dataesr/scientific-paragraphs-categorization huggingface dataset:
Accuracy In Table  4  we summarize the angular accuracy of the nine methods for all samples; Table  5  shows the relative endpoint error. The absolute endpoint error as well as robustness measures for angle and endpoint error are provided in the supplementary material. Given that the accuracy of each algorithm varies  The relative error is given with respect to the manual measurement. somewhat across the dataset, it is difficult to detect a trend or identify the best performing method. Note however that among the LucasKanade variants, the Savitzky-Golay filter scores best in terms of angular accuracy on 4 out of 5 samples, as does the DirectionSelective filter. The Savitzky-Golay variation of the LocalPlanes method computes accurate angles but struggles with the correct vector magnitude on three of the samples.
DISCUSSION This study compares accuracy and processing time of nine eventbased optical flow algorithms. A direct comparison with framebased methods is possible by applying them on the frames included in this dataset (which has not been done yet). In order to use existing frame-based benchmarks (e. g. , on the Middlebury database),  (Barranco et al. , 2015)  created synthetic events by simulating 50,000 frames for every two frames and interpolating frame-by-frame changes in intensity. This was not feasible here because our implementations compute normal flow, whereas the Middlebury ground truth provides 2D flow. However, the comparison of event-and frame-based algorithms running on seven samples of the Middlebury dataset, as done by  Barranco et al. , offers at least some rough indicator for the performance of the methods presented here with respect to previous results.
All methods take less than 10 µs to calculate the motion vector of a single event; DS, IMU and LP SG take less than one µs per event. Thus, they all run in real-time on contemporary PCs 17  if the event-rate does not exceed 1e5 events per second (eps), or 4000 events per frame with a frame-rate of 25 fps. The mean event rate of our rotating disk sample is 1e5, and 3e5 eps for the rather dense translating sinusoid, which can still be processed in real-time by four of the methods. Natural input even from data recorded by DAVIS240 cameras on moving platforms seldom exceeds 1e6 eps. In case it does, the sequence would have to be processed by LP SG or DS, or subsampled to reduce event density and make it suitable for slower algorithms. Subsampling is usually unproblematic in global motion estimation (e.
This error is due to the fact that the events along the direction of motion are by no means homogeneously 19 RefractoryFilter source code. distributed. For an object moving with constant velocity (e. g. , the translating sinusoid), a certain pixel may fire very quickly after an adjacent pixel (resulting in high speed), while another pixel of the same edge fires much later than its neighbor (resulting in low speed). A test stage that filters out speeds far above average helps remove this effect in large part. Another source of error is the quantization of vector direction in bins of 45 •. In our dataset, the DS filter is favored by the use of pure pan and tilt movements and this bias should be taken into account by users who desire continuous angle motion vectors. A different event-based approach to motion estimation using direction-selective filters has been taken recently by  Brosch et al.
Compared to the original Lucas-Kanade  (Benosman et al. , 2012)  and Local Plane Fit  (Benosman et al. , 2014)  algorithm, our implementations 20  LK BD and LP orig reduced the computational cost by 26 and 29% respectively. We also discuss the error statistics used so far and suggest a purely angular measure between flow vectors in the image plane. This serves to lessen the bias inherent in the conventional average angular error and to separate a deviation in direction from speed error, to better expose aspects requiring improvement. With the IMU-integration we establish a new performance measure to compare various motion flow algorithms in situations where the direction normal to edges is known. The data set of consisting of a mixture of DVS and DAVIS data collected for this study has been shared to provide a baseline for future comparison 21.
All the algorithms developed here are open-sourced in the jAER project, in the Java package ch. unizh. ini. jaer. projects. rbodo. opticalflow 22. The supplementary data to this paper includes images of the experimental setup and the real data samples. Videos (in the database repository) of several of the algorithms show how they behave dynamically for some of the test cases studied here. Complete result tables compare the algorithm accuracy and cost for the different test cases, including robustness measures (like the percentage of flow vectors with angle errors above 3 • ). It is easy to record natural data for which all of the described algorithms fail rather dramatically, but further pursuit of accurate event-based methods with DVSs is worthwhile considering that this neuromorphic hardware fits many of the challenging demands of real-time applications in terms of low power consumption, small response latency, and efficient use of hardware resources.
ACKNOWLEDGMENTS This work is supported by the  European Union  funded project  SEEBETTER  ( FP7-ICT-2009-6 ),  VISUALISE  ( FP7-ICT-2011. 9. 11 ), the  University of Zurich  and the  Swiss Federal Institute of Technology. We greatly appreciate the helpful reviewers comments, suggestions from  G. Orchard ,  E. Muggler  and  M. Osswald  regarding camera calibration,  M. Milde  and  G. Orchard  for insights into the original Local Planes method, and  L. Longinotti  for his complete integration of the IMU data acquisition in the DAVIS camera logic.
This assumption does not hold if the neighborhood covers motion boundaries, which are admittedly the most interesting regions for determining structure from motion. Because most information in event-based methods comes from contours, this may well be a significant error source that our dataset does not cover well because of its basis in the motion field caused by camera rotation. However, events at an edge typically span a width of several pixels when accumulated over the time window set for flow computation, so except for the outermost events the assumption will hold. Frontiers in Neuroscience | www. frontiersin. org.
Systematic uncertainties Systematic uncertainties are summarized in Table  1. In both data and simulated event samples, trigger efficiencies are evaluated with a tag-and-probe technique. The ratio between data and simulation is applied to simulated events, and the size of the resulting change in expected yield is taken as the uncertainty for the determination of the trigger efficiency. This uncertainty is around 2% of the final estimated yield. For Z → e + e -e + e -events, the uncertainty increases to 4%. The lepton identification and isolation efficiencies in simulation are corrected with scaling factors derived with a tag-and-probe method and applied as a function of lepton p T and η. To estimate the uncertainties associated with the tag-and-probe technique, the total yield is recomputed with the scaling factors varied up and down by the tag-and-probe fit uncertainties.
Acknowledgments We thank  Massimiliano Grazzini  and his collaborators for providing the NNLO cross section calculations. We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies:  BMWFW  and  FWF (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ , and  FAPESP (Brazil) ;  MES (Bulgaria) ;  CERN ;  CAS, MoST , and  NSFC (China) ;  COLCIENCIAS (Colombia) ;  MSES  and  CSF (Croatia) ;  RPF (Cyprus) ;  SENESCYT (Ecuador) ;  MoER ,  ERC IUT  and  ERDF (Estonia) ;  Academy of Finland ,  MEC , and  HIP (Finland) ;  CEA  and  CNRS/IN2P3  (France);  BMBF ,  DFG , and  HGF (Germany) ;  GSRT (Greece) ;  OTKA  and  NIH (Hungary) ;  DAE  and  DST (India) ;  IPM (Iran) ;  SFI (Ireland) ;  INFN (Italy) ;  MSIP  and  NRF (Republic of Korea) ;  LAS (Lithuania) ;  MOE  and  UM (Malaysia) ;  BUAP ,  CINVESTAV ,  CONACYT ,  LNS ,  SEP , and  UASLP-FAI (Mexico) ;  MBIE (New Zealand );  PAEC (Pakistan) ;  MSHE  and  NSC (Poland) ;  FCT (Portugal) ;  JINR (Dubna) ;  MON, RosAtom, RAS  and  RFBR (Russia) ;  MESTD (Serbia) ;  SEIDI  and  CPAN (Spain) ;  Swiss Funding Agencies (Switzerland) ;  MST (Taipei) ;  ThEPCenter, IPST, STAR  and  NSTDA (Thailand) ;  TUBITAK  and  TAEK (Turkey) ;  NASU  and  SFFR (Ukraine) ;  STFC  ( United Kingdom );  DOE  and  NSF (USA).
Environmental measurements A meteorological station to continuously monitor environmental variables was set up on-site in June 2014. This included measurements of air temperature (T a ; model CS 107, Campbell Scientific Inc. , Logan, UT, USA), photosynthetically active radiation (PAR; model LI-190SL, LI-COR Inc. , Lincoln, NE, USA) and precipitation (PPT; tipping bucket model 52202, R. M. Young Company, Traverse City, MI, USA) at 1. 2 m height above the ground. Soil temperature (T s ; depths of 5 and 30 cm) was measured with temperature probes (model CS 107, Campbell Scientific Inc. , Logan, UT, USA) and soil volumetric water content (VWC; depth 5 cm) with water content reflectometers (model CS615, Campbell Scientific Inc. , Logan, UT, USA). All automated abiotic data were collected in 1 min intervals and stored as 10 min averages on a data logger (CR1000, Campbell Scientific Inc.
Acknowledgements. This study was supported by the  European Regional Development Fund  ( Centre of Excellence in Environmental Adaptation ENVIRON and Centre of Excellence in Biodiversity Research FIBIR ), by the  Ministry of Education and Research of the Republic of Estonia  (grants  IUT2-16 ,  IUT34-7  and  IUT34-9 ) and by the  Estonian Environmental Observatory Biosphere-Atmosphere Science and Development Programme: BioAtmos (KESTA ,  SLOOM12022T ). We would like to thank  Eeva-Stiina Tuittila  for her valuable comments on the original.
Alternatively, in some experiments, 24-h treatment with 1 mM actinomycin D was used as 100% death control. For cell death analysis by flow-cytometry, cells were stained using Alexa Fluor 647 Annexin V (BioLegend #640912) according to the manufacturer's protocol and quantified on a BD FACSCalibur instrument. For clonogenic survival assay, 800 cells stably expressing the construct of interest were plated into each well of a 6-well tissue culture plate. The following days cells were treated with the indicated stimuli. Ten days later, cells were stained with 1% Methylene Blue in methanol/H 2 O (1:1 vol/vol). Following image capture, colonies were counted automatically using Fiji software (http://fiji. sc/Fiji) and compared with untreated cells (taken as 100% survival). Images were processed as followed: 1/ conversion of scans into 8 bits images and threshold adjustment to remove background; 2/ separation of colonies using the Watershed tool; 3/ counting of colonies using the Analyze Particles tool.
Acknowledgements This work was supported by funding from the  Royal Society , a  Cancer Research UK Programme Foundation  award ( C40872/A20145 ),  BBSRC  (grant  BB/K008374/1 ) and TENOVUS Scotland. S. W. G. T. is a  Royal Society University Research Fellow. J. L. was supported, in part, by the  University of Lyon  and by fellowships from  Fondation ARC pour la Recherche sur le Cancer  and  Hospices Civils de Lyon. G. I. was supported by an  EMBO  long-term postdoctoral fellowship (ALTF  55-2013 ). E. G. was supported by a  Cancer Research UK  studentship. F. T. and F. E. were supported by the  Emmy Noether program  and the  CRC746 of the German Research Council (Deutsche Forschungsgemeinschaft, DFG)  and the  Centre for Biological Signalling Studies (BIOSS ,  EXC-294 ). We thank  Andrew Keith ,  Billy Clark ,  Tom Gilbey , ( Beatson Institute )  Monica Hou  and  Catriona Thompson  ( University of Glasgow ) for technical assistance.
Measurements and EIH definition Oxygen saturation level of haemoglobin was assessed by the peripheral capillary oxygen saturation (SpO 2 ). SpO 2 was measured continuously during tests using an ear-lobe pulse oximeter (Nonin, Minnesota, USA). PureSAT1 technology used in Nonin Medical pulse oximeter guarantees an measurement accuracy of ± 2. 1% compared to the gold standard which is CO-oximetry analysis of arterial blood samples. The ear was pre-warmed by a vasodilating capsaicin cream (Finalgon, Fher, Spain) to avoid poor perfusion during exercise. EIH may be considered to exist when SpO 2 decreases of 4% between rest and maximal effort of the test at SL of at least the last 3 minutes  [9]. At the same time, respiratory data were collected by a portable automatic breath-by-breath metabolic system (K4b 2 , Cosmed, Rome, Italy): VO 2 (ml.
Statistical treatment The results are expressed as means ± SD. Differences with no repeated measures among the three groups were analysed using one-way analysis of variance (ANOVA). Two-way ANOVA were used for repeated measures to analyse the main effect and interaction of altitude and group on measured parameters. Correlations between the variables were tested using Pearson's product-moment correlation coefficient test. For all tests, the level of statistical significance was set at p < 0. 05. Analyses were conducted using SigmaStat software (Ver 3. 5).
MATERIALS AND METHODS Patients. This study was performed within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), a European Society of Gynecological Oncology (ESGO) consortium aiming to improve and individualise treatment of women with uterine cancers by sharing expertise. All ENITEC members were invited to participate in this study and to include patients treated for stage I EEC (a maximum of 150 cases per centre), stage II-IV EEC, or NEEC. Cases with any non-endometrioid component were included in the NEEC group, except for the mucinous carcinomas that were included in the EEC groups as their characteristics and prognosis are similar to that of endometrioid carcinomas  (Lax, 2004). Only cases diagnosed by an expert gynecological pathologist, with complete data on treatment and pathology, and at least 36 months of follow-up were included.
Clinical and pathological data were recorded from the patient files into a database, including patient age, date of diagnosis, surgical treatment (including lymphadenectomy and omentectomy), tumour histology and grade, myometrial invasion, cervical invasion, LVSI, FIGO stage, adjuvant treatment (including radiotherapy, chemotherapy and chemoradiation), residual disease, recurrent disease, and death. Tissue and staining. One representative slide was selected per case. Blank 4 mm sections, cut from the corresponding formalinfixed, paraffin-embedded tissue blocks, on Superfrost slides were sent to the Radboud University Medical Center. A haematoxylin and eosin and an immunohistochemically stained L1CAM slide were made for every case. Immunohistochemical staining was performed in semiautomatic staining devices using an optimised version of the previously described staining protocol  (Fogel et al, 2014).
These risk factors were deep myometrial invasion, patient age over 60 years, LVSI, non-endometrioid (except mucinous) histology, advanced FIGO stage, and nodal involvement. The Kaplan-Meier curves of 10-year disease-free and overall survival were generated for the stage I EEC, stage II-IV EEC, and NEEC subgroups. The corresponding hazard ratio (HR) and 95% CI was calculated using Cox regression analysis. For stage I EECs a multivariate analysis was performed including covariates that were significantly associated with outcome in the univariate analysis. Sample size calculation accounted only for multivariate Cox regression analysis of the stage I EECs. Statistical differences were considered significant at a two-sided P-value of p0. 05. SPSS version 22 (SPSS IBM, New York, NY, USA) statistical software was used to perform the statistical analyses.
In light of the recently proposed subdivision of endometrial carcinomas into four subgroups based on the molecular profile, it would be interesting to analyse the L1CAM expression in these four groups (Cancer Genome Atlas Research Network et al, 2013). The studies of both Dellinger et al (2016) and Van Gool et al  (2016) looked at L1CAM expression in the mRNA data from the TGCA database, but unfortunately they did not describe the expression of L1CAM relative to the four proposed subgroups. If either L1CAM expression or the proposed genetic subdivision are to be used in the future management of endometrial carcinomas, it is imperative to know how these markers are related to each other. Strengths and weaknesses. This is the largest study to date including all endometrial carcinoma types. Complete surgical staging was performed in the majority of cases, limiting the risk of under diagnosis, and a minimal follow-up of 36 months was required, limiting the risk of missing disease recurrences and deaths.
For p-arm acrocentric chromosome identification, whole-chromosome painting (MetaSystems) was performed after subtelomeric-FISH. Images of hybridized metaphases were captured with a Zeiss Axioplan II fluorescence microscope and processed using ISIS software (MetaSystems). Telomere quantification. Following telomere hybridization, images were captured, using either Metacyte ® software (MetaSystems) for global telomere length (around 5000 nuclei, in quadruplate) or Autocapt ® software (MetaSystems) for single telomere length (around 30 metaphases). In both cases, quantification was evaluated by grayscale analysis (Q-FISH). For determining global telomere length, Cy3 intensity was normalized by DAPI (4′ 6′ diamino2-phenylidole) intensity to compensate for the variable number of chromosomes in each PD.
Acknowledgements We would like to thank  Luis Martins ,  Ronan Pendu ,  Jean-Patrick Pommier  and  Luc Morat  for contributing to preliminary experiment. This work was partially supported by a grant from the  European Community 's  Seventh Framework Program  (EURATOM) contract Fission-2011-269533 (EpiRadBio). William Hempel is paid by the  European Community 's  Seventh Framework Program  (EURATOM) contract Fission-2011-249689 (DoReMi).
Background Mucopolysaccharidosis type IVA (MPS IVA) or Morquio A disease (MPS IVA; OMIM 253000) is a metabolic lysosmal and autosomal recessive disease resulting from the deficiency of the enzyme N-acetylgalactosamine-6sulfate-sulfatase (GALNS: E. C. 3. 1. 6. 4), and the accumulation of undegraded or partially degraded glycosaminoglycans (GAGs): keratan sulfate (KS) and chondroitin-6-sulfate (C6S) in lysosme. Phenotypes vary from the classical form (life span of 20 to 30 years old) with corneal opacity, short trunk dwarfism, heart valvular disease, and severe bone dysplasia to attenuated forms with normal life span, mild bone and visceral complications. There is no impairment of the central nervous system in all Morquio A phenotypes  [1, 2]. The GALNS gene, located on chromosome 16q24. 3, contains 14 exons spanning 50 kb (GDB accession ID: 129085) and is transcribed into a 1566 bp cDNA, which encodes a 522-residue glycopeptide.
To date, more than 200 different mutations associated with MPS IVA have been identified [Human Gene Mutation Database (HGMD, 2014); http://www. hgmd. org/] including point mutations, splice-site mutations, deletions and insertions. This heterogeneity may explain the important phenotypes variability observed in MPSIVA patients  [2] [3] [4]. Consanguineous marriages are associated with a higher frequency of autosomal recessive disorders. Thus, firstly an association between parental consanguinity and the frequency of MPS IVA exists  [2] , secondly the impact of consanguinity in MPS IVA was treated in several studies highlighting the major role of intermarriage in the recurrence to have haplotype  [2]. The incidence of MPS IVA in Tunisia is also high, estimated at 0. 45 in 100. 000 live births  [5].
Acknowledgements We thank  Sébastien Wielgoss  and  Jean-Claude Walser  from the  Genetic Diversity Center (GDC)  at  ETH Zürich  for their help with bioinformatic analysis and SNP calling of evolved populations. We are grateful to  Yuen-Tsu Nicco Yu  and  Dominique Schneider  for helpful discussion and critical reading of the manuscript. We thank  Francesca Fiegna  and  Michaela Amherd  for technical assistance. OR is recipient of an  EMBO  ( European Molecular Biology Organization) Long-Term Fellowship.
Materials and equipment Dry marigold flowers were used as the main source of dye extraction. Lab-grade sodium hydroxide and dilute hydrochloric acid solutions were used for pH adjustment during dye extraction. Labgrade Glauber's salt was used to promote dye exhaustion during dyeing. All the dyeing experiments were completed on industrially prepared ready-to-dye mercerized cotton fabric using lab-scale high temperature exhaust dyeing machine. Data color SF-600 spectrophotometer with color measurement software was used for measuring color strength of the dyed fabrics. Washing, crocking and light fastness properties fabric dyed with extracts were determined by using launder-o-meter, crock meter and fado meter respectively.
Design of experiment Response Surface Methodology (RSM) comprises a set of advanced design of experiment techniques that help better understanding and optimizing a response. Central Composite Design (CCD) is a popular design of experiments in RSM that is commonly used for finding the levels of input variables that optimize a response. Response surface equations in CCD can also model how changes in input variables influence a response of interest  [14]. Total 20 experiments were designed and analysis of experiments was conducted using "Design-Expert 7. 0" software package.
Color value assessment of dyed fabric The color strength (K/S) values of dyed fabric samples were measured with Spectraflash -SF650 spectrophotometer by Data color International. The spectrophotometer gave the K/S values according to the given relation K/S=(1-R) 2 /2R, where R represents sample reflectance, K is coefficient of absorption and S is the coefficient of scattering. A higher value of K/S indicates higher color strength, as a darker sample gives lower light reflectance and higher light absorbance  [15].
). The experiment was programmed in Matlab (The MathWorks), using custom software (BPyNIC^) that functioned as a connector to the Python interface of the NIC2 drivers (Cochlear Corp. ). Pulse trains consisted of anodic-leading biphasic pulses presented in monopolar (MP1 + 2) mode, with a phase duration of 40 μs and an inter-phase gap of 8 μs. For the Bbasalĉ ondition, electrode #11, in the middle of the array, was used. For the Bapical^condition, four of the patients were tested on electrode #17. The fifth patient was tested on electrode #18 instead, because electrode #16 was switched off in their map. All stimuli were loudness balanced at each stimulation site and base rate. To loudness balance two stimuli, A and B, the most comfortable level (MCL) of A was first measured by asking the subject to rate loudness on an 11-point clinical loudness scale, where MCL corresponded to point 7.