dataesr/scientific-paragraphs-categorization huggingface dataset:
). They were then transferred to 100% resin mix overnight. New resin was made and the samples left in it for at least 6 h before being placed in embedding capsules and further incubated at 60uC for 15-24 h until the resin was solid. Embedded samples were cut in 90 nm sections on an ultramicrotome (Reichert Ultracut E) with a diamond knife (Diatome) and visualised using a Transmission Electron Microscope (Hitachi H600). Images were developed on electron microscope film 4489 (Kodak), then scanned at high resolution (12,800 dpi612,800 dpi), and analyzed with ImageJ software, version 1. 34s.
Statistics Data are mean 6 s. e. m. The p values are from ANOVA and post hoc Student's two-tailed t tests. For multiple comparisons p values are corrected using a procedure equivalent to the Holm-Bonferroni method (for N comparisons, the most significant p value is multiplied by N, the 2nd most significant by N-1, the 3rd most significant by N-2, etc. ; corrected p values are significant if they are less than 0. 05) or Dunnett's post hoc test. Normality of data was assessed using Shapiro-Wilk tests, and nonparametric Kruskal-Wallis and Mann-Whitney tests, which do not assume data follow a normal distribution, gave the same conclusions for significant and nonsignificant differences in all cases. For Figure  2 , when the ANOVA gave an insignificant p value (. 0. 05), we used the more conservative Student's two-tailed t test without correction for multiple comparisons to give a lower limit to the p value for post hoc comparisons (i.
Acknowledgments We thank  W. Stallcup  for  NG2 ,  J. R. Bermingham  for SCIP,  D. Colman  and  J. Huang for Caspr ,  K. W. Roche  and  B. S. Chen  for pNR2C antibodies,  Mike Peacock  for EM assistance, and  Kirsten Caesar ,  Claudia Eder ,  Alasdair Gibb ,  Nicolas Granger ,  Nicola Hamilton ,  Kristjan Jessen ,  Ilias Kazanis ,  Karolina Kolodziejczyk ,  Lesley Probert ,  Angus Silver , and  Jing-Wei Zhao  for comments on the manuscript.
Data analysis The data was analysed by the chi-squared, Bartlett's chisquared, and Kruskal-Wallis tests using Sigma Plot 2001 software (Sigma Plot 2001 Statistical Analysis Software, San Jose, CA, USA) and Epi Info version 3. 5. 1. The results were expressed as mean ± standard deviation. Statistical significance was reached if P <0. 05, with a 95% confidence interval (CI).
Statistical and Data Analysis ANOVA with repeated measures was used to test the 7-day changes of inflammatory markers, the average effect of polymorphisms and the polymorphisms/7-day changes interaction. Data were log transformed for CRP concentrations. Results are presented as arithmetic means (SD) or geometric means (range of 1 SD). Statistical analyses were performed using SAS 9. 3 software (SAS Institute, Cary, Cary, NC, USA). Statistical significance was set at p ≤ 0. 05.
Structural characterization The structure and phase distribution of the coatings were determined by x-ray diffraction (XRD) using a Siemens diffractometer in a Bragg-Brentano geometry and Co Kα radiation (1. 788 97 Å). The grain sizes were calculated applying the Scherrer equation after a nonlinear Voigt curve fit on the (111) peaks of the diffractograms using OriginPro 8 software. The chemical bonds were evaluated by micro-Raman spectroscopy. Raman spectra were acquired with a Renishaw InVia microscope using the 514. 5 nm Ar laser line.
Structural analysis Figure  1  shows the XRD diffraction patterns for the deposited coatings with three different Ag/Ti atomic ratios (0, 0. 37 and 0. 62) and the lattice parameters (a). The reference peaks, obtained from the International Centre for Diffraction Data (ICDD) database, for TiC 0. 3 N 0. 7 (ICDD card no. 00-042-1488) and Ag (ICDD card no. 00-004-0783), are also included at the top of figure 1. The differences in the composition are well correlated with those observed in the structure evolution. In fact, the film without silver crystallizes in a B1-NaCl crystal structure typical for TiC 0. 3 N 0. 7. The diffraction peaks at 2θ = 42. 39 • and 49. 32 • were assigned to the (111) and (200) planes of TiC 0. 3 N 0. 7 , respectively. Both peaks are shifted to lower angles as compared to the reference values, as a result of a lattice parameter slightly higher than the standard value (a = 4.
Acknowledgments IC acknowledges the financial support of  FCT-Fundação para a Ciência e a Tecnologia  through grant  SFRH / BD / 67022 / 2009. The authors are grateful to  Dr Tomas Polcar ,  Czech Technical University in Prague, Czech Republic , for his assistance in carrying out the Raman spectroscopic analysis. This research was sponsored by  FEDER  funds through the program  COMPETE-Programa Operacional Factores de Competitividade -and by national funds through FCT-Fundação para a Ciência e a Tecnologia-in the framework of the Strategic Projects  PEST-C/FIS/UI607/2011  and  PEST-C/EME/UI0285/2011 , and under the project  PTDC/CTM/102853/2008.
Methods The two previously described stages of work can also be distinguished in the system that we are developing. The first stage -the construction of the classifiers from the preprocessed database of image triplets -is depicted in Figure  1. After a database creation, triplets of images are formed. An (ordered) triplet contains the images acquired at the same slice location. Each of the images in the triplet corresponds to a different moment of contrast media propagation in the hepatic vessels. The first of them is acquired without contrast, the second and the third -after its injection, in the two typical phases of its propagation, arterial and portal, respectively. The next step, the preprocessing of images, could be optional. It aims at improving the contrast, eliminating the noise or the artifacts.
Another way to evaluate the usefulness of the feature could be assessment of its dependency on a ROI size. This is particularly important when the ROI size is different for different patients or for different images (which is true in the case of the database that we explore). The instability of a feature and its dependency on the ROI size can be determined by a standard coefficient of variation (CV). The coefficient of variation is calculated from a set of feature values, obtained for ROIs located at very close positions, or having almost the same size. It expresses the importance of the variability of several feature values (given by the standard deviation) compared to the absolute value of their average. The more unstable the feature is, the greater its coefficient of variation and the lower its reliability in the process of tissue characterization.
For each of the 24 subsets, the average of 62 values of coefficient of variation, obtained separately for each of 62 ROIs, was used for further analyses. Next, the experiment consisted of selecting a subset of features ensuring the best possible classification accuracy. In this step, only the triplets of ROIs from the Circular-ROI-Set were used. Each triplet was described by 120 texture features, 40 features for each acquisition moment. Only the features insensitive both to small ROI displacements and to small changes in ROI size were considered. This experiment was performed with the Weka software  (Hall et al. , 2009). The following selection settings were applied: the wrapper method -as an evaluator of each tested subset of features (WraperSubserEval), the C4. 5 tree  (Quinlan, 1993)  (called J48 in Weka), as a classifier, and the BestFirst searching strategy with the two searching directions, Forward and Backward (tested separately).
Western Blot and Immunoprecipitation Analysis. 40 g of total protein extract was applied on 7. 5% to 12. 5% SDS polyacrylamide gels and Western blot conducted by standard procedures  [16]. e primary antibodies used   Valencia). cDNA was diluted 20-fold and 5 L was used in each quantitative PCR reaction (qPCR). Reactions were conducted in Rotor Gene 6000 equipment using ABsolute SYBR GreenQPCR kit (Abgene, Epsom). Primers sequences for reference genes: B2M, GAPDH, HMBS, ACTB, DDX5 and gene of interest COMMD1 were selected from http://primerdepot. nci. nih. gov/ database  [18]. e gene expression of selected genes was conducted following MIQE recommendations  [19]. Speci�city of all products was veri�ed by melting curve analysis. Reference genes were selected using GeNorm soware  [20]. Quanti�cation was carried out using the ΔΔ CT method.
Both cell lines assayed, MCF7 and HT29, showed the accumulation of COMMD1 aer 5 h of treatment with the peptide similar to the obtained results by Western blot (Figure  2(b) ). Talking together these data con�rm that the peptide CIGB-552 induces the accumulation of COMMD1. COMMD1 undergoes constitutive nucleocytoplasmic transport and its nuclear localization is needed for negative regulation of NF-B signaling  [28]. Since our interest in this study is focused on the human lung cancer, the levels of the protein COMMD1 in the cytoplasm and nucleus of the H460 cells treated with CIGB-552 were evaluated by Western blot. We found a low expression of COMMD1 in untreated cells. However, in response to CIGB-552, COMMD1 was increased in the cytoplasm and nucleus of cells at 40 min following treatment, and, most interestingly, this increment remained until up to 5 h aer treatment (Figure  2(c )).
Acknowledgments e authors thank the laboratories of  Dr. Iduna Fitchtner  for kindly evaluating the antitumor activity of CIGB-552. ey also thank  Jeovanis Gil  for the experimental assistance. ey thank  Daniel Palenzuela Gardon ,  Isabel Guillén Perez ,  Dania Vázquez Blomquist , and  Lidia Ines  for the generation of microarray data helpful for the comprehension of possible mechanisms of the antitumor activity. ey thank  Amelia Rodriguez Ruiz  for his critical reading of the paper.
Besides, the high performance of FPGA for many power electronic and drive applications has been proved  [22]. Moreover, by implementing both fault detection and converter control units on a single FPGA chip, the cost will be decreased. In the following, in section II, a general overview of fault tolerant systems is presented. Then, in section III, for the proposed fault tolerant five-leg converter, all three possible cases of reconfiguration are considered and studied in detail. Fault detection method and reconfiguration control scheme are explained in section IV. For verification, first simulations are carried out using Matlab/Simulink. Then experimental tests are realized. The fault tolerant converter was built in our laboratory and the controller and fault detection scheme are implemented on an FPGA target and tested experimentally.
V. SIMULATION RESULTS Simulations are carried out using Matlab/Simulink in order to verify the behavior of the proposed fault-tolerant converter. The converter is placed between a three-phase source and a three phase load. The source side voltage references are calculated from a source-voltage oriented control scheme that tends to control the DC-link voltage with a unity power factor at the point of connection to the source  [28]. A three-phase RL  impedance is placed between the source and the converter. Load side voltage references are sinusoidal balanced three phase voltages. System parameters are provided in Table  II. Simulations are done for all three possible cases of fault. Case 1: in this case, an open switch fault is applied at the leg 1. Fig. 13  shows the output of the counter (Fig.
VI. EXPERIMENTAL RESULTS An experimental set-up, given in Fig. 23 , is used in order to evaluate the performance of the studied fault tolerant five-leg converter. Fault detection and control schemes for this converter are implemented on a single FPGA. The FPGA implementation procedure is explained briefly here, and the details are available in our earlier publications  [11, 29, 30]. After the discrete simulations with Simulink, simulation with Altera DSP Builder blocks are performed. Simulink blocks are replaced with proper DSP Builder blocks and for the exchange of data between DSP Builder and Simulink blocks, proper input/output blocks are used. Using DSP Builder allows us to have visual programming and to translate it to HDL form very easily. The VHDL design is later compiled using Quartus software and uploaded on the Altera FPGA board via a Joint Test Action Group (JTAG) interface.
VII. CONCLUSION Five-leg converter is an interesting component minimized converter, however it is sensible to a failure in one of its semiconductor switches. In this paper, a fault tolerant five-leg converter is proposed which will continue to operate with four legs after an open-switch fault. An FPGA-based reconfigurable control is proposed for this topology. In the proposed method, it is possible to implement both the control and the fault detection tasks on a single FPGA chip. Using this approach, fast detection and reconfiguration is possible, and an increase in the cost of system due to the use of two digital targets is avoided. For evaluation, first all possible cases of fault are studied and the simulated using Matlab/Simulink. Then the fault detection and then the proposed reconfigurable control schemes are implemented on an FPGA board and fully experimental tests are carried out to evaluate the effectiveness of the proposed topology and its control for all three possible cases.
Field surveys and data collection The need to investigate on the current status of the bacterial blight disease, across the hazelnut orchards of central Italy, was based in part on growers report of disease outbreaks in hazelnut fields throughout the province during early summer of 2010  [23]. Twelve municipalities, known for the cultivation of hazelnut, within the province of Viterbo were surveyed (Figure  1 ). The observations were made over the time period between March and September for all the three years. Each municipality had different number of sites, ranging from a minimum of 1 to a maximum of 6, depending on their extent of hazelnut cultivated area. The size of site varied from 5 to 25 ha and, the total number of sites was 30. From each site, 900 hazelnut trees were randomly surveyed (300/ year).
Disease incidence One thousand hazelnut trees/site were randomly analyzed each year (total of 3000 trees/site) for the presence of bacterial blight on leaves, stems, fruits, twigs and branches. Any symptoms suggestive to bacterial blight, based on the literature review, were taken into consideration. The incidence of the disease was calculated by the proportion of diseased plants within the total  [67]. Statistical analysis were performed using software package Statistica H (StatSoft, Inc. , Tulsa, USA). Student's t test, Pearson correlation and regression analysis were performed to determine the effect of plant age and pedo-climatic factors on disease incidence (DI). However, the influence of plant cultivars on DI was not evaluated for the fact that over 85% of the cultivation in Viterbo is represented by cultivar Tonda Gentile Romana and the remaining are grown in different proportions from one site to another.
The final volume was adjusted at 25 mL by adding SDW. The PCR reactions were performed according to the following program: 1 cycle at 95uC for 5 min. , 35 cycles consisting of 30 sec. at 95uC, 1 min. at 55uC and 1 min. at 72uC and 1 cycle (final elongation) at 72uC for 4 min. The PCR product was loaded on 1% agarose gel electrophoresis to determine the presence and size of the bands. The bands at the expected size were sequenced, analyzed with chromas version 1. 45 (32-bit) and aligned with other sequences present in the Genebank by using CLUSTAL W software available online. The similarity of our sequences was compared with those of reference strains present on NCBI by blasting and the sequences were deposited in GeneBank.
Climatic and environmental data The meteorological data recorded hourly by different stations, located around the Cimini Hills, were collected. Temperature data (uC), only of the last ten years, were recorded by 19 stations across the province. Regarding the rainfall (mm), data collected from 1970 to 2012 from several meteorological stations, most of them not active any longer, were considered. In addition, a database of soil chemical-physical analysis of more than 180 geo-referred sites in the area was set up (Figure  5 ). Besides meteorological data, some essential soil parameters contributing to the presence and spread of the disease were investigated. In particular, the effects of rainfall  [75] , total Nitrogen amount (%) in the soil  [76, 77] , soil Mg/K ratio were evaluated. The latter is of considerable importance that explains certain specific Mg deficiency in planta, especially on acidic soils  [76].
Our study sites, characterized by the volcanic soils, have this deficiency which might increase plant susceptibility to various diseases  [78] [79] [80]. The influence of lower pH associated to soil aluminium (meq/hg) was investigated given its influence in plant-pathogen interaction  [81] [82] [83]. Finally, the average thermal shock (D), given by the difference among the day/ night temperature, associated to every frost event recorded was calculated. The latter was found strictly associated to dieback of hazelnut, caused by Pseudomonas syringae pv. avellanae, in the same area  [84]. All the values were spatialized according the geostatistical methods as described above. Kriging was applied to the real or log-transformed data. An exception was made for the average rainfall data given that they were collected in a period of about forty years since 1970 from several meteorological stations, most of them not active any longer.
Geostatistical analysis and kriging of the meteorological and pedological data In order to obtain a basic knowledge of the data set, conventional statistical analysis of the pedoclimatic data was prior conducted using software package Statistica H (StatSoft, Inc. , Tulsa, USA). Student's t test, Pearson correlation and regression analysis were performed to determine the correlation of pedoclimatic factors with DI. Prior to conduct geostatistical analyses, on the spatial patterns of data collected from the meteorological stations and sites of Cimini Hills, the latitude and longitude coordinates of the points were first transformed into plane coordinates with a Universal Transverse Mercator (UTM) projection, Zone 33N, European Datum 50, in ArcGIS (version 8. 0, ESRI, Redlands, CA). The UTM coordinates were used in the subsequent statistical analyses.
Linear and nonlinear models were fitted to semivariograms by least squares regression using Geostatistical Analyst module of ArcGIS (ESRI). The pedoclimatic variables modelled were regressed on distance with or without logarithmic transformation. Successively, the Gaussian, spherical, linear, linear to sill, and exponential models, were used to describe semivariograms  [90]. The coefficient of determination (r 2 ), structural variance (proportion of spatial structure), and mean square error (MSE) were used to evaluate the goodness-of-fit of data and to choose the best regression model  [91]. Anisotropy was determined by comparison of semivariogram characteristics. Oriented semivariograms that displayed differences among semi-variogram characteristics for different directional orientations indicated anisotropy or directionality in the degree of spatial dependence  [86].
Ordinary kriging was applied to estimate logarithmic values of pedoclimatic data for each of 19 meteorological stations or 180 soil analysis sites. In addition, vectorial maps were gained using anti-logging calculation. The whole application, including semi-variogram calculation and kriging (ArcGIS version 8. 0, ESRI, Redlands, CA, USA), was applied to log-transformed data. The reliability of the applied model was tested by cross validation between measured and interpolated values. Interpolated data have been depicted as colored raster maps, limiting the prevision to the areas where data were collected.
The isolates used glycerol, D-mannitol, fructose, galactose, trealose, sucrose, glucose, maltose, L-asparagine, D-sorbitol, Larginine, salicin and inulin as sole carbon sources and caused their acidification except of the last four. All of them were negative for the utilization of L(+) tartrate. On the basis of the results obtained from the morphological, physiological, biochemical and nutritional tests, the isolates causing the aforementioned symptoms were identified as Xanthomonas arboricola pv. corylina. The comparison of our sequences with those present in the database further confirmed the results regarding the belonging of our isolates. Our sequences (Accession numbers JQ861273, JQ861274 and JQ861275) shared 99% identity with the analogous sequences of Xac available in the NCBI database.
After final washes with PBS, cell grown on plastic were covered with glass coverslips to proceed for fluorescence microscopy. For the statistics, the mean granule area was measured using ImageJ (National Institutes of Health, Bethesda, MD) software over at least 800 granules from at least 10 different representative cells. Because stress granules are not round, the apparent radii were not considered. Spacing between cells was estimated by locating the nucleus center of mass and measuring at could no longer grow, even when DFMO and APCHA were washed out. To resume proliferation in the absence of extracellular polyamines, they need to interact with polyamine-rich control cells (Figure  5B ). To explain this phenomenon, two hypotheses can be advanced: a transit of polyamines takes place from control to polyamine-depleted cells via gap junctions, and (or) control cells stimulate polyamine synthesis in polyamine-depleted cells.
Videomicroscopy of microtubule dynamics NRK cells were transiently transfected with a green fluorescent protein (GFP)-EB1 eukaryotic expression vector and then cultured for 24 h before real-time monitoring of microtubule dynamics. Fluorescence videomicroscopy was implemented on an inverted microscope (Axiovert 220; Carl Zeiss MicroImaging, Jena, Germany). GFP emission was detected with a 63×/1. 4 numerical aperture objective. Time-lapse images were captured at 4-s intervals using a Zeiss cooled charge-coupled device camera. To measure microtubule elongation rates, the distances covered by microtubule ends were measured by analyzing sequential images with the ImageJ software. Ambiguous trajectories were discarded. See Supplemental Videos S1-S3.
A negative value of this index is indicative of a situation where the medium is supersaturated with respect to the phase concerned. These data were calculated using the Visual Minteq 3. 0 software, taking into account the solubility products that are generally accepted for these various phases (added in Table  2 ). As may be noted, such conditions (if correctly set up from an experimental point of view) lead to a high supersaturation with respect to HA and to a moderate supersaturation for octacalcium phosphate (OCP), calcite or vaterite, among other phases. In contrast, they are moderately undersaturated with respect to magnesium-containing phases such as MgHPO 4 ⋅3H 2 O and more undersaturated with respect to brushite or monetite. If undesirable (or variations in) ionic concentrations are present during the tests, however, the ionic product is going to evolve and the overall saturation scheme is expected to change.
Background-Inflammatory breast cancer (IBC) is a poorly characterized form of breast cancer. So far, the results of expression profiling in IBC are inconclusive due to various reasons including limited sample size. Here we present the integration of 3 Affymetrix gene expression data sets collected through the World IBC Consortium, which allows us to interrogate the molecular profile of IBC using the largest series of IBC samples ever reported. Materials and methods-Affymetrix profiles (HGU133-series) from 137 IBC patients and 252 non-IBC patients (nIBC) were analyzed using unsupervised and supervised techniques. All samples were classified according the molecular subtypes using the PAM50-algorithm. Regression models were used to delineate IBC-specific and molecular subtype-independent changes in gene expression, pathway activation and transcription factor activation.