dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions Fluorite-structured nonstoichiometric CeO 2 represents the most promising and benchmark oxygen carrier for solar-driven thermochemical fuel production. In this study, the solid-state redox kinetics of CeO 2 during both isothermal CH 4 -induced reduction and CO 2 -induced re-oxidation were investigated. Such a coupling of CH 4 partial oxidation with CO 2 splitting can produce syngas, which is an important feedstock for various industrial processes. The reactions were carried out using concentrated solar energy in a customized solar thermogravimetric reactor designed for carrying out thermochemical reactions under controlled atmospheres. Different classical solid-state kinetic models were utilized to derive the mechanism for CeO 2 redox reactions in the solar thermal reactor. Both 2D and 3D variants of the shrinking core model (SCM) and nucleation and nuclei growth model (NGM) were found to exhibit the best correlation between the experimental data and model predictions.
The main result of the paper on mixing for the 2D Navier-Stokes system perturbed by a random boundary force is presented in Section 3. The appendix gathers a few auxiliary results used in the main text. Acknowledgement. The author is grateful to A. Miranville and J. -P. Puel for useful remarks on boundary-driven Navier-Stokes equations and observability inequalities. This research was carried out within the MME-DII Center of Excellence (ANR-11-LABX-0023-01) and supported by Agence Nationale de la Recherche through the grant NONSTOPS (ANR-17-CE40-0006-02), Initiative d'excellence Paris-Seine, and the CNRS PICS Fluctuation theorems in stochastic systems.
Methods Data were collected from the Necker Enfants Malades Hospital using a document-based data warehouse, Dr Warehouse, which employs Natural Language Processing, a computer technology consisting in processing written information. Using Uni ed Medical Language System Meta-thesaurus, phenotype concepts can be recognized in medical reports. We selected individuals with DS (DS Cohort) and individuals with FS (FS Cohort) with con rmed diagnosis after the age of four years. A phenome-wide analysis was performed evaluating the statistical associations between the phenotypes of DS and FS, based on concepts found in the reports produced before two years and using a series of logistic regressions.
Materials And Methods Data were collected from Necker Enfants Malades Hospital, a paediatric University hospital belonging to the Assistance Publique Hopitaux de Paris group (400 paediatric beds, 200 adult beds), which is a national and European reference center for rare and undiagnosed diseases, including the reference a centre for rare epilepsies. DrWarehouse Ò (21) (DrWH) is a document-based open-source clinical data warehouse oriented toward free text, containing more than 4. 5 million clinical free-text documents produced at Necker Hospital from 2009, for more than 465,000 individuals and more than 20 hospital departments. DrWH uses UMLS Metathesaurus to recognize phenotype concepts inside narrative medical reports. In this manuscript, the word "concepts" will refer to phenotypes extracted automatically from hospital reports, without a priori, by using a UMLS subset of 20,000 phenotypic words or expressions.
"Dravet Syndrome Cohort" (DS Cohort) The term "Dravet" and/or "severe myoclonic epilepsy of infancy" appeared in 305 individuals present in the warehouse: 194 of them had a nal diagnosis of DS in the last document on the database, 51 had at least one document produced under the age of two years. All had a clinical and genetic diagnosis of DS. These individuals constituted the DS Cohort. DS cohort included 28 males and 23 females. The mean age at rst seizure was 5,5 months (min 2 -max 12). The average age of the rst produced document was 1,05 years, median is 1,15 (min 0,25 -max 1,98). The average length of the follow-up of these individuals was 5,68 years, median 4,98 (min 3,75-max 13,42). In order to compare this population with a population with FS at the same age, documents produced exclusively before two years was selected, for a total of 318 documents (mean: 6,24; median: 3 for each individual).
To do this, we used the Morphologi G3 Malvern instrument. This optical microscope is coupled to a data acquisition system and image processing software. Indeed, with an adequate adjustment (focus, light and threshold), every particle detected is photographed and its size measured. We opted for a compromise between the measurement duration and the counting of a sufficiently high particle number in order to obtain a reliable statistical result. Thus, for each experiment, particle resuspension measurement is performed by scanning the particle deposit on the surface before and after exposure to airflow. The scanning is performed on a circular area (314 mm2) with a diameter of 20 mm, located at the centre of the deposit (tungsten square surface area of 1,521 mm2). Since a measurement with the Morphologi G3 lasts eight hours, we set the microscope in a clean laminar airflow hood inside an ISO 7 cleanroom environment to get rid of any contamination by the atmospheric aerosol.
Herschel photometric fields As anticipated in Section 2, we have exploited the IR photometric catalog of the Herschel Legacy Extragalactic Program (HELP, Vaccari 2016), as input data to determine how many galaxies, that have been detected with the Herschel photometric surveys, would be detected with the SPICA SMI spectroscopic surveys at each redshift and luminosity. In particular, we have used the data already analyzed with the Code Investigating GALaxy Emission (CIGALE;  Ciesla et al. 2015) , which are available on the HELP ( ) service with estimated total IR luminosity, stellar mass and SFR, for a total of about 15,000 objects selected in the whole COSMOS field  (Scoville et al. 2007) , covering an area in the sky of 2 deg 2. All the selected sources have 24m fluxes from available at: https://herschel-vos.
7 M galaxy residing in the Main-Sequence (M. -S. ;  Scoville et al. 2017). For the low metallicity galaxies (LMG) presented in Fig. 2 (b) the detection threshold of SMI-LR is about one order of magnitude below the knee of the luminosity function, but only at redshift up to z∼2. 2. Finally, for the AGN population, as shown in Fig. 2(c ), SMI-LR can detect all objects at about 0. 5-0. 8 dex below the knee of the luminosity function up to redshift z∼3. 5. The results of our simulations of the ultra-deep 1 deg 2 SMI spectroscopic survey, using the HELP database, are shown in Fig. 3 (a) the detections of the expected PAH features in SF galaxies with solar metallicity, in Fig. 3 (b) the detections of fine structure lines in low-metallicity galaxies, and in Fig. 3(c ) the detections of fine structure lines typical of AGN.
Figure2. Redshift-luminosity diagrams simulating the SMI 120 arcmin 2 (0. 033 deg 2 ) hyper-deep survey using the HELP database. In all three panels, the grey dots represent the whole galaxy population as detected photometrically by Herschel, while each continuum coloured line represent the detection limit of SMI at the given line or feature, as indicated by the legend, which also gives the total number of detections in that particular line or feature. The green broken line shows the knee of the luminosity function, as a function of redshift for a 10 10. 7 M galaxy in the Main-Sequence (M. -S. ; Scoville et al. 2017). (a: left): SF galaxies detectable with SMI in the PAH features. On the right-hand y-axis the SFR correspondent to the total L   is also given, adopting the conversion factor from Kennicutt & Evans (2012).
Figure3. Redshift-luminosity diagrams simulating the SMI 1 deg 2 ultra-deep survey using the HELP database. We refer to Fig. 2for the lines coding and legends in each frame. (a: left): SF galaxies detectable with SMI in the PAH features. On the right-hand y-axis the SFR correspondent to the total L   is also given, adopting the conversion factor from Kennicutt & Evans (2012). (b: center): SF galaxies, adopting the line calibration of low-metallicity galaxies (∼ 1/5 Z ), detectable with SMI in intermediate ionization fine-structure lines. (c: right): AGN detectable with SMI in high-ionization fine-structure lines.
ACKNOWLEDGEMENTS This paper is dedicated to the memory of  Bruce Swinyard , who initiated the  SPICA  project in Europe, but unfortunately died on 22 May 2015 at the age of 52. He was ISO-LWS calibration scientist, Herschel-SPIRE instrument scientist, first European PI of SPICA and first design lead of SAFARI. We acknowledge the whole  SPICA Collaboration Team , as without its multi-year efforts and work this paper could not have been possible. We also thank the  SPICA Science Study Team  appointed by  ESA  and the  SPICA Galaxy Evolution Working Group. LS and JAFO acknowledge financial support by the  Agenzia Spaziale Italiana (ASI)  under the research contract  2018-31-HH. 0. AAH acknowledges support from grants  PGC2018-094671-B-I00  ( MCIU/AEI/FEDER,UE)  and No. MDM-2017-0737  at  Unidad de Excelencia María de Maeztu-Centro de Astrobiología (INTA-CSIC ).
FJC acknowledges financial support from the  Spanish Ministry MCIU  under project  RTI2018-096686-B-C21  ( MCIU/AEI/FEDER/UE ), cofunded by  FEDER  funds and from the  Agencia Estatal de Investigación ,  Unidad de Excelencia María de Maeztu , ref. MDM-2017-0765. HD acknowledges financial support from the  Spanish Ministry of Science, Innovation and Universities (MICIU)  under the  2014 Ramón y Cajal program   RYC-2014-15686  and  AYA2017-84061-P , the later one co-financed by  FEDER (European Regional Development Funds). AL acknowledges the support from  Comunidad de Madrid  through the  Atracción de Talento  grant  2017-T1/TIC-5213. MPS acknowledges support from the  Comunidad de Madrid, Spain , through  Atracción de Talento Investigador Grant   2018-T1/TIC-11035.
Detection of respiratory syncytial virus cases We prospectively collected laboratory data from the university hospitals of Lyon and Saint-Etienne in the Rhône-Loire metropolitan areas with ca 2 million inhabitants, from September 2018 to May 2021  [7]. All respiratory samples (nasopharyngeal aspirates, nasal/ throat/oral swabs, tracheobronchial aspirates, and bronchoalveolar lavages) taken from patients with respiratory tract infection (upper or lower/mild or severe) and received by the virology laboratories from in-and outpatients were tested for RSV and included in our analysis. An RSV case was defined as any laboratory-confirmed RSV infection detected by real-time reverse transcriptase (RT)-PCR during the study period. As SARS-CoV-2 and RSV co-detections are rare events  [8] , they were not further investigated in the present study.
Calculation of hospitalisation rates and incidence of very severe and severe cases In order to calculate hospitalisation rates, we collected data from children born at the Hospices Civils de Lyon over three consecutive years (1 June 2018-01 April 2021) whose parents are living in the Métropole de Lyon (around 1. 4 million inhabitants). From this birth cohort (Lyon cohort), hospitalised cases with confirmed RSV infection during the first year of life were identified using the diagnostic laboratory database on three consecutive RSV seasons (2018/19; 2019/20 and 2020/21 between 1 September and May 2021). VS-LRTI was defined as a laboratory-confirmed RSV infection leading to hospitalisation occurring during the first year of life, and meeting the World Health Organization case definition (SpO2 < 90%, inability to feed)  [9].
Farm characterization and diagnosis Characterization involved describing the farms' structure and functioning in terms of two interacting subsystems: the management subsystem and the biophysical subsystem  (Dogliotti et al. , 2005; Dogliotti et al. , 2014). Information on the management subsystem was obtained in several interviews with the farmers and concerned farm history, decision-making procedures, labor force, income sources, succession expectations, support by extension agents or projects, and participation in study groups or unions. Information on the biophysical subsystem was acquired from observations and measurements on the farms and consultation of the farmers and their records. We obtained data on land use in each field of the seven farms over the three years before the project started.
Acknowledgments We are very grateful to the farmers that made this work possible and to  Felipe García ,  Andrés Castagna ,  Guadalupe Tiscornia ,  Liliana del Pino ,  Pablo Clara , and  Sergio Montaldo  for their contributions. This study was conducted in the frame of the project  PF 07: "Coinnovando para el desarrollo sostenible de sistemas de producción familiar de Uruguay " funded by  Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay.
Even if a DFA is defined as an abstract mathematical concept, still it has got myriad of practical applications. More specifically, it is used in text processing, compilers, and hardware design  [23]. Quite often it is implemented in small hardware and software tools for solving various specific tasks. For example, a DFA can model a software that can figure out whether or not online user input such as email addresses are valid. DFAs/NFAs are also used for network packet filtering. In some of these applications, the alphabet is large and there is a failure/exit state so that only a subset of transitions go to non-failure states; so we call the latter ones non-failure transitions. Despite having so many applications in practically motivated problems, we are not aware of, to the best of our knowledge, any study of DFAs and NFAs from the point of view of succinct data structures where the goal is to store an arbitrary element from a set Z of objects using the information theoretic minimum log(|Z|) + o(log(|Z|)) bits of space while still being able to support the relevant set of queries efficiently, which is what we focus on in this paper.
We alleviate this discrepancy in the space bounds by designing optimal succinct data structures for these objects. Towards this goal, we start by listing all the preliminary data structures and graph theoretic terminologies that will be required in our paper in Section 2. Then, in Section 3. 1 we first discuss the relevant prior work from  [3] , and show that, by using suitable data structures, their work already gives a succinct encoding of DFA. But the major drawback of this encoding is that it is not capable of handling the problem of checking whether a string is accepted by the DFA extremely efficiently. In Section 3. 2, we overcome this problem by designing a succinct data structure for DFA, which can also check the string acceptance almost optimally. We summarize our main result in the following theorem.
23:5 We can improve the above space bound significantly if the given DFA is acyclic along with obtaining optimal query time for string acceptance checking. More specifically, in Section 3. 3, we obtain the following result in this case. Theorem 2. Given an initially-connected acyclic deterministic finite automata A having n -1 transient states, a unique dead state and working over an alphabet Σ of size σ, there exists a succinct encoding for A taking (σ -1)(n -1) log n + 3n + O(log 2 σ) + o(n) bits of space, which can optimally determine, given an input string x over Σ, whether A accepts x in time proportional to the length of x, using constant words of working space. This is followed by the succinct data structure for NFA in Section 3. 4 where we prove the following result. Theorem 3. Given an initially-connected non-deterministic finite automata N having n states and working over an alphabet Σ of size σ, there exists a succinct encoding for N taking σn 2 + n bits of space, which can determine, given an input string x over Σ, whether N accepts x in O(n 2 |x|) time, using 2n bits of working space.
23:6 Succinct Representation for (Non)Deterministic Finite Automata more specifically their graphical representation i. e. , state transition diagram, as a special case of an edge labeled directed graph G having n nodes corresponding to the n = |Q| states of DFA/NFA, m = σn edges where |Σ| = σ as each node has exactly σ outgoing edges, and each edge is labeled with some elements from Σ. It is with this point of view, we will design our succinct data structures for DFA/NFA in this paper.
Succinct Data Structure for DFA Data structure: To design a succinct data structure for DFA, we need the following three bitvectors F , P and T in addition to an integer array NewBoxed  [1. m] (that can be obtained from the Boxed  [1. m] array of the previous section, as described later), which are defined as follows. P is a balanced parentheses sequence of length 2n obtained from the lexicographic depthfirst search (DFS) tree of the given input automaton D. More specifically, given any DFA D, we first perform the lexicographic DFS on D to generate the lexicographic DFS tree R of D, i. e. , while looking for a new edge to traverse during DFS, the algorithm always searches in lexicographic order of edge labels. For example, in Figure  3 , from any vertex, lexicographic DFS first tries to traverse the edge labeled a, followed by b and finally c.
Instead of this specific ordering (followed in the Boxed  [1. m] array), NewBoxed  [1. m] lists the same node labels in the order of their appearance in the T bitvector (from left to right). Note that, as mentioned previously, these node are marked by 0s in T and they are in one-to-one correspondence with all the non-tree edges of the lexicographic DFS tree of the automaton D. Thus, the NewBoxed  [1. m] array contains the same node labels as the Boxed  [1. m] array, but in a different order. See Figure  4  for an example. This completes the description of our succinct data structure for DFA. Note that Max is no longer used in our data structure. We now analyze the space complexity of our data structure. The array NewBoxed  [1. m] takes (σ -1)n log n + O(log 2 m) bits (by similar analysis as before for the Boxed  [1.
Succinct Data Structures for Acyclic DFA As mentioned previously, an acyclic DFA A with total n states always has a unique dead state and n -1 transient (i. e. , non dead) states. Another way to visualize A is to see that the state transition diagram of A does not have any cycles except at the unique dead state. Given such a setting, one can always use the succinct encoding (of the previous section) of an arbitrary DFA to represent them. In that case, we end up using (σ -1)n log n + O(n log σ) bits of space. In what follows, we show that by exploiting the acyclic property, one can obtain improved space bound for representing A. We basically view the state transition diagram of A as a directed acyclic graph with a single source (i. e. , the initial state), and a single sink i. e. , the dead state (call it d).
23:12 Succinct Representation for (Non)Deterministic Finite Automata the navigational queries on W (in particular, the parent query) in O(1) time. As done previously in Section 3. 2 while constructing the succinct data structures for DFA, here also we relabel all the states of A such that the i-th vertex (state) in W in preorder has label i, and modify the transition function accordingly. Note that the dead state d is labeled with label 0 in this ordering, and we do not need to store the transition function for the dead state. We also mark in a bitvector of size n all the final states of A, and we store the label of the start state. We then store a two dimensional array L[1. n -1][1. σ -1] such that L[q][i] = δ(q, i) using data structure of Theorem 9. Thus, the overall space usage is (σ -1)(n -1) log n + 3n + O(log 2 σ) + o(n) bits.
Concluding Remarks We considered the problem of succinctly encoding any given DFA D, acyclic DFA A or NFA N so as to check efficiently if they accept a given input string. To this end, we successfully designed succinct data structures for them that also support the string acceptance query efficiently for DFAs, acyclic DFAs, and NFAs. To the best of our knowledge, our work is the first attempt to encode any mathematical models from the world of automata theory using the lens of succinct data structures, and we believe that our work will spur further interest in other similar problems in future. q 0 q 0 q 1 b,c a b,c a q' 0 q' 1 = (Σ, Q , q 0 , δ , F ) such that (i) Σ = {a, b, c}, (ii) Q = {q 0 , q 1 }, ( iii) q 0 = q 0 (marked with an incoming arrow coming from nowhere), (iv) F = {q 1 }, and (v) the transition function is defined as the following set, {δ(q 0 , a) = q 0 , δ(q 0 , b) = q 1 , δ(q 0 , c) = q 0 , δ(q 1 , a) = q 0 , δ(q 1 , b) = q 1 , δ(q 1 , c) = q 0 }.
All samples were put in a box of water filled until the neck of the glass vials and positioned in a climate-controlled room at 20 • C ± 2 • C and 60% relative humidity (Figure  3 ). To ensure that water evaporation did not take place, the mass of each sample (vial + paste, stopper and pipette) was recorded before introducing it into the bath of water, then after 24 h and a last measurement was taken at 28 days at the end of the experiment. If the difference between the initial and the final masses for a given sample was greater than 0. 02 g, that specimen's chemical shrinkage data were discarded. For the specimens with w/c = 0. 2, the thickness of the paste in the tube was equal to 3 mm or below, a value recommended by ASTM for w/c < 0. 4. In a thick paste layer, C-S-H gel formed can create a lot of inclusive pores where external water cannot penetrate.
b. Pre-study of Energy Condition Based on land functions and floor area, a simulation is conducted to estimate energy demands (heating, cooling and electricity). By considering local climate, building types, envelope structure, operation mode, the annual hourly demand is estimated, which is one of the main input data for the optimization. The annual accumulated energy demand is then distributed to each plot, show in figure  2. The spatial distribution and the density of the energy demand provide valuable indications for positioning the energy systems. The energy demand distribution shows that the east part has a larger and denser energy demand than the west; meanwhile, land functions in the east are more mixed which leads to diversified energy load features. Therefore, the study zone is divided into two parts, show in figure  3 , the east part (zone1) will adopt centralized energy system and the west part (zone2) will use discrete energy solution at plot level.
4, diphoton invariant mass greater than 6 GeV, diphoton transverse momentum lower than 2 GeV and diphoton acoplanarity below 0. 01. The measured fiducial cross section is σ f id = 70 ± 24 (stat. ) ± 17 (syst. ) nb, which is in agreement with the predicted values of 45 ± 9 nb  [5]  and 49 ± 10 nb  [6]  within uncertainties. The first essential point in this kind of analysis is to record the needed events during the data taking, what we also call trigger the events. In this sense, events have been recorded using a trigger specially designed to detect events with a muon and little additional activity in the detector. The primary requirement is for the presence of a region of interest associated with a track in the muon spectrometer, with no lower bound on p T in order to be sensitive to relatively low transverse momentum muons.
0 ± 2, 6 ± 1. 2 ± 0. 3 fb and σ µµ = 7. 2 ± 1. 6 ± 0. 9 ± 0. 2 fb in the di-electron and di-muon channels respectively. Fig. 33  shows the difference between the momentum loss measured from the di-lepton pairs or with the RP detectors. This figure is equivalent to Fig. 32  (for CMS). In addition, recently, the CMS and TOTEM Collaborations have reported a preliminary search for exclusive two-photon production via photon exchange in proton-proton collisions using intact protons  [67]. The data correspond to an integrated luminosity of 9. 4 fb -1 collected in 2016 at 13    ) (GeV.