dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The authors acknowledge financial support from the project CASTRUM, commissioned by the  EU DG Santé. The following people were members of the CASTRUM network and had a significant contribution to the present study:  Christine Leeb ,  University of Natural Resources and Life Sciences, Austria; Evert Heyrman, ILVO, Belgium; Todor Stoyanchev, Trakia University, Bulgaria ;  Goran Kušec ,  Faculty of Agriculture in Osijek, Croatia ;  Susanne Støier ,  DMRI, Denmark; Patrick Chevillon, IFIP, France; Csaba Szabo, Debrecen University, Hungary ;  Luca Buttazzoni  and  Sebastiana Failla ,  CREA, Italy; Leonardo Nanni Costa, Department of Agricultural and Food Sciences, University of Bologna, Italy; Gé Backus, ConnectingAgriandFood, the Netherlands; Bente Fredriksen, Animalia, Norway; Katarzyna Skrzymowska, Polski Zwiazek Hdowcow i Producentow Trzody Chlewnej, POLSUS, Poland ;  Sandra Cavaco-Gonçalves ,  Instituto Nacional de Investigacão Agraria e Veterinaria, INIAV, Portugal ;  Mercedes Izquierdo ,  Centro de Investigaciones Científicas y Técnologicas de Extremadura, CICYTEX, Spain ;  Galia Zamaratskaïa ,  SLU, Sweden ;  Rex Walters ,  British Pig Association, BPA ,  United Kingdom.
, 2007;  Shalloo et al. , 2011; McCarthy et al. , 2013). One recent innovation has been to focus on the number of grazings achieved on individual paddocks. This is now a key performance indicator for Irish grassland systems. Such tools assist farmers in short-to medium-term grass management (MacDonald et al. , 2010). Smartphone, and to a lesser extent personal computer, based applications are the platforms used. These provide greater flexibility to the user. Furthermore, internet-based architecture enables the collation of large quantities of data in central databases. This extends the data usefulness beyond farm level. Data collected on a wide number of farms can be used to benchmark performance of a single operation, but also for research purposes (e. g. animal and plant genetics, precision nutrition) and policy formulation (Hanrahan et al.
Holistic farm solutions derived from the integration of sensor data, data interrogation and providing information to the end users through an appropriate medium and time framework are increasingly feasible (Figure  1 ;  Shalloo et al. , 2018). However, to date, literature about decision making with precision technologies is sparse, especially regarding pasture based dairy systems. Not specifically related to pasture but related are animal health databases. Veterinary use of medicines (especially antibiotics) is regulated in most countries with the recording of information regarding diagnosis and treatments being a common requirement. The quantity and type of medicines administered to individual cows could potentially be stored in a central database. However, in most countries, although this information has been systematically recorded on paper, it generally has not been recorded electronically and has not been collated centrally  (Egger-Danner et al.
, 2012). One example country where a significant effort has been put into standardising and aggregating animal health data relating to dairy cows is Austria. In Austria, the recording of animal health treatments was made a legal requirement in 2002 but the form and coding of this recording were not standardised or aggregated until 2006  (Egger-Danner et al. , 2012). In relation to animal genetics, there are a number of databases that are critical to increasing herd genetic merit (e. g. International Committee for Animal Recording Interbull database; Irish Cattle Breeding Federation database). Such data can be collected by public companies or associations such as in Ireland and Italy but also by private genetic companies. Information regarding animal performance including milk yield, fertility, longevity, animal health, administered treatments, calving, etc.
is routinely recorded. Precision technologies offer significant potential to inform breeding programmes through the automated collection of phenotypic traits such as activity and behaviour, which may be of economic value to select for. An example might include monitoring activity data that is collected by devices on individual animals as well as diagnoses of illness. Many of the traits that these devices collect information on are heritable, and it is desirable to record it to improve future breeding programmes. The robustness of data collected by sensors is still perceived as a priority and thus most research focusses on sensing accuracy and systems validation. Decision making remains pivotal, but underdeveloped, to the successful application of precision technologies. Decision support and automation is the basis of value creation from precision   (Rutten et al.
These needs can be addressed through the integration of existing databases, capturing new data and the application of best practice in data science to generate the most value from the data. Technological solutions which can increase the utilisation of pasture and the productivity and fertility of seasonal calving herds are likely to add significant value to pasture based systems. These should provide real benefits in profitability, sustainability and resilience by providing informed, real-time solutions to the farmer through an appropriate medium. In order for big data and smart technologies to realise their potential in grassland agriculture, there is a requirement for the different industry stakeholders to work together and to develop business models that facilitate and encourage the different stakeholders to integrate their solutions within an overall platform.
Conclusions This review focussed on precision within pasture based systems. Precision technologies offer significant potential to increase efficiency, reduce costs and labour, increase sustainability, improve sustainability verification and raise animal welfare standards of pasture based systems of milk production. The integration of sensor data, collated within centralised databases enriched with existing data and analysed for specific end use requirements, is recommended. Outputs provided through appropriate media and in realtime fashion will alter the use of these technologies in pasture based farming. A key shortcoming to date in this area is the failure to add value to data collected as the focus has been on accuracy. Farmer's time is limited and their skills and capabilities are variable.
On simulated data, our algorithm correctly identified the sites of interest for 99% of "high confidence" paths. For the cattle data, the algorithm identified the two known sites of interest: a watering hole and a milking station. It also identified several other sites which can be related to hypothesized environmental drivers (e. g. , food). Our algorithm gives an efficient method for turning a long, high-resolution movement path into a schematic representation of broadscale decisions, allowing a direct link to existing point-to-point analysis techniques such as optimal foraging theory. It is encoded into an R package called SitesInterest, so should serve as a valuable tool for making sense of these increasingly large data streams.
There are also more general techniques for path segmentation that have arisen in subject areas beyond ecology  (Demšar et al. , 2015). The modern era of high-resolution data offers a great opportunity to make better inference of such behavioral modes. However, the sheer size of most modern data sets makes statistical analysis tricky to perform in a reasonable time frame. Furthermore, for a path where locations are recorded many times per second, the animal is often simply continuing to carry out a decision made some time previously. Therefore, an important part of the behavioral information is contained within a small subset of the data stream  (Potts et al. , 2018). The development of techniques to infer behavioral decisions from high-resolution data is thus timely and necessary. Here, we aim to describe an animal track as a sequence of "sites of interest," which are areas where the animal spends a disproportionately long time, together with movements between these sites.
gorithm turns long, complicated streams of data into simple schematic decisions of broadscale behavioral decisions. This technique gives a foundational basis for tractable analysis of high-resolution movement data. ACK N OWLED G M ENTS RM was funded by a Leverhulme Trust Studentship as part of the Leverhulme Centre for Applied Biological Modelling. JRP acknowledges support from the National Environmental Research Council (NERC) grant NE/R001669/1. Data collection was partly supported by a grant from the College of Science, Swansea University, for the ALPEN project to LB, as well as Start-Up funding for LB (College of Science, Swansea University). We thank the cow owner, Patrice.
A number of regular, brownish colonies, reaching 2 mm after 48 h, were isolated from the only adult batch showing lesions. Testing using the commercial API20-NE identification system (Biomérieux, France) pointed to Ochrobactrum anthropi. MALDI-TOF assay (Bruker Daltonics, France) run on a spot of pure culture overlaid with 1 µL of HCCA matrix indicated Brucella spp. using the Biotyper Security-Related (SR) database  (26). Brucella misidentification using commercial biochemical tests is frequently reported (  27 );  (28) , and can result in laboratory-acquired infections  (29, 30). Isolates were subsequently sent to the national reference laboratory for reliable identification and refined characterization.
Improvement of the identification methods Correct identification of yeasts and moulds recovered from respiratory secretions from CF patients is required, not only to improve our knowledge on the epidemiology of fungal infections in this clinical context but also for early detec-tion of difficult to treat species capable of chronic colonization of the airways and of hematogenous dissemination in case of lung transplantation. Until recently, yeasts were identified according to their carbohydrate assimilation pattern and moulds by their macroscopic and microscopic features according to standard descriptions. Alternatively, species identification can be obtained by sequencing short variable genetic regions and subsequent comparison with reference sequences stored in appropriate databases. ] [49]  Matrix-assisted laser desorption ionization-time of flight/mass spectrometry (MALDI-TOF/MS) is now increasingly used for routine identification of yeasts.
50, 51 This technology is also about to revolutionize the identification of moulds as it could replace the traditional examination of macroscopic and microscopic morphology requiring highly skilled mycologists. 52 4] [55] [56] [57]  Common prerequisites are the previous establishment of adequate reference spectrum libraries and the optimization of the initial extraction procedure. A first-developed relevant database including 146 strains belonging to only 63 species and 33 different genera allowed the identification at the species level of 87% of the isolates identified in the routine activity of a clinical laboratory for 5 months. 58 A second-developed relevant library comprising 294 individual isolates representing 152 species and 76 genera allowed the identification of 88. 9% of blinded clinical isolates at the species level, 4.
3% additional isolates at the genus level, the remaining strains corresponding to Basidiomycetes or Penicillium that were not represented in the database. 59 Nevertheless, improvement of the databases is still needed since cryptic species have not been identified to date using all MALDI-TOF equipments. Results appear system-specific, and for instance only some of the available MALDI-TOF instruments include in their supplied databases reference spectra allowing precise identification of Scedosporium species, and differentiation within the R. argillacea species complex is currently not feasible. In addition, one may be cautious when interpreting the results of mycological examination of sputum cultures because of their possible contamination by environmental molds with the prolonged incubation time, and of possi-ble transient carriage of inhaled fungal spores that were entrapped into the sticky bronchial mucus at time of sampling.
4 Mbp. A total of 10,919 coding sequences (CDS) was predicted and putative functions were attributed to more than 80% of these CDS. A refined functional annotation was performed recently using Interproscan and allowed the identification of roughly 1,000 supplemental predicted proteins, which was confirmed by the analysis of transcriptomic data using the programs BRAKER/Augustus (unpublished results). As observed in other filamentous fungi, S. apiospermum genome encodes a large number of transporter proteins (particularly ATP-Binding Cassette (ABC) and Major Facilitator (MF) transporters), aspartyl proteases and transcription factors (with zinc finger C 2 H 2 or Zn( 2 )-C 6 fungal-type DNA-binding domains) (Fig. 1 ). Several two-component system (TCS) elements as well as G-protein coupled receptors were also detected and which be used for sensing of and adaptation to environmental variations.
107 In the same way, it is highly likely that Scedosporium transcriptomic data will increasingly accumulate in dedicated databases. For instance, transcriptomic analyses are currently underway to unravel the mechanisms developed by the fungus to establish within the respiratory tract of CF patients. These would certainly shed light shortly on the genes differentially expressed upon S. apiospermum exposure to the physicochemical conditions encountered in the respiratory tract of CF patients (including hypercapnia, hypoxia and acid pH), and in turn help in deciphering the crucial mechanisms allowing these opportunistic pathogens to specifically adapt to the CF bronchial mucus. Despite the availability of the genome sequence of some Scedosporium species, further efforts are needed in order to access efficient genetic strategies for exploring the role of selected genes in pathogenesis of scedosporiosis.
Acknowledgments The genomic studies have been supported by a  National Health and Medical Research Council (NH&MRC)  grant from  Australia   APP1031943  to WM for S. aurantiacum, by the  French association Vaincre la Mucoviscidose  ( RF20120600725/1/1/110 ) to JPB for S. apiospermum and by  Angers University  (Appel à projets internes 2014) to AG for S. boydii. Some of the works performed regarding improvement of the biological diagnosis of fungal respiratory infections in CF were supported by grants from  Vaincre la Mucoviscidose  to JPB ( 2010/IC1003 ),  MEB  ( RC20120600707/1/2/110 ) or MF ( RF20130500840 ).
9% NaCl and SO) were included (n = 3). Incubation times were 18 h ± 30 min (EpiDerm™) and 24 h ± 1 h (SkinEthic™ RHE) at 37 °C, 5% CO 2 , 95% air humidified atmosphere, according to the protocol of the supplier. After the incubation the tissues were rinsed with PBS and cell viability was determined by the MTT method. The following acceptance criteria were set. NC and VC acceptance criteria: the optical density (OD) of the NC and VC reflects the viability of the tissues used in the test conditions. For the EpiDerm™ tissue model the NC and VC were considered to meet the acceptance criteria, if the mean OD value of the three tissues was ≥0. 8 and ≤2. 8. For the SkinEthic™ RHE tissue model the NC and VC data met the acceptance criteria if the mean OD value of the three tissues was ≥0. 8 and ≤3.
Data processing All data obtained by the various laboratories were centrally collected and analyzed. Results of the various participating laboratories are presented anonymously and randomly. Variability of measurements (i. e. the percent cell viability per sample and experiment), was investigated on two levels. Reproducibility of results within each laboratory was evaluated for each test method by concordance of classifications, where a score of 100% concordance was given if all seven samples were classified consistently (either non-irritant (NI) or irritant (I)) in all three experiments. Concordance of classifications across laboratories was assessed using the combined outcomes of the three experiments. The results were compared with the expected outcomes for the various samples as presented in Table  3.
Although the discovery of the Higgs boson at the LHC has allowed for the completion of the particle spectrum of the Standard Model (SM), the issue of its extension still stands. Despite the experimental success in predicting most data observed so far, the SM indeed exhibits several limitations and shortcomings that motivate the study of beyond the Standard Model theories. Among those, supersymmetry, and in particular its minimal incarnation known as the Minimal Supersymmetric Standard Model (MSSM), is one of the most appealing options. Unifying internal and external symmetries, supersymmetry provides a natural solution to the long-standing hierarchy problem, allows for gauge-coupling unification at high energies and predicts a stable particle that could address the problematics of Dark Matter.
Along these lines, the ATLAS and CMS collaborations have searched for Z bosons by investigating dilepton and dijet final states. In detail, by using high-mass dilepton data at  13  TeV, the ATLAS collaboration  [18]  set the mass exclusion limits M Z > 4. 5 TeV in the SSM and M Z > 3. 8-4. 1 TeV in U(1) models, whereas CMS obtained M Z > 4. 0 TeV (SSM) and M Z > 3. 5 TeV (GUT-inspired models)  [19]. For dijets, the limits are much milder and read M Z > 2. 1-2. 9 TeV (ATLAS)  [20]  and M Z > 2. 7 TeV (CMS)  [21]. In a UMSSM framework, the inclusion of the supersymmetric decay modes of the Z bosons may nonetheless change these conclusions  [22] [23] [24] [25] [26] [27]. Above all, the opening of new decay channels lowers the branching ratios into SM final states and therefore the Z mass exclusion limits.
In fact, Ref. [28]  found an impact of about 200 GeV on the mass exclusion limits by comparing the 8 TeV ATLAS and CMS data on high-mass dileptons with UMSSM predictions for a benchmark point of the parameter space. Furthermore, in the UMSSM, a leptophobic Z can yield the production of dilepton final states only through cascade decays into intermediate electroweakinos, which contrasts with the leptophobic non-supersymmetric case where this is simply not allowed  [29]. The bounds on the Zboson mass and production cross section derived from the above-mentioned searches should then be revisited when more general theoretical contexts like the UMSSM or leptophobia are considered. On different grounds, the hadronic environment at the LHC is so complex that new physics searches always rely on some simplifying assumptions in the form of the potential signals.
Supersymmetric Z Phenomenology In this section, we analyze the phenomenology of the two classes of UMSSM scenarios introduced in Section 2. 2. In the subsequent Section 4, specific configurations where the Z boson is leptophobic by virtue of the kinetic mixing of U (1) Y and U (1) are in contrast investigated. In order to apply the LHC constraints on the properties of Z bosons, we calculate the Z production cross section at next-to-leading order (NLO) accuracy in QCD  [52, 53]. This relies on the joint use of FeynRules version 2. 3. 27 [54]  and the included NLOCT package  [55] , as well as FeynArts  [56] , for the automatic generation of a UFO library  [57]  containing both tree-level and counterterm vertices necessary at NLO. This UFO model is then used by MadGraph5 aMC@NLO (version 2. 5.
5) [58]   g values and dilepton branching ratios for commonly studied U (1) models with UMSSM parameters satisfying the constraints detailed in subsection 2. 2. Quoted are g min , the minimum value of g (M Z ), along with the corresponding spread ∆g and the smallest possible branching ratio into leptons with (UMSSM) and without (USM) supersymmetric contributions to the Z decays. the hard-scattering matrix elements, which are convoluted with the NLO set of NNPDF 2. 3 parton distribution functions (PDF)  [59]. Using the decay table provided by the SPheno package and assuming the narrow-width approximation, we compare our predictions with the ATLAS limits on Z bosons in the dilepton mode  [18]  in order to estimate the impact of supersymmetric decay channels.
Overall, Z bosons lighter than 4 TeV are still strongly disfavored by ATLAS data, regardless of the U (1) model. In Fig. 2  (upper panel), we reexpress the same results by emphasizing the dependence of σB on the dilepton branching fraction, by superimposing the predictions of the different U (1) realizations, regardless of the actual θ E 6 mixing angle, and displaying the values of BR(Z → ll) by means of different colors. We find that the dilepton rate varies between 4% and 12%, and that the yielded exclusion masses are roughly between 4 and 4. 5 TeV. In the lower panel of Fig. 2 , we present instead the distribution of the allowed Zboson masses as a function of the E 6 mixing angle, with the value of the g coupling for each scenario indicated by a color code. In order to determine the allowed regions, we first impose the experimental constraints in Table  4  and then the exclusion limits coming from the direct comparison with the ATLAS data in Fig.
1. The points ruled out by the ATLAS results are shown in grey. We observe, similarly to the findings of Ref. [27] , that only |θ E 6 | values in the intervals [0, π/4] and [3/4π, π] can accommodate all the imposed experimental constraints. Outside of these regions, the U (1) charge of the extra singlet supermultiplet S is in fact close to zero so that either the SM-like Higgs boson or the Z boson, or even both, are predicted to be too light with respect to current data. In particular, Fig. 2  (lower panel) dictates that models U (1) χ and U (1) S are largely ruled out by the current data (see also the above discussion), while U (1) I is only marginally consistent. As a whole, after adding the recent ATLAS constraints  [18]  (the grey points), it turns out once again that scenarios exhibiting a Z boson lighter than 4 TeV can hardly ever be realized, the corresponding parameter-space regions getting more and more restricted.
Leptophobic Z Scenarios in UMSSM Models The results presented in the previous section have shown that the inclusion of supersymmetric decays has a substantial effect on the Z searches and exclusion limits, but nevertheless the ATLAS bounds originating from the dilepton channel strongly constrain any phenomenologically viable UMSSM realization. Furthermore, the very fact that the Z boson has to be quite heavy impacts all sfermion masses through the U (1) D-terms, which may even lead to discarding some scenarios, such as U (1) χ , as yielding unphysical sfermion spectra. All LHC constraints studied so far can, however, be evaded by enforcing the Z boson to be leptophobic. In these scenarios, resonance searches in the dijet final state become the main probes of the new boson, Run II results for the top-antitop mode including the analysis of the full 2016 dataset being still not available.
In Fig. 6 , we present the Z dilepton branching ratio, scanning the parameter space as presented in Section 2. 2, in terms of the mixing angle θ E 6 and sin χ. In agreement with Eq. (2. 11), we realize that values of sin χ around ±0. 3 can lead to leptophobia whenever the E 6 mixing angle obeys the condition in Eq. (2. 12) and the U (1) charges fulfill the relation QE ≈ QL ≈ 0. In particular, the condition BR(Z → l + l -) 0 can be achieved for -π < ∼ θ E 6 < ∼ -3π/4, which includes the U (1) η model, and for π/8 < ∼ θ E 6 < ∼ π/4, hence in the neighborhood of U (1) ψ. The other U (1) symmetries are either ruled by the experimental data or, even in the most optimistic case, can hardly lead to dilepton rates below 5%. Of course, these leptophobic scenarios cannot be constrained by standard Z -boson searches in dimuons or dielectrons at the LHC, and novel strategies must be designed.