dataesr/scientific-paragraphs-categorization huggingface dataset:
[9] , and postprocessing of the acquired images, Scharstein et al. [20]  have provided a set of 33 scenes with subpixel disparities, some of which achieve 0. 2 pixel accuracy. This method, however, due to the complexity of its implementation, encounters a number of problems  [22, Section 4. 1] such as: • some pixels have partial occlusion; • some pixels have no signature because of shadow and reflection effects; • the presence of aliasing or blurring in signatures; • some signatures are inconsistent because of the illumination changes; so that it takes at least twenty steps to process the raw data [20, Figure  3 ] to obtain the disparity maps. The KITTI Vision Benchmark Suite. Geiger et al. [7]  proposed an image database acquired from a vehicle with different sensors namely two high resolution cameras, a laser scanner and a GPS location system.
This database serves as a tool for benchmarking and ranking matching algorithms. They provide a training set of nearly 200 stereo pairs with ground truths composed of disparity, occlusion and optical flow maps. However, these ground truths were obtained from the scans of a rotating 3D laser scanner, so that the laser sampling does not correspond to the pixel sampling of the image. Nearly half of the pixels of the image have no ground truth, and it must be deduced by interpolation. In addition, disparities and optical flow maps have integer values. Image Sequence Analysis Test Site (EISATS). Reinhard Klette et al. [13]  proposed ten stereo sequences acquired from cameras and a laser scanner mounted on vehicles. Most of these scenes are grayscale and made in a real environment. Among them, the sequence 1 has car kinematics ground truths, sequence 2, in synthetic images, has temporal optical flow between frames, and sequence 6 has disparity and depth maps deduced from the scan, but relatively noisy and incomplete.
Stereo Ground Truths in a Virtual Environment University of Tsukuba Stereo Flow. Martull et al. [16]  produced a 1800 stereo pairs dataset of 640 × 480 photo-realistic images with ground truths including: disparity, occlusion and discontinuity maps as well as the position and orientation of the cameras. The pairs were extracted from a 3D synthetic scene representing an office created with the Autodesk Maya 2012 software then textured using real and synthetic textures. These maps are pixel-accurate. It is not possible to use such a database for a tenth-pixel or even a quarter-pixel benchmark because this operation would imply reducing the images' size, which is already small. MPI Sintel Flow. The MPI Sintel database  [28, 2]  is a set of sequences and images picked from an animated film containing varied and realistic environments.
Its features are: long movements, non-rigid moving objects, specular reflections, camera shake and other atmospheric effects. It is mainly dedicated to the optical flow evaluation: objects and characters are moving from one image to another. The database consists of 35 excerpts split into a training set (23 sequences) and an evaluation set (12 sequences). Optical flow, (poorly) estimated edges, occlusion maps and rendering effects are indicated there. This database cannot be used for the evaluation of stereo algorithms which assume rigid deformations between images.
Ground Truths Dedicated to 3D Reconstruction. The following bases cannot be used for stereo matching in itself, but for the next step which, is to build surfaces from point clouds estimated by matching. Middlebury College. Middlebury College  [23]  proposes two scanned objects (a Roman temple and a dinosaur) through 395 different points of view but whose acquisition was not coupled with a camera. The laser scanner used was moved to cover a hemisphere. However, only 80% of the hemisphere of the Roman Temple object is exploitable. Stanford University. The Stanford 3D Scanning Repository database  [3]  is a set of a dozen 3D scans of objects which contains the coordinates of 3D points and the triangulations of the mesh. University of Utah. Berger et al. [1]  studied the problem of surfaces reconstruction.
To this end they simulated the acquisition of data from a laser scanner to reproduce realistic point clouds. They propose a set of 5 items scanned synthetically and for each of these, 48 point clouds. However, the views of these clouds are always the same, only the sampling changes. Institut Farman. Digne et al. [6]  have produced a 3D points dataset composed of nearly 200 scenes of items that have been both scanned by a 3D high precision scanner laser and photographed by a CCD camera. Each of the 11 items presented was scanned under 18 views. The high-precision images are accompanied by 3D point coordinate files.
Our Approach As we can see, databases acquired in a real environment suffer from a lack of accurate information. This is due to difficulties in handling and synchronizing acquisition devices. On the contrary, images obtained by synthesis like for Sintel or Tsukuba provide accurate and complete sets. These however do not reach subpixel precision regarding the edges and they are more oriented towards optical flow estimation. Nevertheless the use of synthetic scenes takes on its full meaning because it can precisely control many parameters and work on more realistic scenarios. Our approach is to use images produced by the renderer and also to exploit the data generated during rendering. When creating an image, the renderer generates, for each pixel p, a number N(p) of rays that will intersect the objects in the scene at 3D points P(p, n) with depth r n for n = 1,.
, N(p). The color characteristics of these points are then averaged to determine the final color of p. We will give more details in Section 5 on the calculation of these colors and the underlying mathematical model. These contributions thus form for each pixel a cloud of 3D points and therefore, in their entirety, an oversampling of the objects in the scene much more important than the oversampling of the image itself. This set of data is the starting point to create precisely all ground truths that we need and that are the subject of the next sections. Table  1  summarizes the main properties of the bases previously mentioned as well as ours, entitled "CMLA dataset". Y Y N N Y N Y Y noise esti- mate N N N N N N N Y noise es- timate of 3D points position N N N N N N N Y 1 optical flow map N Y Y N N Y depth map N Y Y N N N N Y disparity map preci- sion 0.
2 pix. 1 pix. 1 pix. 1 pix. 1 pix. N 10 -6 pix. 1 occlusion map partially Y N N Y Y N Y The creation of synthesized images and ground truths led us to choose the rendering engine LuxRender  [27]. This software presents many advantages. It is a clone of the software PBRT developed by Pharr et al. [27]  whose design is very detailed and whose interest is to rely on physical characteristics of materials such as metals and photometric features of the light sources so that the rendering is very realistic. It also provides natively floating 16-bit EXR or 16-bit PNG image formats as well as a depth map. Finally, it may be coupled to the 3D builder software Blender 2.
Conclusion The qualitative evaluation of very accurate stereoscopic algorithms requires having at one's disposal stereo pairs with minimal and quantified noise, accompanied by ground truths as accurate as possible. We presented a new method of generating ground truths with synthetic images. This approach, which takes advantage of spatial oversampling ray tracing, allows to make maps of disparities and occlusions with a level of accuracy which has never been reached before. Furthermore, the iterative creation of image synthesis during rendering allows us to make an analytical estimate of the residual noise. This method allows us to offer to the scientific community, a new dataset of 66 reference stereo pairs, directed to evaluating stereoscopic and 3D reconstruction algorithms.
B Constitution of the Database We used seven different synthetic scenes observed from four points of view and named v +000 , v +001 , v +010 and v +050. Four of these scenes were considered with two different color characteristics: with and without reflective materials. In the end, the base consists of 66 stereo pairs. Figure  9  shows the different scenes for view v +000. The images produced have a size of 960 × 540 in portrait mode and of 540 × 960 in landscape mode. They are offered in three formats, namely: EXR 16-bit, 16-bit PNG and TIF 16 bit float. The first two mentioned formats come directly from the rendering engine LuxRender while the third was obtained by a post-processing of EXR images detailed in Section B. 3. Each pixel received an average of over 2 million contributions. The noise estimate was made by creating, for each of the 11 scenes u K , a identical u k scene but with a rendering duration k much lower by around 100 000 contributions per pixel and then by applying formula  (11).
Acknowledgements This work was partly funded by the  Centre National d' Études Spatiales (CNES ,  MISS  Project), the  European Research Council  (advanced grant Twelve Labours), the  Office of Naval research (ONR  grant  N00014-14-1-0023 ), the  DGA   Stéréo project , the  ANR - DGA  (project  ANR-12-ASTR-0035 ) and the  Institut Universitaire de France.
Methods The motor neuron diseases included in this study were amyotrophic lateral sclerosis, spinal muscular atrophy, hereditary spastic paraplegia, primary lateral sclerosis, progressive muscular atrophy, and pseudobulbar palsy. Incidence, prevalence, and DALYs were estimated using a Bayesian meta-regression model. We analysed 14 165 site-years of vital registration cause of death data using the GBD 2016 cause of death ensemble model. The 84 risk factors quantified in GBD 2016 were tested for an association with incidence or death from motor neuron diseases. We also explored the relationship between Socio-demographic Index (SDI; a compound measure of income per capita, education, and fertility) and age-standardised DALYs of motor neuron diseases.
Interpretation Motor neuron diseases have low prevalence and incidence, but cause severe disability with a high fatality rate. Incidence of motor neuron diseases has geographical heterogeneity, which is not explained by any risk factors quantified in GBD, suggesting other unmeasured risk factors might have a role. Between 1990 and 2016, the burden of motor neuron diseases has increased substantially. The estimates presented here, as well as future estimates based on data from a greater number of countries, will be important in the planning of services for people with motor neuron diseases worldwide.
Additionally, world wide data on other metrics of motor neuron disease burden (eg, mortality, years of life lost [YLLs], years of life lived with disability [YLDs], and disability-adjusted life-years [DALYs]) are still scarce. Within the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016, we quantified the burden of motor neuron diseases in terms of incidence, prevalence, mortality, and DALYs (a sum of YLLs and YLDs) between 1990 and 2016 by age, sex, year, and geographical location. Our study considers motor neuron diseases across the whole age spectrum including spinal muscular atrophy, a rare disorder in the first years of life affecting proximal limbs and respiratory muscles. The relationships between motor neuron disease burden and country development level, as measured by the Sociodemographic Index (SDI), a composite measure of income per capita, years of schooling, and total fertility rate, were also analysed.
Research in context Evidence before this study Motor neuron diseases are a group of rare neurodegenerative disorders (amyotrophic lateral sclerosis, spinal muscular atrophy, hereditary spastic paraplegia, primary lateral sclerosis, progressive muscular atrophy, and pseudobulbar palsy) that are fatal in 50% of affected people within 15 to 20 months after diagnosis. Previous epidemiological studies of motor neuron diseases showed large geographical variations in incidence, but no data on motor neuron disease incidence existed for most countries. We did a systematic review of prevalence, incidence, and mortality risk in PubMed for articles published in English from Jan 1, 1990, to Dec 31, 2015. In the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), systematic reviews for motor neuron diseases are done every 3 years, with new sources suggested by GBD collaborators included in each round of estimates.
Non-fatal disease modelling The El Escorial Criteria  15  were used as the reference diagnostic criteria for amyotrophic lateral sclerosis. Spinal muscular atrophy cases defined by ICD codes were also included. Data from administrative health records reporting by ICD codes were also included. We identified 55 sources through our systematic literature review, including 47 sources on incidence, covering seven of the 21 world regions, and eight sources on prevalence, covering five of the 21 world regions (appendix). We also added 3 years (2000, 2010, and 2012) of US medical claims data. There were no data for southeast Asia, Oceania, central Asia, eastern Europe, Australasia, the Caribbean, Andean Latin America, central Latin America, south Asia, central sub-Saharan Africa, southern sub-Saharan Africa, and western sub-Saharan Africa.
Where data points spanned age ranges greater than 20 years, we split the data into 5-year age bands using the age pattern of the USA, where we had the most detailed motor neuron disease data by age. We used DisMod-MR 2. 1, the Bayesian metaregression modelling tool developed for GBD, to generate results that were consistent with the available data on prevalence and incidence, as well as with our estimates for mortality due to motor neuron diseases. In the model, we included a setting of no remission (ie, no cure). We used DisMod-MR 2. 1 to adjust for systematic bias in the first 2 years of US claims data, because the data for 2000 and 2010 were systematically lower than the data for 2012. Additionally, we included the absolute value of latitude, as a country-level predictor on prevalence, and included national income, with a built-in short lag, as a country-level predictor on excess mortality rate.
Motor neuron disease severity and YLDs To identify the different health consequences of motor neuron diseases, we analysed data from the largest amyotrophic lateral sclerosis clinical dataset, with a total of 8635 patient records: the Pooled Resource Openaccess ALS Clinical Trials (PRO-ACT). 16 These data were compiled by the PRO-ACT Consortium, which is a collaboration between Prize4Life and the Northeast ALS Consortium, with funding from the ALS Therapy Alliance. The data available in the PRO-ACT database have been volunteered by PRO-ACT Consortium members. 17 We used records with complete information on the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R; n=4838) and selected only the observation at enrolment into a trial to eliminate potential bias from treatment effects.
DALYs The proportions from the ALSFRS-R analysis were applied to the prevalence estimates derived from DisMod-MR 2. 1, and the prevalence of each long-term outcome was multiplied by the combined disability weights to get uncorrected YLDs. The initial YLD estimates were adjusted for comorbidity by use of the comorbidity simulation across all causes included in GBD 2016. 19 We calculated YLLs by multiplying the number of deaths in each age group by the remaining life expectancy derived from the GBD standard life table (appendix). DALYs were then calculated by summing YLLs and YLDs. Uncertainty was propagated by sampling 1000 draws at each computational step, which allowed for the combination of uncertainty from different sources, including input data, data processing steps, and residual non-sampling error.
Results All results presented in this paper can be found in the GBD 2016 online results tool, with all estimates from 1990 to 2016 for all world regions. The same results can also be explored by use of the GBD 2016 data visualisation tool. In ). The lowest all-age prevalence was in sub-Saharan Africa, especially in central sub-Saharan Africa (0•9, 0•8-1•1), followed by eastern sub-Saharan Africa (1•0, 0•8-1•1) and western sub-Saharan Africa (1•0, 0•9-1•2). Only a small proportion of these geographical differences in the prevalence can be explained by a different age structure of the countries: in 2016, agestandardised prevalence per 100 000 population ranged from a high of 22•6 (20•9-24•7) in Canada to a low of 1•1 (0•9-1•2) in the Central African Republic. Among regions with high SDI values, age-standardised prevalence per 100 000 population was lowest in highincome Asia Pacific, southern Latin America, eastern Europe and central Europe (figure  1 ).
The prevalence of spinal muscular atrophy is established, as for other genetic diseases of early years of life, by several factors, including family size of the proband, the availability of genetic counselling, prenatal diagnosis with genetic testing, and access to and willingness to have pregnancy termination. Additionally, spinal muscular atrophy frequency seems higher in white populations compared with other ethnic groups, similar to amyotrophic lateral sclerosis. 26, 27 everal limitations of the study should be considered. First, given the diagnostic challenges of motor neuron diseases, some categories of motor neuron disease are probably still underdiagnosed, especially in older people and ethnic minority groups. 28 Although the criteria for amyotrophic lateral sclerosis diagnosis in adults changed several times over the study period,  29  we did not detect a systematic bias between data based on El Escorial criteria and data based on alternative case definitions.
Second, data are scarce from large parts of the world, including sub-Saharan Africa, most of Latin America, eastern Europe, and south and central Asia. Despite the fact that the Asian population constitutes more than 50% of the world population, few epidemiological studies of motor neuron diseases have been done outside Europe and North America. 30 he data indicate a difference in the prevalence and incidence of motor neuron disease, with lower estimates in Asia, Latin America, and Africa, as compared with the rest of the world. This difference might, at least in part, reflect missed diagnosis because of the absence of appropriate diagnostic instru ments. Third, mortality rate estimations were based on data classified using ICD-9 and ICD-10. Although both versions of the ICD are highly congruent in the field of motor neuron disease, we cannot exclude an influence of the classification evolution, even if unlikely.
Epidemiological studies of subpopu lations of countries with diverse ethnicities are also important, given the supposed lower motor neuron disease incidence in mixed populations as compared with homogeneous populations. 34 ur estimate of the severity of disability is based on the PRO-ACT database and therefore indicative of disability in amyotrophic lateral sclerosis and not in spinal muscular atrophy and other motor neuron diseases. Another limitation is that participants in randomised trials are characterised by a less severe form of amyotrophic lateral sclerosis than are participants from population-based studies. 35 Finally, no data exist on the effect of cognitive impairment on disability, an important clinical trait of amyotrophic lateral sclerosis that affects about 50% of individuals at diagnosis,  36  and this might have led to underestimation of the overall motor neuron disease disability.
Unfortunately, no effective treatment for motor neuron diseases exists. The only licensed drugs for amyotrophic lateral sclerosis are riluzole and, more recently, edaravone. 8] [39]  Conversely, a promising new approach exists for gene-modifying therapy for spinal muscular atrophy. 40 hese data show that, with ageing of the world population, the burden of motor neuron diseases on health services is likely to increase substantially in coming decades. New epidemiological studies in areas without data are needed. Epidemiological studies in diverse populations might improve estimates of motor neuron disease frequency, understanding of disease phenotypes and risk factors, and the completeness of case ascertainment and referral. 41 In the meantime, with limited possibilities for effective medical intervention, these GBD 2016 data are of relevance to healthcare planning and resource allocation for the extensive care needs of people with motor neuron diseases.
Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need for flexible electrophysiology setups becomes apparent. With that aim, we designed Multimed, which is a versatile hardware platform for the real-time recording and processing of biosignals. Digital processing in Multimed is an arrangement of generic processing units from a custom library. These can freely be rearranged to match the needs of the application. Embedded onto a Field Programmable Gate Array (FPGA), these modules utilize full-hardware signal processing to lower processing latency. It achieves constant latency, and sub-millisecond processing and decision-making on 64 channels.
Introduction The growing number of technological advances in electronics and materials has enabled many innovative approaches in biology and medicine to interact with excitable cells and tissues. Information communicated by organs, tissues, and cells about their activity are recorded through biophysical sensors and produce information regarding body health. Electronics captures this information, Figure  1. Multimed and its interfaces. From left to right: User parameters are fed into the system, which is connected to the measured and/or stimulated cell culture. The board then processes the data using a Field Programmable Gate Array (FPGA), which displays measurements on an external screen and records unprocessed and processed data to SD cards. Signals from biological material are electrical readings of ionic fluxes at the plasma membrane captured by micro-or macro-electrodes.
Position to the State of Practice The democratization of electrophysiology techniques has motivated the design of many electrophysiology platforms, notably commercial products proposed by National Instruments (NI)  [6] , Intan  [7] , Multi Channel Systems (MCS)  [8] , or open-source alternatives  [9] , like Neurorighter  [10]  or Open Ephys  [11]. They propose bench-ready, high-performance material and processing software that is capable of real-time processing and feedback. Moreover, the availability of generic acquisition systems, especially from NI, MCS, or Intan gave birth to open-source analysis software  [9] , including MEABench  [12] , ArtE  [13] , Nspike  [14] , and RTXI  [15]. These also provide real-time processing tools and promote always-expanding analysis tools with limited hardware investment.
However, applied research, and particularly, closed-loop research cannot always rely on software processing solutions. Indeed, computation speed is bound by general-purpose operating system performance: processing latencies slower than biological delays limit decision making within physiological windows (e. g. , Spike Timing Dependent Plasticity)  [16]. Only RTXI claims to achieve consistent sub-millisecond processing, relying on a real-time Linux kernel. On that note, the presence of a workstation in the computation flow disqualifies these setups for implant-scaled miniaturization, and the proposed processing software is too complex for on-chip integration. Some products answer these issues with a hybrid approach, and they take advantage of both software and hardware processing: Intan proposes acquisition devices with a mounted FPGA board that can host low-latency material computing, alongside its standard processing software.