dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analyses Data were summarized descriptively by mean, standard deviation, median and range (minimum, maximum) for continuous data or by frequencies and percentages for categorical data, using SAS â version 9. 3 (SAS Institute, Cary, NC, USA). All PCT-PLT transfusions administered to a patient were included in the full analysis population, and data were summarized on a per-transfusion basis and a per-patient basis. P values for ATR and SAE rates were calculated utilizing the two-sided Fisher's exact test. The primary assessment of safety was the proportion of PCT-PLT transfusions associated with an ATR. Additionally, patient demographics, primary indication for transfusion, the number of PCT-PLT transfusions received, the characteristics of the PCT-PLT transfused, the AEs reported and the time to first reaction were summarized to characterize the safety profile of PCT-PLT.
Discussion This active HV programme prospectively monitored routine transfusions of 19 175 PCT-PLT components into 4067 recipients. Only 94 patients (2Á3%) experienced an ATR during the study (Table  5 ). On a per-transfusion basis, 123 transfusions (0Á6%) were associated with ATRs (Table  5 ). The active design of this HV programme stipulated that all transfusions were evaluated, allowing for a greater amount of clinical data to be collected for a large patient population. This approach facilitates the detection of unexpected or low-grade AEs. There are several published reports on the frequency of ATRs for conventional PLTs that can be used as a comparison to determine whether use of PCT-PLTs is associated with an increased risk. Concurrent to this PCT-PLT HV programme, independent national HV programmes in France and Switzerland documented their experience with PLT transfusions  [24].
Acknowledgements F Knutson ,  J Osselaer ,  L Pierelli ,  M Lozano ,  J Cid ,  R Tardivel ,  O Garraud ,  T Hervig ,  D Domanovic ,  M Cukjati ,  S Gudmundson ,  IB Hjalmarsdottir ,  A Castrillo ,  R Gonzalez ,  D Brihante ,  M Santos ,  P Schlenke  and  L Corash  contributed to study design and data acquisition. A Elliott,  J Lin ,  D Tappe ,  A Stassinopoulos ,  J Green  and  L Corash  contributed to the analysis and interpretation of the data. J Green  drafted the manuscript. All authors critically evaluated and revised the manuscript and approved the submitted version. A Elliott ,  J Lin ,  D Tappe ,  A Stassinopoulos ,  J Green  and  L Corash  are employees and own stock or stock options of  Cerus Corporation. M Lozano  received research grants from  Cerus Corporation. J Osselaer  and  O Garraud  have served on Cerus's European Scientific Advisory Board.
Data extraction and management Two of us (VP, CVR), working independently, used a standardised data collection form to extract data from each selected study. The data collection form was first tested on three studies and was modified by an iterative process involving discussion between the authors. The following data were extracted from each study: study identification, study design and general characteristics, study population, inclusion and exclusion criteria, settings, summary details of the index test (i. e. sign) used to detect G-PLE, reference standards, flow of patients, data for the construction of 2 x 2 contingency tables for G-PLE outcomes for the various diagnostic tools evaluated and QUADAS judgments. We assessed the methodological quality of all the included studies. We classified the risk of bias and applicability as "low", "unclear", or "high" with the QUADAS 2 tool (Quality Assessment of Diagnostic Accuracy Studies)  [24] , and disagreements between reviewers were resolved by discussion to reach a consensus.
The use of diagnostic ultrasonography for gynaecological emergency diagnosis has greatly increased over the last 20 years. However, survey data suggest that, in many healthcare settings, and particularly in the United Kingdom, emergency access to ultrasonography is still unreliable. This problem concerns women who are not pregnant in particular, because women with early pregnancy problems are seen exclusively in stand-alone units with immediate access to ultrasound  [49]. Women with acute pelvic pain should be examined by ultrasound whether or not they pregnant. It has been shown that the availability of transvaginal ultrasound at the initial assessment of both pregnant and non-pregnant women decreases time to patient management, unnecessary admissions and outpatient follow-up examinations, and modifies treatment decisions  [79, 80].
Spectroelectrochemistry Spectroelectrochemistry (SEC) measurements were carried out on the four porphyrins 1-4, to obtain the absorption spectra and establish the stabilities of their oxidised and reduced species. Absorption measurements of the oxidised and reduced species for all porphyrins are listed in Table  3. Apart from our published study,  7  there is only one study on the parent porphyrins using a thin-layer SEC cell and two spectroscopic studies on porphyrin radical anions generated electrochemically. The reported data from these studies are shown in Table  3  for comparison.
Computations All computations were carried out with the Gaussian 09 package. 39 The four model S 0 geometries 1′-4′ with no symmetry constraints were fully optimised with the B3LYP functional 40 using the 3-21G* basis set 41 for all atoms. Frequency calculations on these geometries revealed no imaginary frequencies. Computed absorption data were obtained from TD-DFT  42  calculations on S 0 geometries using the CAM-B3LYP functional. 43 As the CAM-B3LYP functional generally overestimates the transition energies, compared to that of experimental and B3LYP data, a scaling factor of 0. 85 was applied. 44 The MO diagrams were generated with the Gabedit package  45  and the %MO contributions were obtained using the GaussSum software. 46.
Acknowledgements We thank " Re'gion Bretagne " (ARED; A. M. ),  China Scholarship Council  (CSC; D. Y. and X. Z. ), MENRT (S. D. ) and  EPSRC  (J. A. G. W. and M. A. F. ) for funding. We also thank  CNRS  and  Durham University  for supporting the Rennes-Durham collaboration.
As a result, the evolution through time of monsoon systems and its correlation with the tectonic evolution of Asia are becoming better known. However, this does not hold true for our knowledge of the impact on resident faunas. Although drastic evolutionary responses may be expected for species living under monsoon-driven climatic conditions, no supporting data using phylogenetically constrained species-level information from the fossil record have been offered. By comparing rates of biodiversity change for a group of mammals studied by means of cladistic analyses, it is possible to calculate the rates of taxonomic turnover, which will allow inferences concerning the times of biodiversity crisis (net loss of biodiversity) and their causes (extinction or speciation decline) 5. The growing knowledge of the fossil record and the growth of phylogenetic information coupled with biogeographic and evolutionary rate studies allow more detailed studies of the coevolution of the Earth and its biota 6.
Cladistic analysis. The calculation of speciation rates and the assessment of speciation patterns require a detailed knowledge of the temporal framework and phylogenetic relationships of the considered taxa. This kind of information is supplied by cladograms calibrated in time (stratocladograms) in which the operational taxonomic units are species  5. The evolutionary relationships of rhizomyine rodents have been studied in detail by Lopez-Anton ˜anzas et al. 64. The analyses of the evolutionary rates and paleobiogeography of rhizomyines that we present in this work build upon the character/taxon matrix from therein. As running that data matrix produced several trees  64  and there is evidence of the improvement of phylogenetical analyses of morphological datasets when applying implied weighting  70  , we have downweighted characters according to their homoplasy.
The matrix has been processed with the phylogenetic reconstruction software TNT  71  under weak implied weighting with a concavity value of 8 (k 5 8). Branch support was estimated through two complementary indices: Bremer Support 72 and Relative Bremer Support  73. The resultant cladogram (Supplementary Figure  1 ) has been chronostratigraphically calibrated as a ''stratocladogram'' (Fig. 1 ), in which the chronostratigraphic range of any given taxon in the fossil record is completed backward to its origin according to the tree topology. Rhizomyine species range from Late Oligocene to present. This time span has been subdivided into 13 temporal intervals following the international chronostratigraphic chart of 2013  74  , from which numerical ages are taken. Speciation mode determination. Species level phylogenies are a key source of explanation for fossil record biogeographic patterns  75, 76.
Acknowledgments We deeply acknowledge  P. Molnar  ( Cooperative Institute for Research in Environmental Science, Boulder, USA ) for his interest and commitment in enhancing this work through careful, critical reading,  B. S. Lieberman  ( University of Kansas, Lawrence, USA ) for having kindly answering all our enquires and  P. Donoghue  ( University of Bristol, Bristol ) for general advice and stimulating discussions. M. Maslin  ( University College London, London ) nicely improved a previous version of this paper. The numerous curators and researchers who assisted in providing access or loan of rhizomyine specimens or helped in any other way are duly acknowledged in Lopez-Anton ˜anzas et al. R. L. A. and F. K. are supported by the  European Union Marie Curie Actions  ( PIEF-GA-2013-623352  and  PIEF-GA-2013-624969 , respectively).
The determination of track reconstruction efficiencies at LHCb using J/ψ → µ + µ - decays is presented. Efficiencies above 95% are found for the data taking periods in 2010, 2011, and 2012. The ratio of the track reconstruction efficiency of muons in data and simulation is compatible with unity and measured with an uncertainty of 0. 8 % for data taking in 2010, and at a precision of 0. 4 % for data taking in 2011 and 2012. For hadrons an additional 1. 4 % uncertainty due to material interactions is assumed. This result is crucial for accurate cross section and branching fraction measurements in LHCb.
The purity of the sample is enhanced by selecting J/ψ from b-hadron decays. The tag track is fully reconstructed and is well identified as a muon. The probe track is only partially reconstructed, not using information from at least one subdetector which is probed. The track reconstruction efficiency is determined by checking for the existence of a fully reconstructed track corresponding to the probe track as this allows to determine the efficiency of the subdetector that is not used in the reconstruction of the probe track. It is calculated as a function of the momentum of the probe track, p, its pseudorapidity, η, and the track multiplicity of the event, N track. These are chosen because the efficiency is most affected by them. No strong dependence on the polar angle φ is observed. The main result of this paper is the track reconstruction efficiency ratio between data and simulation for prompt tracks and tracks from B and D mesons.
This ratio is used in physics analyses to correct the track reconstruction efficiency in simulated events and to determine its uncertainty. The measurement is performed on several data samples to meet the requirements of the analyses performed at LHCb. In this paper, the results are presented for the three data samples from run I, corresponding to different running conditions, proton-proton (pp) centre-of-mass energies and integrated luminosities: data taken in 2010 at √ s = 7 TeV corresponding to 29 pb -1 , data taken in 2011 at √ s = 7 TeV corresponding to 1 fb -1 , and data taken in 2012 at √ s = 8 TeV corresponding to 2 fb -1. The 2010 results are valid for the full 2010 data set, corresponding to a luminosity of 37 pb -1 , since the same running conditions and track reconstruction were used throughout this period.
The polarity of the dipole magnet is reversed periodically throughout data taking. The configuration with the magnetic field vertically upwards (downwards), bends positively (negatively) charged particles in the horizontal plane towards the centre of the LHC. Different types of charged hadrons are distinguished using information from two ring-imaging Cherenkov detectors, RICH1 and RICH2. Photon, electron, and hadron candidates are identified by a calorimeter system consisting of scintillating-pad and preshower detectors, an electromagnetic calorimeter, and a hadronic calorimeter. Muons are identified by a system composed of alternating layers of iron and multiwire proportional chambers  [8]. The trigger  [9]  consists of a hardware stage, based on information from the calorimeter and muon systems, followed by a software stage, which applies a full event reconstruction.
The hit efficiencies have been measured in data using tracks. For the different subdetectors, they range from 98-100%. Dead channels are included in the simulation, using an average over the data taking period. From simulations it is known that the (high) hit efficiency does not have any impact on the track reconstruction, as the algorithms have been written to be robust against small hit inefficiencies. The size of the sensitive detector elements are known very accurately and the positioning of the sensitive elements in the simulation is accurate at the level of 0. 5 mm. Compared to the overall size of the tracking system, any inaccuracy at this level has negligible impact on the acceptance of the detector.
Efficiency dependencies Using the momentum spectrum of the J/ψ decay products obtained with the VELO method from data as a benchmark, the average track reconstruction efficiency for long tracks is measured to be (95. 4 ± 0. 7)% for 2010 data, (97. 78 ± 0. 07)% for 2011 data and (96. 99 ± 0. 05)% for 2012 data. All results confirm the good performance of the LHCb tracking system. The uncertainties on these numbers are statistical only; they are binomial errors with additional terms to account for the statistical uncertainty on the number of background events. Systematic uncertainties are discussed in Sect. 8. The difference in the efficiencies between the three years is a consequence of changes in the track reconstruction and the higher centre-of-mass energy, leading to a higher track multiplicity and hence lower reconstruction efficiency for the 2012 running period.
For the final result, the weighted average of the combined and long method is taken in each bin of p and η. Figure  7  shows the efficiency ratio versus p for run I, weighted by the event track multiplicity observed in data; the data are split into two ranges of η. Overall a good agreement of the track finding efficiency is found between events in simulation and in data for all data taking periods and most momenta and pseudorapidity regions. The difference between the track finding efficiencies is generally smaller than 1% between events from simulation and data and no trend can be observed for the 2011 and 2012 dataset, with the number of events being too low to draw conclusions from the 2010 dataset. The agreement is worse for tracks with momentum below 10 GeV/c, which might point to a less accurate modelling of multiple scattering effects in the simulation.
Acknowledgements We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from  CERN  and from the national agencies:  CAPES ,  CNPq ,  FAPERJ , and  FINEP (Brazil) ;  NSFC (China) ;  CNRS/IN2P3  (France);  BMBF ,  DFG ,  HGF , and  MPG (Germany) ;  SFI (Ireland) ;  INFN (Italy) ;  FOM  and  NWO  (The Netherlands);  MNiSW  and  NCN (Poland) ;  MEN/IFA (Romania) ;  MinES  and  FANO (Russia) ;  MinECo (Spain) ;  SNSF  and  SER (Switzerland) ;  NASU (Ukraine) ;  STFC  ( United Kingdom );  NSF (USA). The Tier1 computing centres are supported by  IN2P3 (France) ,  KIT  and  BMBF (Germany) ,  INFN (Italy) ,  NWO  and SURF (The Netherlands),  PIC (Spain) ,  GridPP  ( United Kingdom ).
genetic counseling and patient management as new therapeutic options are being assessed in clinical trials (TTR gene silencing). ANN NEUROL 2015;78:901-916 F amilial transthyretin amyloid polyneuropathies (TTR-FAP) are severe high-penetrance autosomal dominant polyneuropathies that are generally fatal within a decade without treatment. They are due to polyvisceral deposits of amyloidogenic transthyretin (TTR) protein, predominating in the endoneurial space of peripheral nerves, heart, bowel, and urogenital tract. Pathological studies of TTR-FAP peripheral nerves show amyloid deposits in endoneurial spaces and axonal degeneration, especially in the distal portion. 1  TTR is a protein mostly secreted by the liver. The TTR gene (Online Mendelian Inheritance in Man database 176300) located in chromosome region 18q11.
Clinical Neurological Assessment The time between symptom onset and the first neurological examination was assessed, along with the initial symptoms and course of neuropathy. Clinical data consisted of: Age at onset. Weight loss and pain at initial examination. Personal history of carpal tunnel syndrome (CTS) in patients with nerve conduction study fulfilling the American Association of Electrodiagnostic Medicine criteria for CTS. 18, 19 amily history of neuropathy or TTR-amyloidosis in at least 1 member of the kindred. Two functional questionnaires assessing sensorimotor disability in the 4 limbs, namely the modified Norris test (MNT; best maximum 5 75)  20  and the polyneuropathy disability (PND) score for walking capacity. 21 ight touch, pinprick, vibratory, joint position sense, and temperature sensation at 4 8C and 40 8C to explore all sensory modalities.
Literature Review The NIH PubMed database was scanned for reports in English containing detailed clinical descriptions and mutation analysis up to June 2015. Cases purported to be TTR-FAP but with no available DNA analysis or biopsy were discarded, as were case series linked to Val30Met mutation without individualized late and early onset groups. Authors of reports on Japanese and French cases were contacted directly for further information (Haruki Koike and Gen Sobue; Guillaume Nicolas). All reviewed reports are listed in Supplementary Table  2.
First optimization (performed on all enzymes) Second optimization Optimal H 2 concentration (mM) In the first stage optimization all the enzymes are modified on the initial concentration (E 0 ). The modifications are evaluated in order to obtain the best hydrogen final concentration (mM) from E0 modifications. Next, the optimized value for E 0 was integrated in the system for a second optimization round on another optimization parameter, K m or λ. Simulations of 9000 min were executed with starting concentrations of 70mM for cellobiose, 70mM for phosphate and 1mM for NADP. Percentages between parentheses are with respect to maximum theoretical H 2 concentration that could be achieved. Initial number experiments available for the construction of the initial dataset. The size of dataset must be large enough to build an ANN model.
If the size is too small, ANN method is not relevant. After validation, ANN model allows to predict the value of output vectors from a set of input vectors. System predictions from ANN method are the most valid and relevant in the system conditions encountered in the initial dataset. Prediction from of out-of-the-box conditions must be subject to caution. The more the distance between the conditions of the dataset and the out-of-the-box conditions, the higher is the probability to have inaccurate and even false predictions. Here we explored the use of ANN to model cell-free systems. Our aim is to validate its application for modeling output of cell-free systems knowing only the starting state of the system. Artificial neural network is a computational model based on biological neural networks.
The model structure is similar to the structure of the biological neural networks with the presence of computational units interconnected between them. One computational unit is assimilated to a formal neuron. A formal neuron can receive one or several input signals. The neuron treats the weighted summation of input signals to produce an output signal by the action of an activation function. Artificial neural network have a learning phase to identify a model with the adequate weights so that the model outputs match the system output. Because they can approximate nonlinear functions between inputs and outputs from incomplete databases and with specific accuracy, ANNs are now commonly used to model complex systems. The construction of an ANN model is achieved following four classical steps: (i) building of a database, (ii) determining model structure, (iii) fitting parameters and (iv) validating model.
Each of these steps is detailed below. In first instance, the knowledge-based model, as described in the previous section, was used to generate a database of hydrogen production trajectories that were simulated with different sets of starting conditions for the system. The starting conditions for the simulations, i. e the initial concentrations of the 13 enzymes and 3 substrates (NADP, cellobiose and inorganic phosphate), served as inputs for the ANN while the observed initial rate of hydrogen production at t=0 min and final hydrogen concentration reached at the end of the simulations served as outputs for the ANN. These inputs were chosen because they can be realistically set up experimentally. To constitute the database, initial values for the different simulation runs were varied between the following ranges: between 5 and 20 U/mL for enzyme concentration, between 0.
5 and 2 mM for NADP concentration and between 35 and 140 mM for both cellobiose and inorganic phosphate concentrations. The database comprised four distinct datasets. These are further detailed below. A first very large dataset, hereby called "Base zero", was constituted for the purpose of evaluating whether ANN can indeed be used and to build a model that can account for the rate of H 2 production and for the final level of H 2 in the system. The starting conditions that were used to build this dataset consisted in setting two possible values for each the 16 inputs and generating all possible combinations of these starting values, hence making a total of 2 16 =65,536 starting conditions. Starting enzyme concentrations were set to 5 and 20 U/mL, NADP concentrations to 0. 5 and 2 mM and for both cellobiose and phosphate to 35 and 140 mM.
After validating the use of ANN to model both production rate and final concentrations using "Base zero" dataset, we investigated whether smaller training datasets could generate efficient ANN models. Hence, two smaller datasets, hereby called "Base A" and "Base B" were constituted for that purpose. "BaseA" dataset comprises The model was conceptualized under the SBML format (Systems Biology Markup Language) that is a standard to represent biochemical networks  [10]. Cell Designer and Copasi are software tools used for the model implementation in SBML format. The resolution of ODE was performed by the SBML ODE Solver Library or Copasi ODE solver.