dataesr/scientific-paragraphs-categorization huggingface dataset:
Sanger variants were manually inspected to detect overlapping variants with discordant descriptions between the two datasets. To facilitate interpretation, each unique variant was further annotated with its PKDB clinical significance, single-nucleotide polymorphism database version 144 (dbSNP) identifier, and the number of patients where it was detected in the cohort. Surrounding bases were evaluated to identify and remove potential sequencing artifacts occurring in homopolymer stretches. Finally, variants were considered as highconfident variants if previously reported in PKDB or dbSNP, showed strong PacBio sequencing evidence of being present, or detected in any patient by both Sanger and PacBio sequencing.
and Sanger variants were manually inspected to detect overlapping variants with discordant descriptions between the two datasets. To facilitate interpretation, each unique variant was further annotated with its PKDB clinical significance, single-nucleotide polymorphism database version 144 (dbSNP) identifier, and the number of patients where it was detected in the cohort. Surrounding bases were evaluated to identify and remove potential sequencing artifacts occurring in homopolymer stretches. Finally, variants were considered as highconfident variants if previously reported in PKDB or dbSNP, showed strong PacBio sequencing evidence of being present, or detected in any patient by both Sanger and PacBio sequencing.
Twenty-five image sections of selected areas were acquired with a step size of 0. 3 lm, and z-stack images analyzed and processed using Leica Applied Systems (LAS AF6000) image acquisition software. For deconvolution, image sections of selected areas were acquired with a step size of 0. 12 lm, and deconvolved using Huygens Essential Deconvolution software. Quantification of colocalization of mutant or kinaseinhibited LRRK2 with acetylated or detyrosinated a-tubulin was performed essentially as described  (82). For each condition, five individual cells were analyzed. Eight LRRK2-positive MT tracks were randomly selected from each cell and a line drawn over the length of a straight part of the track. Tracks were scored for the level of colocalization using image calculator and plot profile functions of ImageJ.
Membranes were incubated with primary antibodies in 5% BSA (w/v) in TBS-0. 1% Tween-20 for 1. 5 h at RT, or overnight at 4 C. For ECL detection, membranes were incubated with secondary antibodies in 5% BSA in TBS-0. 1% Tween-20 for 1 h, or with secondary antibodies in PBS (1:10 000) for detection by Odyssey, followed by three times 5 min rinses in PBS. Westerns were developed with ECL reagents (Roche), and a series of timed exposures to ensure that densitometric analyses were performed at exposures within the linear range. Most determinations of steady-state protein levels, as well as all GTPbinding assays were quantified by ODYSSEY infrared imaging system application software LI-COR Image Studio Lite version 5. 2. For determination of S935-phosphorylation status, HEK293T cells were transiently transfected with the indicated constructs to express wild-type or mutant LRRK2 using 1 lg of DNA in 50 ml OPTI-MEM (Thermo Fisher) and 2 lg of linear polyethylenimine (PEI, Polyscience) per P24 well.
1% Tween-20 overnight at 4 C. Membranes were washed three times for 10 min with TBS-Tween buffer, and incubated for 1. 5 h at room temperature with anti-mouse Alexa-488 and anti-rabbit Alexa-568 secondary antibodies (1:1000) in 5% BSA (w/v) in TBS-T buffer. Membranes were washed in TBS-T buffer followed by visualization on Typhoon FLA9500 (GE Healthcare) and densitometry analysis carried out using ImageJ software. In some cases, analysis was performed as described above by ODYSSEY infrared imaging system application software LI-COR Image Studio Lite version 5. 2. In all cases, total LRRK2 protein levels were comparable amongst the different mutants analyzed.
Membranes were blocked for 40 min in 5% (w/v) skimmed milk in TBS-T buffer [20 mM Tris-HCl, pH 7. 4, 150 mM NaCl, 0. 1% (v/v) Tween-20], followed by incubation for 1 h with an antibody against the LRRK2 autophosphorylation site T2483 (MJF-R8, Abcam, 1:2000). Membranes were washed four times for 10 min with TBS-T buffer, and incubated for 1 h at room temperature with horseradish peroxidase-conjugated rabbit secondary antibodies (1:15 000) in 5% (w/v) skimmed milk in TBS-T buffer. Membranes were washed in TBS-T buffer followed by visualization using ECL Western Blotting Detection Reagents (GE Healthcare). Data were normalized to the concentration of the individual proteins on PVDF membranes directly stained with Coomassie [40% methanol, 10% acetic acid, 0. 1% (w/v) Comassie R-250], and densitometry analysis carried out using ImageJ software, with kinase activities of the various proteins expressed relative wild-type LRRK2, which was present on every gel for comparison.
Data Acquisition and Analysis of Cardiovascular Variables The ECG and P DA signals were recorded using standardized electronic devices whose output were digitalized at 1000 Hz, FIGURE 1 | Raw tracings of 30-s duration in a single unanesthetized trout illustrating the changes observed in pulsatile dorsal aortic blood pressure (P DA ) and electrocardiographic (ECG) signals between the pre-injection period (A) and the post-injection period (B) after intracerebroventricular (ICV) injection of 50 pmol UII. Note that, compared with the pre-injection period, ICV injection of UII produces an elevation of systolic blood pressure (SBP) but a decrease in the R-R interval of the ECG (reflecting a tachycardia). visualized on the screen of a PC during the 30-min recording period and finally stored using PowerLab 4/30 data acquisition system (ADInstruments, Oxford, England) and LabChart Pro software (v.
Their mean values were calculated. R-R interval and SBP time series were resampled at 2. 56 Hz to obtain equidistant data points. The linear trend was removed from the new time series and 29 segments of 256 data points (100 s) overlapping by half were subjected to a Hanning window. To investigate to what extend the input signal, SBP, influences the output signal, the R-R interval, the coherence, phase and transfer function spectra of SBP against the R-R interval were determined  (Lancien et al. , 2011). A relatively high coherence between the two signals and a negative phase shift (SBP changes precedes R-R interval fluctuations) indicates that the SBP mediates the changes in the R-R intervals. The cardiac BRS was estimated as the mean of the gain of the transfer function when the coherence was high and the phase negative.
5 mmol/L, 2 h post prandial ≥7 mmol/ L, or a post prandial value at any time ≥ 9 mmol/L. We excluded women taking metformin dose <500 mg/ day; women with suspected type 1 diabetes presenting in pregnancy or marked hyperglycaemia (fasting ≥7 mmol/ L, 2 h ≥ 11. 1 mmol/L); women with allergies to either glibenclamide, insulin or any of their excipients; women with contraindications to sulphonylurea therapy; and women unable to give informed consent. The study was approved by the Scotland A Research Ethics Committee (reference number:13/SS/0223) and the Medicines and Healthcare products Regulatory Agency (EudraCT number:2013-004706-25) and was registered with clinical trials. gov (registration number:NCT02080377). The trial was overseen by a Trial Steering Committee and an independent Data Monitoring Committee.
Randomisation and masking We randomly assigned women to receive glibenclamide or insulin (standard care) in addition to their metformin therapy using a secure web-based randomisation system hosted by the NPEU Clinical Trials Unit, University of Oxford. Randomisation used a minimisation algorithm to ensure allocation concealment, target a 1:1 allocation ratio and balance between the groups with respect to study site, BMI status (BMI <40 or ≥40 kg/m 2 ) recorded at antenatal booking (typically between 11 and 13 weeks' gestation) and multiplicity (singleton or multiple pregnancy). Neither participants nor caregivers/those collecting outcome data were masked to treatment allocation; however, using minimisation made it impossible to predict the next allocation with any certainty.
If women failed to achieve adequate glycaemic control with dual oral therapy, glibenclamide was discontinued and replaced with insulin therapy. Women randomised to insulin (standard care) were treated according to the clinician's standard practice and doses adjusted to achieve target glycaemic control. For those who achieved normoglycaemia, allocation to glibenclamide or insulin treatment, in combination with the maximum tolerated dose of metformin, was maintained until delivery. Participants were asked to check their blood glucose 4 times per day (fasting prior to breakfast, and 2 h post-breakfast, lunch and evening meal). Data on the participants' blood glucose readings were directly downloaded during each clinic visit from the home blood glucose meter using the Diasend® platform (Diasend Ltd.
Outcomes The primary outcome was the absolute number and throughput/recruitment rate of eligible women with GDM who were on maximum tolerated metformin and who agreed to be randomised to glibenclamide or insulin. Other key feasibility outcomes included: the proportion of women who agreed to participate (uptake); the proportion of women randomised who were retained in the study (retention); the proportion of women who remained on allocated treatment (adherence) and provided outcome data (i. e. who were not lost to follow-up); the proportion of clinicians who adhered to the protocol per se (compliance); the safety of the two treatment regimens including the number of episodes of hypoglycaemia needing treatment; any other serious adverse events (SAEs, defined as an untoward medical occurrence that does not necessarily have a causal relationship with the investigational medicinal product but is life-threatening, requires hospitalisation, consists of a birth defect or congenital abnormality, results in death, persistent or significant incapacity or disability, or any other serious medical event), and suspected unexpected serious adverse reactions (SUSARs, defined as any adverse event that is serious and suspected to be causally related to the investigational medicinal product).
Unadjusted comparative analyses were performed for clinical outcomes, except where the number of events in either arm was less than 2, in which case overall counts with 95% CIs were given. For continuous outcomes, results are given as differences in means, or differences in medians (if the data were skewed) with 95% CIs. For binary or categorical outcomes, risk ratios with corresponding CIs were calculated. Participant satisfaction was presented as counts and percentages by trial arm, and overall 95% CIs. Blood glucose outcomes (waking and post-prandial) were compared by trial arm. To adjust for variation in the duration of therapy in the groups, prior to unblinding it was agreed to determine number of excursions per woman, per week of treatment, and to present the number and percentage of women with at least one excursion.
Acknowledgements This study would not have been possible without the commitment of the pregnant women who participated, and we are enormously grateful to them. We are grateful to the members of the Trial Steering Committee:  John McKnight  (chair),  Nick Embleton , and  Jason Waugh ; Data Monitoring Committee:  Graeme MacLennan  (chair),  Fiona Williams  and  Jane Ramsay ;  Bernadette Gallagher  and  Tariq Derbeb  for Trial Administrative Support;  Andy King  ( NPEU ) for Database Support;  Karen Adamson  ( PI) St John 's hospital, Livingston and co-investigators  Alison Macleod ,  Rohana J. Wright  and  Liesbeth Vanlook  ( St John 's hospital, Livingston);  David Carty ,  Janice Gibson  and  Andrew Gallagher  ( Queen Elizabeth University Hospital, Glasgow ); research midwives and nurses; diabetes specialist nurses and pharmacy staff and all the others who have helped with the study but we have been unable to name.
IV. EXPERIMENTAL RESULTS. A. Test Bench. A three-phase induction machine has been rewound to obtain an asymmetrical six-phase induction machine whose electrical parameters have been determined using conventional AC-time domain experiments and stand-still with inverter supply test  [44] [45]  (see obtained results in Table  1 ). The six-phase machine is driven by conventional three-phase power converters from Semikron (SKS22F modules) that correspond to VSCs1 and VSCs2 in Fig. 1. The control actions are performed by a TI TMS320F28335 digital signal processor. This control unit is programmed through JTAG and TI proprietary software Code Composer Studio. Current and speed measurements are taken with four hall-effect LEM LAH 25-NP sensors (with an accuracy of the «0,5%) and a GHM510296R/2500 digital encoder, respectively.
In this paper, an energy management strategy (EMS) for a specific multi hybrid plug-in electric bus is designed. This bus is equipped with an internal combustion engine, a hydraulic motor, an electric motor and battery. Considering the physical characteristics of the studied hybrid electric bus (i. e. , the system dynamics and the power sources limits), an optimal control technique based on Pontryagin's minimum principle (PMP) is used in order to ensure that the bus achieve a significant improvement in energy efficiency. Furthermore, information of traffic conditions obtained from intelligent transportation systems is used to further optimize the energy management strategy and to accurately control the battery depleting rate. The work proposed in this paper is conducted on a dedicated high-fidelity model of the hybrid bus, that was developed on MATLAB/TruckMaker software.
SIMULATION RESULTS The implementation of the proposed energy management strategy is carried out using a dedicated high-fidelity model of the hybrid bus, that was developed on Matlab/TruckMaker software (cf. Figure  5 ), in order to investigate their performance in a test platform which reproduces accurately the real operating behavior of the bus. Figure  6  shows the overall simulation results of the proposed energy management strategy over an optimized driving cycle which represents different usage conditions of the studied hybrid electric bus including urban and extraurban driving environments. The video showing this overall demonstration using TruckMaker is available from this link: https://goo. gl/8mJT3s. Figure  6 (a) gives an outline of the desired speed and the actual bus speed when the designed optimization algorithm is applied to calculate the optimal power split.
While Virtual Reality applications are increasingly attracting the attention of developers and business analysts, the behaviour of users watching 360-degree (i. e. omnidirectional) videos has not been thoroughly studied yet. This paper introduces a dataset of head movements of users watching 360-degree videos on a Head-Mounted Display (HMD). The dataset includes data collected from 59 users watching five 70 s-long 360-degree videos on the Razer OSVR HDK2 HMD. The selected videos span a wide range of 360-degree content for which different viewer's involvement, thus navigation patterns, could be expected. We describe the open-source software developed to produce the dataset and present the test material and viewing conditions considered during the data acquisition. Finally, we show some examples of statistics that can be extracted from the collected data, for a content-dependent analysis of users' navigation patterns.
For this reason, in this paper, we present a 360-degree video head movement dataset gathered by recording the navigation patterns of 59 users watching five 70 s long 360-degree videos. The dataset is available on our website. 1 In order to help the community to reproduce our results and to upgrade this dataset, we release the open source software developed for our data collection campaign and allow new contributors to share their datasets on our website. 1  The rest of the paper is organized as follow. Section 2 reviews the existing works that have reported an analysis of the navigation patterns of viewers consuming 360-degree content via HMDs. Section 3 describes the choices made to setup our data collection, the software and the experimental conditions. Section 4 details the structure of our dataset so that it can be reused by the community.
The method used to process the information on user's head movements and derive saliency maps is described by Upenik and Ebrahimi  [16]. De Abreu et al. [7]  describe a study of navigation patterns collected during 360-degree image viewing on a HMD. The testbed and collected dataset are publicly available. To the best of our knowledge, the research community misses a dataset of head movements of users consuming 360-degree videos via HMDs, which is the contribution described in this paper.
Software We developed a 360-degree video player to capture and save to a log file the user's head position at each frame or whenever a head movement (i. e. a motion event) occurs during the visualization of a video on an HMD. The main purpose of the software is to accurately associate each motion event to a timestamp corresponding to a video timestamp at frame level, thus, to the id of the video frame displayed by the HMD when the motion event occurred. Please note that we share the software in a public repository 1 with the MIT open source license  [1]. Therefore, it can now be used by the scientific community, potentially to extend the dataset with more viewers, more videos, and different viewing conditions. The software has been implemented in C++, based on the Open-Source Virtual Reality (OSVR) Application Programming Interface (API)  [4] , the Open Graphics Library (OpenGL) [3], and the ffmpeg library [2].
We performed all tests and the data collection campaign on Linux OS with the Razer OSVR Hacker Development Kit 2 (HDK2) HMD  [14]  but the software is expected to be compatible with any HMD and Windows OS. 2  Figure  2  illustrates a high-level diagram of the input and output interfaces of our software. The experimenter can set some input parameters by using a configuration file. This file specifies: (i) the sphere to plane projection used to produce the planar video file ; (ii) the time offset in second starting from which the video file is displayed; (iii) the number of video frames, i. e. the duration of the segment, to be displayed. The time offset and duration are specified because the input 360-degree video can be a video of several minutes of duration: the configuration file allows to specify what portion of the video to display to the user, so that the navigation patterns are measured over a fixed limited duration.
Test Material The navigation patterns in the dataset have been collected on five 360-degree YouTube videos, described in Table  1. We limited the test material to few videos to be able to perform a viewing session of reasonable duration and collect data from many users. Therefore, the test videos have been chosen to span a wide range of 360-degree content, including tourism, thrill, and discovery, for which different viewer's involvement, thus navigation patterns, could be expected. Each video file has been downloaded in equirectangular format, at the maximum resolution and bit-rate available on YouTube (reported in Table  1 ), The videos do not have the same frame rate but this does not impact the data collection since, as detailed in Section 3. 2, the head position is captured for each motion event, rather than at a fixed rate.
Pre-Processing The population of users from which we collected the dataset is close to the typical audience expected for viewport adaptive streaming, therefore there is no need to filter the users. In Section 4. 2, we mentioned that the head position sampling rate is not constant. This means that some sample are very close in time and some are farther away. In order to compute head movement statistics, we resampled the collected data, i. e. the quaternions, using a sampling frequency of 30 Hz. We chose 30 Hz because most of the videos used to generate the dataset have a frame rate of 30 fps. There are multiple ways to interpolate quaternions based on existing samples: we chose to use the spherical linear interpolation (SLERP)  [11] , using the two samples that are the closest in time to the timestamp we want to extract.
Head movements With adaptive streaming, it is often not possible to switch from video representations once a specific representation started to be displayed to the user, so it is important for the video segment size to be short enough to allow frequent representation switching. On the other hand, if the video segment is too short, video codecs are less efficient and the service provider needs to store and transmit more metadata to describe the segments. To estimate the maximum duration a video segment should have, we compute "how static the user is". Particularly, for each user, we compute the angular distance between the center of the viewport at the beginning of a segment and the center of each viewport attended by the user during the duration of a segment. Figure  5  shows the cumulative density function (CDF) of the maximum angular distance traveled during a fixed duration inside each segment by each user and for each video.
We used segments of length 1 s, 2 s, 3 s, and 5 s. It can be noticed that, for instance, within a segment duration of 2 s, 95% of the users move less that π /2 radians. This means that within a 2 s length segment, 95% of the user stay inside the hemisphere centered on the head position of the user at the beginning of the segment. Therefore, we conclude that 2 s is probably a good compromise for the duration of the segment. Figure  6  shows the CDF of the maximum angular distance per video for a segment length of 2 s. The data shows that, in this dataset, there are three categories of videos: a video triggering with very few head movements (Roller-Coaster), a video triggering many head movements (Timelapse), and intermediary videos (Venice and.
CONCLUSION In this paper we presented a dataset including the head positions of 59 users recorded while they were watching five 70 s-long 360degree videos using the Razer OSVR HDK2 HMD  [14]. The dataset is available on our website 1 alongside the used videos and the open-source software that we developed to collect the dataset. We described our settings, the test material and how we performed the data collection. We also detialed the structure of the dataset. Finally we introduced examples of statistics that can be extracted from the dataset to provide an overview of the users' behaviour and the videos characteristics, focusing on the viewport adaptive streaming scenario. We expect that this dataset will help researchers to study and understand 360-degree video consumption. The prediction of navigation patterns is a cornerstone of the new generation viewport-adaptive streaming systems for 360-degree content.
2008 ). Historically, one of the first invertebrate species described from Antarctica was a sea spider (Decolopoda australis Eights, 1835) and since then, pycnogonids have been considered as a flagship group in Antarctica. Moreover, taxonomists were particularly interested in Antarctic sea spiders because of their large size and their "extra-legged" representatives (ten legs or more) (e. g. ,  Bouvier 1910). In contrast, species from non-Antarctic regions are often tiny in size, and thus more difficult to collect or study by non-specialists. As a consequence, most of the barcode sequences (5' fragment of the gene encoding the first subunit of cytochrome c oxidase, CO1) currently available for Ammotheidae in the nucleotide databases come from southern ecoregions (South Australia, South America and Antarctica; Fig.