dataesr/scientific-paragraphs-categorization huggingface dataset:
In this data sampling setting, the Telecom operator provides us only with the information on whether a data point is observed or not, not with its precise temporal occurrence within the considered 15 min time stamp. This makes the time information unreliable. That said, for new datasets with an accurate temporal information on the sampled data points, we could harness the time information, by using, for instance, a Conditional Random Field (CRF ) to explicitly model the transition probability to a node at time t conditionally on a node at time t-1, and the previous observations, unlike the HMM where such a probability is conditional only on the node at time t-1. To do this however, we need a larger dataset as CRF is more prone to overfitting. Along the same lines, We expect that using a dynamic weight matrix, which is compatible with the traffic model at different times of the day, is likely to enhance the mapping results.
Investigating the complexity of the multilayer transportation graph, a transition probability model leveraging the transportation layer type and topological properties was estimated and used in an unsupervised HMM-based mapping algorithm. We carried experiments on a test dataset of 80 real multimodal trajectories collected from 10 participants during one month (Aug-Sept 2014) to evaluate our algorithm. Considering the sparsity of cellular observations (with a frequency of 15 minutes), the percentage of retrieved paths of smartphone users is notable. To validate our transition probability model, we compared it with a baseline algorithm that does not take into account the transportation properties of each layer. The results show up to 20% of accuracy improvement of the first over the second.
Acknowledgments We would like to thank  Ghyslaine Benginya  and  Dany Nzididi  of the parasitology department (INRB, Kinshasa) for technical support;  Albert Kanza ,  Jan Bosco Mayunda  and  Joel Mbatshi  of the National Tuberculosis control programme (PNLT),  Briston Mongita ,  John Ngoyi ,  Leopold Morisho ,  Bernadette Tchola ,  Paulin Madingi  and  Godé Nganda  of provincial health division and  Taty Salumu ,  Adon Kapajika  for the EQA distribution.
S3A ). The single CHGB P413 or CHGB L413 transgenic mice reproduced well and did not exhibit overt phenotypes during aging. However, we noticed that the CHGB L413 transgene, unlike the CHGB P413 transgene, was not transmitted in females with the expected Mendelian ratio of 50% (Supplementary Material, Table  S1 ). Instead, the breeding of heterozygous CHGB L413 transgenic mice with C57BL6 mice yielded only 37% of offspring females carrying the CHGB L413 transgene. The single SOD1 G37R mice as well as doubly transgenic SOD1 G37R ;CHGB P413 mice and SOD1 G37R ;CHGB L413 mice were monitored during aging by the rotarod score and body weight. The non-transgenic mice and single transgenic mice CHGB P413 and CHGB L413 showed no deficiency on the rotarod test or on body weight loss until 500 days of age (data not shown).
Expression of CHGB L413 enhanced ER stress in female SOD1 G37R mice As accumulation of misfSOD1 is known to induce ER stress in motor neurons of ALS  (39, 40) , we examined the effects of variants CHGB L413 and CHGB R230 on ER stress and unfolded protein response (UPR). First, we analyzed Neuro2a cells co-transfected with CHGB and SOD1 vectors for ER stress. As shown in Figure  5A , expression of CHGB L413 or CHGB R230 variants caused an upregulation of ER stress markers (Bip, pPERK, CHOP, cleaved cas- (D) The decline of motor performance on rotarod test at disease onset due to overexpression of CHGB L413 in SOD1 G37R female mice and at late stage of disease due to overexpression of CHGB P413 in both sexes of SOD1 G37R mice. Data are mean 6SEM. # P < 0. 05, ## P < 0. 01 between SOD1 G37R and SOD1 G37R ;CHGB L413 ,! P < 0.
The analyses of CHGB mislocalization and neurite outgrowth in cultured cells For the calculation of CHGB percentages colocalizing with TGN-38 (trans-Golgi marker), the merged and unmerged CHGB vesicles with TGN-38 marker were analyzed. More than 40 cells were analyzed for each condition  (28). For the analysis of the percentage of cells expressing neurites, average number of neurites per cell, and average length of neuritis, cells with neurites were defined as cells that possessed at least one neurite of greater than the diameter of the cell body  (52) (53) (54). The data presented are the mean of three individual transfected 2 cm 2 dishes and are representative of three independent experiments. At least 100 cells per transfection were scored for neurite outgrowth.
Quantitative real time RT-PCR Real-time RT-PCR was performed with a LightCycler 480 (Roche) sequence detection system using Light-Cycler SYBR green I at the Quebec Genomics Centre  (56). Total RNA was extracted from frozen spinal cord tissues using Qiazol reagent (miRNeasy, Qiagen, Valencia, CA). Total RNA was treated with DNase (Qiagen) to get rid of genomic DNA contaminations. Total RNA was the quantified using Nanodrop, and its purity was verified by Bioanalyzer 2100 (Agilent Technologies, Mississauga, ON, Canada). Gene-specific primers were constructed using the GeneTools software (Biotools, Jupiter, FL). Two genes, Atp5o and 18S were used as internal control genes. The primers used for the analysis of genes are given in Supplementary Material, Table  S4.
For the analyses of denervation, 100 neuromuscular junctions from each mouse were analysed (n ¼ 3 mice for each group). For the calculation of MN percentages expressing misfolded SOD1 or BiP, double positive MNs (MN markers was ChAT) and signal intensity values inside cells for the antigen of interest were calculated in five lumbar cord sections (n ¼ 3-4 mice for each group)  (57). Data of signal intensity were acquired using identical confocal settings.
Data analysis Data are expressed as means 6 SEM. Statistical comparisons of data were performed using t-tests or one-way ANOVA followed by a Tukey-Kramer post hoc comparison. Kaplan-Meier survival analysis and the log-rank test were used for survival and comparison of onset. Statistical analyses were done using GraphPad Prism 5 (version 5. 00; GraphPad Software, Inc. , San Diego, CA). Statistical significance was set at P < 0. 05.
Immunofluorescence and Confocal Microscopy ABCB4-wt-and ABCB4-ΔQNL-expressing HepG2 cells were fixed with methanol/acetone (4:1, v/v) at -20°C. Incubations with primary and secondary antibodies were performed as previously described  [8]. Confocal imaging was acquired with a Leica TCS SP2 Laser Scanning Spectral system attached to a Leica DMR inverted microscope. Optical sections were recorded with a 63/1. 4 oil immersion objective. Laser scanning confocal images were collected, and analyzed using the on-line "Scan Ware" software. Images were processed using ImageJ 1. 41 and Photoshop softwares.
Analysis of ABCB4 Protein Stability ABCB4-wt-and ABCB4-ΔQNL-expressing HepG2 cells were incubated with cycloheximide (25 μg/mL) to inhibit further protein synthesis. Following incubation for different time periods, cells were harvested, lysed and subjected to SDS-PAGE and immunoblot analysis. Band density was quantified by the ImageJ 1. 41 software and normalized so that the density at time point 0 was 100%. The amounts of remaining ABCB4 were expressed as a percentage relative to point 0.
Acknowledgments We thank  Romain Morichon  ( UPMC, INSERM, UMS LUMIC ) for confocal microscopy imaging,  Anne-Marie Durand-Schneider  for her technical help and  Dr. Véronique Barbu  ( CDR Saint-Antoine ) for fruitful discussions and support during this study. We also acknowledge  Lynda Aoudjehane  ( Human HepCell ) who provided preparations of human hepatocytes and  Yves Chrétien  ( UPMC ) for his help with Adobe softwares.
For this purpose, various hillslopes, typical of the Mediterranean environment in terms of spatial variability of soil depth, soil hydraulic properties, pedology, vegetation and geomorphology were selected and instrumented. The instrumented hillslopes were located in three small catchments (Valescure, Tourgueille, Gazel, see locations in Figure  1 ), corresponding to different geologies: granite, schist, marl and limestones respectively (see details in  [2]  and in Section 3). The small to medium sized catchments appear in orange in Figure  1. They were chosen to document various geologies: granite, schist, marls, limestones and basalt, and land use: forest and agricultural areas. To document the landscape spatial variability, high resolution information was acquired to document topography (1 m Digital Elevation Model (DTM) from LiDaR measurements); land use (5 to 10 m resolution land use maps derived from Quickbird or Pleiades images); as well as collection of existing data about geology and pedology (1/ 250 000 resolution).
Main results from the hillslope and small scale catchments observation and modelling The experimental set-up at the hillslope and small to medium catchment scale was designed to address the following questions: 1/ What is the storage capacity of soils in the studied area? 2/ In which conditions do we observe sub-surface lateral flow or direct surface runoff and can we quantify the speed of sub-surface lateral flow? 3/ What is the respective part of surface, subsurface and deeper layers flow in the discharge at the outlet of the catchments? 4/ Is the impact of land use larger than the impact of soil texture on soil surface hydraulic properties? 5/ What is the impact of active river network extension on the efficiency of the hydrological response? 6/ What is the respective role of rainfall, soil moisture, geology, land use variability on the hydrological response? The effort of the past four year was mainly dedicated to data acquisition, data validation and data provision to the HyMeX data base b.
Although the intra-transect spatial variability is quite large, the inter-transect distribution appears quite stable (Figure  4 ). For soil depth, the average is around 30 cm, and the spatial variability in this area can be considered as following a log-normal distribution, with parameters -1. 14 and 0. 72 respectively for the mean and the standard deviation of the soil depth logarithm. Soil moisture data were analyzed to derive the soil retention and hydraulic conductivity curves for the surface horizon, but also the deeper horizon using the HYDRUS-1D software and an inverse modelling technique detailed in  [16]. The method reveals, consistently with in situ measurements, high value of hydraulic conductivity in the top horizon (several hundreds of mm hr -1 ), but more interestingly, also large values of hydraulic conductivity towards deeper soil horizons.
Geochemistry sampling performed during some rainfall and flood events allowed to go towards a quantification of the fraction of water coming from the surface and sub-surface. A large panel of elements including physico-chemistry, trace elements, stable water isotopes and organic carbon were analyzed. During floods, Ca, Sr and electrical conductivity analyses show a contribution of about 60-80% of rain water to the peak, and only 20-40% of pre-existing water. However, at the scale of the event, these proportions are inverted. At the small catchment scale, but also for the whole Cévennes-Vivarais region, a synthesis of infiltration tests performed by  [18]  and of the data collected during the project  [19]  showed that land use and geology were significant controlling factor of surface hydraulic conductivity (significant differences between natural/cultivated and forest/crops and between different geologies, Figure  6 ) and that pedo-transfer functions, based only on texture or porosity data failed to reproduce the range of observed values.
Progress in rainfall and high discharge estimation and quantification of their uncertainty In terms of rainfall, the objective was to progress in rainfall spatial and temporal variability description, as well as in the quantification of uncertainty. A 1 km²rainfall reanalysis over the Cévennes-Vivarais region (32 000 km²), was produced for the 2007-2014 period and is available on the HyMeX database c. For the 133 most intense rain events, an hourly rain product based on radar -raingauge merging was produced for two types of geographical supports: 1/ 1-km² raster maps and; 2/ spatial divisions of the main Cévennes watersheds into hydrological meshes of almost constant size in the range of 5 -300 km². The methods and their comparison to other rainfall products are described in Delrieu et al.
Algorithms were also developed to use videos of flooding rivers from the internet for the estimation of discharge, based on the same principles as those used with LS-PIV  [31]. In the framework of the Enhanced Observation Period, distributed and multi-scale hydrometry was set up and tested. This includes the setup of dense networks of water level monitoring for catchments ranging from 0. 2 to 12 km 2  [11]  allowing discharge measurements at scales much smaller than currently available for flash floods (see Figure  7 ). FLOODrisk 2016 -3 rd European Conference on Flood Risk Management For the establishment of the stage-discharge relationships, a Bayesian framework aiming at including prior knowledge of hydraulic controls and gauging uncertainty was developed  [32]. The BaRatin d software implements the method and is freely available.
Synthesis of the main results and interest for operational purposes The main outcome of the FloodScale project is the unique data set it assembled and the demonstration that the proposed observation strategy mixing continuous measurements over a four-year period and opportunistic measurements during four autumns was adapted to capture flash floods. In addition, effort was made to quantify uncertainty at all levels. All those elements render the collected data set unique given the variety of sampled space and time scales, which are much finer than those captured by operational networks. The project also demonstrated the importance of high quality discharge date, even at low flow, as it was shown that recession data were containing useful information for understanding and simulating flash floods.
The whole data set is available for the international research community through the HyMeX data base portal. In terms of process understanding and innovative measurements, the following points can be highlighted: 1/ A method for merging radar and rain gauges data was proposed and validated and error on the estimated rainfall fields was quantified; 2/ A method for quantifying rainfall field uncertainty in non-homogeneous areas has also been proposed (use of a stochastic rainfall generator); 3/ Various non-contact measurements techniques for flooding discharge have been proposed and validated and are already used in operational services; 4/ An objective method for quantifying stagedischarge uncertainty and its propagation to discharge times series has been validated and a software implementing this method is freely available; 5/ Geology was highlighted as an important factor in modulating the hydrological response and the soil water storage, with the necessity to include storage capacity of the weathered soil horizons in the modelling; 6/ Lateral sub-surface flow must be taken into account even when surface runoff is important; 7/ The iterative modelling strategy mixing observation and modelling for hypothesis testing proved to be successful and allowed building simulation models that are consistent with observations.
Acknowledgements The FloodScale project was funded by the French National Research Agency (ANR-2011 BS56 027) and received complementary funding from the MISTRALS/HYMeX program, the Rhône-Alpes region, Montpellier 2 University, Alès School of Mines, Irstea, CNRS, CNR, Schapi, SINTEF. We also thank the following data providers: Météo-France, SPC Grand Delta and EDF-DTG. The Ardèche and Languedoc-Roussillon data bases come from the « Inventaire et Gestion des Sols/ Référentiel Pédologique Régional » program. Pleiades images were made available by the CNES/TOSCA CALVADOVS project. We thank the HyMeX (ESPRI/IPSL et SEDOO/Observatoire Midi-Pyrénées) data base for their help in access and processing the data and Météo-France for the access to the http://sop. hymex. org / site during autumn campaigns.
Introduction Model-based development is a leading technique in developing software for critical embedded systems such as automotive, avionics systems, train controllers and medical devices. Typically such systems are modeled using a mix of dataflow formalism and hierarchical state machines. For instance, Matlab Simulink  [20]  or Esterel SCADE  [9]  diagrams are typically used to specify aspects of a system that can be modeled by differential equations relating inputs and outputs (i. e. , dataflow), while Matlab Stateflow  [21]  charts or Esterel SCADE automata usually model the control aspects. The extensive use of the aforementioned formalism in the development of safety-critical systems, associated with certification standards  [8]  that recommend the use of formal methods for the specification, design, development and verification of software, makes a formal treatment of these notations extremely crucial.
For the purpose of safety analysis, Simulink/SCADE models are compiled to a lower level modeling language, usually a synchronous dataflow language such as Lustre  [5]. Preserving the original (hierarchical and modular) structure of the model is paramount to the success of the analysis process. In  [10]  we have illustrated a technique to preserve such structure via a modular compilation process. Specifically, we presented a technique that consists of compiling in a modular fashion Lustre programs into constrained Horn clauses. In this paper, we extend our previous compilation schema to handle hierarchical state machines (i. e. Stateflow diagrams or SCADE automata). Hierarchical state machines allows to capture the complex modal behavior of a reactive system. In these systems, the modes (or state) of the software drive the behavior of the device.
In this paper, we propose a technique to faithfully compile hierarchical state machines expressed as automata in the Lustre language into modular Horn clauses. Our compilation technique preserves the structural and modal behavior of the system, making the analysis of such models more tractable. Specifically, this paper makes the following contributions: • a state-preserving encoding of hierarchical state machines as pure clocked-dataflow models. This encoding is inspired by the work described in  [4]. Our technique differ in how we encode the state of each automaton, which gives a more flexible encoding. • a compilation of hierarchical state machines into modular Horn clauses. • finally, an implementation of the proposed compilation in LUSTREC  [11]  -an open source compiler for Lustre programs.
The rest of the paper is structured as follows: in the next sub-section, we give an overview of the synchronous dataflow language Lustre. In Section 2 we describe the semantics of the hierarchical state machines that we consider in this paper. In Section 3 we describe our structure preserving compilation scheme. In Section 4 we illustrate the extensions of the compiler to handle the compilation of automata in to Horn clauses. Finally, in Section 5 we illustrate our compilation approach on a simple yet representative example.
Background Synchronous languages are a class of languages proposed for the design of so called "reactive systems" -systems that maintain a permanent interaction with physical environment. Such languages are based on the theory of synchronous time, in which the system and its environment are considered to both view time with some "abstract" universal clock. In order to simplify reasoning about such systems, outputs are usually considered to be calculated instantly  [2]. Examples of such languages include Esterel  [3] , Signal  [1]  and Lustre  [5, 12]. In this paper, we will concentrate on the latter. Lustre combines each data stream with an associated clock as a way to discretize time. The overall system is considered to have a universal clock that represents the smallest time span the system is able to distinguish, with additional, coarser-grained, user-defined clocks.
Therefore the overall system may have different subsections that react to inputs at different frequencies. At each clock tick, the system is considered to evaluate all streams, so all values are considered stable for any actual time spent in the instant between ticks. A stream position can be used to indicate a specific value of a stream in a given instant, indexed by its clock tick. A stream at position 0 is in its initial configuration. Positions prior to this have no defined stream value. A Lustre program defines a set of equations of the form: y 1 ,. , y n = f(x 1 ,. , x m ) where y i are output or local variables and x i are input variables. Variables in Lustre are used to represent individual streams and they are typed, with basic types including streams of Real numbers, Integers, and Booleans.
Lustre programs and subprograms are expressed in terms of Nodes. Nodes directly model subsystems in a modular fashion, with an externally visible set of inputs and outputs. A node can be seen as a mapping of a finite set of input streams (in the form of a tuple) to a finite set of output streams (also expressed as a tuple). The top node is the main node of the program, the one that interface with the environment of the program and can never be called by another node. At each instant t, the node takes in the values of its input streams and returns the values of its output streams. Operationally, a node has a cyclic behavior: at each cycle t, it takes as input the value of t y p e run_mode = enum { S t a r t , Stop } ; f u n c t i o n s w i t c h ( mode_in : run_mode ) r e t u r n s ( mode_out : run_mode ) ; l e t mode_out = i f mode_in = S t a r t then Sto p e l s e S t a r t ; t e l  each input stream at position or instant t, and returns the value of each output stream at instant t.
This computation is assumed to be immediate in the computation model. Lustre nodes have a limited form of memory in that, when computing the output values they can also look at input and output values from previous instants, up to a finite limit statically determined by the program itself. Typically, the body of a Lustre node consists of a set of definitions, stream equations of the form x = t (as seen in Figure  1 ) where x is a variable denoting an output or a locally defined stream and t is an expression, in a certain stream algebra, whose variables name input, output, or local streams. More generally, x can be a tuple of stream variables and t an expression evaluating to a tuple of the same type. Most of Lustre's operators are point-wise lifting to streams of the usual operators over stream values.
For example, let x = [x 0 , x 1 ,. ] and y = [y 0 , y 1 ,. ] be two integer streams. Then, x + y denotes the stream [x 0 + y 0 ; x 1 + y 1 ,. ]; an integer constant c, denotes the constant integer stream [c, c,. ]. Two important additional operators are a unary shift-right operator pre ("previous"), and a binary initialization operator → ("followed by"). The first is defined as pre(x) = [u, x 0 , x 1 ,. ] with the value u left unspecified. The second is defined as x → y = [x 0 , y 1 , y 2 ,. ]. Syntactical restrictions on the equations in a Lustre program guarantee that all its streams are well defined: e. g. forbidding recursive definitions hence avoiding algebraic loops. Figure  1  illustrate a simple stopwatch example using Lustre enumerated clocks and node reset. Enumerated clocks are an advanced form of the traditional Lustre clocks.