dataesr/scientific-paragraphs-categorization huggingface dataset:
It succeeded when all trajectories from the detected experiments were pooled together. Indeed, this small subset contains only experiments which have been selected for being significantly different of controls in terms of single cell motility: it is enriched in rare trajectories. After retaining the first seven principal components (explaining 95% of the variance), k-means was applied to the resulting dataset of $1. 1 million trajectories. Figure  6  shows the evolution of intra-cluster cohesion and silhouette score with respect to the number of clusters. It points to k ¼ 8 as being both the best and a good quality clustering on this dataset. Indeed, a break and a maximum are respectively expected in the cluster cohesion and the silhouette score curves at the correct cluster number, if it exists.
Discussion This article presents a generic methodological framework for studying single cell motility in a HT setup. It combines single cell tracking, newly designed trajectory features and an original statistical procedure. Furthermore, its output could be used to obtain an ontology of cell motility in an unsupervised manner: cell motion types were inferred from the data without using any prior knowledge. We found that clustering procedures might not scale in the presence of great biological variability, as is typically observed in HT datasets. We suspect that this is due to highly unbalanced classes and large biological variability. Taken together, those effects produce continuous looking datasets. However, applying hit detection with the described statistical procedure prior to clustering solved the problem for our trajectory analysis.
It may be a promising procedure to apply to other clustering problems in HCS, such as clustering of nuclear or cellular morphologies. As cell population migration during metastasis are thought to be led by some leader cell, it is crucial to study single cell motility. The workflow we have presented in this article allows to quantify single cell trajectories. Therefore its application to large-scale datasets will provide useful insights into the molecular regulation of single cell motility, thereby complementing previous studies on collective cell migration. The application of this workflow is not limited to RNAi data. In a next step, we are going to apply this workflow to newly generated Environmental Toxicology data in order to identify environmentally relevant chemicals which perturb cell motility.
Data sets Two data sets were used to assess the performance of the series and parallel versions of the SPARSE model over a whole growing season. The first experimental data set was collected over a rainfed wheat with green leaf area index values up to 2 and the second over an irrigated wheat with green LAI values up to 4. Both have been grown in a semiarid climate (central Tunisia and Morocco). Surface temperature data were acquired with a nadir-looking Apogee ther-moradiometer, while energy fluxes were measured according to classical FLUXNET recommendations  (Baldocchi et al. , 2001)  with Campbell ™ CSAT sonic anemometers and Krypton fast-response hygrometers. Observed and simulated latent heat flux values (half-hourly averages in W m -2 ) are compared at midday (local standard time) in all sky conditions.
For the rainfed wheat site, there was clearly a problem with the fast-response psychrometer with an energy balance closure of 60 %. Thus for that site the closure was forced and the corrected LE was computed as Rn-H-G. For the irrigated site, the half-hourly closure was of the order of 80 %. For this site closure was achieved with the conservation of the Bowen ratio H / LE; thus, the corrected LE was computed as (Rn-G)/(1 +H / LE). Data for the irrigated wheat site were acquired during the 2004 growing season (B124 site,  Boulet et al. , 2012) , while the experiment for the rainfed wheat took place in 2012. Leaf area index was estimated with hemispherical photography every 2 to 3 weeks depending on the phenological cycle, validated by destructive measurements during key stages (growth and full cover).
The impact of uncertainty on available meteorological data (reanalysis or remote-sensing meteorological products vs. local meteorological stations network) on SPARSE model performance will also be assessed in the future. where a rads = - ε s (1 -f c ) + ε v f c 1 -f c (1 -ε s ) (1 -ε v ) , b rads = a radv = ε v ε s f c 1 -f c (1 -ε s ) (1 -ε v ) , c ratms = (1 -f c ) ε s R atm 1 -f c (1 -ε s ) (1 -ε v ) , c rads = R g (1 -α s ) (1 -f c ) 1 -f c α s α v + c ratms , b radv = -f c ε v 1 + ε s + (1 -f c ) (1 -ε s ) 1 -f c (1 -ε s ) (1 -ε v ) , c ratmv = f c ε v R atm 1 + (1 -f c ) (1 -ε s ) 1 -f c (1 -ε s ) (1 -ε v ) and c radv = R g (1 -α v ) f c 1 + α s (1 -f c ) 1 -f c α s α v + c ratmv. (α s and ε s are the albedo and the emissivity of the soil, α v and ε v are the albedo and the emissivity of the canopy, and R g is the global incoming radiation, f c = 1 -e -0.
Acknowledgements. This work was mostly supported by the  French Space Agency (CNES)  through  TOSCA  projects  EVA2IRT  and  EVASPA3. Financial support by  ANR  for  TRANSMED  project  AMETHYST  and  PHC Maghreb for project N • 32592VE (Estimation spatialisée de l'utilisation de l'eau par l'agriculture pluviale et irriguée au Maghreb)  is also gratefully acknowledged. Sustained financial and kind support by  IRD  and the  MISTRALS (Mediterranean Integrated STudies at Regional And Local Scales) program  through its SICMED component is also acknowledged. The authors extend their thanks to the technical teams of  IRD, INAT, CTV-Chebika and INGC  for their strong collaboration and support for the implementation of ground-truth measurements. Edited by:  P. Gentine.
Introduction Distances or contacts are of increasing importance in the determination of three-dimensional (3D) structures of biological macromolecules or complexes. Nuclear Magnetic Resonance (NMR) plays a privileged role in structural biology due to its ability to measure many distance restraints and thus making it possible to determine high resolution 3D structures. It is at the same time a tool of choice for studying dynamics, flexibility and function  (Markwick et al. 2008). During the last 25 years, NMR structure calculation has been the subject of many  developments (Gu ¨ntert 2009; Williamson and Craven 2009; Guerry and Herrmann 2011)  and metrics to validate NMR-derived structures are increasingly reliable  (Nabuurs et al. 2006; Rosato et al. 2013). In the mean time, methods for NMR structure determination can be extensively tested, as large databases of NMR structures and data sets are available  (Nederveen et al.
Simulated annealing and ARIA iterative protocols The standard iterative protocol was used with ARIA version 2. 3  (Bardiaux et al. 2012). For CASD-NMR 1 targets, the following protocol was used. Nine iterations with 50 conformers were calculated. The 15 conformers with the lowest value of energy were analysed to filter the set of distance restraints for false positives and assign ambiguities. For the calculations, we used an in-house computer cluster operating under Linux, and the Grid ReNaBi GRISBI  (Blanchet et al. 2006a, b) , making use of a dedicated version of ARIA  (Mareuil et al. 2011 ). The ''geometric'' force field PARALLHDG (version 5. 3), developed for NMR structure calculations with  CNS (Bru ¨nger et al. 1998)  and ARIA  (Linge and Nilges 1999; Linge et al. 2003)  and based on the standard force field for X-ray crystal structure refinement  (Engh and Huber 1991) , and PROLSQ non-bonded parameters  (Konnert and Hendrickson 1980) , were used.
ARIA structure calculations For CASD-NMR 1 targets, five sets of simulations were performed. FBHW and FBHWs* used a flat-bottom harmonic wall energy potential (FBHW) for distance restraints. LogH used a log-harmonic distance restraint potential with Bayesian weighting of restraints (Nilges   -423,426-432,437-443,447-451,453-457,460-462,472-  For each protein, the number of residues, the number of peak lists, and the total number of peaks, as well as the residue ranges used for RMSD calculations and the corresponding PDB entry, are given For each protein, the number of residues, the number of peak lists, and the total number of peaks (unrefined and refined), as well as the residue ranges used for RMSD calculation and corresponding PDB entry, are given  et al. 2008). LogHs used a log-harmonic potential and reduced force constant for angles.
The new, larger hydrogen radii introduce geometric inconsistencies that would make a distance geometry program abort during the ''bound smoothing'' phase. Since the log-harmonic potential does not have bounds, the principal role of the bounds in ARIA is to decide which restraint is violated, and thus to select the peaks that are used for the structure determination. The standard procedure is purely user determined. The log-harmonic potential together with the automated weighting allows us to develop a statistically more meaningful criterion, which takes into account, in an iterative way, the convergence of the structure ensemble in each ARIA iteration to the experimental distance restraints (see ''Material and methods'' section).
Effect of adaptive violation tolerance on convergence and accuracy The iterative generation of protein conformations based on NMR distance restraints, as implemented in the software packages ARIA  (Rieping et al. 2007 ) and CYANA (Gu ¨ntert 2004), uses a restraints list generated from the data before the actual structure calculation. At every iteration, the restraints are analysed and the most violated ones are removed from the list. The restraint rejection is a crucial step of the iterative calculation, as convergence can be missed because of a too large rejection rate, whereas a too low rejection rate will produce a set of inconsistent restraints which impairs also the convergence. To identify wrong assignments and noise peaks, the obtained restraints are subject to a violation analysis.
Conclusion In the present paper, we showed that the introduction of Bayesian concepts into automated iterative structure calculations with ARIA can significantly improve the results, in particular if calculation parameters optimised for the ''classical'' structure calculation are appropriately modified. In particular, we introduced the log-harmonic potential together with an automated weighting procedure that we had shown to have several advantages  (Nilges et al. 2008; Bernard et al. 2011)  into the automated structure calculation framework. The improved calculation set up was used ''blind'' on the ten CASD-NMR 2 targets, both with refined and unrefined peak lists. Structures generated by ARIA from refined NOE data sets were consistently accurate, i. e. extremely similar to the final structures determined independently by experienced scientists from the same data.
Acknowledgments We acknowledge the  Institut Pasteur  and the  CNRS  for support. This work was funded by the  European Union  ( FP7-IDEAS-ERC 294809 ), the  ANR  ''Massively parallel simulation and analysis of protein structure and dynamics'', and the  Pasteur-Weizman council. We are grateful to the work of the  North East Structural Genomics consortium  for providing the NMR data prior to deposition. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http:// creativecommons. org/licenses/by/4. 0/),which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
In asynchronous collaboration mode, e. g Distributed Version Control System (DVCS) softwares, users modify their document in isolation and synchronize after to establish a common view of the document. Usually, these kind of systems manages the modifications as a set of state (state-based approach) as on git system  [46]  or So6  [26]. When a replica receives a remote state, it computes the difference between the local state of the document and the received one before merging the modifications. If there are modifications in the same part of the document in both versions, the system can return a conflict information to the user and let him resolve them. The conflict is generated when the system cannot merge the concurrent modifications. Many solutions have been proposed to improve automatic merge.
Both approach kinds are designed to reduce the effort of users during the collaboration. However, study what degree their result satisfy the users on real collaboration is never established. In this regard, this paper studies the behaviors of different approaches during the merge procedure and understand in which case they create conflicts to reduce the user's effort. This paper studies for the first time a decentralized solutions that offer a best merge than usual tool. The contribution of this paper consists of observing through a tool, different patterns of collaboration in git histories. We analyze eight open-source repositories and examined more than 3 million publicly available lines of code from repositories containing thousands of commits made by hundreds of developers. Afterward, we replay the same collaboration as in these git histories and observe the common cases that create a conflict during the merge procedure.
State-Based Algorithm: Git Merge Tool In distributed collaborative software development  [12] , developers work on separate workspaces that they modify locally. They edit, compile and test their own version of the source code. Submission of developer modifications on their code is a "commit". A developer decides when to commit, when to publish their commits to others and when to incorporate other developer commits. Different developers submissions appear on different branches. When incorporating other developer commits, in the absence of the local commits, the action is made silently, and the git recorded history is linear. If the user had produced a commit, git uses git merge to produce a best effort merge of the concurrently modified files. When concurrent modifications occur at the same position in the document, git merge produces a conflict.
The developers have to resolve these conflicts before committing the result of the merge  [46]. To help them to resolve these conflicts, the git software can be configured to call an interactive visual mergetool such as emerge, gvimdiff or kdiff3. During a merge, the working tree files are updated to reflect the result of the merge. Among the changes made to the common ancestor's version, if both sides made changes to the same area, git cannot randomly pick one side over the other, and asks users to resolve it by leaving what both sides did in that area. The basic idea is presented in Figure  1.
Git merge compares the versions that have diverged from the origin version (let be version A and version B) with the original version (let be O). First, git compares versions A and B with O to find the maximum matchings between O and A and between O and B. It then parses the results and identifies the region where the original version O differs from A and B. When the region are different the modifications are applied automatically, otherwise a conflict block containing both modifications is produced. Git system returns the results to the users with markers as in Figure  1  By default, git uses the same style as the one used by the "merge" program from the RCS  [45]  as presented in Figure  1. These markers called awareness  [8]  are useful, especially if the size of the document is large. It specifies exactly the position of conflict, in addition to other information, like the modifications made by other users and the original document.
Corpus available A large number of available Distributed Version Control Systems (DVCS) history publicly available constitutes a very interesting corpus of distributed asynchronous editing traces. DVCS are widely used to manage large scale asynchronous collaborative editing. For instance, the Linux kernel is developed 1 https://github. com/score-team/replication-benchmarker by thousands of programmers around the world using Git  [46]. Several web-based hosting services for software development projects provide large DVCS history such as GitHub (3. 4M developers and 6. 5M repositories)  2  , Assembla (800,000 developers and more than 100,000 projects)  3  , or SourceForge(3. 4M developers and 324,000 projects)  4. In this paper, we selected traces from the most used system: Git.
Empirical Study We analyzed eight open source projects (see Table  1 ). We chose these projects from GitHub and Gitorious web services, based on the following criteria: (1) popularity of the projects 6 from GitHub, (2) activity of the projects from Gitorious, (3) the project is developed by using git in Github/Gitorious, and not a mirror of another system repository such as SVN. We also selected the git repository of the git software it-self, since it contains more commits and merges than these projects and since we think that it contains the best merge result since they are done by specialists of the tool. Since there is no collaboration when the files are not merged, the framework replays only histories of files that are merged at least one. In Table  1 , we present the characteristics of eight projects.
Results Figure  6a  and 6b present respectively the percentage of merge blocks and merge lines for git merge, TTF, WOOT, Logoot and TTF. Since git merge is the default algorithm used in git system to merge the modifications, we use its results as the reference (=100%). Difference between state-based and operation-based merges During the merge procedure, git merge detects which part of the document is changed. It analyzes also the modifications made by each user. If two users insert concurrently the same content in the 6 https://github. com/popular/starred, April 2013 same position for instance, git merge merges correctly the updates. In addition, git merge tool asks users to correct their document each time the merged document conflict. While, operation-based algorithms merged automatically the modifications.
However, these two branches contains code with many lines in common that git merge is able to merge. This pattern is known as a "accidental-clean-merge" by the VCS community, and is not well handled by existing operation-based merge. We analyzed, in the different projects, the history of the files where git merge outperforms the operation-based merges. We also noticed that the number of commits that Revert other commits can be high in the studied repositories (sometimes half the number of merge commit). This can lead to well-known undo puzzles  [43]. For instance, a developer deletes the element A when concurrently another developer deletes the same element A and then undoes this deletion. Git merge manages well this case to obtain the document without A, while others reinsert the element.
We found that for 1335 files, we compute 5799 accidental clean merge, 118409 undo/redo operations, a gain of 3583 blocks and 21675 lines by using CMUndo algorithm. Figure  14  presents the total merge blocks and merge lines. In addition, we separate both algorithms (accidental clean merge -CM-and undo/redo) from our approach to observe the effect of each one on the result. TTF gains 26% in blocks and 23% on lines, while our solution gains 43% blocks and 50% lines. Moreover, accidental operations have the greatest effect on the document with a gain of 40% in blocks and 45% on lines. While undo/redo operations represent a gain of only 5% on blocks and lines. Statistical analysis. We also perform a statistical test of significance. Since the dataset used is independent, a non-parametric analysis method would be the most adapted approach for analysis.
Related Work As presented in this paper, evaluate software merging by using operation-based algorithm during a concurrent collaboration plays an important role in the software development process. Indeed, understand the conflicts and resolve them, improve the productivity of the development team. Here we discuss some related work on evaluation of merge results. Textual, syntactic and semantic merging is widely studied in  [11, 16, 18, 25, 30, 33]. However, the git system deploys a generic model to allow any collaboration. The users can collaborate to produce XML files or a simple textual collaboration such as software source code. For this purpose, it is difficult to implement semantic and syntactic algorithms on git system. Thus, in this paper we focused only on textual merging. In  [23] , many policies are proposed to solve conflict in structured documents such as XML files or file systems.
These policies can be applied with our methodology to manage the files of git system. In this manuscript, we focused only in a simple linear text such as software development. Palantir  [39] , Crystal  [4]  and CollabVS  [7]  propose a solution to detect and resolve the conflicts earlier. They anticipate the actions a developer may wish to perform and execute them in the background. The conflict can only be detected after the conflict has already developed in background. Cassandra  [17]  proposes a novel conflict minimization technique that evaluate task constraints in a project to recommend optimum task orders for each developer. However, all methodology has been proposed just to measure the size of the conflict and the quality of the merges. Among them, no paper published to understand the conflicts and using operation-based merge.
The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains.
This article is organized as follows. In Section 2 is presented related work in visible and far-infrared domains in a multi-modality context. Section 3 overviews our main contributions. In Section 4, we present existing datasets for pedestrian detection and classification and also introduce a new dataset that we have acquired and annotated using both a visible and an FIR camera, which we call RIFIR. In Section 5, we evaluate different features over two domains and three modalities, followed by a discussion in Section 6. We conclude in Section 7.
Related Work There is a significant amount of research work in the domain of pedestrian detection and/or classification. In  [9] , a review of pedestrian safety and collision avoidance systems is presented, which includes infrastructure enhancements. Pedestrian detection approaches are classified according to type and sensor configurations. In  [10]  is presented another survey that treats the task of pedestrian detection for advanced driver assistance systems (ADAS), but only describing the components of different pedestrian detection systems without a performance benchmark on a unique dataset. A few surveys make a direct comparison of different systems at the feature and classifier levels on visible images. For instance, in  [11] , the authors describe the components of a pedestrian detection system, and a few representative systems are compared on the same dataset.