dataesr/scientific-paragraphs-categorization huggingface dataset:
Unfolding of detector effects The measurement of the steeply falling jet transverse momentum spectrum is affected by the imperfect track reconstruction efficiency and finite track momentum resolution of the detector. The inference of the true spectrum from the smeared one, a process usually called unfolding, requires construction of a detector response matrix. The jet production yields are corrected by the unfolding method  [63] , as implemented in the RooUnfold package  [64]. A 2-dimensional detector response matrix maps the transverse momentum of particle-level charged jets clustered from stable charged particles produced by a MC event generator (p jet,particle T ) to the detector-level jets reconstructed from tracks after full GEANT3based detector simulation (p jet,detector T ). The entries of the response matrix are computed by matching particle-and detector-level jets geometrically, according to the distance d = ∆η 2 + ∆φ 2 between the jet axes.
No significant energy dependence nor change with collision species is observed for smaller radii. It should be noted, however, that the earlier ALICE measurements of cross section ratio used for comparison performed the UE subtraction. Since the UE contribution is more pronounced for larger radii (R = 0. 6), the cross section ratio σ (R = 0. 2)/σ (R = 0. 6) is higher after UE subtraction, and the UE subtracted cross section ratio is consistent to earlier measurements in pp collisions at √ s = 7 TeV as presented in Fig. 7  (right). Fig. 6 : Charged jet cross section ratios for σ (R = 0. 2)/σ (R = 0. 4) (Red) and σ (R = 0. 2)/σ (R = 0. 6)(Blue) in comparison with LO (PYTHIA) and NLO event generators with matched parton showers and modelling of hadronization and the UE (POWHEG+PYTHIA8). The systematic uncertainty of the cross section ratio is indicated by a shaded band drawn around data points.
Acknowledgements The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the  Worldwide LHC Computing Grid  (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the  ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL) ,  State Committee of Science and World Federation of Scientists  (WFS), Armenia;  Austrian Academy of Sciences, Austrian Science Fund (FWF) : [M  2467-N36 ] and  Nationalstiftung für Forschung ,  Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan ;  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ,  Universidade Federal do Rio Grande do Sul (UFRGS) ,  Financiadora de Estudos e Projetos (Finep)  and  Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Brazil; Ministry of Science & Technology of China (MSTC) ,  National Natural Science Foundation of China (NSFC)  and  Ministry of Education of China (MOEC) , China ;  Croatian Science Foundation and Ministry of Science and Education, Croatia ;  Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear  ( CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic ; The  Danish Council for Independent Research | Natural Sciences , the  Carlsberg Foundation  and  Danish National Research Foundation (DNRF) ,  Denmark ;  Helsinki Institute of Physics (HIP) ,  Finland ;  Commissariat à l'Energie Atomique (CEA) ,  Institut National de Physique Nucléaire et de Physique des Particules  ( IN2P3 ) and  Centre National de la Recherche Scientifique (CNRS)  and  Région des Pays de la Loire, France ;  Bundesministerium für Bildung und Forschung (BMBF)  and  GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany ;  General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece ;  National Research, Development and Innovation Office, Hungary; Department of Atomic Energy Government of India  (DAE),  Department of Science and Technology, Government of India (DST) ,  University Grants Commission, Government of India (UGC)  and.
Implementation and Computing Platform Our computing platform is a machine with Intel(R) Xeon(R) CPU E5-2620 v3 at 2. 40 GHz, 24 virtual cores, 128 GB RAM, and running Ubuntu Linux version 4. 4. 0-22-generic (machine available at Dipartimento di Informatica, Università di Pisa, Italy). The code has been written in Java, using Java 1. 8, for both of the competitors.
Dataset In order to perform our experiments, we used the following temporal graphs (other temporal networks will be considered in Section 5, in which we will perform a case study based on the directed public transport networks of 25 cities): A small subset of posts to another user's wall on Facebook. The nodes of the network are Facebook users, and each directed temporal edge represents one post, linking the users writing a post to the user whose wall the post is written on  [28] [29] [30].
We have grouped the 25 cities into five groups according to the vale of R. In particular, group i contains all the cities such that 10(i -1) < R ≤ 10i, for 1 ≤ i ≤ 5. Our goal is to analyze the reachability efficacy of each public transport network. To this aim, we compute the (approximate) value of the temporal neighborhood functions corresponding to different time intervals of the day in which the data were collected. In particular, we divide the interval between 6:00 a. m. and 9:00 p. m. into 30, 15, and 10 intervals of length 30, 60, and 90 min, respectively. For each interval I = [t α , t ω ], we compute the approximate value of the temporal neighborhood function |N (I)| (normalized with respect to the number of all possible pairs of nodes), by using the ATNF algorithm. In the following, we will represent the distributions of these values by reachability diagrams such as the one shown in Figure  5 , which refers to the city of Adelaide.
Observe that, in the case of transport networks, going from one stop to another, i. e. , following an edge, takes some time. Therefore, in our dataset, the temporal edge list contains the starting time s e and the arrival time a e of each temporal edge e between two nodes u and v. In order to apply our approach, we have used the following transformation. For each edge e in the dataset from u to v with starting time s e and arrival time a e , with a es e > 1, we have replaced e with a pair of two edges: one from u to z e with appearing time s e , and the other from z e to v with appearing time a e -1, where z e is a new dummy node. For the edges e from u to v in the dataset such that a es e = 1, we replace e by an edge from u to v with appearing time s e. It is easy to show that there is a one-to-one correspondence between the feasible journeys in the original dataset and the sequences induced by the non-dummy nodes in the temporal paths of the resulting temporal graph.
Moreover, it is worth remarking that, when computing the temporal neighborhood function in our transformed temporal graph, we have to focus only on non-dummy nodes. To this aim, we have slightly modified our approach in order to exclude the dummy nodes from the sketches of our reverse temporal cones and, hence, not to count them in the final estimation of the temporal neighborhood function. In particular, to do this, in the base case in Section 3, it is enough to exclude u from R(u, [t α , t α ]), whenever u is a dummy node. Table  6. The 25 cities included in the public transport network dataset  [14]. The Stops column indicates the number of nodes, the Edges column the number of temporal edges, the Day column the day in which the data were collected, the R column the city's radius (in km), and the G column the group the city belongs to.
A meta-analysis of data from these three RCTs  [5]  has shown higher pregnancy rates following thawed frozen embryo transfer (odds ratio 1. 32, 95% CI 1. 10 to 1. 59). However, these existing trials have a number of significant limitations: They reported implausibly high pregnancy rates (e. g. 84% per embryo transfer), which are far in excess of those reported by national and international registries. Key outcomes including healthy baby, live birth, costs, safety and acceptability were not measured by any of the trials. They were limited in terms of design with highly selected populations, inadequate sample sizes and per protocol analysis rather than by intention-totreat and conduct, since all involved cointerventions which were not accounted for in the analysis. One of the publications  [2]  has been retracted on the grounds of serious methodological flaws.
A single episode of thawed frozen embryo transfer (after elective freezing of embryos) will be compared to a single episode of fresh embryo transfer with a healthy baby (defined as a live singleton baby born at term with an appropriate weight for gestation)the primary outcome. With 90% power and a two-sided 5% level of statistical significance, we will need to randomise 1086 couples (543 in each arm) to show an absolute difference in the primary outcome of at least 9% (e. g. from 25 to 34%), between fresh and thawed frozen embryo transfer respectively. A full economic evaluation will assess the costs and consequences of the new strategy compared with standard practice. The trial data will be combined with modelling to estimate the long-term costs of health and social care using a previously developed decision analytic model.
After consent, couples will each fill in a short questionnaire on how they are feeling emotionally. Each participant will seal their questionnaire in an envelope after completion and questionnaires will be destroyed unopened if the couple do not proceed to randomisation. Data needed for randomisation/minimisation will be recorded by the consent and randomisation program. On the first day after egg collection the embryologist or research delegate will confirm consent during a routine phone call to the couple to discuss the outcome of fertilisation. On the third day after egg collection couples with at least three good quality embryos will be randomised by the embryologist or research nurse to fresh or thawed frozen embryo transfer. Good quality embryos on day three are defined as those with 6-8 cells grade 3/3 or above using the agreed national grading scheme  [6].
Outcomes presenting themselves >six weeks post-delivery will not be recorded. All women who conceive by IVF/ICSI are followed up by their IVF centres routinely, as there is a mandatory requirement to report early pregnancy outcomes as well as delivery outcomes to the regulatory body, the Human Fertilisation Embryology Authority (HFEA), including stillbirth, congenital anomalies and perinatal mortality. Usually this information is provided to each IVF clinic by couples themselves. Alternatively, clinic staff contact couples by telephone to collect this information to report it back to the HFEA. The participant pathway and data collection points are shown in the Study Matrix (Fig. 2 ).
Ineligible and non-recruited participants Details of all consenting couples will be entered on a dedicated secure online database. It is anticipated that a proportion of those consented may not proceed to randomisation; the reasons for this will be recorded (if available) including non-availability of three good quality embryos on day three. As part of routine practice, the embryologist contacts the couple by telephone to let them know how many eggs are fertilised (next day after egg collection, day one) and the quality of their embryos (on day three after egg collection). The embryologist or research delegate will confirm consent on day one and inform them whether or not they fulfilled the final inclusion criteria (at least three good quality embryos on day three) and which arm they have been randomised to at the time of their routine phone call on day three.
Withdrawal procedures Couples will be able to withdraw their consent to take part in the trial at any time without giving a reason. Withdrawal from the intervention/study will not affect their ongoing care. Non-adherence to the allocated intervention may also occur; this is defined as a difference between the treatment allocation provided at randomisation and the allocation received by the woman at the time of embryo transfer. Non-adherence to the allocated intervention may occur if the clinician feels it is in the couple's best interests, e. g. freezing all created embryos is necessary for medical reasons, or transferring fresh embryos for clinical reasons. In the case of a non-adherence to the allocated intervention, the couple, with their on-going consent, would continue to be part of the trial, with outcome data collected in the routine manner.
Safety reporting Foreseeable serious adverse events (SAEs) are those events which are expected in the patient population or as a result of the routine care/treatment of a patient. Foreseeable SAEs will be collected on the electronic Case Report Form (eCRF) as part of routine data collection. The following events are foreseeable in women or couples undergoing IVF treatment and as such do not require reporting as SAEs. Foreseeable events relating to the female partner, or couple: Ovarian hyperstimulation syndrome (OHSS) Miscarriage Hypertensive disorders of pregnancy Antepartum haemorrhage Gestational diabetes mellitus (GDM) Multiple pregnancy Failure of any embryos to survive thawing Foreseeable events relating to the baby, when born:.
Economic evaluation A formal economic evaluation will be undertaken to assess the cost effectiveness of the alternative approaches to treatment used in the trial. Resource use and costs will be estimated primarily from a health and personal social services perspective. However, personal time and travel costs, associated with any additional treatment-related visits which are not part of standard routine practice, will also be estimated via a short questionnaire administered at the time of embryo transfer. This is to be completed by both partners. In addition, longer-term social costs associated with child health outcomes will be modelled based on existing literature. Trial data collection instruments (eCRFs) will be used to capture participant level resource use associated with treatment, up to the trial end points of delivery or failure to become pregnant following the initial transfer.
Trial Management The trial co-ordinating centre will be at the NPEU CTU, University of Oxford, where the Trial Manager will be based. The NPEU CTU will be responsible for trial oversight, IT system/functions such as randomisation, clinical and administrative databases, all programming and statistical analyses, servicing both the DMC and TSC, and, in collaboration with the Chief Investigator and the Local Research Nurse for the general day-to-day running of the study including recruitment of sites and training of staff. A 24/7 (365 days a year) emergency helpline is available for out-of-hours queries relating to the trial. The economic analysis will be conducted at the University of Aberdeen.
Confidentiality, data protection and data management Direct access to source data/documents (including hospital records/notes, clinical charts, laboratory reports, pharmacy records and test reports) will be granted to authorised representatives from the NPEU CTU, the Sponsor and host organisations to permit study related monitoring, audits and inspections. Overall responsibility for ensuring that each participant's information is kept confidential will lie with the study Sponsor who has delegated this responsibility to the NPEU CTU. All paper documents will be stored securely and kept in strict confidence in compliance with the Data Protection Act (2018). Data entered onto the eCRFs will be automatically transferred for storage in an electronic database hosted by NPEU CTU on behalf of the Sponsor, in which the participant will be identified only by a study specific number.
The participant's name and any other identifying details will be stored in a separate database also held by NPEU CTU on behalf of the Sponsor which will be linked to the database containing study data only by the participant's study number. After the study has been completed and the reports published, the data will be archived. Electronic and paper documents will be archived by the NPEU using their secure archiving facilities, as detailed in NPEU Standard Operating Procedures. Electronic files will be stored on a file server that has restricted access. The server is in a secure location and access is restricted to a few named individuals. Access to the building in which the NPEU CTU is situated is via an electronic tag and individual rooms are kept locked when unoccupied. Authorisation to access restricted areas of the NPEU CTU network is as described in the NPEU CTU security policy.
Availability of data and materials Applications for data sharing should be made to the NPEU CTU, using ctu@npeu. ox. ac. uk, with an accompanying protocol for the intended use of the data. This will be reviewed by the Trial Steering Committee if still operational or Data Sharing Committee/Data Controller. If approved, a Data Sharing Agreement will be compiled laying out the conditions to which the requestor must abide. Protocol E-Freeze Protocol, Version 2. 0 (18/01/2017).
Measurement and Presentation of Transient Local Structures As mentioned above, our goal is to relate the biological functions of tau40 and MAP2c to transient secondary structures observable in a free state. Therefore, we start our discussion by briefly commenting how the structural data were obtained, and how they are presented in this paper. So-called intrinsically disordered proteins (IDPs), including tau40 and MAP2c, do not adopt a random conformation as many synthetic polymers. Instead, they exist in multiple rapidly inter-converting structures defined by the same interactions as well-ordered proteins. Therefore, transient secondary structure motifs and long-range order are present in IDP samples, and their populations can be estimated by analyzing experimental data. Formation of transient local structures discussed in this paper was inferred from NMR chemical shifts, measured in several studies  [38, 40, [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] , and converted to populations of conformers occupying different regions of the Ramachandran diagram by the ASTEROIDS algorithm  [39, 56, 57].
Thus, ensuring and maintaining the thermal comfort inside the vehicle is one of the most important challenges for the researchers, designers and manufactures in the automotive industry. The actual standard which, is proposing comfort evaluation methods for vehicles environment is ISO 14505  [9] [10] [11]  standard "Evaluation of thermal environments in vehicles" being structured into three parts: 1. Principles and methods for assessment of thermal stress  [9] ; 2. Equivalent temperature determination  [10] ; 3. Evaluation of thermal comfort by the human subjects  [11]. In the first part of the above-mentioned standard, is presented a comfort evaluation method based on the PMV and PPD model developed in the 1970 professor Fanger  [12]. This comfort evaluation model was developed using data collected from human subjects evaluated in controlled laboratory conditions.
Methods Altimetry dataset. The SSALTO/DUACS delay-time altimetry product provided by AVISO is used here (issue 5. 0 updated 2016/08/20). This multiple-satellitemerged data contains global gridded daily sea surface height, sea level anomaly, sea surface geostrophic velocity anomaly (u g , v g ) with a ¼ degree resolution from year 1993 to 2016. Surface drifter data. The drifter data used here is provided by the Drifter Data Assembly Center (DAC) of National Oceanic and Atmospheric Administration. The DAC assemble and provide uniform quality control of sea surface temperature (SST) and surface velocity by satellite-tracked surface drifting buoy observations. The surface velocity (u, v) and SST T measurements are provided for every 6 h from year 1993 to 2011. They have a global coverage and contain a total of 22,249,337 observational data points.
Data availability The altimeter data can be accessed form website: https://www. aviso. altimetry. fr/en/data/ products/sea-surface-height-products/global/gridded-sea-level-heights-and-derivedvariables. html. The surface drifter dataset can be downloaded from the website: ftp://ftp. aoml. noaa. gov/phod/pub/buoydata. The chlorophyll data can be accessed from website: http://hermes. acri. fr/index. php?class=archive. The source data underlying Figs. 1  and  2, 4-7 and Supplementary Figs. 1-4 are provided as Source Data file.
Clonal diversity Clonal relationship of the isolates was evaluated by pulsed-field gel electrophoresis (PFGE)  [15]. Total DNA from Escherichia coli, Klebsiella pneumoniae and Enterobacter spp. were digested using the XbaI enzyme (New England Biolabs, Ipswich, MA, USA). The generated fragments were separated by PFGE using a CHEF-DR III System (Bio-Rad) creating a unique PFGE profile for each clonal strain. Multilocus sequencing typing was performed for pan-drug aminoglycoside-resistant strains belonging to the species E. coli (strain no. 31) and K. pneumoniae (strain no. 62)  [16]. Sequence types (STs) were investigated using the online databases (http://genomicepidemiology. org/).
The plot suggests that, for the values of the charged-Higgs mass allowed in this scenario by the constraints on the neutral sector (say, M H ± 600 GeV) and intermediate values of tan β, the rates for top-associated production of H ± followed by decays to EW-inos are comparable to those recently probed by ATLAS in the τ ν channel with 36 fb -1 of Run-2 data  [154]. Even considering the complications in the reconstruction of the subsequent EW-ino decays, we believe that a study of this scenario with the full Run-2 dataset would be well motivated. In summary, as was discussed e. g. in Refs. [15, [228] [229] [230] , the presence of light EW-inos in the M 125 h ( χ) scenario lowers the sensitivity of the traditional searches for heavy Higgs bosons decaying to pairs of SM particles, especially in the region with intermediate tan β, but opens up the possibility to probe the same region through the Higgs decays to SUSY particles.
Acknowledgments This work was initiated in the context of the activities of the  LHC-HXSWG , and some of our findings were presented in a preliminary form at recent meetings of the group. We thank  F. Staub  for his help concerning the usage of Vevacious,  L. Shang  for communications about CheckMATE, and  F. Domingo ,  S. Paßehr  and  J. Wittbrodt  for helpful discussions. E. F. is supported by the  Minerva foundation. The work of S. H. is supported in part by the  MEINCOP Spain  under contract  FPA2016-78022-P , in part by the  Spanish "Agencia Estatal de Investigación" (AEI)  and the  EU "Fondo Europeo de Desarrollo Regional" (FEDER)  through the project  FPA2016-78022-P , and in part by the  AEI  through the grant  IFT Centro de Excelencia Severo Ochoa   SEV-2016-0597. The work of P. S.
is supported in part by the  French "Agence Nationale de la Recherche" (ANR) , in the context of the  LABEX ILP  ( ANR-11-IDEX-0004-02 ,  ANR-10-LABX-63 ) and of the grant " HiggsAutomator " ( ANR-15-CE31-0002 ). P. S. also acknowledges support by the  Research Executive Agency (REA)  of the  European Commission  under the  Initial Training Network "HiggsTools"  ( PITN-GA-2012-316704 ) and by the  European Research Council (ERC)  under the  Advanced Grant "Higgs@LHC"  ( ERC-2012-ADG 20120216-321133 ). T. S. acknowledges support from the  DESY   Fellowship programme. The work of C. W. at  University of Chicago  is supported in part by  U. S. Department of Energy  grant number  DE-FG02-13ER41958 , and his work at  ANL  is supported in part by the  U. S. Department of Energy  under Contract No.