dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions This study represents our first steps in producing geologically reasonable training sets for ML and geophysical inversion applications. We have used Noddy to generate a very large, open-access 1-million-model set of 3D geology and resulting gravity and magnetic models as ML training sets. These training sets can also be used as test cases for gravity and/or magnetic inversions. The work presented here may be a first step to overcoming some of the fundamental limitations of applying these techniques to natural geoscientific data sets.
Acknowledgements. We acknowledge the support from the Loop consortia. This is MinEx  CRC Document 2021/52. We would like to thank  AARNet  for supporting this work by hosting the 500 GB model suite at CloudStor. Financial support. This research has been supported by the  Australian Research Council  (grant nos. LP170100985 ,  DE190100431  and  IC190100031 ), the  Mineral Exploration Cooperative Research Centre  and the  National Natural Science Foundation of China  (grant no. 41671404 ). Review statement. This paper was edited by  Jens Klump  and reviewed by  Jiajia Sun  and one anonymous referee.
This neutralino is considered stable enough on detector scales that it can only be detected through missing transverse momentum, unless it approaches or exceeds the top-quark mass, when it can decay through the RPV coupling. These events were generated at leading order using the Monte Carlo (MC) program M 5_ MC@NLO [21] version 2. 61 together with the RPV MSSM UFO model  [22]. Shower evolution and hadronisation was performed by P 8 [23] version 8. 23. The NNPDF2. 3 [24] PDF was used with a set of tuned parameters called the A14 tune [25]. All RPV couplings except  231 were set to zero, so only the smuon RPV interaction is considered. Supersymmetric particles other than the neutralino and smuon were decoupled by setting their masses to a large value. The M hard processes permitted at most one additional light parton in the final state, and they were matched to the P parton shower using the CKKW-L [26] merging scheme.
In particular, for the model-independent statistical analysis of the measured  in this Letter it is assumed that the SM hypothesis covers values of  less than or equal to one, an assumption that is checked in data in the analysis event selections 2. Thus evidence for new physics would only be claimed if the BSM contribution is strong enough to overcome any residual biases that have not been accounted for. For calculating limits on signal model parameters the strength of the residual biases are estimated from an SM-enriched control region. The structure of this Letter is as follows: in Section 2 the ATLAS detector is described and Section 3 details the datasets used in the analysis. Section 4 describes the object reconstruction and Section 5 defines the regions of phase space that  is measured in and how experimental effects that could impact its measurement are corrected for, including the verification of these corrections with the measurement of  in SM-enriched control regions.
√︃   2  , are given for data to support the choice made to model the yields with a Poisson distribution. The yields in the  +  - channel are constrained to match the data by the fit. --   Expected and observed exclusion limits are shown for RPV-supersymmetry models which allow for production of a single smuon (decaying into a muon and neutralino) in association with a top quark (decaying leptonically). The expected limits is calculated with the asymptotic approximation, by considering when there is a 50% chance of exclusion at 95% CL s , under the SM-only hypothesis. The smuon is produced through the  231 coupling, which takes values up to 1. 5. All limits are computed at 95% CL and all uncertainties are included. Expected and observed exclusion limits are shown for models featuring production of a single scalar leptoquark which decays into a muon and charm quark.
Acknowledgements We thank  CERN  for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of  ANPCyT , Argentina; YerPhI, Armenia;  ARC, Australia ;  BMWFW  and  FWF , Austria; ANAS, Azerbaĳan; SSTC, Belarus;  CNPq  and  FAPESP, Brazil ;  NSERC ,  NRC  and  CFI ,  Canada ; CERN;  ANID, Chile ;  CAS ,  MOST  and  NSFC, China ;  Minciencias ,  Colombia; MSMT CR ,  MPO CR  and  VSC CR, Czech Republic ;  DNRF  and  DNSRC, Denmark ;  IN2P3-CNRS  and  CEA-DRF/IRFU , France; SRNSFG, Georgia; BMBF,  HGF  and  MPG , Germany; GSRI, Greece; RGC and  Hong Kong SAR, China ;  ISF and Benoziyo Center, Israel ;  INFN, Italy ;  MEXT  and  JSPS, Japan ; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR;  MES of Russia  and  NRC KI , Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain;  SRC and Wallenberg Foundation, Sweden ;  SERI ,  SNSF  and  Cantons of Bern and Geneva, Switzerland; MOST, Taiwan ;  TAEK, Turkey; STFC, United Kingdom ;  DOE  and  NSF ,  United States of America.
In addition, individual groups and members have received support from  BCKDF ,  CANARIE ,  Compute Canada  and  CRC ,  Canada ;  COST ,  ERC ,  ERDF ,  Horizon 2020  and  Marie Skłodowska-Curie Actions ,  European Union ;  Investissements d'Avenir Labex, Investissements d'Avenir Idex  and  ANR, France ;  DFG and AvH Foundation ,  Germany; Herakleitos ,  Thales  and  Aristeia  programmes co-financed by  EU-ESF  and the  Greek NSRF, Greece; BSF-NSF  and GIF, Israel; Norwegian Financial Mechanism 2014-2021, Norway;  NCN  and  NAWA, Poland ;  La Caixa Banking Foundation ,  CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden ;  The Royal Society and Leverhulme Trust ,  United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from  CERN , the ATLAS Tier-1 facilities at  TRIUMF (Canada) ,  NDGF (Denmark, Norway, Sweden) ,  CC-IN2P3.
Frequency calculations were performed at the same level of theory to obtain the total enthalpy (H) and Gibbs free energy (G). The reaction enthalpies (∆H) and Gibbs free energies of reaction (∆G) of the studied molecules were calculated as the difference of the calculated H and G between the reactants and products, respectively. The excited states and UV-Vis electronic transition spectra were calculated in the gas phase using the time-dependent (TD) DFT method  [36]  within the Tamm-Dancoff approximation  [37]  at the PBE0-D3/6-31 + G** level of theory. The Maestro 9. 7 program  [38]  was used for the visualization of calculated UV-Vis spectra.
Chemical Composition Figure  3  shows the FTIR spectra of the samples prepared for TDBS experiments. The curing conditions correspond to the minimum refractive index (Figure  1  and Table  1 ) when porogen was fully (or almost fully) removed. One can see that the chemical composition of all these films was very similar. energy (G). The reaction enthalpies (∆H) and Gibbs free energies of reaction (∆G) of the studied molecules were calculated as the difference of the calculated H and G between the reactants and products, respectively. The excited states and UV-Vis electronic transition spectra were calculated in the gas phase using the time-dependent (TD) DFT method  [36]  within the Tamm-Dancoff approximation  [37]  at the PBE0-D3/6-31 + G** level of theory. The Maestro 9. 7 program  [38]  was used for the visualization of calculated UV-Vis spectra.
The pressure sensors are piezoelectric sensors PCB113B26 and transmit a voltage signal with a rise time ≤1 µs. The constructor defined the rise time in shock tube and the sensor is in the reflected position. The signals then pass through an amplifier before being transmitted to the data acquisition system with a range of 10 V. The data acquisition system is a Dewetron DW-801 with 16 channels and a sampling rate of 1 MHz/channel independently of the acquisition time. Thanks to its large storage capacity, this system allows long periods of pressure acquisition, while maintaining maximum signal quality. However, in order to avoid storing unnecessary data, only 5 ms are recorded after the explosion is initiated, which is more than necessary to measure the passage of the shock wave in our configurations.
The first camera, called C 1 , records the horizontal propagation of the shock wave, while the second camera, called C 2 , records the shock wave propagation in the vertical direction thanks to a tilted mirror. The surface of the mirror is 1 m 2 and is inclined about 34 • from the horizontal direction. The cameras are focused to observe the shock wave propagation along the axis that passes through the center of the explosive charge and the center of the obstacle. Figure  3  illustrates the optical installations. The recorded images were processed using the open-source software ImageJ. The processing method used is background subtraction.
Thus, the most extensive study dedicated to the phosphorylation of bovine caseins is undoubtedly the study reported by Fang et al. They investigated the variation in phosphorylation degree of α S -caseins among milk of individual cows and the relationships among different phosphorylation isoforms of α S -caseins through the analysis of morning milk samples from 529 French Montbéliarde cows using liquid chromatography (LC) coupled with ESI-MS  (Fang et al. , 2016). Capillary electrophoresis was also evaluated for its capability to analyze phosphopeptides. Ultra-low flow capillary electrophoresis was reported to significantly improve the detection sensitivity of phosphopeptides in equal sample load and equal sample concentration conditions while providing complementary data to LC -MS  (Heemskerk et al.
Gold standard ratings of the videotaped interviews were also provided, which allowed the research team to increase rater competency. The trained research psychologists had previously received full training regarding the other measures used in this study [PANSS, SANS, and Calgary Depression Scale for Schizophrenia (CDSS)]. Once recruitment for this study was ready to begin, patients were contacted to participate in this study. All participants received a full explanation of the study and its objectives before giving their informed written consent. Participant inclusions began with collecting sociodemographic data and treatment dosages before administering the different clinical assessments. Interrater reliability was possible with the assistance of the second trained research psychologist who scored simultaneously the CAINS assessment for 22 participants.
Statistical analysis The effect of composting time on the analysed physicochemical parameters for H5 and H6 was analysed by one-way analysis of variance (ANOVA) with two replicates (P < 0. 05). The variability study of the composting process, between H5 and H6, is carried out by one-way ANOVA test (two replicates) for all the analysed parameters and for the nine analysis times. The effect of C/Ni and TF factors on the physicochemical parameters at the end of composting for H1 to H6 was studied by unbalanced two-way ANOVA (P < 0. 05) without replicates. Tukey's test is calculated only for factor for which the effect is significant. The software used is the SPSS software (Version 20).
The highest heap maximum temperatures recorded were 56. 6 °C on the 35th day and 61. 3 °C on the 31st day for H5 and H6 respectively. During maturation, the temperature converges to an equilibrium with the ambient temperature whether it is for the top, the middle, or the bottom of the pile, thus indicating the stability of the compost. H5 and H6 have kept mesophilic and thermophilic temperatures for similar lengths (45 days and 42 days respectively) since they are identical. Table  4  summarizes data on mesophilic and thermophilic durations and the maximum temperatures (T °C, max) of the six heaps. As H1 and H2, H5 and H6 kept the temperature less than H3 and H4 because they have less straw and therefore less porous. Generally, the heaps in which C/Ni is high (H3, H4) recorded a delay in reaching the thermophilic phase given the low nitrogen content compared to carbon which delayed microbial proliferation.
Study design MRI/MRS protocols MRIs were done without sedation during the infants' natural sleep. Infants were positioned inside the scanner wrapped in a vacuum pillow and monitored with electrocardiography and pulse oximetry. Earmuffs were used to minimize noise reduction. MRI brain scans were performed using a 1. 5T or 3T MRI system with a dedicated 8-channel head coil. The MR devices with a magnetic field of 1. 5T were Philips Achieva R , Philips Intera R , Toshiba MRT 200 R , GE SignaHdxt R (General Electric Healthcare), Siemens Avanto R , Siemens Symphony R , and Siemens SymphonyTim R (Siemens Heathineers). The MRI device with a 3T magnetic field was the Philips Achieva R (Philips Healthcare). We obtained T2 datasets by using an axial T2 morphological sequence (fast spin echo/turbo spin echo with a 90 flip-back pulse); slice thickness, 3 mm; pixel size, 0.
Choline levels increase with cell proliferation, membrane turnover, myelination, or inflammation and decrease with age as rapid brain growth in the neonatal period decelerates  (8, 24). Data were processed using proprietary software developed on IDL (Interactive Data Language, Research System Inc. , Boulder, CO). Spectral processing and spectral reconstruction were performed using the automated shimming program provided by the manufacturer after an additional water suppression using the HLSVD-MRUI FORTRAN code. Spectra were fitted using the AMARES-MRUI FORTRAN code  (17)  by CEREMM in Marseille  (25, 26).
Data collection To determine gestational age, we based our best estimate from the last menstrual period date and an early prenatal ultrasonogram. The antenatal and obstetrical data collected at birth were: Complete antenatal corticosteroid therapy (two injections of corticosteroids, 24 h apart). Classification of prematurity related to five causes: preterm labor, preterm premature rupture of membranes, hypertensive disorders without suspected fetal growth restriction (FGR), hypertensive disorders with suspected FGR, and placental abruption after an uncomplicated pregnancy, suspected FGR without hypertensive disorders. Neonatal morbidities: Intraventricular Hemorrhage (IVH), Cystic Periventricular Leukomalacia stages II or III (cPVL), Necrotizing Enterocolitis (NEC) stage 3 or greater, Retinopathy of prematurity (ROP), stage 3 and/or laser treatment.
Data collection and characteristics of participants The fourth and fifth authors conducted semi-structured interviews with participants between September 2020 and April 2021. Although data collection overlapped with the second and third waves of COVID-19 in Québec, interviews focused on the initial planning of large-scale testing during the first wave, and discussed adaptations made during the first, second, and third waves. Interviews were conducted in French via Zoom. They were audio recorded and transcribed in their original language. Excerpts used in study reports were subsequently translated into English by the first author, fluent in French and English. A total of 17 interviews, lasting between 30 minutes and 1 hour and a half, were conducted with 19 stakeholders. The participants, 17 women and two men, came from various organisations and played different roles in largescale testing (Table  1 ).
Data analysis We analysed the interview data using thematic analysis  [29]. The first author read the interview transcriptions multiple times and wrote memos to note initial code and theme ideas, as well as preliminary analytical insights. Data were analysed deductively and inductively in NVivo. Three initial transcripts were coded to create a preliminary list of codes, followed by the systematic coding of all transcripts  [30]. As per an inductive coding approach, codes were developed inductively from the data to closely reflect the words of participants. As per a deductive coding approach, these codes were subsequently fitted into the four axes of the theoretical bricolage previously described  [31]. Consequently, while codes and categories ascribed to interview excerpts were developed inductively, the themes used to regroup them were deductive, reflecting the content of the theoretical bricolage  [31].
Funding This work was supported by the  Canadian Institute of Health Research  under Grant number  DC0190GP ; the  French National Research Agency  ( ANR Flash COVID 2019 ) Grant number  ANR-20-COVI-0001-01 ; and the  Japan Science and Technology Agency (JST J-RAPID)  grant number  JPMJJR2011. The authors thank the  Quebec Population Health Research Network (QPHRN)  for its contribution to the financing of this publication.
| Electronic olfactometer: The MiteMap system Detailed technical, mechanical and computer information is available from the MiteMap github on a Zenodo repository (Data Availability Statement). The core of the tool was an ARM processor single board nanocomputer (Raspberry Pi 3 model B, Raspberry Pi Foundation), connected to a camera (Raspberry Pi PiNoir Camera Module V2, Raspberry Pi Foundation). The system was assembled inside a body made out of LEGO ® pieces and inserted into a cylindrical polyvinyl chloride (PVC) structure of approximately 20 cm of height and 4. 0 cm base radius (Figure  1 ). The cylindrical structure was assembled on a PVC box containing the test arena (rigid plastic T-shaped chamber, Figure  1 ). A threaded metal rod attached to the LEGO ® body was used to keep the camera at the correct focal distance (4.
0 cm) from the test arena. During analysis, the end of the rod was lying directly on the glass ceiling of the arena and was capped with a nylon nut to protect the glass. A 76. 5 mm diameter ring of 940 nm infrared lightemitting diodes (LEDs) was placed at the bottom of the PVC box below the experimental arena (40 mm diameter) to transilluminate the test arena (LED strip Solarex). The Raspberry Pi nanocomputer was programmed in Python 3 using openCV library (https://opencv. org/) F I G U R E 1 Schematic representation of the MiteMap system. The exploded view on the left represents the sandwich that forms the arena once assembled (from the top glass panel to the bottom glass panel) positioned in the lower part of the PVC chamber (tube and rectangular base, LED strip). The mite under test is enclosed in the circular hole of the upper polytetrafluoroethylene (PTFE) plate, on the Joseph paper.
No pictures are stored by default to save memory space, although it is possible to collect snapshots manually or instruct the system to save a picture in specific conditions. In addition, a live feed allows us to monitor the evolution of the path followed by the mite. Two sets of images show the arena live and allow us to observe the mite itself (raw images) as well as its last 20 positions (processed images), respectively. The last 20 positions of the tested mite are visualized by drawing a tail of decreasing thickness according to the time elapsed since the current position. Lastly, a tab of the web interface allows us to visualize the heatmap of the mite's positions from the beginning of the test. The heatmap as well as all the data in csv format are downloadable. The test arena was built through the creation of a so-called "sandwich": a sheet of 100% cellulose nitrate Joseph paper (23 g/m 2 ; 0.
A living adult female mite was then introduced into the arena (i. e. , circular hole in the upper PTFE plate) using a thin paintbrush by gently shifting the upper glass plate, then the whole sandwich was quickly aligned and sealed. The sandwich was inserted into the test chamber, which was then closed as described above. The Python program was launched via the buttons on the MiteMap. Each bioassay lasted exactly 10 min starting from the first movement detected by the camera inside the arena and was checked via the web interface. We checked the correct positioning of the virtual arena boundaries on the real arena via the live feed at the beginning of each test for all MiteMaps (MiteMap interrupted in case of mismatch and restarted after repositioning). In the case of T A B L E 1 Summary of the tested substances and modalities of bioassays | 51 prolonged inactivity at the beginning of the bioassay (i.
| Statistical analysis We first examined the results of experiments with the two reference substances (geraniol and NH 3 ) to establish how mite responses to odors are expressed in our system. Then we successively treated the results of experiments with the kairomonal patented blend and those obtained with mite odors. We automatically grouped the heatmaps into folders by modality (script of the function available on the Zenodo repository; see below) and visually screened the individual heatmaps by modality to identify possible recurrent path patterns (qualitative approach). To characterize in a quantitative way the response of D. gallinae to the proposed odor in MiteMaps, we measured the proportion of time spent in the half of the arena containing the odor source (division by vertical diameter).
To assess a preference for the proposed odor, we assigned each mite to a choice based on the ratio of time spent in the half containing the odor source as follows: >0. 5, odor chosen, ≤0. 5, odor not chosen. We then analyzed the resulting binary data set using two-tailed binomial tests based on the null hypothesis that the probability of scores for the half containing the odor source or for the opposite half is equal to 50%. Lastly, to evaluate the effect of the odor on the general locomotor activity of the mite, we calculated the average speed during the experiment and the proportion of time spent immobile. We conducted Kruskal-Wallis tests to assess whether any significant difference (p < 0. 05) was detectable among modalities in the three batches of data sets and pairwise Wilcoxon tests on significant batches to identify pairs with significant differences.
| Validation of the MiteMap olfactometric system and qualification of mite responses During preliminary experiments, we estimated the risk of signal loss during recording or inconsistent signal by confronting via the web interface live feed and data recording during 25 tests (10 min sequences for one mite each). We did not observe any erratic movement of the mites during these experiments. Adding a mite to the upper surface of the sandwich produced the expected loss of signal acquisition when the mite passed over the arena, as it represented a second target. We did not observe any error in the recordings at that step. When we screened all the heatmaps, we observed a few cases of erroneous points, recorded outside the arena. Filters were applied to exclude them from the analysis. Examination of individual heatmaps of the controls revealed heterogeneity in the amplitude and shape of the path traveled by the mites, with some remaining less mobile than others and traveling only a portion of the arena (Figure  2 ).
gallinae. This new knowledge helps to fill important gaps reported as impediments to progress in the management of D. gallinae in the DISCONTOOLS database (https://www. discontools. eu/database/ 112-poultry-red-mite. html). Furthermore, while the general profile of said responses seems conserved across populations, our results suggest potential interpopulation variations in their magnitude, or the concentration threshold needed to obtain a specific behavior. If behaviors differ significantly among farms, it will be necessary to consider the development of different control or monitoring solutions adapted to the farm or geographical area to develop IPM strategies integrating semiochemicals in a relevant way. In addition, a better understanding of the genetic determinants and consequences of the interindividual variation of responses to kairomone is a major issue to take advantage of such attractant in farm conditions: if indeed the response oscillates between attractive and repulsive within populations due to co-occurrence of contrasting foraging strategies, setting the effective concentration will require taking into account the ratio of responses.