dataesr/scientific-paragraphs-categorization huggingface dataset:
The PK data were well described using a two compartmental model (central and peripheral distribution volume). Body weight was retained as a covariate to explain the volumes, including sex-specific reference weights, but age was not retained as a covariate in the model. An evaluation of the PK data from JNJ-56136379 indicated that the initial population PK model (using the same approach for body weight and the same parameters) generally well described the JNJ-56136379 concentrations observed in this study for both the 75 mg and 250 mg doses in the initial and extension treatment phases. No additional effects of race (Asian vs non-Asian) were observed. Comparing plasma concentrations and PK parameters between the JNJ-56136379 monotherapy arms and combination arms with an NA, a PK drug-drug interaction between TDF and JNJ-56136379 was apparent.
Acknowledgements The authors would like to thank the patients and their families, the study investigators and site staff and all the members of the  JNJ-56136379 Compound Development and Operations Teams  for conducting this study and other  Janssen  staff members for their important contributions to the manuscript. Medical writing support for the development of this manuscript was provided by  Ian Woolveridge of Ashfield MedComms , an  Ashfield Health company , and  Jessica Swanner, PhD , of  Lumanity Communications Inc. , and was funded by  Janssen. Merck and  Roche. RGN has received grant/clinical research support from  Janssen ,  Assembly ,  AbbVie ,  Alkermes ,  Gilead Sciences ,  Merck  and  ViiV , and has participated in speaker panels for  Gilead Sciences, Merck, Insemed and ViiV. SB has participated in advisory committees or review panels for  AbbVie ,  Gilead Sciences  and  Merck , and has received speaking and teaching support from  AbbVie ,  Bristol Myers Squibb and Gilead Sciences.
Experimental Procedure 2. 2. 1. Reading Tasks A one-minute word reading test was performed to assess the efficiency of the orthographic reading procedure. It consisted of 120 bisyllabic words presented on a printed sheet containing six words per line. The words were between four and nine letters in length (mean = 6. 4; sd = 1. 29), were of low to high frequency (mean = 28. 6; sd = 43. 4) and were selected using the lexique. org database  [103]. Participants were instructed to read the written words aloud as fast and accurately as possible within a 1 min time limit. An efficiency score that took account of both accuracy (A) and reading time (RdT): (A × 60)/RdT was then calculated for each participant individually. A two-minute pseudoword reading test was also administered to assess the efficiency of the participants' decoding skills (i.
Following the guidelines of  [108]  and according to the methodology used in  [109] , it is possible to calculate three types of indicator: 1. The articulation rate (number of syllables/minute), which makes it possible to estimate the quality of supralaryngeal articulation; 2. The speech proportion (i. e. , ratio between the cumulated speech durations and the total session time); and 3. The pause proportion (i. e. , ratio between the cumulated pause durations and the total session time), which provides information on the respiratory control required for speech production. The task was recorded and audio files of the participant's productions were pre-processed and analyzed using dedicated software (Praat http://www. fon. hum. uva. nl/praat/, accessed on 16 December 2022 ) and following the methodology adopted by  [109].
Results Statistical analyses were performed using the statistical open-source software packages JASP  [110]  and JAMOVI  [111]. Given the percentage of individuals with both dyslexia and a motor impairment in our sample (27%), we first tested whether the two groups with dyslexia shared the same reading skills profiles. Analyses of variance (ANOVA) were conducted for each reading test (connected text reading fluency, one-minute word reading test, two-minute pseudoword reading test) and were performed with a one-way independent group (SR vs. DYS-noCoM vs. DYS-CoM) design. The dependent variable was the efficiency score in each case. The reading skills performances of the different groups are summarized in Figure  1. * Classical Phoneme awareness task (Classical PAT)-In this condition, the task was administered under time pressure, with the participants being required to give the answer as quickly and accurately as possible; * Delayed Phoneme awareness task (Delayed PAT)-In this second condition, a longer interval was allowed between the end of pseudoword presentation and the response in order to facilitate access to phonemic representations of the pseudoword strings to be processed and the programming of the oral response.
Results Statistical analyses were performed using the statistical open-source software packages JASP  [110]  and JAMOVI  [111]. Given the percentage of individuals with both dyslexia and a motor impairment in our sample (27%), we first tested whether the two groups with dyslexia shared the same reading skills profiles. Analyses of variance (ANOVA) were conducted for each reading test (connected text reading fluency, one-minute word reading test, two-minute pseudoword reading test) and were performed with a one-way independent group (SR vs. DYS-noCoM vs. DYS-CoM) design. The dependent variable was the efficiency score in each case. The reading skills performances of the different groups are summarized in Figure  1. The ANOVA run on the one-minute word reading performances (Figure  1A ) yielded a significant effect of Group (F(2, 108) = 48.
Decay of the mediator particle The mediator particle behaves like a light SM Higgs boson, as it interacts with SM particles through the mixing between H and Φ. Its partial decay width into SM particles is Γ (φ → SMs) = sin 2 θ Γ(h SM → SMs)| m 2 h SM →m 2 φ , ( 2. 6) with h SM being the SM Higgs boson. We will discuss each decay mode in more detail. φ → γγ. The mediator particle decays mainly into two photons when m φ ≤ 2m e. We use the formula developed in ref. [33]  to calculate its partial decay width Γ(φ → γγ) within the region of m φ ≤ 0. 6 GeV, though this decay channel is not dominant anymore when m φ ≥ 2m e. The partial decay width is computed using the HDECAY code  [34]  when m φ ≥ 2 GeV. On the other hand, the formula in ref. [35]  is used in the region of 0. 6 GeV ≤ m φ ≤ 2 GeV, where it connects the two regions m φ ≤ 0.
6 GeV and m φ ≥ 2 GeV continuously. φ → e -e + /µ -µ +. In the region of 2m e ≤ m φ ≤ 2m µ with m µ being the muon mass, φ decays mainly into an electron and a positron. Its partial decay width is given by the formula, Γ(φ → e + e -) = sin 2 θ × m 2 e m φ 8πv 2 H 1 - 4m 2 e m 2 φ 3/2. (2. 7) When the mediator mass is above the muon threshold but below the pion threshold, namely 2m µ ≤ m φ ≤ 2m π , the mediator decays mainly into a pair of muons. Its partial decay width is computed by the same formula as above, with m e being replaced by m µ. The formulae for the two channels are used up to m φ = 2 GeV. On the other hand, in the mass region of m φ ≥ 2 GeV, the HDECAY code is used to compute partial decay widths of the channels.
The letter in the figure shows the dominant annihilation mode of the scalar dark matter in each mass region (except the intermediate mass region, 500 MeV ≤ m φ ≤ 4 GeV): the scalar dark matter annihilates into a pair of electrons, muons, and pions/muons when m φ ≤ 2m µ , 2m µ ≤ m φ ≤ 2m π , and 2m π ≤ m φ ≤ 500 MeV, respectively, where we estimate the efficiency f eff (m χ ), i. e. , the fragmentation functions dN e, γ /dE| f SM , using the HAZMA code  [57]. On the other hand, the dark matter annihilates into a pair of gluons/charm quarks/tau leptons and bottom quarks when 4 GeV ≤ m φ ≤ 2m b and m φ ≥ 2m b , respectively, with m b being the bottom quark mass. The efficiency f eff (m χ ) in such mass regions is estimated using the micrOMEGAs code  [58]. In the intermediate-mass region, 500 MeV ≤ m φ ≤ 4 GeV, however, there is no robust way to calculate fragmentation functions for hadronic final sates.
Acknowledgments This work is supported by  Grant-in-Aid for Scientific Research  from the  Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan ;  20H01895 ,  20H00153 ,  19H05810 , 18H05542  (for S. Matsumoto), by  World Premier International Research Center Initiative (WPI) ,  MEXT, Japan  ( Kavli IPMU ), by the  JST SPRING , Grant Number  JPMJSP2108 , and by  JSPS  Core-to- Core Program  ( JPJSCCA20200002 ). SC also acknowledges support from the  Indo-French Centre for the Promotion of Advanced Research  ( CEFIPRA Grant  no:  6304-2 ).
The resulting graph is used to enhance the user experience for the spoken language understanding (SLU). Like the previous representation, the representation illustrated by these authors is centered on users, with attributes such as children's names, employment, date, place of birth, and family relations. Another representation of personal knowledge was elaborated by  [11]  in the domain of research. The personal research knowledge graph (PRKG) is designed to acquire the researcher's professional activities, as well as shared laboratory resources and fine-grained knowledge items related to his/her research work. The concepts used are attributes of the user-centric graph and can also be linked to each other. To make effective use, PRKG can be populated manually or automatically from information extracted from specialized databases such as ORKG  2  and OpenAlex 3  or from the user conversation with a chatbot.
Illustration To illustrate the above model of the interpersonal knowledge graph, the case of teaching activities within a university will be addressed. The illustration graph concerns two teachers, one teaching database design and the other teaching Python programming. The two teaching activities are carried out in the Each teacher has a specific file organization for his/her course, but both use markers for their lecture. The courses' objectives are to teach student database and Python programming. In terms of file system organization, each teacher has a different folder structure. The database teacher puts his/her document directly in the folder named database books, while the Python teacher uses two sub-folders for his/her Python codes and books. For implementation, the established knowledge graph used Wikidata 4  as an external knowledge to enhance the semantics of resources.
Learning from Interpersonal Activity Graph (IAG) From the above illustration of an IAG, the following questions can be asked with a SPARQL query language: The query in Block 3 bellow is an example from the illustrated case to find resource for Python programming. Block 4 is the result of the query in Block 3. It shows resources used to carry out activity Teach Py1. The result print out documents including folders and sub-folder of this activity. • Other questions can be related to goals and activities Similarly, queries can be carried out with the intention of rules or processes. For example, one can be interested in rules that govern a given activity. Queries can also be used to find sub-activities of a given activity. Block 4: Results of query in Block 3 ic| resource: 'markera', subresource: 'markera' ic| resource: 't1folder00', subresource: 't1folder00' ic| resource: 't1folder00', subresource: 't1folder10' ic| resource: 't1folder00', subresource: 'python_programming' ic| resource: 't1folder00', subresource: 't1folder01' ic| resource: 't1folder00', subresource: 'learning_python'.
The flow field was simulated using a modified Stokes equation implemented in the open-source software OpenFOAM (https://openfoam. org/), which calculates the depth-averaged velocity between the two plates  (Ferrari et al. , 2015; Soulaine et al. , 2021). For the porous medium, we performed three simulations with different locations of the point source injection within a radius of 2 mm from the middle of the cell. Further details of the numerical methods are given in the Figure  S2  in Supporting Information S1.
Conservative Mixing In Figure  5  we show the conservative tracer concentration in the Hele-Shaw cell and the porous medium for Pe = 0. 31. Concentration profiles across the mixing front were extracted from the 2D data in sections close to the stagnation point. In the Hele-Shaw cell, this point is easily identified in the middle of the cell (Figure  5a ). In the porous medium, the exact location of the stagnation point is more difficult to assess. According to the simulated velocity fields (Figure  11b ) and reactive images (Figure  7 ), the stagnation points are localized on a pillar (Figure  5b ) because of the splitting of streamlines upstream of the stagnation points on the same pillar. The mixing interface is thus split between 2 stagnation points on each side of the pillar. The concentration gradient across the mixing front increases with Pe, in both the Hele-Shaw cell and the porous medium.
Acknowledgments Funding for this study was provided by  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie Grant  Agreement No  722028  to the project  ENIGMA (European training Network for In situ imaGing of dynaMic processes in heterogeneous subsurfAce environments)  and by  ANR   JCJC   SUCHY   ANR-19-CE01-0013 , as well as the  CPER (Contrat de Plan État-Région) BUFFON  for part of the equipment. We acknowledge funding by  ERC  project  ReactiveFront 648377.
Whole-brain simulations have been proposed previously to simulate global properties such as brain states or functional connectivity. Here, our aim is to build a whole-brain model to simulate a simple cognitive paradigm involving multiple brain areas. We focus on auditory discrimination, using a paradigm designed for the macaque cortex. To model at the whole-brain scale, we use The Virtual Brain (TVB) [18] simulation environment. TVB is a computational framework which simulates the brain as a network of small brain regions, where each node models neuronal populations and the connectivity between nodes determines the pathway of information flow over the brain. We use Adaptive Exponential (AdEx) neuronal population models  [4, 11]  to describe each node. For the connectivity, we use the open-access CoCoMac connectivity dataset [2], which is a matrix containing the connection weights between the nodes.
Therefore, it ignores the information routing in the brain, more specifically in the sensory-motor pathway corresponding to the relevant decision-making task. To tackle these points, we use The Virtual Brain (TVB)  [18] , which is an open-source software and freely available on EBRAINS. It simulates all regions in the brain as a network of mean-field models. Each mean-field model approximates the dynamics of one region. We use the AdEx mean-field model embedded previously in TVB  [13, 14]. This embedding was proposed to model awake and sleeping brain states, for both spontaneous and stimulated activity. However, it does not consider any cognitive task. Our principal contribution is to extend the AdEx mean-field model and its embedding in TVB such that TVB can produce the neuronal dynamics related to auditory discrimination.
This work shows the potential of AdEx in simulating whole-brain dynamics corresponding to cognitive functions. Moreover, it provides computational support for experimental studies focusing on cognitive tasks in the macaque brain. It provides the whole-brain simulations based on AdEx, which is biophysically plausible, therefore can be tuned to the neural data recorded via multielectrode arrays. In Section 2, we explain the auditory discrimination tasks considered in our simulations. In Section 3, we explain the TVB framework. Then, in Section 4, we describe the AdEx mean-field models which we use for the nodes in TVB. Finally, in Section 5, we present our TVB simulation results, and then, in Section 6, we provide the conclusion and perspectives.
Simulations of the model In our simulations, we modeled the difference of the pitches by changing the stimulus strength representing the auditory frequency. We introduced the stimuli to A1. We then analyzed the resulting data in different PFC areas of the macaque by using TVB. We aimed to discern which areas produced the most distinguishable signals. Regarding this point, the dorsolateral PFC (PFCdl) provided the most distinguishable results in our simulations. This is in coherence with the experimental evidence, which suggests the involvement of PFCdl in auditory discrimination tasks [3,  [15] [16] [17]. Moreover, we took advantage of the hemispherical symmetry and restricted the simulations to the right hemisphere for the sake of simplicity. Pipelines of the information flow in the simulations for Task 1 and Task 2 can be found in Figure  2.
19, 20  Obeticholic acid (OCA) is a first-in-class farnesoid X receptor (FXR) agonist and antifibrotic agent in development for the treatment of pre-cirrhotic liver fibrosis due to NASH. 10, 22  OCA is an analogue of the bile acid chenodeoxycholic acid (CDCA), the natural FXR ligand, but it is 100x more potent than CDCA. 10  Because of its bile acid-like properties, OCA circulates enterohepatically and engages FXR in the liver and gut. [23] [24] [25]  OCA reduced the progression of liver fibrosis in animal models of NASH  [26] [27] [28] [29]  and demonstrated improved fibrosis in 35% of participants on OCA 25 mg in the phase II FLINT study of participants with non-cirrhotic NASH after 72 weeks of therapy. 30  For the previously reported planned 18-month interim analysis of REGENERATE (NCT02548351) in the prespecified intent-to-treat (ITT) population, fibrosis improved > -1 stage with no worsening of NASH in 23.
03. An independent data-monitoring committee was tasked with reviewing unblinded safety data on an ongoing basis. Four blinded independent committees comprising experts were assembled to review and adjudicate all potential cases of (1) hepatic outcome events, (2) hepatic safety events, (3) acute kidney injury, and (4) major adverse cardiovascular events (MACEs) that occurred after administration of the first dose of investigational product. Improvement in adjudicated clinical outcomes, such as death, liver transplant, and progression to cirrhosis, will serve as the final primary endpoint of the REGENERATE study. As the study is ongoing, they are not included in this planned 18-month interim analysis. In 2017, a major safety amendment was implemented for the study with the goal of improving participant safety.
Safety The original interim analysis included safety data from the first 1,968 participants enrolled with a median of 15 months of exposure to the study drug. 22  Since that time, full enrollment was achieved, and additional safety data from a total of 2,477 participants has been incorporated. As of the data cut-off, 8,054 total PYs of exposure data were available, with a median exposure of 39 months. A total of 976 participants had received study drug for >4 years. Deaths were balanced across treatment groups. Treatment-emergent adverse events (TEAEs) and serious TEAEs were numerically higher for the combined OCA groups vs. placebo, with the difference primarily driven by pruritus (Table  2 ).
REGENERATE represents the largest and longest-duration trial in pre-cirrhotic fibrosis due to NASH and provides the most extensive safety database in NASH to date. The length of study, including many participants receiving OCA for >4 years, allowed for examination of the long-term tolerability of the drug. This large and long-term safety exposure enables appropriate characterization of a favorable safety profile in this population and supports chronic dosing. Treatment groups did not show substantial differences in TEAEs, serious TEAEs, or deaths. Although there was an increase in cholelithiasis and cholecystitis events with OCA treatment, the data from the study confirm that these events are not uncommon in this patient population and were appropriately managed by study investigators in gastrointestinal or hepatology clinical practices.
Acknowledgments Medical writing assistance was provided by  MedLogix Communications, LLC  and was funded by  Intercept Pharmaceuticals, Inc. PNN  was supported by the  Birmingham NIHR Biomedical Research Centre. This paper presents independent research supported in part by  National Institute for Health and Care Research Birmingham Biomedical Research Centre  at the  University Hospitals Birmingham NHS foundation Trust  and the  University of Birmingham  (grant reference number:  BRC-1215-20009 ). The views expressed are those of author(s) and not necessarily those of  NIHR  or the  Department of Health and Social Care.
End-user survey: analysis of the results A total of 164 responses were received from end-users working on all continents and have been evaluated; 70 % of them belong to public institutions, while 25. 6 % are from private companies. These percentages are close to the ones corresponding to end-users downloading data from the Copernicus Marine Data Store  (Le Traon et al. , 2019). Figure  3  gives a comprehensive overview of end-user feedback by showing the absolute number of detected uses of EOVs in the different applications. Currents and sea level variables are the most demanded variables for applications related to coastal management and disaster risk reduction (entries higher than 10 for each considered application), and temperature has major impact on applications that refer to fisheries, aquaculture, ecological and biological uses (entries at around 10 for each application and up to 15 for the fisheries one), together with biochemical and biological variables (entries lower than 10).
Electrical response Hysteresis response is an essential parameter in the sensor's performance, and it is defined as the maximum change in impedance between the absorption and desorption process of the sensor. We studied the hysteresis response for 0. 25 wt%, 0. 5 wt%, and 1 wt% PVP-CDs-based humidity sensors shown in Fig. 5a-c. The hysteresis response was normalized for data analysis using the formula (R30-Rch)/ (R30), where R30 represented for the baseline impedance at 30% relative humidity (RH) and Rch for the change in impedance resulting from higher humidity levels. Figure  5a  shows the PVP-CDS (0. 25 wt%) sensor shows a low hysteresis response and a low sensitivity. As the concentration of PVP-CDs increases to 0. 5 wt%, the sensitivity increases. The hysteresis response remains low and further increases the concentration of PVP-CDs to 1 wt%; an increasing hysteresis response is observed.
Here we report the reconstruction of the osteobiography of an adult male buried in the Longobard cemetery of Povegliano Veronese (Northern Italy, late 6th -early 8th century CE), who shows signs of interpersonal violence. The palaeopathological investigation reveals sharp force traumas on the body of the fourth lumbar vertebra and on two right ribs. The absence of signs of healing or bone remodelling indicates that the defects were perimortem. The injuries probably affected vital organs, leading to death. Further macroscopic observations of the skeleton suggest horseback-riding activity. Strontium isotope data from tooth enamel indicate a non-local origin of the individual. X-ray and CT scan acquisition and Scanning Electron Microscopy analyses were performed to investigate the bone defects.
Therefore, to evaluate T19 possible in-life movement, it was used the already published strontium data from Povegliano Veronese cemetery  (Francisci et al. 2020). Further multi-tissue stable carbon, nitrogen, and oxygen isotope analyses are available for a subset of the Povegliano Veronese population, including T19  (Marinato 2016). The data were integrated into the life-history reconstruction of this individual to evaluate dietary intra-life variations. A summary of all the isotope analyses performed on this individual and the comparative sample from Povegliano Veronese cemetery is reported in Supplementary Table  S3.