dataesr/scientific-paragraphs-categorization huggingface dataset:
At the issue of this process, three meta-periods are extracted (P1=1996-2000, P2=2000-2005, P3=2006-2010). This is between these periods that the diachronic analysis would be lead. This process should allow to monitor topic evolution in medical research across these periods. In each period, we use clustering to group documents of same topics. GNG clustering is therefore launched several times with standard Fritzke parameters settings  [11]  on the data of each metaperiod (P1= 4054 data and 3023 terms, P2= 2012 data and 2036 terms, P3= 3713 data and 3288 terms) making varying the number of clusters in a range from 2 to 50 clusters. The different quality indexes are exploited to highlight an optimal model in each period. On this optimal model, the feature selection and contrast (  [22] ) method described in Section II is used to extract characteristics and salient terms for each cluster, i.
We consequently exploit two complementary criteria for the evaluation of the behaviour of the indexes: • The total number of matches that can be found between the periods using the optimal clustering models provided by the index. • A matching quality criteria (QMA) combining the number of matches, the size of the matching kernels and the matching probability. This criteria is expressed as : QM A = (i,j)∈M |S ij | * P (i|j) + P (j|i) 2 (18) where M represents the set of couples of clusters of different periods for which a match has been detected. In Table  V , we give the results of our evaluation on the corpus we constitued from the ISTEX database which is related to medical care research. It highlights that, similarly to our former experiments (see Section IV), some indexes are unable to find any optimal model (being out-of-range) whatever time period is considered.
We have performed experiments in two different contexts including a "real life" context related to diachronic analyis environment. Both experiments confirm the clear advantages of our new indexes, especially the ones of our EC quality index. However, further experiments are required using both an extended set of clustering methods and a larger panel of high dimensional datasets to confirm this promising behavior. Especially the influence of the sparsity and the one of cluster overlapping ratio on the performance of our indexes must be more precisely evaluated. Taking a larger panel of indexes, including score functions and entropy based indexes would be also a complementary and important issue. Additionally, we plan to test the ability of our indexes to discriminate between correct and degenerated clustering results in the context of large and heterogeneous datasets.
www. elsevier. es/bmhim EDITORIAL Why computational methods for the study of biological macromolecules and their effectors? ¿Por qué utilizar métodos computacionales para el estudio de las macromoléculas biológicas y sus efectores? Perhaps we should start this editorial by raising the following question: Why appeal to theoretical approaches for studying biological macromolecules and the effectors with therapeutic potential? Let us take the time to look at some statistics concerning the biological databases. As of June 2016, there were around 9000 completed and published genome sequences (archaea, prokaryotes, and eukaryotes) including strains or varieties of the same species (GOLD database, https://gold. jgi. doe. gov/). The exponential growth of sequenced genomes has kept steady over the past 15 years.
On another hand, the growth of the databanks containing protein sequences doubles in less than 1. 5 years. As a result, there are more than 15 million protein sequences at 50% sequence identity in the UniProt database (http://www. uniprot. org/). However, the growth of the databank of the 3D structures of proteins, PDB (http://www. rcsb. org/pdb/), is several orders of magnitude smaller (10 -3 ). As it is, the number of non-redundant sequences in the PDB database at 30% sequence identity is of approximately only 26000; not to mention that the overall number of membrane protein structures (pharmacological targets par excellence) remains small in spite of recent experimental advances in the determination of their 3D structure; it only reaches less than 300 redundant structures in the PDB. Accordingly, there is an increasing need to develop and apply in silico methods to obtain reliable 3D molecular models, given that the experimental determination of the 3D structures of all sequences is impossible on the one hand, and useless on the other hand.
A long way to go, in any case! Now, there EDITORIAL are several approaches and levels for the rational discovery, design, and development of de novo pharmaceuticals. Structure-based drug design applies when the structure of the biological target is known. For that purpose, mining of drugs is accomplished through access to libraries of druglike chemical compounds stored in public and corporate databases. These databases represent an enormous diversity of tens of millions of potential drug molecules (enzyme activators and inhibitors, receptor agonists and antagonists, ion channel openers or blockers, modulators that bind to secondary sites) and their effects. However, it is still necessary to estimate their ADME-Tox pharmacokinetic properties from the chemical structure (Absorption/solubility), Distribution, Metabolism, Excretion ---Toxicity (carcinogenicity, mutagenicity, oral LD50, developmental toxicity potential, skin sensitization) in order to filter out those compounds that do not possess the appropriate properties.
01,  (12)  salt and pepper noise (SP) with density 0. 05,  (13)  speckle noise (SN) with variance 0. 04,  (14)  gamma correction (GC) with gamma value 0. 9, and (  15 ) sharpening (SH). The algorithms are implemented in MATLAB environment on a PC with 4 GB RAM and Core 2 Duo processor. Normalized correlation (NC)  [33]  coefficient is used as a similarity measure between the original and extracted watermark images. In order to justify the performance of the proposed scheme, results are compared to the false positive free SVD-based watermarking scheme (FPF-SVD-W)  [33]. The average of PSNR values of the watermarked images obtained by the proposed scheme is 34. 5769 while in case of FPF-SVD-W it is 30. 8663. Also, the average PSNR over all the test images corresponding to each embedded watermarks is plotted for both the schemes in Figure  7.
These operators take into account not only the names of the constructs but also the inter-constructs relationships and the semantics. Then, we extract replicated constructs as interdependent language modules whose dependencies are expressed through well-defined interfaces. Those language modules can be later assembled among them to build up new DSLs. The approach presented in this paper is implemented in a language workbench on top of the Eclipse Modeling Framework. The validation of our approach is twofold. Firstly, we apply the reverseengineering strategy to a case study, deeply explained by Crane et al. [8] , and composed of a set of DSLs for finite state machines. Secondly, we explore public GitHub repositories in search of insights that indicate how common is the phenomenon of specification clones in DSLs development process.
A required interface contains the set of constructs required by the requiring module that are supposed to be replaced by actual construct provided by another module(s). We use model types  [23]  to express both required and provided interfaces. A module can have some references to the constructs declared in its required interface. In turn, the relationship between a module and its provided interface is implements (deeply explained in  [9] ). A module implements the functionality exposed in its model type. If the required interface is a subtype of the provided interface, then the provided interface fulfills the requirements declared in a required interface. Implementation. The approach presented in this paper is implemented in the Puzzle tool suite 3  , which is developed on top of the Eclipse Modeling Framework (EMF).
Evaluation The evaluation of our approach is twofold. First, we evaluate the correctness of the approach using a test oracle that consists of a well-documented case study where we exactly know the existing overlapping among the involved DSLs. We execute the reverse-engineering on the case study, and we check that the produced language modules are consistent with the known overlapping. Second, we evaluate relevance of our proposal. More concretely, we use empirical data to demonstrate that the phenomenon of specification clones actually appears in DSLs that we obtain from public GitHub repositories.
* Contract grant sponsor: Fondecyt Postdoctoral of  CONICYT Chile ; contract grant number:  3150314  (to P. A. ); contract grant sponsor:  ANR  project  Stint  under reference  ANR-13-BS02-0007  operated by the  French National Research Agency (ANR)  (to N. B. , F. H. , N. T. ); contract grant sponsor:  ANR  project  Heredia  under reference  ANR-10-JCJC-0204 , and by the  LABEX MILYON  ( ANR-10-LABX-0070 ) of  Universit é de Lyon , within the program " Investissements d' Avenir"  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR)  (to N. B. , N. T. ); contract grant sponsor:  European Research Council (ERC)  grant "PARAMTIGHT: Parameterized complexity and the search for tight complexity results," reference  280152  and  OTKA  grant  NK105645  (to D. M. ).
Such a practice is disproved mathematically and practically by Chang  [22]  who showed that the first components do not necessary contain more discriminative information than the others. In addition, reducing the dimension of the data may not be a good idea since it is easier to discriminate groups of points in high-dimensional spaces than in lower dimensional spaces, assuming that one can build a good classifier in high-dimensional spaces. Let us illustrate the possible disadvantage of PCA in the context of clustering high-dimensional data. For the purpose of illustration, we consider her biomedical data where a supervision is available. We consider the "prostate" data set which is available in the ChemometricsWithR package  [40]  for R. The data were presented in  [1]. The data set consists in 327 spectra of blood samples measured on 10523 variables from 2000 to 20000 Da.
We now present in Listing 3 an application of the Fisher-EM algorithm to the Mars data (described in the previous section). The Fisher-EM algorithm is available in the R software through the FisherEM package  [8]. Here also, Fisher-EM was used for a specific model and for K = 5, but the automatic selection of the model and K is possible. The object out contains several information which require some comments. First, cls and P contain respectively the partition into 5 groups of the data and the posterior probabilities that each observation belongs to the groups. The sub-object prms gathers all information about the learned mixture model. Astrophysicists will be mostly interested in visualizing the group means which are stored in prms$my. The estimated group means are plotted on Figure  8. Another parameter which is useful from the practical point of view is the loading matrix U.
e. , low spatial details. Also, the Bookarrival, Café, and Pantomime sequences contains higher T-I value for both texture and depth maps, which indicates high level temporal of detail. HEVC and MVC standards were utilised to analyse the performance of the proposed adaptation system. Therefore, HM v10. 1 and JMVM v8. 1 were used to encode each MVV content. Various QPs were selected, i. e. , 20, 26, 32, 38, and 44, for each colour texture sequence. Also, the depth maps bitrates were chosen to be equal to the percentage of 20% of the colour texture bitrates, as suggested in  [77]. Hence, appropriate compressed depth maps were chosen by trials. Hierarchical B pictures were used with a GOP length of 16, and a single GOP was inserted into each transmission segment. In the case of MVC, the inter-view prediction structure was determined based on the view discarding pattern.
To further evaluate the performance of the proposed approach, MPEG-DASH  [78]  was incorporated in the sever-client setup  [79]. Three regular PCs were used in this setup. A PC was used as a transmitter (i. e. , streaming server), one regular PC as a receiver (i. e. , streaming client), and one regular PC as a router based on the Dummynet tool  [80]  to emulate network environment. To evaluate the performance of the proposed approach, MPEG View Synthesis Reference Software VSRS v3. 5  [36]  was incorporated as an adaptation reference. In MPEG-VSRS, the two nearest left and right adjacent views are utilised in this reference to synthesise discarded view(s). MPEG-VSRS was used as the base to estimate the views that are not delivered along with the received SI and codebooks of various sizes. The additional overhead from the proposed method (i.
In order to help facilitate a quality-aware bandwidth adaptation mechanism, the best sets of views to be discarded are calculated for various network throughput levels, such that the best overall MVV reconstruction quality is achieved on the client side. The proposed adaptive 3D MVV streaming method was evaluated using a prototype HTTP streaming client and two different state-of-the-art coding standards. These were compared to the corresponding reference techniques that use MPEG's reference view synthesis software (VSRS). The experiment results have shown that significant quality improvements are obtained under challenging network conditions. For some content types, the performance reduction has been reported. In doing so, as a future work, perceptual MVV metric, adaptive codebook transmission, and advanced loss-resilient coding will be integrated in the proposed adaptive delivery scheme.
Acknowledgements This work was supported by the  ROMEO  project (grant number:  287896 ), which was funded by the  EC FP7 ICT collaborative research programme. This paper is an extended version of the original paper [19] which appeared in the Proceedings of the 2013 ACM International Workshop on Immersive Media Experiences [84]. Special thanks to the anonymous reviewers and program chairs in the workshop and the journal for their constructive comments and suggestions that assisted in enhancing the paper.
Acknowledgments We thank the members of the laboratory for insightful discussions. This material is based in part upon work supported by the  Centre national de la recherche scientifique (CNRS) , the  Fondation ARC pour la recherche sur le cancer  grant  SFI20121205916  and the  Agence nationale de la recherche (ANR)  grants  ANR-13-JSV5-0007-01  and  ANR-14-CE09-0006-02 , and the  France-BioImaging infrastructure  ( ANR-10-INSB-04  grant). We apologize to our colleagues whose work using MTM sensors escaped our scrutiny or were published too recently to be cited in this review.
The growing body of literature in Mars research is enabled by the wealth of data that has been provided by recent space missions. A consequence is that the Mars scientific community is becoming increasingly specialized in particular research areas, evidenced by the rising frequency of topical conferences and workshops (e. g. , regarding polar caps, eolian landforms, impact craters, recent gullies, etc). However, it is important to place new datasets and findings in a global context that spans Mars' ancient past to its present, to develop our understanding of Mars' evolution and present state as a whole. Thus, our review also aims to emphasize what has changed in the understanding of Mars' evolution in the last decade to provide guidance for scientists interested in this terrestrial planet.
The lower atmosphere Our knowledge of the lower atmosphere's composition and thermal structure goes back to the 1970s, when two most successful space missions provided us with datasets that are still of use today. The Mariner 9 orbiter, in operation in 1972, revealed Mars' volcanoes and main surface features, but also measured, through its infrared spectroscopic measurements, the surface pressure and the thermal profile (through CO 2 absorption bands) and the abundance of the main minor species (H 2 O, CO) as a function of the seasonal cycle. The Viking missions, comprising two orbiters and two landers, produced datasets with unprecedented coverage of Mars' seasons, both in situ and from space, which elucidated the variability in temperature and pressure, and allowed us to observe the martian water vapor cycle.
Datasets The thermal atmospheric structure of Mars is best retrieved from the inversion of the strong CO 2 υ2 band occurring at 15 μm in Mars' thermal spectrum (Fig. 2 ). This Fig. 2  Infrared spectrum of Mars in the 15-μm CO 2 band. Top mid-latitudes; bottom high-latitudes, above the polar ice cap. The figure is taken from  Fouchet et al. (2007)  method was first used with the InfraRed Imaging Spectrometer (IRIS) instrument aboard Mariner 9  (Hanel et al. 1972) , then with the InfraRed Thermal Mapper (IRTM) aboard the Viking orbiters  (Martin 1981) , which both observed in the nadir mode. In addition, local seasonal variations of the surface pressure were measured by the Viking landers over several Martian years. After the Viking mission, the next important milestone was, in 1999, the infrared dataset recorded by the Thermal Emission Spectrometer (TES) aboard the Mars Global Surveyor (MGS) mission.
In addition to nadir measurements, used to study both the surface mineralogy  (Christensen et al. 2001)  and the thermal structure of the lower atmosphere  (Conrath et al. 2000) , TES acquired limb data that were used to retrieve the thermal structure up to about 65 km  (Smith 2002). The thermal mapping with TES covered almost 3 Martian years  (Smith 2004 ). Later, new atmospheric datasets were obtained with the Thermal Emission Imaging   (Seiff 1982 ) and the grey dotted line shows the CO 2 condensation curve. The figure is taken from  Smith et al. (2016). Right near-surface atmospheric temperatures as a function of height above the surface for different times of day as retrieved from upward-looking observations taken by the Mini-TES instrument onboard the Spirit MER rover. The figure is taken from  Smith et al.
Detection of H 2 O and variability in abundance Our understanding of the water cycle on Mars is based on a series of remote-sensing campaigns, achieved first from ground-based telescopes and later from orbiting spacecraft. Since 2012, the relative humidity sensor of the REMS suite aboard Curiosity has been monitoring the water content at the rover site  (Martín-Torres et al. 2015b ). The first REMS measurements at Gale Crater show evidence for the formation of night-time transient liquid brines in the first 5 cm below the surface which evaporate after sunrise. Changes in the hydration state of salts under the surface also indicate an active atmosphere-surface interaction  (Martín-Torres et al. 2015b). This new dataset 123  used to infer the vertical distribution of water vapor, which condenses at low altitudes near aphelion  (Clancy et al.
The next major milestone came with the Thermal Emission Spectrometer instrument aboard the MGS orbiter, which monitored the water vapor content, through its rotational lines around 20-30 μm, as a function of latitude and season for a fixed local time (14:00) over 3 martian years  (Smith 2002 , 2004, Fig. 5 ). These datasets have been complemented with observations performed by several instruments aboard the Mars Express Orbiter: SPICAM-IR in the 1. 38 μm band  (Fedorova et al. 2006) , OMEGA in the 2. 65 μm band  (Melchiorri et al. 2006) , PFS in the rotational lines  (Fouchet et al. 2007 ; Fig. 7 ), and in the 2. 65 μm band  (Tschimmel et al. 2008). The OMEGA and PFS observations were in global agreement with the TES data, although indicating a lower maximum water content at the north pole (close to 70 pr-μm, whereas 100 pr-μm were originally reported by TES), while the water content inferred from SPICAM-IR appeared to be systematically lower.
Information on the water vapor vertical distribution was also obtained by PFS. On the basis of an inverse correlation observed between the water column, normalized to a fixed pressure, and surface pressure,  Fouchet et al. (2007)  inferred a vertical distribution intermediate between saturation and confinement to a surface layer. Tschimmel et al. (2008)  also suggested a non-uniform distribution of water with confinement in the few kilometers above the surface at high northern latitudes in summer. Such behavior was previously reported from ground-based heterodyne spectroscopy measurements of HDO that give access to the vertical water distribution  (Clancy et al. 1992; Encrenaz et al. 2001). As a complement to the TES dataset, the Mars Express data were important for observing in detail the polar caps at different local times.
2012)  have considered the radiative effect of these clouds, which in some cases can generate temperature inversions. A further improved 3D GCM model has been developed by  Navarro et al. (2014) , including the nucleation on dust particles, ice particle growth in a supersaturated atmosphere, and scavenging of dust particles due to ice condensation. This study illustrates the importance of microphysics in the modeling of the water cycle. Comparison of the results of this GCM with the TES database is quite satisfactory, except for an underestimation of the water vapor content at mid-latitudes after Ls = 180 • and a slight overestimation of the maximum content at Ls = 90 • at the north pole (Fig. 8 ). In addition, this model is also able to predict supersaturation above the hygropause, with a good overall agreement in the Northern hemisphere (Fig.
The upper atmosphere Mars' upper atmosphere is considered to be that above ∼80 km. The related science investigations are called "aeronomy", a term suggested by Sydney Chapman in the 1940s. Our knowledge of Mars' upper atmosphere started with the first radiooccultation profiles acquired in the 60/70s by Soviet Mars and US Mariner spacecraft. In 1976, the two Viking landers provided in situ measurements of the thermosphere and ionosphere, which established a reference point in terms of plasma composition and temperature during their descent in the Mars' atmosphere. The Viking orbiters provided many more radio-occultation profiles, a rich dataset later augmented by Mars Global  Surveyor (1998 Surveyor ( -2005) )  and by Mars Express since 2004. Mars Global Surveyor also provided a useful dataset on energetic electrons and mapped the peculiar crustal magnetic field.
g. ,  Fox and Dalgarno 1979). Figure  14  shows the variation of the electron density as a function of solar zenith angle, as deduced from Mars Express radio-occultation data. Seasonal influence is important to consider, given the planet tilt angle and the orbit eccentricity. These effects, difficult to distinguish in the data, are best addressed by 3D modeling work (e. g. Valeille et al. 2009) , and indicate that they are important for the spatial distribution of neutral species, moderate for altitude variations of atmospheric boundaries and for neutral thermospheric densities. One issue is that the Mars orbit eccentricity demands that both the solar cycle and seasonal variations in upper atmosphere be considered together  (Bougher et al. 2014). Concerning the solar cycle, the relevant dataset in term of minimum temporal coverage is just being completed; therefore, many studies are expected from now on.