dataesr/scientific-paragraphs-categorization huggingface dataset:
Resolution of original facial images is 256 × 256 pixels. After cropping, each image has a resolution of 138 × 128 pixels. The head is almost in frontal pose. The number of images corresponding to each of the seven categories of expressions is roughly the same (around 30 images per class). A few of them are shown in figure 3. It is obvious that expressions are over exaggerated. Nonetheless this database has often been used in literature to evaluate the performance of some facial expressions recognition algorithms. JAFFE Database Protocol: Identities that appear in the training data sets do not appear in the test set. 1. train set: 20 images per class are picked out as training set. In total we have 143 facial expression images, randomly shuffled, for training our algorithm. 2. development set: Leave-one-out cross validation is considered over the training set to tune the algorithm parameters.
CONCLUSION In this paper, a robust spontaneous facial expression recognition algorithm (SFER) based on facial images that recognizes non-basic affective state including mental state is presented. We developed a method to pre-train the dictionary that enforces sparsity and enhances dictionary performance. We shown that it was possible to learn under-complete dictionary once good discriminative features are extracted prior to dictionary refining stage which ensures the uniqueness of the selected atoms from the dictionary during the optimization process. We proposed the use of random projection as a mean of dimensionality reduction and as a mean of solving the problem of shared subspace. We exhibited very good recognition rates over the recent spontaneous facial database DynEmo. A possible work for the future is exploiting the temporal dynamics of facial expressions in order to improve the recognition rates.
Sharing Models across organizations is a good idea but the lack of a tailored and lightweight tool hinders its adoption. In this paper, we explain how to turn any computer into a Model server, which is a server specialized in Models' location and retrieval. Such a server relies exclusively on specific URIs and commands thereof. The result, called "WWM", is an out-of-the-box module built upon Node. js. WWM targets the EMF ecosystem and takes the form of a JavaScript API for both server-side and client-side programming.
Meanwhile, Eclipse Modeling Framework (EMF) is a very popular modeling workbench that implements the 3-layer modeling stack, and in which (Essential) MOF is embodied by the Ecore metalanguage. The prevalent serialization mechanism of EMF is XMI. As a direct consequence, the solution proposed in this article is designed for, but is not limited to, the EMF ecosystem, provided that there is a XML-based storage under the hood. This means that remote Models are purposely retrieved so that they can be integrated into EMF projects or as inputs of EMF-based tools. To illustrate the aforesaid hurdles, most of EMF tools are based on Models locally registered through platform-independent identifiers ("nsURIs" in the jargon) that are actually neither linked to anything tangible nor commonly shared. One of our ambitions is that these URIs become effective, delivered by clearly identified Model servers, starting with those of the OMG itself.
Besides, it is worthwhile recalling that a Model server is useless without a Model client thereof. That is why these two programs, which are two sides of the same corner, have all together been merged into a single package dubbed "wwm", and built using Node. js (https://nodejs. org). In doing so, we want to encourage developers to build various applications on top of this JavaScript API. Notice that in this paper the term "Model" (notice the uppercase first letter) is used in its broadest sense, referring indifferently to M3, M2 or M1, whereas "model" strictly refers to an instance of a metamodel. Once this assumption made, the remainder of this paper is the following: Section 2 gives rationales for building a Model server. Section 3 describes the features of such a server while Section 4 elaborates on some aspects of its implementation.
A Domain-Specific Server The first question that may spring to mind is: Why not merely hosting the models on a regular server (e. g. HTTP, FTP, Version Control System …)? One may observe the same skepticism about domainspecific languages whilst general-purpose languages can do everything. Yet, they are legitimate since they are special for a narrow area of interest. The same applies for servers. Firstly, it must be pinpointed that a Web server (saying, Apache HTTP server) is a heavy, general-purpose container that can deliver evenly any kind of resources like pages, images, videos…. Only the MIME type differs and brings a few semantics when comes the time to handle resources. Yet, Models are specific abstractions on their own. Also, the gateway program layer provided by any modern Web Server is useless for inert resources, as are the cases of Models.
Server Setup The specific directories are created when the module is first launched. This structure has to be perennial for the Model server run in a correct way. To that purpose, an integrity checking subroutine is performed every time the server boots. As attested by the code below, launching the server is a breeze. Optionally, a callback allows listening which URIs are requested (line 3) by a client. Argument passed through the callback is a custom object modeling the URI and providing a set of useful methods to know its pattern. if (uri. isFragment()) { 5. console. log('Someone asked for a fragment at' + Date. now()); 6. } 7. });.
Samples We first illustrate an exhaustive assignment of callbacks in order to handle all cases (ranging from line 3 to 14). Notice that method chaining is a convenient way to do that. Once the chosen callbacks functions are assigned, the client is ready for requesting the server with connect(). Here, the "UML" metamodel then "myshop" business model are requested, that will both trigger the same callback. Thus, the elected code (lines 4-5) calls save(), a helper bundled with wwm that creates a physical file with the proper XMI content on the client-side, and finally displays a message to the console. As a second illustration, we give a programming idiom that solves nicely a frequent client-side intent, which consists in sending a list command having the final purpose to retrieve all the available Models.
We are expecting that its tiny size and its quick install procedure should ease its adoption, at least within the MDE community. From a practical point of view, while the server part of our solution can run effortlessly on any computer once the Node. js interpreter is installed, the default client currently written in JavaScript is not really intended to mobile OS, albeit this is technically possible on Android. So, the straightforward way to carry out the Android architecture introduced in Figure  2  is to write a whole new Android Java client. Nevertheless, Microsoft for example is hoping to power the IoT revolution and has announced new native support for bringing Node. js to its Windows Phone OS. It's a safe bet that other platforms will do the same in a near future. Beyond mobile computing concerns, a Model client directly integrated into EMF as a plugin is probably a good idea for language engineers.
Equation of state a b s t r a c t This work aims to incorporate compressible multiphase flow into the conventional reactive transport framework using an operator splitting approach. This new approach would allow us to retain the general paradigm of the flow module independent of the geochemical processes and to model complex multiphase chemical systems, conserving the versatile structure of conventional reactive transport. The phase flow formulation is employed to minimize the number of mass conservation nonlinear equations arising from the flow module. Applying appropriate equations of state facilitated precise descriptions of the compressible multicomponent phases, their thermodynamic properties and relevant fluxes. The proposed flow coupling method was implemented in the reactive transport software HYTEC.
Our alternative method This work proposes a new approach for incorporating the compressible two-phase flow in a conventional reactive transport simulator. It is based on the phase flow formulation and preserves all the sustainability and facilities of the reactive part. This method builds on the unconditional stability of the fully implicit scheme and can model advective-dominant and density-driven regimes. The following simplifications are considered in this work: isothermal flow and no geomechanics. The method was applied to the (SIA) reactive transport simulator HYTEC  ( Lagneau and van der Lee, 2010b; van der Lee et al. , 2003 ). The HYTEC code has been widely evaluated in several benchmark studies  ( Carrayrou et al. , 2010; Lagneau and van der Lee, 2010a; Trotignon et al. , 2005; de Windt et al.
Numerical solution Applying the OSA to subsurface environmental modeling enables the independent development of separated modules of code and the rigorous solution of each. Consequently, the majority of RT simulators rely on the OSA  ( Steefel et al. , 2014 ). The assessment of different coupling methods was studied for the MoMaS benchmark of RT codes  ( Carrayrou et al. , 2010; Carrayrou and Lagneau, 2007 ) , during which the reliabilities of both the SIA and GIA were determined, and the detailed results of HYTEC were reported in Lagneau and van der Lee (2010a ). Following the general strategy of integrating the (un)saturated flow in RT codes by OSA, we solved the compressible two-phase flow block first. This process involved the flow system, the gas transport equations, and the EOS and fluid property models.
The fluid properties and solubility are also treated differently. In HYTEC, the gas and liquid densities are provided by Peng-Robinson models  ( Ahlers and Gmehling, 2001; Jaubert and Mutelet, 2004; Robinson and Peng, 1978 ) , and the viscosities are  predicted by  Altunin (1975)  ;  Islam and Carlson (2012). The partial molar volume at infinite dilution in water is averaged over the relevant pressure range, and the aqueous activities and gaseous fugacities are simulated according to the b-dot and PR78  ( Robinson and Peng, 1978  ) models, respectively. In  Pruess et al. (2002)  , the TOUGH2-ECO2 module was used, which is described in  Pruess and García (2002). Despite the aforementioned deviation in parameters, the gas saturation front is similar in both cases, particularly over the first 10 0 0 d, as shown in Fig.
The tolerance of Newton's method ( Algorithm 1 ) is ε N f = 10 -7 , and the gas quantity criterion Eq. (  21 ) is ε g = 10 -5. The mass conservation error is on the order of 10 -6. The initial time step is set to 156 s, which is also the minimum time step min( dt ). The time stepping for HYTEC and DUNE is listed in Table  3. The HYTEC's user-imposed maximum time step max( dt ) is slightly higher (by 8%), and thus, the average dt is larger and the HYTEC is executed faster (by at least 9%). ( Pruess et al. , 2002 ) , where IFP -SIMUSCOPP, IRL, CSIRO -modified TOUGH2, LBNL -TOUGH2-ECO2, ARC -GEM, PNNL -STOMP,  (Pruess et al. , 2002, Figs. 3. 5-3. 7). In Table  4  , the HYTEC execution time includes the grid construction, initialization, output printing, solvers, and secondary property modules.
2D Injection and impact on chemistry An application is proposed to test the coupling with chemistry. The application builds on the previous 1D radial and 2D injection problems. The gas injection of CO 2 and H 2 S takes place in an initially fully saturated reservoir at 3. 1 km depth. The reactivity of the host-rock is now taken into account. A homogeneous carbon- ated reservoir is simulated: Table  5. All reactions are considered at equilibrium, using the LLNL database  ( Wolery and Sutton, 2013 ). Ion and water activity were corrected by the b-dot and Helgeson formalisms  ( Helgeson, 1969 ). The Henry's constants are pressureand temperature-dependent, the gas-liquid equilibria modeling is described in Section 2. 3. 2. Sulfur oxidation and sulfate reduction are disabled in this context: the intermediate temperature (80 °C) and the relatively short time frame (30 y) do not enable active thermal nor bacterial sulfate reduction  ( Riciputi et al.
Acknowledgments This work was supported by  MINES ParisTech and BRGM. I. Sin  thanks  Christophe Coquelet  ( Centre for Thermodynamics of Processes, MINES ParisTech ) for his insightful suggestions regarding the thermodynamics development and  Claude Tadonki  ( Centre for Computer Science, MINES ParisTech ) for productive discussions about linear solvers. We thank three anonymous reviewers for constructive and valuable comments. Their careful analysis helped us significantly improve the manuscript, especially Section 4.
Particularly, a new morphological tool, the Aurora Transform (AT), is introduced and then used to improve the automatic extraction of SV edges compared to previous studies  [1, 13]. The efficiency and the reliability of each step are assessed and discussed. The proposed methods allow image registration, 2D modeling, valve tracking, morphological classification and metrological characterization of SV. This work leads to a software dedicated for a quick and reliable analysis of the SV and the aortic root.
Apparatus and Stimuli We used a rear-projected wall screen (3 m x 2. 25 m) with a resolution of 1400 x 1050 and the Ninento Wiimote as interaction device. The platform is illustrated in figure  1. Stereo was possible through active shutter glasses tracked using a Vicon tracking system based on 6 IR Bonita cameras (200Hz) providing a tracked space of 6 m 2. The refresh rate was of 60Hz per eye. The virtual eyepoint height was set automatically corresponding to the subject's eye height. When the head tracking was not used, the experimenter calibrates this parameter before disabling the tracking system. Interocular distance was fixed to 6. 3cm for all participants. Our program is developed in C++ and is based on the VRJuggler library for device management.
Analysis Translating the interventions content into app features involved repeated iterations between members of the research team conducting the systematic review of the current available evidence and the members of the team with expertise on app development. The initial step was to agree on the theoretical basis and principles underpinning the intervention based on previous studies. This evidence informed the production of guiding principles that described the key features to be included in the app. These discussions also explored the best ways to deliver the BCTs selected and the agreed guiding principles for the intervention. After reaching an agreement over the key app features and design, we met regularly to evaluate progress of the app design. Data retrieved from these discussions were collated to develop interactive mock-ups and a workflow for the mISkin app.
One of the key challenges was the need to adapt to similar technical language when communicating within a multidisciplinary team. The developed interactive mock-up and workflow of the mISkin app are presented in Figure  2  and Figure  3  respectively. Interactive mock-ups of the app were developed and used to test for ease-of-use, graphics appeal, and the general comprehension and acceptability of the distinct features of the mISkin app, using semi-structured interview methods. The workflow was used as a design brief depicting the interaction process within the mISkin app that informed the development of a functional version of the intervention prototype by the app developers.
Limitations While the views of the 17 participants were coherent and data saturation was achieved, not all groups of potential users were similarly represented and it is possible that a more extensive engagement of potential users would lead to further improvements in acceptability and usability. The mISkin app was only developed for devices using the Android operating system, limiting the possibility of including users owning other smartphones (eg, iPhone and Blackberry). It is also important to highlight that the participants' views were based on only visualizing a prototype intervention aimed to be delivered during holidays. Views of using the app could change participants were given the possibility of interacting with the mISkin app in a real scenario of holidays. It would have been useful to have a group of users that tried out the app on their own, followed by an interview about their experiences (ie process evaluation built into a pilot acceptability and feasibility study).
Acknowledgments The work described in this paper was funded by a PhD fellowship from the  Portuguese Science and Technology Foundation (FCT)  (Reference: SFRH/BD/60392/2009). Angela M. Rodrigues  and  Falko F. Sniehotta  were funded by  Fuse , the  Centre for Translational Research in Public Health , a  UK Clinical Research Collaboration Public Health Research Centre of Excellence  based on funding from the  British Heart Foundation ,  Cancer Research UK , the  Economic and Social Research Council, Medical Research Council , and the  National Institute for Health.
Hygroscopic growth of hydrophilic species is taken into account in the computation of the aerosol optical properties only. Following the emission release, the aerosol species are subject to wet and dry deposition and the largest size bins of sea salt and dust are also subject to sedimentation. The chemical source of sulfate is modelled by climatological conversion rates using a SO 2 tracer, which is independent of the SO 2 simulated as MACCRA in CB05. The SO 2 tracer is driven by prescribed SO 2 and dimethyl sulfide (DMS) emissions. Its loss is simulated by wet and dry deposition as well as the climatological chemical conversion to SO 4. The aerosol and chemistry modules used to simulate source and sink terms are not coupled. Wet and dry deposition are also modelled with different parameterisations but with the same meteorological input as precipitation fields.
5 scenario. The anthropogenic CO emissions were increased following  Stein et al. (2014). Time se-ries of the anthropogenic CO emissions for Europe, North America, East Asia (see Table  3 ) and the globe are shown in Fig. S2  of the Supplement. The anthropogenic emissions of organic matter, black carbon and aerosol precursor SO 2 are retrieved from the AERO-COM database, which is compiled using EDGAR and SPEW data  (Dentener et al. , 2006). In contrast to the anthropogenic gas emissions, the aerosol anthropogenic emissions did not account for trends but only for the seasonal cycle. The biogenic emissions for the chemical species were simulated offline by the MEGAN2. 1 model  (Guenther et al. , 2006)  for the 2000-2010 period (MEGAN-MACC,  Sindelarova et al. , 2014). For the remaining years 2011-2015 a climatology data set of the MEGAN-MACC data was put together.
Natural emissions from soils and oceans for NO 2 , DMS and SO 2 were taken from the POET (Precursors of ozone and their Effects in the Troposphere) database for 2000  (Granier et al. , 2005; Olivier et al. , 2003). Daily biomass burning emissions for reactive gases and aerosols were produced by the Global Fire Assimilation System (GFAS) version 1. 2, which is based on satellite retrievals of fire radiative power  (Kaiser et al. , 2012). This is an important difference with respect to the MACCRA, which used early versions of the Global Fire Emissions Database (GFED 3. 1) data from 2003 until the end of 2008 and daily GFAS v1. 0 data from 2009 to 2012. The GFED 3. 1 is on average 20 % lower than GFAS v1. 2  (Inness et al. , 2013). Time series of the biomass burning CO emissions for tropical Africa, South America, Maritime South East Asia (see Table  3 ) and the globe are shown in Fig.
, 2006; Textor et al. , 2006). likely caused by an exaggeration of the sea salt emission by an earlier version of the emissions module. The desert dust burden in the CR was 27 Tg, which was higher than the AeroCom median of 20 Tg. It was largely reduced to 18 Tg by the assimilation in CAMSiRA. MACCRA had an even lower desert dust burden of 12 Tg because of the underestimation of the desert dust emissions scheme used in MACCRA. As in the case of the sea salt, the underestimation of the desert dust loss by deposition and sedimentation may play an important role in the overestimation of dust burden in the CR. The strongest relative change in the global burden by the assimilation occurred for sulfate, which was 1. 2 Tg in the CR but was 4. 7 Tg in CAMSiRA and 3. 3 Tg in MACCRA. The respective AeroCom median value is 2 Tg.
Acknowledgements. CAMS is funded by the  European Union 's  Copernicus Programme. The GOZCARDS data were obtained from the  NASA Goddard Earth Science Data and Information Services Center. We are grateful to the  World Ozone and Ultraviolet Radiation Data Centre (WOUDC)  for providing ozone sonde and Dobson photometer observations. We thank the  Global Atmospheric Watch  programme for the provision of CO and ozone surface observations. We thank the  European Environmental Agency  for providing access to European ozone observations in the AirBase database. We also thank the  MOZAIC (Measurements of OZone , water vapour, carbon monoxide and nitrogen oxides by in-service AIrbus aircraft) and  IAGOS (In-Service Aircraft  for a Global Observing System) programmes for providing CO profile observations.
EMEP stations are located in rural areas, while AirBase stations are designed to monitor pollution at different scales. AirBase and European Monitoring an Evaluation Programme (EMEP) databases host operational air quality observations from different national European networks. All www. atmos-chem-phys. net/17/1945/2017/Atmos. Chem. Phys. , 17, 1945-1983, 2017.
Proxy and Cache. Scraping web forums implies a significant number of connections to the websites from which we want to extract data. In order to minimize the network load and avoid overwhelming the destination servers, it is important to avoid duplicate requests and have a delay between sequential connections. In web forums, a web page can be scraped several times if a thread belongs to several sub forums or if the scraping process is restarted for any reason. To handle the first case, a log file keeps track of all the visited URLs in a website. Before requesting a new URL, the scraping script checks if the URL has already been visited, in which case, it will be ignored. To handle unexpected issues relating to retrieving a URL that was already visited, a proxy with a cache database is proposed.
Before opening a new connection with the destination server, the scraping function checks if its database already contains the desired HTML page. If so, the HTML page is sent back to the scraping function; otherwise, a connection is established with the destination server, and a copy of the received HTML page is saved to the cache. Moreover, the proxy maintains a minimum delay of 0. 330 seconds between two sequential requests. This delay is extended to 2 seconds during working hours at our university to preserve the performance of the network.
The main goal of ANSM is to detect ADRs from posts in social networks, particularly medical-related web forums. To achieve this goal, the partners of the Vigi4Med project have agreed upon the following protocol: 1. A declaration about extracting medical information from web forums is sent to the CNIL  [36] , the national organization of data protection in France. 2. Pharmacovigilance experts select the websites with medical-related forums. 3. A message is sent to the forum's owners and administrators to inform them about the motivation of the project and their data crawling policy. This message also verifies our commitment to refrain from distributing or republishing the collected data. 4. The scraping algorithm respects a pre-defined delay between requests. 5. The scraped data are anonymized and organized in a semantic structure before proceeding with any further steps.