrary threshold for amoebal loss of more than 50% after 24-48 h was used to define the possible presence of a lytic agent.
Sybr green was used to label DNA (SYBR Green I nucleic acid gel stain; Molecular Probes, Life Technologies, USA). The final concentration of SYBR Green I was a 10 -4 dilution of the commercial stock solution. For an amoebal suspension at a density of 1 × 10 6 , we added 5 µl of the DiD cell labeling solution and mixed thoroughly by gentle pipetting. The cells were then incubated for 1 h at 30 • C, washed three times by centrifugation and re-suspended in PAS (the purpose was to eliminate amoebal debris from the gating). We used Mimivirus, Marseillevirus, Faustovirus, and a parachlamydia-like bacterium (an intra-amoebal chlamydia isolated in our laboratory). Data for this chlamydia, that we proposed to name Candidatus Rubidus. massiliensis (C. R. massiliensis), were submitted to the EMBL database and were assigned Bio-projects number PRJEB6078; the accession numbers for the genome at EMBL are CCSC01000001-CCSC01000005) and the corresponding paper has been also submitted.
A second sample contained a Mimivirus of genotype A from Lebanon, and the eight remaining samples contained a mix of Mimivirus genotypes A and C, 3 from Dakar and 5 from Marseille. For the same sewage samples inoculated on V. vermiformis, five were positive and we isolated a new giant virus specific for Vermamoeba, named Faustovirus E12  (Reteno et al. , 2015). Seven other viruses belonging to the same family were also isolated from the different sewage samples (3 from Marseille, 3 from Dakar, and 1 from Lebanon; the genomic data corresponding to these isolates were submitted to the EMBL database and were assigned Bio-projects numbers respectively: E24: PRJNA279158, E23: PRJNA279157, E9: PRJNA279166, D3: PRJNA279161, D5: PRJNA279159, D6: PRJNA279164, Liban: PRJNA279165). No lysis was detected on the other tested protozoa.
This material was analyzed by HPLC, using a 250 mm x 4. 6 mm Kromasil Reverse phase C-18 HPLC column 5μ pack and a JASCO model 2000 (PU2080, UV 2075, AS2055) HPLC system with CHROMPASS software. The extract was resolved with an isocratic mobile phase of 0. 2% Orthophosphoric acid (aqueous): Acetonitrile (ratio 78:22) at 1. 5 ml/min and monitored on-line by UV detection at 280 nm. The structures of the individual fractions were confirmed by mass and NMR spectroscopy. The trimer form of the above composition of IND02 was isolated and purified in the following procedure. The crude cinnamon extract used for isolating the IND02 was used after removal of all unwanted compounds. The clarified extract was passed through a sequence of chromatographic columns consisting of a Nonpolar Adsorbent resin to trap the other oligomers and eluted with ethyl alcohol.
Acknowledgments This work was supported by the  Agence Nationale de la Recherche sur le SIDA (ANRS)  and B. J. C. was supported by a grant from  Sidaction  and ''la  Fondation Pierre Bergé". Sui-Yuan Chang  acknowledges the funding from  National Science Council (NSC) ,  Taiwan. Soluble CD4  and mAb 17b were obtained through the  NIH AIDS Research and Reference Reagent Program  from  Drs. S. Iyer ,  J. Robinson  and  J. Sodroski , respectively. The following HIV-1 strains were obtained through the  NIH AIDS Research and Reference Reagent Program  from the  UNAIDS Network for HIV Isolation and Characterization  ( 92UG029  and  98IN017 ),  Dr. N. Halsey  ( 92HT599 ),  Drs. D. Ellenberger ,  P. Sullivan  and  R. B. Lal  ( 96USHIPS4 ). This work used the platforms of the Grenoble Instruct centre (ISBG;  UMS 3518 CNRS-CEA-UJF-EMBL ) with support from  FRISBI  ( ANR-10-INSB-05-02 ) and  GRAL  ( ANR-10-LABX-49-01 ).
This work was supported by  Indus Biotech  and the  Agence Nationale de la Recherche sur le SIDA (ANRS). B. J. C. was supported by a grant from  Sidaction  and ''la  Fondation Pierre Berge''. SYC acknowledges the funding from  National Science Council (NSC) ,  Taiwan. This work also used the platforms of the Grenoble Instruct centre supported by the  Agence Nationale de la Recherche  ( ANR-10-INSB-05-02  and  ANR-10-LABX-49-01 ). Dr. Ekambaranellore Prakash  from  Indus Biotech  was involved in planning the experimental study. Indus Biotech  was involved in the preparation and analysis of the compounds IND02 and IND02-trimer which were isolated, purified and characterized by  Dr. Mohan Vishwaraman. The other funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.