dataesr/scientific-paragraphs-categorization huggingface dataset:
(v) Audio + Video no. 3: the events (i. e. , speech segments) are detected from audio only; however the assigned confidences are given by the combination of acoustic and visual confidence scores. Graphical outputs presented by the DET plots in Figures  16  and 17  indicate that the VAD based on both audio and video modalities (audio + video no. 1) outperforms audioonly VAD for most of the potential operating points. In more detailed view, the largest improvement was obtained for audio + video no. 1 VAD system, where the events (i. e. , speech segments) are first detected independently from both modalities and then merged into a single output stream of events. In case of the simple scenario provided by Dataset 1, where the audio signals from the remote rooms were well separated using echo cancellation and the audio has relatively high SNR, the audio + video combination did not significantly improve over audio-only VAD.
It can be seen that audio-based VAD outperforms video-based VAD. However, the combination of Audio and Video is able to enlarge a potential set of operating points (especially when a low false alarm rate is expected). In Dataset 2 the audio is not echo cancelled, and combined Audio + Video offers better detection results over the whole DET curve (especially for low miss probabilities) compared to uni-modal VAD systems. SAOC objects  [2]  has to be evaluated with respect to a negligible loss of quality compared to other parametric spatial coding techniques. If we achieve comparable audio quality, SAOC offers the desired advantage of extensive user interaction. In  [20] , SAOC has been compared against DirAC on the basis of a MUSHRA listening test  [40]. Both coding techniques SAOC and DirAC were based on a single-channel downmix signal.
Overall, our main contributions are the design of an integrated real-time system with latency below 130 ms comprising several state-of-the-art audio-visual processing algorithms and a thorough performance evaluation of the different components of the system on two different challenging datasets. The main evaluated components of the system are face tracking, speaker localisation and match, multimodal voice activity detection, estimation of visual focus of attention, and spatial audio object coding with respect to a negligible loss of quality compared to other parametric spatial coding techniques.
Rats were placed in elevated plastic boxes with a wire mesh floor 15 min before the test. The plastic tip was then applied perpendicularly to the medial plantar surface of hind paw from below the mesh floor, until a clear withdrawal was observed. Mechanical thresholds (expressed in grams) corresponding to the force eliciting a behavioral reaction (withdrawal of the hind paw) was automatically registered by the electronic device. Five measurements were taken at 5 min intervals and averaged for each animal. For each behavioral assessment, data were obtained at preoperative stage and 1, 3 and 5 weeks after surgery. At the completion of the behavioral assessment (5 weeks after surgery), animals were deeply anesthetized with a sodiumpentobarbital solution (60 mg/kg, i. p. ), and perfused through the heart with a 4% paraformaldehyde solution.
Photomicrographs of immunostained sections were captured and all image analysis was completed using ImageJ software (ImageJ v1. 41o, National Institute of Health, USA). The total number of immunoreactive cells was counted and expressed as the percentage of the number of cell measured of shams (mean ± standard deviation). Statistical analysis was made using Statistica software (Stat-Soft France, Maisons-Alfort). The body weight, results of von Frey and locomotor activity were compared using a two-way ANOVA for repeated measures (time), followed by a post hoc Student-Newman-Keuls test. The total numbers of TH immunoreactive cells were compared by a Student t-Test. Differences between groups were considered significant for a p value inferior to 5%. In spite of nursing, one of the 6-OHDA-lesioned rats died at two weeks after surgery.
Stained aortas were washed in 60% isopropanol and imaged with a Nikon CoolPix digital camera. Quantification of the percentage of aortic surface area occupied by oil red O positive plaque was performed using digital image analysis (Simple PCI, C-Imaging). The heart and proximal portion of aortic root were also fixed and embedded in OCT. Subsequently, the aortic root area was sliced. The atherosclerotic lesion areas in oil red O-stained cryostat sections of the aortic root were quantified using the Leica image analysis system, consisting of a Leica DMRE microscope coupled to a video camera and Leica Qwin Imaging software (Leica Ltd. ). Mean lesion area (in lm 2 ) was calculated from 10 oil red O-stained sections, starting at the appearance of the tricuspid valves. Plaque necrotic areas were quantified from the average of 6 sections per mouse, spaced 30 lm apart, by measuring the area of hematoxylin and eosin-negative acellular and anuclear white areas.
Statistical Analysis The Kolmogorov-Smirnov test was used to determine whether each variable had a normal distribution. When data were normally distributed and variances were similar across comparison groups, the statistical significance of data between the groups was assessed by analysis of variance (ANOVA). Except for the date on determination of lesion area between the groups, statistical significance was estimated by Wilcoxon rank-sum test. All values are reported as mean AESEM. Analyses were performed using the SPSS (version 16. 0; APSS), statistical package and the P<0. 05 values were regarded as statistically significant.
Plasma Lipids Are Not Modulated by Haematopoietic Rev-erba Knock-Down Next, we assessed the potential influence of Rev-erba knock-down on plasma lipids. Our data showed no significant difference in plasma total cholesterol, triglyceride, or choline-containing phospholipid concentrations between the mice injected with lentivirus-shRev-erba-transduced bone marrow and the control mice (Table ).
Quantification of the lesion area (top, left panel) was performed by using Leica Qwin Imaging software as described in Methods. The mean area of lipid staining per section from 10 sections was determined for each mouse. The statistical significance of the differences between the groups was estimated by Wilcoxon rank-sum test. The data represent meanAESEM (n=10, **P<0. 01). Aortic root sections from LDLr À/À mice transplanted with shNT (Lenti-shNT) or shRev-erba (Lenti-shRev-erba) bone marrow were subjected to histochemical analysis. Images of representative sections of aortic roots stained for macrophage Moma-2 (middle panel). Representative sections of hematoxylin and eosin (HE)-stained aortic root sections from Lenti-shNT and Lenti-shRev-erba mice (bottom panel) are shown. Magnification, 9100.
Discussion The present study demonstrates that haematopoietic Rev-erba knock-down increases the size of atherosclerotic lesions in LDLr À/À mouse, thus providing evidence for an antiatherogenic role of macrophage Rev-erba. The possible molecular mechanisms through which Rev-erba could influence lesion development were evaluated. Our results in vitro and in vivo strongly suggest that Rev-erba promotes the differentiation of macrophages towards the M2 phenotype. Atherosclerosis is a chronic inflammatory disease manifested as vessel wall lesions 1 in which macrophages play key roles in the inflammatory response and lipids accumulation. Heterogeneity of circulating monocytes and the functional diversity of macrophages likely influence plaque formation and phenotype. 22, 23 Our in vitro data and experiments in live mice provide the first evidence that Rev-erba regulates the differentiation of macrophages, resulting in a more antiinflammatory M2 macrophage state.
Peritoneal cells from recipients of Lentivirus-shNT and Lentivirus-shRev-erba bone marrow are shown (left, top), and quantification of the Western blot signals for Rev-erba (left, bottom; n=6); The right panel shows the efficiency of Rev-erba knock-down after the 16 weeks Western-type diet and quantification of the protein level (n=3); statistical analysis was performed by Kolmogorov-Smirnov test followed by two-factor ANOVA, *P<0. 05 and **P<0. 01. C, Analysis of atherosclerotic lesions in the aortic root after BMT, 8-week recovery and 11-week Western-type diet. Aortic sections from shNT?LDLr À/À (Lenti-shNT) or shRev-erba?LDLr À/À mice (Lenti-shRev-erba) were stained with oil red O (up panel). Quantification of the lesion area (top, left panel) was performed by using Leica Qwin Imaging software as described in Methods.
The mean area of lipid staining per section from 10 sections was determined for each mouse. The statistical significance of the differences between the groups was estimated by Wilcoxon rank-sum test. The data represent meanAESEM (n=10, **P<0. 01). Aortic root sections from LDLr À/À mice transplanted with shNT (Lenti-shNT) or shRev-erba (Lenti-shRev-erba) bone marrow were subjected to histochemical analysis. Images of representative sections of aortic roots stained for macrophage Moma-2 (middle panel). Representative sections of hematoxylin and eosin (HE)-stained aortic root sections from Lenti-shNT and Lenti-shRev-erba mice (bottom panel) are shown. Magnification, 9100. D, Representative aortas displayed en face; atherosclerotic lesions of aortas from shNT?LDLr À/À (Lenti-shNT) or shRev-erba?LDLr À/À mice (Lenti-shRev-erba) were stained with oil Red O.
5 ml/min) continuously with an oxygenated recording solution of the same composition. Experiments were conducted at 32uC. Using the patch-clamp technique (Axopatch 200B; Clampex 10, Molecular Devices), whole-cell recordings in current clamp mode were performed in NRT neurons visualized with an Olympus BX51WI (x60 lens). Recordings were filtered by a 4-pole Bessel filter set at a corner frequency of 1 kHz and digitalized at 10 kHz and latter analyzed using Matlab R2009b (The MathWorks, Inc. ). Electrodes were filled with the following solution (in mM): 140 methanesulfonic acid, 4 MgCl 2 , 10 HEPES, 4 Na-ATP, 15 phosphocreatine, 150 units/ml creatine phosphokinase; pH 7. 3, osmolarity 280 mOsm. Alexa Fluor 594 and Oregon Green 488 Bapta-1 (Molecular Probes) were added with a final concentration of 15 and 100 mM, respectively (tip resistances: 1.
Calcium Imaging Images were obtained with a custom-built 2-photon laser scanning microscope. Two-photon excitation of the fluorescent dyes was performed by a femtosecond Ti:Saphir laser (Mai Tai HP, Spectra-Physics, Mountain View, CA) tuned to 800 nm. Image acquisition was controlled by MPScope software  [13]. Before imaging, neurons were loaded with indicators for 30 min. The fluorescent signals from Alexa Fluor 594 and Oregon Green were acquired simultaneously across dendrites at selected regions of interest (ROI) (acquisition frequency = 40-60 frame/s) by two high gain photomultiplier tubes (PMT Hamamatsu H9305-03, Hamamatsu photonics, Japan). At the end of the recordings Z series of 160-190 images (512 pixels, 0. 26 mm/pixel) were taken with 0. 5 mm focal steps to construct a two-dimensional maximum intensity projection of each neuron.
Data Analysis Recordings were analyzed off-line using Matlab R2009b (The MathWorks, Inc. ). Morphological distances were approximated by measuring along the dendrite from the beginning of the dendrite to the ROI of interest on the two-dimensional maximum intensity projection of each neuron. Fluorescence signals were measured by integration of the signal over a region of interest. The reported change in fluorescence (DG/R) was calculated as the change in fluorescence (Gpeak) from baseline (G0, average of the 400 ms period before stimulus) of the Ca 2+ -sensitive indicator (Oregon Green 480 Bapta-1) normalized to the average fluorescence of the Ca 2+ -insensitive indicator (RAvg, Alexa Fluor 594): DG/ R = (G Peak 2G 0 )/R Avg  [14]. The peak response was calculated as the combined average of 10-20 trials to maximize signal-to-noise ratio.
Apparatus An EyeLink 1000 eye tracker (SR Research Ltd. ) was used to control for eye position. The eye tracker had a sampling rate of 1000 Hz and used an automatic saccadic detection algorithm based on a velocity threshold of 30˚/s and an acceleration threshold of 8000˚/s 2 , which corresponds to the cognitive configuration for the EyeLink 1000. Stimuli were presented on a ViewSonic P227 monitor with a refresh rate of 100 Hz and a screen size of 1024 × 768 pixels. Stimulus presentation was controlled with Experiment Builder software (SR Research Ltd. ). Eye movements were recorded from the right eye.
DATABASE Subjects were 8 patients [two female, mean age ± standard deviation (SD) 36. 3 ± 10. 5 years] with pharmacologically intractable temporal lobe epilepsy who were implanted with 8-14 intracranial depth electrodes in order to localize epileptogenic regions for possible resection. The placement of the electrodes was determined exclusively by clinical criteria  (Fried et al. , 1999). Extending beyond the tip of each electrode were nine Pt-Ir microwires (40 μm diameter) with inter-tip spacing of 500 μm, eight active recording channels and one reference. Each microwire was sampled at 28 kHz (Cheetah recording system, Neuralynx Inc. , Tucson, AZ). Spatial localizations were determined on the basis of postimplant computed tomography scans coregistered with preimplant 1. 5T MRI scans. Our results are based on microelectrode recordings located in the anterior hippocampus (n = 40 channels in 5 patients) and entorhinal cortex (n = 24 channels in 3 patients).
SPIKE SORTING In order to detect single-units, all channels were high-pass filtered at 300 Hz and were visually examined for the presence of unit activities. In those microwires with clear unit activities, we performed spike detection (>4:1 signal to noise ratio) to obtain multi-unit activities (MUA). Single-unit activities were extracted with spike sorting using KlustaKwik 1. 7 program (Software: http://klustakwik. sourceforge. net/; Harris et al. , 2000)  which employs the 10 principal components of the spike shape and an unsupervised Conditional Expectation Maximization (CEM) clustering algorithm  (Hazan et al. , 2006). After automatic clustering, the clusters containing non-spike waveforms were visually deleted and then the units were further isolated using a manual cluster cutting method.
For any given cell pair where at least one bin in the [1. 5 ms, 30 ms] interval exceeded the 99% confidence interval, the interaction was considered significant. (2) A method for identifying statistically conspicuous spike coincidences was implemented to detect the number of quasi-simultaneous appearances of spikes over small coincidence windows, here of 5 ms  (Gütig et al. , 2002; Quian Quiroga et al. , 2002). Their occurrence was then studied in relation to surrogate data generated by dithering the individual, original spike times within a given time interval. Here, each spike in the original data set was randomly and independently jittered on a uniform interval of  [-5, +5]  ms to form a surrogate dataset. By repeating the procedure 1000 times, the 99. 9% confidence interval for each bin (p = 0.
ACKNOWLEDGMENTS Catalina Alvarado-Rojas  was supported by the  Administrative Department for Science, Technology and Innovation (COLCIENCIAS) ,  Colombia. Vincent Navarro  was supported by a  Contrat Inferface INSERM. This work was supported by funding from the program " Investissements d'avenir "  ANR-10-IAIHU-06  and from the  ICM  and OCIRP.
Data Analysis We analyzed the iSPs in the ipsilateral-left OP, the MEP in the contralateral-right OP, the average background EMG activity in the left OP during the 0. 5 sec preceding the TMS pulse  [19]  and the RMS values in the right OP during the 0. 1 sec preceding the TMS pulse. Measurements of MEPs were made on single trials. The amplitude of contralateral MEPs (right OP muscle) was evaluated by taking the peak-to-peak difference in the raw EMG signals. However, the onset and the end of the iSP were difficult to define with precision in single trials. To overcome this difficulty, single trials (n = 20) were rectified and averaged within experimental condition and iSP duration was measured from the averaged trace  [32, 33]. The onset of iSP was defined as the point after TMS at which EMG activity dropped constantly under the mean background EMG preceding the stimulus (i.
Schultz et al. [11]  examined IL of strongly metrical patterns in two experiments. Although the two conditions reported here were identical, the aim of the two experiments differed (see 11). In Experiment 1, IL of strongly metrical in a multiple response task was compared to IL in a single response task (i. e. , both were adaptations of the classical SRT) with task type as a between-subjects variable. In Experiment 2, the IL of strongly metrical and nonmetrical patterns was investigated using a single response task, with metricality as a betweensubjects variable. The present study examines recognition data from the strongly metrical conditions using the single response task in Experiments 1 and 2. In Experiments 1 and 2, results of the SRT demonstrated that metrical patterns were learned. There was also evidence that the metrical framework was learned in both experiments, as the introduction of a novel weakly metrical pattern resulted in a greater RT increase than the introduction of a novel strongly metrical pattern.
Stimuli In the training blocks of the SRT, the stimuli could emanate from the left headphone, the right headphone, or both headphones in accordance with the cover story of a computer game for the blind (see 11). The cover story was implemented to reduce awareness of the temporal pattern in the SRT. In the recognition task, all stimuli were presented through both headphones (i. e. , binaurally). The stimulus was a 394Hz triangle waveform of 200ms duration with 10ms rise and fall times. Stimuli were created using MAX-MSP and were presented using PsyScope software  [44]  through Sennheiser (HD 650) headphones. The strongly metrical acquisition pattern used in the training blocks and the four sequences in the recognition task in the two experiments are shown in Figure  2. For example, the acquisition pattern in Figure  2  displays an IOI sequence (in ms) of 500-1500-1000-1000-500-500-1000-2000.
A "No" response in the exclusion condition reflects conscious recollect ion of the learned sequence. Under each instruction, responses to the five sequences can be either "Yes" or "No". In total, 20 different sets of responses can be made: 2 (instruction) x 5 (sequences) x 2 (answer, "Yes"/" No"), and each response corresponds to a different outcome in the processing tree (see Appendix A in Text S1, and Figure  S1 ). Participants were presented with each sequence three times and the order of sequence presentations was random. In total, 60 responses were made per participant in the recognition task. The combined frequencies of responses from all participants were used to calculate the probabilities of the latent variables using the multinomial processing tree. The SIMM calculates the parameter estimates based on the pooled data of participants and, as such, parameter estimates reflect the contribution of processes at the group level, rather than the individual level.
Results Recognition data from Schultz et al. [11]  (data is available upon request to the corresponding author) were analyzed using multiTree software  [46] , designed specifically for the analysis of joint multinomial processing tree models such as the SIMM and the adapted SIMM. MultiTree can be used to estimate model parameters, calculate variability (e. g. , confidence intervals and standard error), and goodness-of-fit statistics. The Δ Akaike Information Criterion (ΔAIC) was used to assess the model fit to the data. The ΔAIC is a measure of a model relative to the "best" model given the current parameters  [47]. ΔAIC does not give a significance level but, instead, provides a measure of the strength of evidence supporting the model where: 0 < ΔAIC < 2 suggests substantial evidence for the model; 3 < ΔAIC < 7 suggests considerably less support, and ΔAIC > 10 indicates that the model is unlikely.
The model was also run on the pooled data from Experiments 1 and 2 (see Appendix C in Text S3), but the evidence for the model using the pooled data was not as strong (ΔAIC = 9. 45, PD λ = 21. 45, p =. 002) as the evidence found for the data with the two datasets separated (ΔAIC = 0. 16, PD λ = 24. 16, p =. 049) when the same restrictions were applied.
In doing so, we compared different criteria and various measures of poorpitch singing. The SPB is formed by 5 tasks, after an assessment of participants' vocal range: (1) single-pitch matching, (2) pitchinterval matching, (3) novel-melody matching, (4) singing from memory of familiar melodies (with lyrics and on a syllable), and (5) imitation of familiar melodies (with lyrics and on a syllable) at a slow tempo indicated by a metronome. The SPB was tested on a group of 50 occasional singers. The renditions were analyzed using acoustical methods. In order to provide the same metric across all the tasks, data was analyzed so as to obtain measures of accuracy and precision in terms of both absolute pitch and relative pitch, as previously suggested by  Pfordresher et al. (2010). In addition, poor-pitch singers were identified using both fixed (i.
ANALYSES The productions obtained from the SPB were analyzed with acoustical methods, which were successfully adopted in previous studies (e. g. , Dalla  Bella et al. , 2007 Bella et al. , , 2009;; Dalla Bella and Berkowska, 2009; Pfordresher et al. , 2010). For the purposes of the present study, the analyses were limited to the pitch dimension (for rhythmic analyses, see Dalla  Bella et al. , 2007). The first step of the analysis consisted in computing the pitch height of the produced notes. In Tasks 1 and 2 this was achieved by extracting the fundamental frequency (F0) from the stable portion of the produced pitch using Praat software  (Boersma, 2001)  with an accurate autocorrelation method  (Boersma, 1993 ; sampling rate = 100 Hz; Gaussian window = 80 ms). In Tasks 3 through 5, given the higher complexity of the text material associated with music (lyrics or repeated syllables), the procedure was more demanding.
GROUP PERFORMANCE From all participants, 3340 complete renditions were recorded across all the tasks (Task1: 1197 performances; Task 2: 1250; Task 3: 297; Task 4: 296; Task 5: 300). Ten performances (0. 3% of the entire data set) were discarded due to erroneous or incomplete sound recordings. The participants had a mean vocal range (i. e. , difference between the lower and the upper boundaries estimated with the adaptive procedure in the SPB) of ∼1 octave and ½ (M = 18. 52 semitones, SD = 4. 56 semit. ). The extent of the vocal range was not associated with measures of accuracy and precision provided by the SPB. Thus, stimulus presentation in the SPB afforded measures of singing proficiency not biased by singers' vocal range. Mean and variability for singing accuracy and precision in the five tasks of the SPB, and additional variables (i.
The expression level of the CMAH transcript was most abundant in platelets. Primer sequences used in qRT-PCR are listed in Table  3. (C) WB analysis of CMAH in platelets revealed that CMAH protein was similarly expressed in platelets from saline (SAL) and 5-HT -infused mice. Actin was used as a loading control. Both gels were run under the same conditions. CMAH transcript was preferentially expressed in platelets compared to other blood cell types. Next, we evaluated the impact of 5-HT on the catalytic rate of CMAH using an in vitro assay. Platelet lysates as the enzyme source were incubated with the CMAH substrate, CMP-Neu5Ac, and formation of the Neu5Gc product was measured by LC-MS. These data revealed increased CMAH catalytic activity in platelets from 5-HT mice. Importantly, CMAH catalytic activity was not significantly different between platelet lysates from salineinfused WT, SERT KO and TPH1 KO mice.