dataesr/scientific-paragraphs-categorization huggingface dataset:
We describe SILIRID (Simple Ligand-Receptor Interaction Descriptor), a novel fixed size descriptor characterizing protein-ligand interactions. SILIRID can be obtained from the binary interaction fingerprints (IFPs) by summing up the bits corresponding to identical amino acids. This results in a vector of 168 integer numbers corresponding to the product of the number of entries (20 amino acids and one cofactor) and 8 interaction types per amino acid (hydrophobic, aromatic face to face, aromatic edge to face, H-bond donated by the protein, H-bond donated by the ligand, ionic bond with protein cation and protein anion, and interaction with metal ion). Efficiency of SILIRID to distinguish different protein binding sites has been examined in similarity search in sc-PDB database, a druggable portion of the Protein Data Bank, using various protein-ligand complexes as queries.
Method SILIRIDs are calculated from the IFP described by Marcou and Rognan  [19]  and stored in the sc-PDB database (version 2011)  [20]. Every IFP consists of 8 bits per amino acid: hydrophobic, aromatic face to face, aromatic edge to face, hydrogen bond donated by the protein, hydrogen bond donated by the ligand, ionic bond with protein cation and protein anion, and metal ion. The length of this IFP depends on the size of the biding site. Preparation of SILIRID vectors from IFP by merging bitstrings for a given type of amino acid is shown in Fig. 1. Here, two bitstrings corresponding to VAL18 and VAL64 are transformed into a vector based on integer numbers; similar operation is performed for PHE80 and PHE82. Amino acids which do not interact with the ligand (all bits are zero) must also be taken into account.
Co-factors are also considered as an additional 8 bit entry. At the second step, bitstrings of 21 entries (20 amino acids and cofactor) are concatenated into one vector. For any protein, the order of the amino acids in SILIRID is fixed according to the lipophilicity and pKa of the amino acids. Thus, any binding site is described by a fixed length 21 * 8 = 168 dimensional vector. SILIRIDs for the whole sc-PDB were generated using in-house script. Similarity between SILIRIDs was calculated using the Jaccard index using R-package vegdist  [21] : Jaccard index ¼ 2 d jk 1 þ d jk : Here, d jk ¼ ∑ i x ij -x ik ∑ i x ij þ x ik À Á ij , where x ik are i-th components of SILIRIDs describing, respectively, PL complexes j and k. The ROCR package  [22]  for R statistical environment  [23]  was used to plot ROC curves and to perform ROC AUC calculation.
Notice that obtaining SILIRID from 3D structure and comparison of SILIRIDs corresponding to different binding sites are very fast. Thus, calculations of SILIRID based pairwise similarities for ~9000 sc-PDB entries take around 15 min on standard Linux station, 64 bit, single core, Intel i5, using standard 64 bit R statistical environment. SILIRID vectors extracted from the sc-PDB database are available for download at https://github. com/chupvl/silirid.
For a given protein family 1a, each representative has been used as query. Therefore, in order to characterize the results of similarity search, the average ROC curves have been plotted and corresponding ROC AUC values have been calculated. Similarity search results reported in Fig. 3  and Table  2  show that SILIRID efficiency to compare protein binding sites is similar to that of the state-of-the-art approaches. Thus, SILIRID-based similarity search with trypsin as queries to retrieve trypsin-like fold proteins among all sc-PDB entries resulted in average ROC AUC = 0. 95 which is similar to the values obtained with SiteAlign  [12]  (ROC AUC = 0. 88) and BSAlign  [9]  (0. 91). Similarly, with CDK2 as queries, we achieved average ROC AUC = 0. 81 to retrieve protein kinases, which is similar to the value obtained by SiteAlign (ROC AUC = 0.
Pose retrieval The question arises whether SILIRIDs are able to retrieve correct binding poses in docking experiments. In order to investigate this question one PL-complex per protein for CDK2, androgen receptor and trypsin families (PDB IDs: 1W0X, 2AX8 and 2UUK, correspondingly) was considered. In each complex, extracted ligand was re-docked with GOLD v5. 1  [27]  to generate 100 conformations with diverse orientation within binding site. Both IFP and SILIRID calculated for X-ray structure were compared with those calculated for each generated conformer in order to retrieve the best pose. RMSD less than 2. 0 Å for a top-one scored conformer was considered as success. In these calculations, IFP displayed good retrieval rate for all proteins. On the other hand, with SILIRID the correct poses have been retrieved only for the androgen receptor.
The snapshot problem addresses a collection of important algorithmic issues related to the distributed computations, which are used for debugging or recovering the distributed programs. Among the existing solutions, Chandy and Lamport propose a simple distributed algorithm. In this paper, we explore the correct-by-construction process to formalize the snapshot algorithms in distributed system. The formalization process is based on a modeling language Event B, which supports a refinement-based incremental development using RODIN platform. These refinement-based techniques help to derive a correct distributed algorithm. Moreover, we demonstrate how this class of other distributed algorithms can be revisited. A consequence is to provide a fully mechanized proof of the distributed algorithms.
III. STEPWISE DESIGN OF DISTRIBUTED ALGORITHMS The correct-by-construction paradigm promotes the development of algorithms using a progressive and incremental approach. The key concept is the refinement which provides linking between discrete models by preserving safety properties. The Event B modeling language designed by Abrial  [1]  borrows features from formal modeling languages like UNITY  [10] , TLA +  [14] , action systems  [3, 4] ; those modeling languages share common aspects and especially the refinement concepts. The Event B is supported by an open environment RODIN integrating formal features for developing discrete logico-mathematical models. The Event B provides structures for expressing the reactive systems as a set of actions called events and maintaining a list of assertions called (inductive) invariants.
METHODS AND DISCUSSION The daily time spent active and inactive are key factors in animal ecology and have important energetic consequences. Thus, behaviour duration should be measured accurately. The quantification of animal behavioural energetics from data recorded by animalattached acceleration loggers is rapidly increasing in popularity  (Brown et al. 2013 ). These accelerometers measure the change in velocity of an animal's body over time and allow the fine-scale measurement of behaviour and body postures, un limited by visibility, terrain, climate, observer bias or the scale of space use. Unfortunately, accelerometer data processing can cause the elongation of behaviour duration and thus an underestimation of resting duration in a behavioural time budget (e. g. Halsey & White 2010). Can the accelerometry technique be improved? Here ABSTRACT: Data loggers that measure acceleration are regularly used to quantify the behavioural energetics of animals.
12 and 0. 37, 0. 40 and 8. 04, 0. 84 and 185. 73 s, respectively). Overestimation of the duration of behaviours naturally causes errors in the calculations of behavioural time-energy budgets for all species that move intermittently, as demonstrated for scallops, crabs, 'amphibious' signal crayfish and humans. Furthermore, behaviours of any duration should be accurately detected, quantified and when appropriate, the behaviour type should be identified. The R package BEnergetix can quickly calculate accurate invertebrate and vertebrate behavioural time-energy budgets from acceleration, metabolic rate and environmental data. KEY WORDS: Behaviour • Activity • Energy expenditure • Ecology • Accelerometer • Accuracy • R package • Crayfish • Scallop • Crab • Human.
2011)). Such data represent the acceleration recorded by the logger owing to the dynamic movement of that individual  (Wilson et al. 2006). DBA can be used to assess the behaviours of the animal and can also be calibrated with rate of energy expenditure. Measurements of DBA in scallops enabled  Robson et al. (2012)  to measure the effects of anthropogenic disturbance on the behaviour and energy expenditure of farmed individuals. To interpret scallop behaviour from the data, the entire DBA and gape angle data set was Initially the scallop is in its typical posture in a depression in the seafloor sediment with the upper (left) valve uppermost (a) and the scallop subsequently flips 180° using rapid valve adduction followed by abduction events (2 to 3 s -1 ) so that its upper valve is resting on the seafloor sediment (b), before flipping back to its initial posture (c).
Middle panel: body roll derived using the equation: + plotted against time, and signatures within the trace indicating active behaviours were selected manually. DBA was selected only where a corresponding rapid change in gape angle  (Robson et al. 2007 ) was recorded. From the manually selected DBA trace for each behaviour, the duration of the behaviour was calculated, along with the mean DBA to estimate energy cost. Furthermore, the behaviour 'type' was identified by eye both from the DBA and depth trace for each behaviour and by viewing the associated infrared video recordings. This manual analysis produces accurate behavioural time budgets, but is labour intensive for large data sets and impractical when analysing similar data recorded at high frequency from hundreds of animals. Furthermore, the Hall sensor needed to record gape angle is not a standard feature of commercial data loggers that record (tri-axial) acceleration e.
g. the AXY-2 data logger (TechnoSmArt), which can record at high resolution (cf. Robson et al. 2009 ) for 6 wk. Thus, there is considerable value in an automated system for analysing acceleration data and without the need for the quantification of gape angle. It is important to note that the method for calculating DBA by smoothing acceleration data using a necessarily long running mean of e. g. ≥1 s (Shepard et al. 2008) (the DBA method) is not appropriate for determining behaviour duration. In fact, the DBA method results in the elongation of behaviour duration (mean ± 95% CI behaviour duration elongation for scallops (n = 10 animals) and humans (n = 10 freeranging aquatic biologists): 508. 5 ± 277. 2 and 19. 3 ± 1. 1%, respectively) and consequently an overestimation of energy expenditure (mean ± 95% CI activity metabolic rate overestimation: 212.
Furthermore, they survived on land for up to 2 wk. In addition, over 5 non-consecutive days in 2013, we opportunistically observed signal crayfish (n = 12 male, 8 female) leaving a lake (53. 1822° N, 2. 0582° W) and walking overland to other water bodies around Danebridge, UK (all crayfish subsequently captured and killed). We believe this is the first scientific corroboration of observations from fish farms and infested ponds that large numbers of 'invasive' signal crayfish can escape and disperse between patchy freshwater habitats overland (e. g. Danebridge Fisheries, UK; Radcliffe Angling Club, UK, pers. comm. ) Carcinus maenas and humans Homo sapiens. Furthermore, DBAbehav and DBA are calculated simultaneously (these data are aligned). Using the behaviour markers, the 'actual' DBA trace for each behaviour is selected and the duration of the behaviour is calculated (Fig.
g. <10 s. Automatic animal behavioural classification of acceleration data using the k-nearest neighbour algorithm  (Bidder et al. 2014 ) can be much improved by analysing behaviours of short duration because, as this report highlights, shellfish (invertebrate) and human (vertebrate) behaviours can frequently be <1 to 10 s in duration. We have now written a freely available R (R Development Core Team 2013) package, BEnergetix (Mans field & Robson 2013), utilising the package Rcpp (v. 0. 10. 6) to optimise large data set analysis (see Supplement 2 at www. int-res. com/ articles/ suppl/ b021p121_ supp. pdf). BEnergetix is easy for ac celerometry beginners to use to quickly calculate behavioural time-energy budgets from acceleration, metabolic rate and environmental data. The beta version of BEnergetix, its algorithms and a user manual are freely available from  Mansfield & Robson (2013).
BEnergetix analyses large data sets recorded at high frequency (e. g. 100 Hz) limited only by available computer memory (RAM), although future releases will seek to remove this limitation  (cf. Sakamoto et al. 2009 , Nathan et al. 2012 , Shamoun-Baranes et al. 2012 , Gao et al. 2013). In conclusion, the overestimation of the duration of behaviours naturally causes errors in the calculations of behavioural time-energy budgets for all species that move intermittently. Furthermore, behaviours of any duration should be accurately detected, quantified and, when appropriate, the behaviour type should be identified.
Acknowledgements. Thank you to Dr Lewis Halsey and 8 anonymous referees for helpful comments on the manuscript. Thanks also to Lydia Robertson, Dr Keith White, the IUEM dive team and Danebridge Fisheries, UK. A. A. R was supported by the 'Laboratoire d'Excellence' LabexMER (ANR-10-LABX-19), co-funded by a grant from the French government under the program 'Investissements d'Avenir' and co-funded by a grant from the University of Manchester, UK.
Acknowledgements. Thank you to Dr Lewis Halsey and 8 anonymous referees for helpful comments on the manuscript. Thanks also to Lydia Robertson, Dr Keith White, the IUEM dive team and Danebridge Fisheries, UK. A. A. R was supported by the 'Laboratoire d'Excellence' LabexMER (ANR-10-LABX-19), co-funded by a grant from the French government under the program 'Investissements d'Avenir' and co-funded by a grant from the University of Manchester, UK. LITERATURE CITED Bidder OR, Campbell HA, Gómez-Laich A, Urgé P and others (2014) Love thy neighbour: automatic animal behavioural classification of acceleration data using the k-nearest neighbour algorithm. PLoS ONE 9: e88609 Brown DD, Kays R, Wikelski M, Wilson R, Klimley AP (2013) Observing the unwatchable through acceleration log- ging of animal behavior.
Implementation and example In order to implement the proposed method, we have developed a Java program called GROM (Graph Rewriting for Ontology Merging). GROM is based on AGG (Algebraic Graph Grammar) API 5  that supports the algebraic graph transformations (SPO and DPO approaches) and manipulates the typed attributed graph grammars. The tool take as input two ontologies in AGG format (. ggx), a mapping in XML and outputs the merged ontology in AGG format (. ggx). Note that the semantic relations, in the mapping process, are identified by the RitaWN 6  that provides access to the WordNet ontology. The following presents a merging example of the two ontologies presented in Figure  3. The ontologies were created in OWL using Protégé. They were converted into AGG graphs using the software OWLToGGx  [10].
2009b). We present a systematic study of the timing and duration of the release processes of near-relativistic electrons (NR; >50 keV) in the low corona by taking interplanetary transport effects into account. We use in situ measurements by both ACE and Wind and context EM observations in SXR, radio, HXR and white light (Sect. 2). We review the data-driven and simulationbased analysis methods used to infer the release time of the first arriving electrons and the release-time history near the Sun (Sect. 3). We select a sample of well-observed events (Sect. 4) suitable for simulation-based analyzes using the database of results of an interplanetary transport model  (Agueda et al. 2012). Modeling results are presented and discussed in Sects. 5 and 6. Finally, Sect. 7 gives the conclusions of this work.
These models allow us to accurately fit in situ data and remove the uncertainties inherent in direct analysis methods, such as VDA and time-shifting analysis. In this study, we make use of the results of the Monte Carlo interplanetary transport model developed by  Agueda et al. (2008 Agueda et al. ( , 2012)). The model assumes a static source of particles at two solar radii and an Archimedean spiral magnetic flux tube connecting the Sun and the spacecraft. The value of the solar wind speed measured by the spacecraft is used to estimate the curvature of the Parker spiral and constrain the global scenario. A turbulent component is assumed to be superposed onto the large structure of the IMF. Various pitch-angle diffusion models have been suggested to parametrize the wave-particle interactions, based on the original results of the classical quasi-linear theory (QLT) of particle scattering  (Jokipii 1966 ) and improved later approaches (e.
1). Group II  (2000 Sep. 12, 2002 Jul. 7 and 2002 Aug. 14)  was associated with gradual SXR flares with rise times larger than 25 min and long SXR decay times. The associated flares were larger than M1. 0 and distributed across the west hemisphere of the Sun (central meridian, nominal footpoint, and beyond the west limb). Unfortunately, the peak in HXR emission was missed by RHESSI for those events when data was available. Type III radio bursts were observed after the onset of the SXR emission. For the 2002 Aug. 14 event, the relevant type III group was not easy to identify due to a type III storm, but long decay microwave emission (5 GHz) was observed, as well as further faint and isolated type III bursts. Type II radio bursts were reported on the Wind/WAVES website. They included intense broad band (2000 Sep.
Results We used the SEPinversion software developed within the FP7 project SEPServer 3  to infer the release time history and the interplanetary transport conditions of NR electrons for each event. SEPinversion is an IDL-based software, freely available online 4  , based on the work by  Agueda et al. (2008 Agueda et al. ( , 2012)). In this study, we employed NR electron data by ACE and Wind covering the approximate energy range between 50 and 300 keV in three energy channels. To find out the best fit scenario, we considered a wide range of interplanetary transport conditions covering 20 values of the radial mean free path, logarithmically spaced between 0. 05 to 1. 20 AU. For each transport scenario, the best possible release time history was obtained. The goodness of the fit for each case was then evaluated by comparing the observations and the modeled data (see  Agueda et al.
We used the eight sectored intensities observed by the LEFS60 telescope on board ACE/EPAM and, when available, the PADs computed by Wind/3DP in eight pitch-angle bins. To provide a general overview of the evolution of the PADs of the event, we included the 50-82 keV electron PADs recorded by Wind in panel F. These plots are normalized to unity in each time interval. They show isotropic distributions during the preevent background period and anisotropic distributions when the event starts. We note that when the event starts the sunward part of the distribution is very small compared to the antisunward part; thus, the reader should not interpret the drop of intensity in the PADs plots as a sign that the intensities do decrease in absolute values. It can be seen that four of the events exhibit large data gaps in Wind observations (dark blue areas).
Acknowledgements. The research leading to these results received funding from the  European Union 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement No. 262773  (SEPServer). N. A. and B. S. were also supported by the  Ministerio de Economía y Competitividad (Spain) , under the projects PN  AYA2010-17286  and  AYA2013-42614. N. A. acknowledges support by the  Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR)  to visit the Observatorie de Paris in Meudon during two months. E. T. and R. V. acknowledge the support from the  Academy of Finland  (project  133723 ). The SOHO/LASCO CME catalog is generated and maintained at the CDAW Data Center by  NASA  and  The Catholic University of America  in cooperation with the  Naval Research Laboratory. SOHO is a project of international cooperation between  ESA  and  NASA.
We see that this notion of authentication successfully captures this attack. Non-injective agreement Sometimes, it is not sufficient to authenticate the other user's identity. We may also want to ensure that both parties agree on some other messages, e. g. the nonces n a and n b in the Needham Schroeder public key protocol. Therefore we may want to parametrize the definition by a set of data which the parties should agree on. Definition 6. 7 (Non-injective agreement  [Lowe, 1997a] ). A protocol guarantees non-injective agreement if, whenever an honest agent A completes a run of the protocol, apparently with another honest agent B on a set of data d then B has previously been running the protocol, apparently with A with the same set of data d. Generally one expects the participants to agree on all atomic data.
Exercises The following exercises require the use of the ProVerif tool available at http://proverif. inria. fr ProVerif's input language is a variant of the applied pi calculus and property specification is similar to the material discussed in this chapter. Exercise 15 (**). Model the Needham Schroeder public key protocol in ProVerif and use ProVerif to verify the following properties, respectively find attacks. 1. Verify that the protocol satisfies (weak) secrecy of nonce n a , but admits an attack on the (weak) secrecy of nonce n b. (Check that the attack found corresponds to the man in the middle attack) 2. Verify that injective weak agreement is guaranteed to the initiator, while non-injective, weak agreement is violated. Exercise 16 (**). Correct the model of the previous exercise by applying Lowe's fix (cf Chapter 2).
, 2010b , Bortolozzo et al. , 2010]. Apart from security APIs many other protocols need to maintain databases: key servers need to store the status of keys, in optimistic contract signing protocols a trusted party maintains the status of a contract, RFID protocols maintain the status of tags and more generally websites may need to store the current status of transactions. Many existing tools, in particular those that allow to verify protocols for an unbounded number of sessions, do not handle well this kind of state. Limitations of an encoding of memory cells are for instance discussed explicitly in the ProVerif manual  [Blanchet et al. , 2013, Section 6. 3. 3] : "Due to the abstractions performed by ProVerif, such a cell is treated in an approximate way: all values written in the cell are considered as a set, and when one reads the cell, ProVerif just guarantees that the obtained value is one of the written values (not necessarily the last one, and not necessarily one written before the read).
" Some works  [Arapinis et al. , 2011 , Mödersheim, 2010 , Delaune et al. , 2011]  have nevertheless used ingenious encodings of mutable state in Horn clauses, but these encodings have limitations. The most recent advances on verification of such stateful protocols are based on the tamarin prover  [Schmidt et al. , 2013, Kremer and Künnemann, 2014]. These works overcome existing limitations but require user interaction. Another kind of protocols for which only very limited tool support exists are group protocols, e. g. group key exchange protocols, where participants need to process lists or other recursive data structures. This kind of data structures also appears in web services that have to process XML documents. Some of the first results on this topic were obtained by  Paulson [1997]  who used the Isabelle theorem prover to prove a recursive authentication protocol.