dataesr/scientific-paragraphs-categorization huggingface dataset:
A new game of thrones: the usual suspects, the space invaders and new nations in a worldwide competition This section gives an overview of the EO imagery landscape in September 2016 with a short presentation of the main providers of EO data and services. The two champions are Digital Globe (US) and Airbus Defence and Space (Europe). DigitalGlobe is today the worldwide leader. It offers today the sharpest imagery (30 cm GSD) with WorldView-3 and WorldView-4 (launched in November 2016). DG's first market is US administration (63. 7% in 2015 and 2016) with 55% for NGA as anchor customer (framework contract). In 2015, DigitalGlobe communicated on its "steady business with the U. S. and other governmental customers" compared to disappointing results to the private sector showing the challenge to address both non-governmental customers and a large number of customers (Ref  [5] ).
It was not anymore the case for SPOT 6 and SPOT 7: satellite development costs have been funded entirely by private funds provided by Airbus Defence and Space. The first market is the commercial market. The Geo-intelligence division is backed by Airbus Defence and Space (Space Systems) for the development of new satellites. For Airbus Defence and Space, the next important milestone is the estimated end of life of Pleiades-1A and Pleiades-1B around year 2020 (Pleiades follow-on, end of DSP). Timely and predictable renewal of space assets, performance improvement (resolution and revisit) and continuity of data supply are essential conditions to maintain customers' trust and fidelity. As announced at the World Satellite Business Week by Nicolas Chamussy, Head of the Business Line Space Systems, Airbus Defence and Space is designing and building a new constellation of optical satellites, comprising four identical and very agile sensors delivering very high-resolution imagery.
The nations Whether they are veterans in space activities (China or India) or newcomers deciding to have their own EO capacities, more and more nations are becoming active players in Earth Observation. This affects both the competition and the accessible market. For example, SI imaging Services (South Korea) distributes since mid-2016 VHR imagery (GSD < 50 cm) acquired by Kompsat-3A. Another example is the drastic reduction of EO data imported by China, since the "Middle Kingdom" operates high and very high resolution satellites. Soon or later, China will enter the worldwide EO market as a new provider. 4. 2. Focus on new Space: business not as usual?.
New space in earth observation is mainly an US story, with the exception of Satellogic in Argentina (Ref  [8] ) and NorStar Space Data in Canada. Most of the investment is from the US, in particular from the Silicon Valley. Other the past ten years, more than 33 projects of EO satellite constellations have been announced. Despite the bloom of new satellite EO constellations, many experts remained sceptical on the capability of all these projects to become operational. On the 33 announcements, today only 9 have actually started and none is fully operational. In June 2014, when acquiring Skybox Imaging for 500 M$, Google surprised space remote sensing experts and traditional players. This acquisition highlighted the potential economic value of "low-cost" satellite EO constellations, even if few demonstration satellites have been launched.
The potential threat was taken seriously by established providers of EO data and services who started to adapt their offer and their organisation. In 2015, Planet and Urthecast have raised sufficient funding to acquire the space assets of established competitors such as Blackbridge and DEIMOS, re-enforcing their business model with a "traditional" satellite constellation and a client portfolio. These first buybacks are observed with interest by satellite EO experts and venture capitalists to understand the dynamic of this new economic ecosystem. Even if none of the newly announced constellations have reached full capacity, there are already concrete consequences on the market and the existing players: the Rapid Eye (Blackbridge) and Deimos acquisitions give better access to market and a customer base for Planet and UrtheCast but creates an exit strategy for the two former European players.
Other actors Some start-ups do not plan to fly their own satellites: based in Palo Alto, Orbital Insights, for instance, has recently received $20 Million in new investment, including $5 Million from In-Q-Tel, the investment arm of the US intelligence community. Orbital insights receives its data through contracts with EO data owners. While gathering data on a large scale from external sources, the start-up develops software to extract insights from satellite and aerial imagery. Typical Analytic data products are: -Counting cars on retail parking lots. -Gauging the amount of oil stored in tanks (floating lids shadows). -And a new list of targets: trucks, ships, trains, plants, deforestation (WRI), WB in Sri Lanka. A second interesting example is SpaceKnow, also based in Silicon Valley. Founded in 2013, SpaceKnow uses space imagery and other data sources to track global economic trends from space through their Analytics-as-a-Service products (analytics, alerts and indices).
Overview Well-known global consulting companies such as Euroconsult, Bryce Space and Technology or Northern Sky Research (NSR) publish regular forecasts and updates. Professional associations such as EARSC or Eurospace provide also comprehensive figures on the health of their respective industry and describe the market trends. Their assessments of total market value differ but they agree on the main trends and evolutions. Except if specifically stated, the figures used in this section are based on the report "Satellite-based Earth Observation, Market Prospects to 2025" released by Euroconsult (Refs  [13, 14] ). Commercial data market reached $1. 7 billion in 2015 (6% growth on 2014), largely driven by defence and IMINT ($1. 1 billion). All other market shares are below 10%. According to Euroconsult, Optical data represented 84% of the market.
Typology of information services and customers In all areas, service market is the main (or first) growth opportunity for the new operators. From satellite manufacturing to service delivery to the end user, the EO value chain is usually structured in tiers with the upstream, midstream and downstream layers, as depicted on Fig. 8. The main components of a generic service chain based on EO data are: -EO Imagery and other data sources. -Processing and access middleware. -Mid-stream and downstream infrastructure (algorithms, cloud, analytics, etc. ) -Service providers, with possible hosting in mid-stream infrastructures or as external components. One can identify several types of services: depending on the weight of image data compared to other data (data-agnostic services), there may be opportunities for EO data owners or satellite operators, EO data brokers or for pure service players.
GEO4i is another good example: this French SME combines the expertise of image analysts and geomatics skills from the Ministry of Defence. GEO4i emphasises its close relation with the final customer and its capacity to propose ad hoc solutions. Fig. 9  highlights the potential use of medium resolution data as information source for added-value services. A coherence map of two radar images (Sentinel-1) reveals the activity detected between the 8th March 2016 and the 20th March 2016. It allowed detecting many passages of vehicles and showed intense activity. This suspicious activity is confirmed by the optical image (Sentinel-2) acquired March, 11th.
A total of 79,957 SSRs (78%) were polymorphic between the three genomes thereby suggesting their promising use in different genomics-assisted breeding applications. From these polymorphic SSRs, 23 were selected and validated to have high polymorphic potential in 48 sesame accessions from different growing areas of Africa. Furthermore, we have developed an online user-friendly database, SisatBase (http://www. sesame-bioinfo. org/SisatBase/), which provides free access to SSRs data as well as an integrated platform for functional analyses. Altogether, the reference SSR and SisatBase would serve as useful resources for genetic assessment, genomic studies, and breeding advancement in sesame, especially in developing countries.
More importantly, there is no database to search for sesame SSR information at the whole genome level and to perform functional analyses, as developed in other crops such as chickpea (CicArMiSatDB:  Doddamani et al. , 2014 ), (CMsDB: Parida et al. , 2015) , Cucumis melo (CmMDb:  Bhawna et al. , 2015) , tomato (TomSatDB:  Iquebal et al. , 2013 ), sugar beet (SBMDb: Iquebal et al. , 2015) , brassicas  (Shi et al. , 2014) , etc. The completion of the full nuclear genome sequence  (Wang et al. , 2014a)  recently updated  (Wang et al. , 2016)  and the newly sequenced landraces  (Wei et al. , 2015 (Wei et al. , , 2016) )  provide a cardinal framework to identify highly informative SSRs at the whole genome level. In this study, we took advantage of these three genome sequence resources and provided not only a large amount of genome-wide informative SSR markers for large-scale genotyping and breeding research in sesame, but also a user-friendly online database for convenient search and functional analyses of SSRs.
Microsatellite Mining and Primer Designing Perl scripts from MISA  (Thiel et al. , 2003)  were used for identifying SSRs based on the reference genome sequence. Perfect microsatellites, as well as compound microsatellites interrupted by a certain number of bases were searched  (Yu et al. , 2016). The parameters were set for detecting mono-, di-, tri-, tetra-, penta-, and hexa-nucleotide (nt) motifs with a minimum of 10, 6, 5, 5, 5, and 5 repeats, respectively. The compound ones were defined as ≥2 repeats interrupted by ≤100 bp. Primer3 software  (Untergasser et al. , 2012)  was employed to design up to three primer pairs to all the identified SSRs. We named all SSRs from SiSSM1 to SiSSMxx following their order on the pseudo-chromosomes and unanchored sequences. To identify the SSRs within genic regions, the general feature format (GFF) files of genes or transcripts were combined with the positions of the SSRs located on pseudo-chromosomes.
Electronic Polymerase Chain Reaction The primer pairs of 105,879 microsatellites located on the 13 pseudo-chromosomes were used to in silico amplify the genomic sequences of "Zhongzhi13, " "Mishuozhima, " and "Baizhima, " employing the software GMATA  (Wang and Wang, 2016). The primer nucleotide mismatch allowed was no more than one nucleotide and other parameters were set as default. The polymorphic primers were selected based on difference in number of repeat-units present in the three genomes.
Additionally, the amplified products were also electrophoretically separated on 1. 5% agarose gel in TAE buffer and stained with ethidium bromide. The number of alleles (Na), major allele frequency (MAF), and polymorphic information content (PIC) were calculated with the software PowerMarker version 3. 25  (Liu and Muse, 2005). Moreover, to identify the pair-wise genetic relationships between the 48 accessions, a neighbor-joining (NJ) tree based on Nei genetic distance  (Nei, 1972)  was drawn in MEGA version 7  (Kumar et al. , 2016).
Development of SisatBase The process of SisatBase development can be divided into two steps: (i) integration and consolidation of microsatellites data and (ii) developing SisatBase and embedding useful tools. The datasets were curated to create a logic relationship among the different types of microsatellite data for their integration in SisatBase. Thereafter, SisatBase was developed using the LMAP (Linux + Apache + Mysql + Perl/PHP/Python) web application program platform. The HyperText Markup Language (HTML) and JavaScript language were also used to develop a user-friendly web interface. With the aim to enrich the functions of SisatBase, Browse, Search, customized BLAST, and MISAweb were developed for users to browse, search, and identify SSRs in the sesame genome conveniently  (Altschul et al.
SisatBase: An Online Database for SSR Functional Analysis in Sesame In order to facilitate the exploitation of the SSRs at the whole genome level in sesame, we developed an online database with an easy-to-use interface 3 (Figure  5A ). SisatBase supplied basic information for SSRs, including location on chromosomes, SSR type, SSR size and up to three primer pairs for each SSR entry, as well as the functional genes associated with the SSRs. Except that, SisatBase also provided the polymorphic SSRs among different sesame genotypes. In addition, SisatBase supplied useful search tools, including keyword, SSR type, and SSR location searches, which can help users to obtain their interested SSR information (Figures  5B, C ). Customized BLAST and MISAweb were also embedded in SisatBase to help users to get or identify conveniently SSR with primers in their interested genomic regions or genomic sequences (Figure  5D ).
, 2016). In the works of  Dossa et al. (2016c) , 33 polymorphic SSRs were employed to assess the genetic diversity of 96 sesame accessions from Africa and Asia which resulted in a high genetic diversity within the African germplasm. The 23 selected SSRs used in the present study to scan the diversity of 48 African accessions were all polymorphic and yielded comparable alleles number (123 vs 137) although fewer genotypes were examined here. Similarly, a high genetic diversity was also observed in the studied germplasm proving that the global 79,957 informative SSR markers could be effectively considered as the reference SSR for large-scale genotyping and molecular breeding research in sesame  (Billot et al. , 2012). All SSR data were integrated into SisatBase which also supplied useful and user-friendly tools to assist users to extract more information related to SSR markers in the sesame genome.
CONCLUSION In conclusion, based on the latest version of the sesame reference genome and the two newly released genome sequences, we identified 138,194 SSRs of which 79,957 are proposed as the reference SSR for future genetics/genomics and breeding studies in sesame. All microsatellite data reported in this study are integrated into a user-friendly online database (SisatBase) for a convenient exploitation and further functional analyses. These tools will undoubtedly help to speed-up sesame molecular breeding especially in the developing countries.
MATERIALS AND METHODS In May-July 2016, a systematic search for randomized, placebocontrolled clinical trials (RCTs) in ALS patients was performed across the MEDLINE and Clinicaltrials. gov databases (published in English language). In addition, ARISLA list of global ALS trials (ARISLA (Fondazione Italiana de Ricerca Per La Sclerosi Laterale), 2014) was used as a supportive information source.
Inclusion Criteria Advanced phase (Phases II, II-III, and III) randomized controlled trials (RCTs) that have recruited ≥100 ALS patients and with the results published between 1995 and July 2016 were included. For the compounds identified in this manner, the search was further expanded to include all the early stage trials that served as a justification for large-scale studies, regardless of the number of patients recruited. One compound, that did not meet pre-specified inclusion criteria with 63 patients recruited in a Phases 2-3 RCT (memantine; EudraCt # 2007-002117-39) was added to the present analysis as this molecule's mechanism of action (antiglutamatergic) is similar to the currently approved riluzole.
v. ), and a further 2 (9%) drugs via continuous i. v. infusion. Only two RCTs, which included pre-specified efficacy measures as the primary endpoint and recruited ≥100 patients, were successful on the primary endpoint. Based on the results of pre-specified interim analysis, oral masitinib has shown therapeutic benefit on the primary endpoint (ALSFRS-R), as well as secondary endpoints of forced vital capacity (FVC), combined assessment of function and survival (CAFS), and ALSAQ-40 (40-items ALS quality of life assessment questionnaire) (AB Science, press-release www. ab-science. com/file_bdd/content/ 1475163914_ABSCIENCESLAEMAFilingvEngVF. pdf) -in a broad ALS patient population in advanced stage Phases 2-3 RCT. The study has recently completed recruitment (392 patients), with the results of the final analysis expected to be available in 2017 (trial ID# NCT02588677).
Edaravone is a second drug that had shown clinical efficacy on the primary endpoint (ALSFRS-R) and ALSAQ-40 secondary endpoint in one of the three Phase 3 RCTs (trial ID# NCT01492686), recruiting 137 patients  (Tanaka et al. , 2016a). The other two RCTs with edaravone in ALS, which recruited patients with a wider inclusion criteria  (Abe et al. , 2014) , and patients with more advanced disease  (Tanaka et al. , 2016b)  have failed to reach statistical significance on the primary endpoint. Edaravone treatment regimen requires 2-weeks on, 2 weeks-off daily continuous i. v. infusions (30 min) of the drug substance, a factor which needs to be taken into consideration when assessing quality of life. In terms of patient inclusion, CT with masitinib recruited a wider, more representative, less restrictive patient population in comparison to the only successful edaravone CT   Rosenfeld, 2001; Groeneveld et al.
The second confirmatory Phase 3 study (trial ID#: NCT00415519) recruited 25 patients with severe ALS, with the inclusion criteria of FVC of at least 60% and the time since disease onset of <3 years. The study failed to demonstrate any treatment effect between placebo and edaravone arms  (Tanaka et al. , 2016b). The third confirmatory Phase 3  (Tanaka et al. , 2016a ) study (trial ID#: NCT01492686) narrowed the inclusion criteria even further (when compared to the first confirmatory study) and excluded both the patients with more severe disease and the patient population with the least severe disease (patients with probable laboratory-supported ALS were no longer part of inclusion criteria). Inclusion criteria included FVC of at least 80% and the time since disease onset of <2 years. This third confirmatory Phase 3 trial recruiting 137 ALS patients was successful on the primary endpoint of ALSFRS-R, as well as on ALSAQ-40 quality-of-life questionnaire.
Masitinib Masitinib is a highly selective tyrosine kinase inhibitor which was previously shown to prevent CNS neuroinflammation in a number of neurodegenerative disease models including in ALS SOD1 G93A rats  (Piette et al. , 2011; Vermersch et al. , 2012; Kocic et al. , 2015; Trias et al. , 2016). In a SOD1 G93A rodent model, masitinib significantly prolonged survival when delivered after paralysis onset, an unprecedented effect in preclinical models of ALS. Masitinib was also shown to be capable of controlling microgliosis, neuroinflammation, and the emergence/expansion of aberrant glial cells in preclinical ALS model. Masitinib's mechanism of action can thus be considered unique among the compounds described in this review  (Trias et al. , 2016). Masitinib is currently undergoing Phase 3 development in ALS patients as an add-on to riluzole therapy (trial ID# NCT02588677), recruiting 382 patients into three treatment arms (placebo versus 3.
The study will be completed when 100% of the enrolled patients have completed the 48-week treatment protocol period. Final data readout is expected before mid-2017. Considering the near total failure of ALS CTs over the last 20 years, these results are encouraging and the prospects of an eventual marketing authorization are currently being explored (AB Science Press Release; www. ab-science. com/file_bdd/content/ 1475163914_ABSCIENCESLAEMAFilingvEngVF. pdf). It will be of interest to evaluate possible clinical potentials of edaravone versus masitinib. Full publication of results from clinical studies with both compounds in ALS will be of great interest so that a more rigorous comparison of efficacy and safety between these promising candidate treatments can be made. However, given the information currently available and assuming equivalence in all other aspects (e.
Several methods have been proposed to enhance the quality of Kinect skeleton data delivered by the associated software  (Shotton et al. 2012). Recently, several authors have proposed to reconstruct badly estimated skeleton data by more plausible one, using a database of accurately captured examples  (Shum et al 2013 , Shen et al. 2014). To ensure continuity of the resulting posture sequence, recent works have proposed to organize the database of examples as a graph connecting two postures without discontinuity  (Plantard et al. 2017). The relevance of such corrected postures in an inverse dynamics process has not been tested in previous studies. The aim of this paper is to evaluate if inverse dynamics based on these corrected postures could provide accurate joint torques for an ergonomic purpose, even in bad measurement conditions: occlusions and unsuitable sensor placement.
Vicon pipeline Vicon data was processed thanks to the Nexus™ software 1. Occluded marker trajectories were reconstructed under the hypothesis of rigid bodies. The geometrical parameters, mainly the lengths of the body segments, were initialized thanks to a scaling process, based on the subject size. Then, a geometrical calibration was performed to adapt the segment lengths and marker positions of the model to those of each subject. This calibration was formulated into an optimization problem trying to minimize the difference between the body segment lengths of the model and those of the subject, obtained from Vicon data. Concurrently we also minimized the distance between the marker positions of the model in the local body segment reference frame and those of the subject, obtained from Vicon data  (Muller et al.
The output data provide Kinect-like skeleton composed of 20 joint 3D positions. Readers are referred to  (Plantard et al. 2017)  for more details about the pose correction method. Figure  5  shows the biomechanical model used for the Kinect calculation pipeline. The position and the orientation of the thorax are assumed to be the basis of the floating-based system. Since the hand position obtained with the Kinect was not accurate enough, the wrist was considered as locked. Moreover, information provided by the Kinect does not provide the pronation/supination movement of the forearm. Therefore, we have chosen to model the elbow joint as a revolute joint. The method used to correct Kinect data is based on a physical model that ensures to maintain constant the distance between two adjacent joints.
2017 ). To achieve this validation, we performed the inverse dynamics calculation with Vicon data for the full-body model, while applying the external forces provided by the force plates. We then analysed the forces and torques applied to the 6-dof ground-to-pelvis joint. For each experimental condition, the RMS of these residual forces and torques were calculated for each axis, expressed as mean values and standard deviations for all the subjects. Residual forces were normalized by the body weight of the subject (BW) and the residual torques by the body weight of the subject multiplied by his size (BW × H). We then evaluated the results obtained using the corrected Kinect data along YXY shoulder axis, and the Z elbow axis, according to the ISB recommendations  (Wu et al. 2005). Firstly, we compared the angles (θi) and joint torques (τi) along axis i, obtained using the Kinect data with those calculated from Vicon data (assumed to be the reference values).