dataesr/scientific-paragraphs-categorization huggingface dataset:
Finally the algorithm samples the posterior probability distribution of the model parameters in a MCMC framework using the emcee package version 3. 0. 2 (Foreman-Mackey et al. 2013). The GP is implemented by using the celerite2 package version 0. 0. 2  (Foreman-Mackey et al. 2017; Foreman-Mackey 2018). Given the complexity and the demand of resources of the model fitting, we ran the code in the HOTCAT computing infrastructure  (Bertocco et al. 2020; Taffoni et al. 2020). Our Monte Carlo fit consisted of 100,000 steps, which corresponded to ∼300 times the auto-correlation length of the chains, estimated following  Goodman & Weare (2010). This suggests that the fit successfully converged 8. We did not find any evidence of a linear long term trend in the data, thus we fixed c 1,o = 0 in Eq. (3) for each of the four TESS orbits.
CHEOPS light curves We analyzed the CHEOPS LCs using the same Monte Carlo framework described in Sect. 4. 1, taking into account the fact that the visits last only a few hours around the secondary eclipses of WASP-43b. Thus, the dataset does not allow the reconstruction of the full phase curve, but only the flux drop during the eclipse. Moreover, given the eclipse depth measured in the TESS band (Sect. 4. 1), we did not expect the eclipse signal in the CHEOPS LCs to be strong enough to constrain the ephemeris of the system. For these reasons, we fixed the orbital parameters and ρ ⋆ to their MAP values in Table  4. We also fixed ∆ϕ = 0, which makes a perfect correspondence between the amplitude of the phase curve, A p , and the eclipse depth, δ ecl. Since the CHEOPS LCs are only a few hours long, much shorter than the stellar rotation period, the rotation signal cannot be modeled with a periodic function.
The temperature-pressure profile depicted in the lower panel of Fig. 9  is almost isothermal near pressures of 0. 1 bar, without any signs of a strong temperature inversion. This suggests that very strong shortwave absorbers such as Fe, Fe + , or TiO are not a dominant opacity source in this atmosphere. The tightest constraints on the temperature profile are obtained for pressures between 1 bar and 0. 1 bar. In the lower and upper atmosphere, on the other hand, the temperature-pressure profile is essentially prior-dominated. Figure  10  shows the posterior eclipse depths for all bandpasses that have been included in the retrieval. The inset plot is a magnification of the HST WFC3/G141 data. Due to the lower error bars of the space-based data (HST WFC3/G141 and Article number, page 12 of 37 Fig.
2014; Stevenson et al. 2014 Stevenson et al. , 2017)) , all observations have been performed over rather wider filter bandpasses. We therefore assumed that the atmosphere is in chemical equilibrium for simplification. This allowed us to describe the chemistry by a single free parameter -the overall metallicity, [M/H] -instead of retrieving separate mixing ratios for all considered chemical species. To calculate the chemical composition during the evaluation of the forward model, we employed the ultra-fast equilibrium chemistry model FASTCHEM 9  (Stock et al. 2018 ) in its 2. 1 version. As opacity sources, we included the following species: H 2 O, CO, TiO, VO, SH, K, Na, H 2 S, FeH, CH 4 , CO 2 , HCN, MgH, 9 https://github. com/exoclime/FastChem Uniform 0. 1-2. 0 Equilibrium chemistry [M/H] Uniform 0.
9  is almost isothermal near pressures of 0. 1 bar, without any signs of a strong temperature inversion. This suggests that very strong shortwave absorbers such as Fe, Fe + , or TiO are not a dominant opacity source in this atmosphere. The tightest constraints on the temperature profile are obtained for pressures between 1 bar and 0. 1 bar. In the lower and upper atmosphere, on the other hand, the temperature-pressure profile is essentially prior-dominated. Figure  10  shows the posterior eclipse depths for all bandpasses that have been included in the retrieval. The inset plot is a magnification of the HST WFC3/G141 data. Due to the lower error bars of the space-based data (HST WFC3/G141 and Spitzer), the retrieval is mostly driven by their reported eclipse depth. The ground-based data, on the other hand, seems to have a consistent shift towards higher eclipse depths compared to those obtained from the space telescopes.
Acknowledgements. CHEOPS is an ESA mission in partnership with Switzerland with important contributions to the payload and the ground segment from  Austria, Belgium, France, Germany, Hungary, Italy, Portugal, Spain, Sweden , and the  United Kingdom. The CHEOPS Consortium would like to gratefully acknowledge the support received by all the agencies, offices, universities, and industries involved. Their flexibility and willingness to explore new approaches were essential to the success of this mission. L. B. o. , G. B. r. , V. N. a. , I. P. a. , G. P. i. , R. R. a. , G. S. c. , V. S. i. , and T. Z. i. acknowledge support from  CHEOPS ASI-INAF  agreement n. 2019-29-HH. 0. M. L. acknowledges support of the  Swiss National Science Foundation  under grant number  PCEFP2_194576. A. B. r. was supported by the  SNSA.
P. M. acknowledges support from  STFC  research grant number  ST/M001040/1. M. F. and C. M. P. gratefully acknowledge the support of the  Swedish National Space Agency  ( DNR 65/19 ,  174/18 ). S. H. gratefully acknowledges CNES funding through the grant  837319. V. V. G. is an F. R. S. -FNRS Research Associate. A. C. C. and T. W. acknowledge support from  STFC  consolidated grant numbers  ST/R000824/1  and  ST/V000861/1 , and  UKSA  grant number  ST/R003203/1. Y. A. and M. J. H. acknowledge the support of the  Swiss National Fund  under grant  200020_172746. We acknowledge support from the  Spanish Ministry of Science and Innovation  and the  European Regional Development Fund  through grants  ESP2016-80435 MDM-2017-0737  Unidad de Excelencia Maria de Maeztu-Centro de Astrobiología (INTA-CSIC) , as well as the support of the  Generalitat de Catalunya/CERCA  programme.
D. S. D. is supported in the form of work contract ( DL 57/2016/CP1364/CT0004 ) funded by national funds through FCT. B. -O. D. acknowledges support from the  Swiss National Science Foundation  ( PP00P2-190080 ). D. G. gratefully acknowledges financial support from the  CRT foundation  under Grant No. 2018. 2323"Gaseousor rocky?Unveiling the nature of small worlds". M. G. is an F. R. S. -FNRS Senior Research Associate. K. G. I. is the  ESA   CHEOPS  Project Scientist and is responsible for the  ESA CHEOPS Guest Observers Programme. She does A17 , page 14 of 33 G. Scandariato et al. : Phase curve and A g of WASP-43b not participate in, or contribute to, the definition of the  Guaranteed Time Programme  of the CHEOPS mission through which observations described in this paper have been taken, nor to any aspect of target selection for the programme.
This work was granted access to the HPC resources of MesoPSL financed by the  Région Ile-de-France  and the project  Equip@Meso  (reference  ANR-10-EQPX-29-01 ) of the programme Investissements d'Avenir supervised by the  Agence Nationale pour la Recherche. This work was also partially supported by a grant from the  Simons Foundation (PI Queloz , grant number  327127 ). I. R. acknowledges support from the  Spanish Ministry of Science and Innovation  and the  European Regional Development Fund  through grant  PGC2018-098153-B-C33 , as well as the support of the  Generalitat de Catalunya/CERCA  programme. L. M. S. gratefully acknowledges financial support from the  CRT foundation  under Grant No. 2018No. 2323"Gaseous or rocky?Unveiling the nature of small worlds". S. G. S. acknowledges support from  FCT  through  FCT  contract nr.
Bacterial strains A total of 75 strains were included in this retrospective study. Sixty-three strains had been isolated from clinical specimens of patients suffering from acute or persistent focalized Q fever. No patient objected the use of their strain for research purpose. Another 12 strains were isolated from ticks or animals. Among the 75 studied genomes, eight were obtained from Genbank (strains RSA493, RSA331, Dugway, CbuK_Q154, CbuG_Q212, 3262, MSUGoat_Q177, Z3055). All other genomes had been sequenced and assembled in our laboratory. Among those sequenced in our laboratory, the genomes of four strains were previously published (CB175, CB196, CB185, Schperling).
Genome assembly and functional annotation Prior to assembly, raw data quality was checked with the fastQC tool version 0. 11. 8 1  (Supplementary Table  1 ). Genomes sequenced with Solid were assembled by mapping using the CLC Genomics Workbench version 7. 5 (Qiagen). Genomes sequenced with Illumina Miseq were assembled using SPAdes version 3. 10  (Bankevich et al. , 2012). All C. burnetii genomes were annotated using Prokka version 1. 12-beta  (Seemann, 2014).
Comparison of Coxiella burnetii genome contents We performed a COG (Cluster of Orthologous Groups) analysis on the 75 whole genomes as well as on the core genome. We looked for insertion sequences using the ISfinder web server. We also explored the presence of resistance genes using the RAST server. Moreover, digital DNA-DNA hybridization (dDDH) and OrthoAni analysis were performed on the 75 genomes in order to evaluate the range of genomic similarity between strains  (Auch et al. , 2010; Lee et al. , 2016). Plasmids were determined in silico with blast and mapping. Virulence factors were determined using the VFDB database  (Chen, 2004 ). The IslandViewer web server was used to predict genomic islands  (Bertelli et al. , 2017).
Phylogenomic and pangenomic analysis Pangenome analyses along with core and non-core region analyses were performed with Proteinortho version 5, with an amino acid identity percentage and coverage threshold of 40 and 60%, respectively  (Lechner et al. , 2011). Prokka annotations were provided to Proteinortho as an input. Briefly, core regions were defined as genome sequences present in all 75 genomes, while the non-core regions were defined as those differentially present in studied genomes. Unique proteins in sequenced strains were identified from the orthologous list generated by Proteinortho after manual correction of split genes. We constructed a phylogenomic tree using the core region of the 75 C. burnetii genomes rather than few genomic loci. Coregenome CDS were inferred from the pangenome, concatenated and aligned using a custom Python script, and then used to construct a phylogenetic tree with MEGA6.
Logistic (exponential) principal component analysis We observed that the dataset mostly consisted of endocarditis cases from France (most strains were isolated from cardiac valves from French patients). The population of strains was organized into four groups identified by plasmids. QpDG was associated with animals such as rodents, cats, dogs, and MST60 (Figure  6 ). QpDV and MST1 were associated with acute Q fever (Figure  6 ). The association between QpDV and acute Q fever was also definitively confirmed in Tables 3,  4  and Figures  6 7 8. The QpH1 plasmid was rather associated with endocarditis in France. QpRS had an opposite behavior and was associated with the absence of acute Q fever, and this was consistent among all analyses (Tables  3, 4  and Figures 5-8 ). Pericarditis, pneumonia, hepatitis, and fever were associated with acute Q fever (Figures  5, 6 ).
Neuropathological studies Brain growth was evaluated according to the biometric data of Guihard-Costa and Larroche  [16]. Macroscopic analysis of gyration was assessed by means of the atlas of Feess-Higgins and Larroche  [14]. After fixation into a zinc-10% formalin buffer solution for at least one month, brain sections were obtained from all cortical areas and deep subcortical structures. Seven-micrometer paraffin embedded sections were stained using Haematoxylin-Eosin. The morphology of the different brain structures analysed was consistent with the foetal age.
1 Â 50 mm, 1. 7 mm) equipped with a frit (0. 2 mm, 2. 1 mm) and set at 40°C under the following gradient conditions: t0 90% A (H 2 O acidified with 0. 1% HCOOH) 10% B (acetonitrile); t(4 min) 60% A and 40% B. The return to initial conditions was held for 1 min. Wavelength detection was set at 278 nm. Chromatographic data were monitored by Empower software (Waters, Milford, MA, USA). The method was validated from 0. 05 to 5 mg/mL of ciprofloxacin with a linear model weighted by 1/X 2 (X = concentration). Precisions and accuracy were checked by injecting six replicates of QC samples over 3 days, at LOQ (0. 05 mg/mL); 0. 075 mg/mL; 0. 75 mg/mL, and 4 mg/mL. Accuracies ranged from 92% to 107%, with intraday and inter-day CV precisions below 5% and 13%, respectively. The limit of quantification was validated at 0.
ACKNOWLEDGMENTS We thank  Dwayne Roach  for the in vitro adaptation of  LUZ19v  to strain PAK, and  Thierry Pédron  for the preparation of phage lysates. This project was supported by a grant from  Institut Carnot France Futur Elevage and Institut Carnot Pasteur Maladies Infectieuses  to A. B. -M. and L. D. and from the  National Institutes of Health  ( 1R01AI46592-01  to L. D. ).
Acknowledgements Thank you to the children who took part in our research, and for the parents and teachers who facilitated their participation. Thank you to  Hayley White  and  Melanie Facon  for help with data collection, and to  Katie Gilligan-Lee ,  John Willoughby ,  Amelia Bennett ,  Mafalda Batista Da Costa ,  Iliana Misheva  and  Aan Ameen  for help with data coding, and to  Boris Gambet  for programming the virtual environments.
The crown areas of shade trees were determined by the drip-line horizontal ground-level crown projection method  (Bellow & Nair, 2003). Total shade levels within farms were based on the number of shade trees, and the estimated proportion of transmitted light reaching cocoa canopies based on previous data  (Abdulai et al. , 2017). Soil chemical properties were assessed in composite soil samples, pooled from the four corners and the center of each farm using a soil auger to a depth of 0-30 cm. Measurements included acidity (pH), percentage organic matter (%OM), and concentrations of nitrogen (N), phosphorous (P), potassium (K), calcium (Ca), magnesium (Mg) and sodium (Na). The tests were undertaken in the Ecological Laboratory of the University of Ghana, where soil pH was determined in a 1:1 soil to distilled water ratio using a Metrohm 691 pH meter  (Mclean, 1982).
Measurement of climatic conditions On-farm temperatures and relative humidity were obtained from two randomly selected farms in each cocoa community during the study. Two data loggers (iButton DS1923-F5#, Hygrochron Temperature and Humidity data logger, Maxim Integrated Productions, CA, USA) were installed in radiation shielded houses at 2 m above the ground and set to read temperature and relative humidity at 30 min intervals. We downloaded data every 3 months and calculated mean monthly temperatures and relative humidity for the two farms separately. Rainfall was measured with rain-gauges (Rosenborg Exclusive Tradløs Regnmåler, Model 35980, Carrin Electronics limited, Hong Kong) installed in the open in each community, and monitored for monthly and annual rainfalls throughout the study.
Analysis of data Following entry, data were ordered in Microsoft Excel, and exported to R version 3. 6. 3 (R Core Team, 2020) for analysis. Differences in farm characteristics and management were analyzed using one-way analysis of variance (ANOVA) with cocoa community (CC) as the single factor. Data relating to cocoa health and yield were analyzed according to a repeated measurements mixed model, using cocoa communities (CC), distances between cocoa tree and nearest shade tree (Distance in m), and crown area of nearest shade tree (CA in m 2 ) as fixed effects. We included individual farms, sampling month and year as random effects, and interaction terms of communities and the distance between shade trees and cocoa trees, shade tree crown area, and year as expressed in the full model below.
Y represents both continuous and ranked dependent variables. Y = α(CC) + β(Distance) + γ(CA) + λ(CC : Distance) + μ(CC : CA) + δ(CC : Year) + A(Farm) + B(Month) + C(Year) Continuous data (relating to yield and damaged pods due to mirids, shield bugs and black pod diseases) were analyzed using linear mixed effect models through the "lme4" package in R  (Bates et al. , 2015). Data on cherelles, matured and harvested pods were square root transformed when visual inspection showed deviation from normal distributions based on normality and homogeneity tests by plots of residuals against fitted values in normal Q-Q plots. Because dry beans of cocoa were obtained by bulking at farm levels, and within very few months of the year, we analyzed dry beans with community and year as factors. Ranked variables including canopy health and flower intensity, were analyzed by ordinal regression models from the "Ordinal-package" in R (Christensen, 2019).
The best fitted models were selected after series of backward model reduction procedures using the Akaike Information Criterium (AIC). For tests of significance, we used likelihood ratio tests to obtain p-values, followed by post hoc Tukey tests via the "emmeans" package in R  (Lenth, 2020)  to ascertain sources of variation where tests showed significant differences. We partitioned the variance explained by the fixed factors (Marginal (R 2 (m) )) and the variance explained by both the fixed and random factors (Conditional (R 2 (c) )) in the models from the "vegan" package  (Oksanen et al. , 2019)  and "MuMIn" package (Barton 2022) in R. We further calculated the proportional changes in variance (PCV) of the random effects of each of the models, and then explored the relationship between climatic conditions (rainfall and temperature) and cocoa productivity (dry weight of cocoa beans) by regression analysis for the three communities.
Acknowledgment The work was funded by  Danida [Ministry of Foreign Affairs of Denmark ] through " Climate Smart Cocoa Systems for Ghana, CLIM-COCOA" [DFC  project no:  16-P02-GHA ]. We also gratefully acknowledge personnel and data contributions from the  International Institute of Tropical Agriculture (IITA)  through the  CocoaSoils program , funded by the  Norwegian Agency for Development Cooperation (NORAD) , Grant number  RAF-17/0009-Cocoasoils , and from  Dr. Issaka Abdulai.
What part of the speech (i. e. the subject, the object or no agreement) the compound verbs must agree with depends on the auxiliary verb used. When the past participle is used with the auxiliary avoir, it has to agree in number 2 with its direct object when the latter is placed before it in the sentence. This is notably the case for object relatives considered here, in which the direct object is the relative pronoun que, whose number information is the same as its antecedent (even if its morphology-que, is the same in singular and plural). To correctly agree the past participle in object relatives, it is therefore necessary to identify the object relative pronoun, its antecedent and the auxiliary. Experimental Setting We reuse the dataset of  Li et al. (2021) : they have extracted, with simple heuristics a set of 68,497 such sentences after having automatically parsed the Gutenberg corpus with a BERT based dependency parser  (Grobol and Crabbé, 2021).
Probing Experiments In a first set of experiments, we propose to use linguistic probes to better identify where in the sentence the information about the number of the past participle is encoded. A probe is a classifier trained to predict linguistic properties from the language representations: achieving high accuracy at this task implies that these properties were encoded in the representation  (Hewitt and Manning, 2019). More precisely, we label each sentence of our dataset with the number of the target verb (i. e. singular or plural) and consider the task of predicting this label from each token representation of the sentence. We trained one logistic regression classifier per category of word 3  considering 80% of the examples as training data and the remaining 20% as test set. 1 ) on two subsets, which differ with respect to whether the transformers correctly or incorrectly predicted the number of the past participle.
Acknowledgments We sincerely thank the reviewers and Program Chairs for their careful reviews and insightful com-ments, which are of great help in improving the manuscript. This work was granted access to the  HPC resources of French Institute for Development and Resources in Intensive Scientific Computing (IDRIS)  under the allocation  2020-AD011012282  and  2021-AD011012408  made by  GENCI. We would also like to gratefully acknowledge support from the  Labex EFL , " Empirical Foundations in Linguistics"  ( ANR-10-LABX-0083 ).
M [8] [9] [10] [11]  However, most analyzed results from retrospective cases series and studied minor LR or LR at low difficulty level. These studies also included various types of LR resulting in additional confounding factors. Studies focusing on major hepatectomy eg, right hepatectomy (RH) or extended RH (ERH), are limited to date. 12 ajor hepatectomy is technically demanding, which hinders the development of minimally invasive surgery in LR. An analysis of the American College of Surgeons National Surgical Quality Improvement Program data showed that major LR was one of the risk factors for open conversion during minimally invasive hepatectomy. 13 The robotic system was developed to overcome some of the challenges in laparoscopic surgery. With the magnified view and the 7 degrees of movement of the EndoWrist (Intuitive Surgical), the robotic system allows fine dissection of individual vessels at the hilar region and the hepatocaval region during RH/ERH.
Methods This is an international multicenter retrospective casecontrol analysis of patients undergoing L-RH/ERH or R-RH/ ERH at 29 centers between January 2008 and December 2020. All institutions obtained their respective approvals according to their local center's requirements. This study was approved by the Singapore General Hospital institution review board, and the need for patient consent was waived. The deidentified data were collected in the individual centers. These were collated and analyzed centrally at the Singapore General Hospital. In this study, only patients who underwent pure laparoscopic or robotic-assisted laparoscopic surgery were included. Laparoscopic-assisted (hybrid) and hand-assisted laparoscopic resections were excluded. Similarly, patients undergoing donor hepatectomy for transplant, associating liver partition and portal vin ligation for staged hepatectomy, and hepatectomy with bilio-enteric anastomoses were excluded.
This conservative number of 50 cases was chosen based on the recently published systematic review,  22  which reported that the overall learning curve of L-LR was 50 cases and for R-LR was 25 cases. Furthermore, the learning curve for minimally invasive liver resection was reported to be decreasing from 48 cases in the 1990s to 24 cases in 2015. All analyses were done in R version 4. 0. 0 (R Foundation) with package 'MatchIt' and 'optmatch', and 2-sided P <. 05 was regarded to indicate statistical significance.
The development of the world of business and trade cannot be separated from technological advances. Applications for ordering food and beverages facilitate consumers to order online by using smartphone when they do not have much time to come directly to the store (offline). The aim of this study is that to find out Shopee Food Indonesia, which will be a strong competitor for other food and beverage service companies. This study was a quantitative research using SPSS 25. The populations in this study were consumers who used Shopee Food with a sample of 280 respondents. Meanwhile, the analysis technique used path analysis and Sobel test.