dataesr/scientific-paragraphs-categorization huggingface dataset:
Temperature 3. 5. 1. 25 Mg(α, n) 28 Si. The 25 Mg(α, n) 28 Si reaction is most influential during explosive Ne/ C-shell burning, at a temperature around 2. 3 GK (E cm = 1. 8-3. 5 MeV). It acts as a neutron source for the neutron-induced reactions described above, as well as reducing the 25 Mg available for proton capture to 26 Al. The reaction rate currently reported in REACLIB  [274]  comes from the NACRE compilation  [229]. Above 2 GK, the rate comes from Hauser-Feshbach calculations and below this temperature it is based on the direct measurements of Van der Zwan and Geiger  [275] , Anderson et al  [276]  and Wieland  [277]. Between 0. 86 and 3 MeV, only the Wieland data are used, even though this work is unpublished. However, Iliadis et al  [241]  questioned both the decision to use HF rates above 2 GK, as experimental data are available, and the exclusion of the Anderson et al  [276]  data.
This reaction rate is now considered to be sufficiently well constrained for this purpose. 3. 5. 3. 24 Mg(n, γ) 25 Mg and 25 Mg(n, γ) 26 Mg. Iliadis et al  [278]  identified the 24 Mg(n, γ) reaction as the most important radiative neutron capture reaction impacting 26 Al abundances. For example, during explosive C/Ne burning a 2 times higher 24 Mg(n, γ) rate is predicted to yield a change in 26t Al abundance by a factor 1. 6. Moreover, a correct interpretation of isotopic ratios in stardust spinel grains, which contain both Mg and Al (section 1. 4), requires an accurate 25 Mg(n, γ) 26 Mg reaction cross section as both this reaction and the 26 Al decay lead to the production of 26 Mg. The Maxwellian-averaged cross sections (MACS) for these reactions were recommended by the Karlsruhe Astrophysical Database of Nucleosynthesis in Stars  Figure 16.
400 5. 41 × 10 -02 8. 30 × 10 -02 1. 29 × 10 -01 0. 450 1. 73 × 10 -01 2. 65 × 10 -01 4. 10 × 10 -01 0. 500 4. 30 × 10 -01 6. 59 × 10 -01 1. 02 × 10 +00 0. 600 1. 63 × 10 +00 2. 49 × 10 +00 3. 86 × 10 +00 0. 700 4. 08 × 10 +00 6. 25 × 10 +00 9. 66 × 10 +00 (Hungary). BC acknowledges the support from the ERC Consolidator Grant (Hungary) funding scheme (Project RADIOSTAR, G. A. n. 724 560), the Hungarian Academy of Sciences via the Lendület project LP2014-17, and the National Science Foundation (NSF, USA) under Grant No. PHY-1430152 (JINA Center for the Evolution of the Elements). RR and DK are thankful for support from BMBF 05P19RFFN1 and the European Research Council under the European Unionsʼs Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement N. 615126. AK acknowledges the funding from the European Unions Horizon 2020 research and innovation program under grant agreement No.
771036 (ERC CoG MAIDEN). DB acknowledges support from the National Science Foundation under grants PHY-2011890 (University of Notre Dame), PHY-1430152 (JINA Center for the Evolution of the Elements), and OISE-1927130 (International Research Network for Nuclear Astrophysics). CLW acknowledges support from the UK Science and Technologies Facilities Council (STFC), projects ST/P004008/1 and ST/M006085/1, and the European Research Council ERC-2015-STG Nr. 677 497. AS acknowledges support from the U. S. Department of Energy through grant DE-FG02-87ER40328 (UM). JJ acknowledges support by the Spanish MINECO Grant PID2020-117252GB-I00, by the E. U. FEDER funds, and by the AGAUR/ Generalitat de Catalunya grant SGR-661/2017. Finally, we thank the ChETEC-INFRA project funded from the European Unions Horizon 2020 research and innovation programme under Grant agreement No 101008324.
Acknowledgments This paper is based upon work from the  'ChETEC' COST Action  ( CA16117 ), supported by  COST (European Cooperation in Science and Technology)  and the  National Science Foundation  under Grant No. OISE-1927130  (IReNA). AML also acknowledges support from  STFC (Science and Technology Facilities Council ). PA thanks the trustees and staff of the  Claude Leon Foundation  for support in the form of a postdoctoral fellowship. MP acknowledges the support of  NuGrid, JINA-CEE (NSF  Grant  PHY-1430152 ) and  STFC  (through the  University of Hulls Consolidated Grant   ST/R000840/1 ), and ongoing access to viper, the  University of Hull High Performance Computing Facility. MP acknowledges the support from the ' Lendület-2014' Programme of the Hungarian Academy of Sciences.
82 × 10 -02 0. 400 5. 41 × 10 -02 8. 30 × 10 -02 1. 29 × 10 -01 0. 450 1. 73 × 10 -01 2. 65 × 10 -01 4. 10 × 10 -01 0. 500 4. 30 × 10 -01 6. 59 × 10 -01 1. 02 × 10 +00 0. 600 1. 63 × 10 +00 2. 49 × 10 +00 3. 86 × 10 +00 0. 700 4. 08 × 10 +00 6. 25 × 10 +00 9. 66 × 10 +00 (Hungary). BC acknowledges the support from the ERC Consolidator Grant (Hungary) funding scheme (Project RADIOSTAR, G. A. n. 724 560), the Hungarian Academy of Sciences via the Lendület project LP2014-17, and the National Science Foundation (NSF, USA) under Grant No. PHY-1430152 (JINA Center for the Evolution of the Elements). RR and DK are thankful for support from BMBF 05P19RFFN1 and the European Research Council under the European Unionsʼs Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement N. 615126. AK acknowledges the funding from the European Unions Horizon 2020 research and innovation program under grant agreement No.
Frequency extraction and classification Computing the Fourier transforms (FT) of the light curves is helpful in examining the periodic signals presented in the data. We used the dedicated software FELIX 2  to perform frequency extraction from the coordinated light curves. The significant frequencies were prewhitened in order of decreasing amplitude until it goes down to the adopted threshold of 5. 2 times the local noise level, which is defined by the median value of the amplitude in the LSP. This signal-to-noise ratio limit of S /N = 5. 2 was adopted as a compromise between the testing results from 2-yr Kepler and 27-d TESS photometry  (Zong et al. 2016b; Charpinet et al. 2019 ). The highest peak was meant to be extracted when several close frequencies were encompassed within 0. 4 µHz, namely, about 3 × ∆ f , where ∆ f = 1/T is the frequency resolution ∼ 0.
We finally chose the fitting function by increasing the index of k after a quantitative evaluation. Then the Markov chain Monte Carlo (MCMC) method was applied to derive the uncertainties for the optimal fittings. MCMC is implemented by the EMCEE code (Foreman-Mackey et al. 2013) and sample posterior distributions of parameters. We can see the detailed processes for such analysis in Sect. 3 of  Ma et al. (2022). Table  2  lists the information of each fitting function for the 45 frequencies with AM and FM, including the fitting coefficients and the correlation between AM and FM. Figure  4  is a gallery composed of eight portraits that depict AM and FM of each frequency through various fitting functions, G k (t). Except for the modulating patterns of f 4 ∼ 254. 6 µHz, they clearly exhibit evident AM and FM in various patterns, with a majority of them containing a sinusoidal component.
2019). We list the information of those RVs in Table  F , with the attributes of observation time, RVs, and associated errors, as well as the S/N values. We first adopted the method of phase dispersion minimization (PDM) to derive the period of the RV curves. Then we used the Keplerian orbit to fit the radial velocities around the PDM period ∼ 0. 5699 d (see Fig. 7, a ). The fitting result of the orbital solution is obtained through the EMCEE code (see, Foreman-Mackey et al. 2013, for a review) and their parameters are provided in Table  3. We then derived the mass limit, M 2 ≥ 0. 36 M ⊙ , for the companion based on the mass function and assumed the sdB star with a canonical mass of M 1 = 0. 47 M ⊙. Our results are overall consistent with the orbital parameters derived from previous literature  (Moran et al.
1999; Geier et al. 2008; Schaffenroth et al. 2023a) , as compared in Table  3  The LSP of the photometry clearly shows low-frequency signals that are attributed to the orbital brightness variations. Their frequencies are derived with ∼ 20. 3107 ± 0. 0015 µHz, or Table  3. Orbital parameters derived by the EMCEE code v. s. the results from the literature. Notes. The parameters P, γ, K, ω, e, a, and i denote the orbital period, system velocity, the semi-amplitude for the primary star, the angle of the pericenter, the orbital eccentricity, the orbital semi-major axis, and the orbital inclination of the binary system, respectively. References: (  1  0. 569851 ± 0. 000042 d, for the primary peak (see Fig. 7, b ). We note there is some phase difference between the photometry and RV curve, mainly introduced by the fact that these two curves were folded into phase by their own ephemeris and optimal periods with very slight differences.
These modulating patterns probably offer observational constraints to future calculations of nonlinear amplitude equations. This shorter timescale modulation should be explored in other sdB stars that had been observed by K2 and TESS. We finally note that this finding could jeopardize the exoplanet detection via the time-pulsation method  (Silvotti et al. 2007 (Silvotti et al. , 2018)). Because the phase modulation can hardly be well derived if we do not have information a priori on the frequency modulations. It is convenient to see that the period spacing of ℓ = 2 sequence is relative to ℓ = 1 sequence with ∆Π ℓ=2 ≈ ∆ Π ℓ=1 / √ 3. Similar to  Ma et al. (2022) , we performed the Kolmogorov-Smirnov (KS) test to identify the average spacing of g-modes in PG 0101+039. This popular test returns spacing correlations as highly negative values for the most common spacing in a data set  (Kawaler 1988).
Acknowledgements. We acknowledge the support from the  National Natural Science Foundation of China (NSFC)  through grants  11833002 ,  12273002 ,  12090040 ,  12090042 ,  11903005  and  12203010. S. C. is supported by the  Agence Nationale de la Recherche (ANR, France)  under grant  ANR-17-CE31-0018 , funding the  INSIDE  project, and financial support from the  Centre National d'Études Spatiales (CNES, France). The authors gratefully acknowledge the  Kepler  team and all who have contributed to making this mission possible. Funding for the Kepler mission is provided by  NASA's Science Mission Directorate. The  LAMOST Telescope  is a  National Major Scientific Project  built by the  Chinese Academy of Sciences. Funding for the project has been provided by the  National Development and Reform Commission.
However, because of the lower atomic mass, low-mass WIMP scattering off argon produces more energetic recoils, with a higher probability of being detected above the threshold. This compensates for the lower cross section in argon compared to xenon and makes DarkSide-50 the most sensitive experiment to date to WIMP interactions in the ½1. 8; 3. 0 GeV=c 2 mass range, with a fiducial LAr target of only ∼20 kg  [6]. Recently, the DarkSide-50 Collaboration reanalyzed data from calibration campaigns with radioactive sources and measured, with high-accuracy, the LAr ionization response (Q y ), shown in Fig. 1 , to electron (ER) and nuclear (NR) recoils down to a few hundred electron-volts  [16]. This measurement represents the first step of a comprehensive re-analysis of the entire DarkSide-50 data-set to provide improved constraints on low-mass WIMP-nucleon interactions.
III. DATA SELECTION The dataset reported in this paper consists of 653. 1 livedays of underground argon data, taken from December 12, 2015, to February 24, 2018, with an average trigger rate of 1. 54 Hz. WIMPs may eventually scatter only once in the LAr target because of the extremely low cross section. Since each particle interaction is associated with an S2 pulse, only events with a single S2 pulse are considered for this analysis. Given the low-energy regime and the low detection efficiency of S1 photons (0. 16 AE 0. 01  [22] ), not all of these events have an associated S1 pulse. Therefore, selected events are divided into two categories, depending on whether they have one (S2-only) or two pulses (S1 and S2). The only exception is made in the presence of "echoes", i. e. , electrons extracted by S1 or S2 128 nm photons from the cathode, via photoelectric effect  [23].
Comparison and ratio between LAr ionization responses to nuclear (NR) and electronic (ER) recoils, as a function of the deposited energy. The two energy scales were measured using DarkSide-50 data and datasets from the ARIS  [17]  and SCENE  [18]  experiments, and are reported in Ref. [16]. 1 From now on, the term acceptance will be referred to as signal acceptance. Monte Carlo simulations  [22]. More details on this volume fiducialization can be found in Ref. [16]. The measured S2 yield, defined as the mean number of photoelectrons per ionization electron extracted in the gas pocket, is 23 AE 1 pe=e -, for events localized beneath the central PMT  [6]. The radial dependence of the S2 yield, already discussed in Ref. [22] , is here corrected to the value at the center of the TPC, using a correction map extracted from 83m Kr calibration data  [16].
V. The final sample is shown in Fig. 2. The S2-only sample is distributed in the energy region where most of the signal is expected, while the S1 þ S2 sample, distributed at the higher energies because of the S1 detection threshold, is key in constraining the background model discussed in the next section. The combined sample contains about 350,000 events and corresponds to a fiducial volume exposure, including the spurious electron veto, of 12306 kg d. The current dataset livetime is about 80% larger than the one used in the 2018 analyses, which included data up to April 2017  [6].
A. Internal background 39 Ar and 85 Kr specific activities in underground argon were estimated in the first 70-days DarkSide-50 dataset at 0. 73 AE 0. 11 mBq=kg and 2. 05 AE 0. 13 mBq=kg, respectively, by fitting S1 spectra  [19]. The 85 Kr specific activity was then corrected by its decay time (τ 1=2 ∼ 10. 8 yr) to 1. 84 AE 0. 12 mBq=kg, averaged over the lifetime of the dataset used in this analysis.
B. External background This analysis is based on extensive simulation of each external background component as measured in the material screening campaign, unlike the 2018 analyses where the external background model was extrapolated from high-energy fits. The main sources of external x ray and γ background are the radioactive contaminants in PMTs and in the stainlesssteel cryostat, both characterized with an extensive materials assay campaign. These measurements and their associated errors, once corrected for decreased activity due to elapsed time at the dataset date, are the inputs for the external background model. The PMT components, which dominate in terms of radioactivity, are the stems in the back of the PMT, the ceramic around the dynodes chain, and the PMT body made of kovar. In contrast, the cryostat is composed only of stainless steel, where contamination is uniformly distributed.
V. BACKGROUND-ONLY FIT The analysis is based on a binned profile likelihood, L, implemented through the RooFit/HistFactory package  [26] , L ¼ Y i ϵ bins Pðn i jm i ðμ s ; ΘÞÞ × Y θ i ϵ Θ Gðθ i jθ 0 i ; Δθ i Þ × Y i ϵ bins Gðm i ðμ s ; ΘÞjm 0 i ðμ s ; ΘÞ; δm i ðμ s ; ΘÞÞ: ð1Þ The first term represents the Poisson probability of observing n i events in the ith bin with respect to the expected ones, m i ðμ s ; ΘÞ, with μ s the signal strength and Θ the set of nuisance parameters. The second term includes the Gaussian penalty terms to account for the nuisance parameters (θ 0 i and Δθ i are the nominal central values and uncertainties, respectively), listed in Table  II , which may act on multiple components in a correlated way. The last term of Eq. (  1 ) accounts for the statistical uncertainties in each bin [m i ðμ s ; ΘÞ AE δm i ðμ s ; ΘÞ] of the simulated sample with respect to the nominal value, m 0 i ðμ s ; ΘÞ  [26].
Name The data pulls from the fit in the full  [4, 170 ] N e range are normally distributed, as shown in Fig. 8 , demonstrating the quality of the background model. Postfit values of nuisance parameters are in good agreement with the nominal ones, as reported in Fig. 9. Improvement between nominal and postfit errors are observed for two parameters: the amplitude of the PMT component and the ionization response to ERs. The former is subject to a large uncertainty from the position of the contaminant within the PMT itself, as discussed in Sec. IV, and the latter relies on a few calibration points, especially at low energies  [16]. In both cases, the fitted dataset provides additional information to improve their uncertainty, as also observed from the fit of an Asimov sample derived from the background model  [28].
V and Table  II ), as well as those associated to the signal. The dominant one is the uncertainty on the NR ionization response, shown in Fig. 1 , obtained from the simultaneous fit  [16]  of spectra from calibration neutron sources deployed in the DarkSide-50 veto, and external calibration datasets from SCENE  [18]  and ARIS  [17]  test beam experiments. The signal amplitude is also affected by the uncertainty on the fiducial volume, a systematic correlated with the background components. The observed upper limit of 90% C. L. computed with the CLs technique  [33]  for the two signal models, with (QF) and without (NQ) quenching fluctuations, are shown in Fig. 11 , along with the expected limits. In both cases, observed limits are compatible within 2σ with the expected ones, and coincide between them above 4 GeV=c 2 WIMP mass, where the impact of quenching fluctuations is negligible.
VII. CONCLUSIONS In this work, we reanalyzed the DarkSide-50 dataset used in 2018  [6]  to produce the exclusion limit in the region below 10 GeV=c 2. Compared to the previous analysis, we improved the data selection, calibration of the detector FIG. 10. Data and background model compared to expected WIMP spectra, assuming binomial quenching fluctuations (solid lines) and WIMP-nucleon scattering cross section equal to 2 × 10 -41 cm 2. The systematic error associated with WIMP spectra is due to uncertainty on the NR ionization response. For reference, WIMP spectra assuming no quenching fluctuation (dashed lines) are also shown. FIG. 11. 90% upper limits on spin independent WIMP-nucleon cross sections from DarkSide-50 in the range above 1. 2 GeV=c 2. Both nonquenching (NQ, solid red line) and quenching (QF, dashed red line) fluctuations models are considered.
ACKNOWLEDGMENTS The DarkSide Collaboration offers its profound gratitude to the  LNGS  and its staff for their invaluable technical and logistical support. We also thank the  Fermilab Particle Physics, Scientific , and Core Computing Divisions. Construction and operation of the DarkSide-50 detector was supported by the  U. S. National Science Foundation (NSF)  (Grants No. PHY-0919363 , No. PHY-1004072 , No. PHY-1004054 , No. PHY-1242585 , No. PHY-1314483 , No. PHY-1314501 , No. PHY-1314507 , No. PHY-1352795 , No. PHY-1622415 , and associated collaborative grants No. PHY-1211308  and No. PHY-1455351 ), the  Italian Istituto Nazionale di Fisica Nucleare , the  U. S. Department of Energy  (Contracts No. DE-FG02-91ER40671 , No. DEAC02-07CH11359 , and No. DE-AC05-76RL01830 ), the  Polish NCN  (Grant No.
UMO-2019/33/B/ST2/02884 ) and the  Polish Ministry for Education and Science  (Grant No. 6811/IA/SP/2018 ). We also acknowledge financial support from the  French Institut National de Physique Nucléaire et de Physique des Particules  ( IN2P3 ), the  IN2P3-COPIN consortium  (Grant No. 20-152 ), and the  UnivEarthS LabEx program  (Grants No. ANR-10-LABX-0023  and No. ANR-18-IDEX-0001 ), from the  São Paulo Research Foundation (FAPESP)  (Grant No. 2016/09084-0 ), from the  Interdisciplinary Scientific and Educational School of Moscow University "Fundamental and Applied Space Research" , from the  Program of the Ministry of Education and Science of the Russian Federation  for higher education establishments, project No. FZWG-2020-0032  ( 2019-1569 ), from  IRAP AstroCeNT  funded by  FNP  from  ERDF , and from the  Science and Technology Facilities Council ,  United Kingdom.
I. Albuquerque  is partially supported by the  Brazilian Research Council (CNPq). The theoretical calculation of beta decays was performed as part of the  EMPIR  Project  20FUN04   PrimA-LTD. This project has received funding from the  EMPIR  program co-financed by the Participating States and from the  European Union 's  Horizon 2020 research and innovation program. Furthermore, this project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under Grant Agreement No. 952480. Isotopes used in this research were supplied by the  U. S. Department of Energy Office of Science by the Isotope Program in the Office of Nuclear Physics.
The T169 was instead directly taken fro the PDB entry 6L4A. 58  To maintain the representation of a random piece of chromatin, we avoided using the linker lengths multiple of 147 + 10n, which are known to force the zig-zag conformation of multiple nucleosomes because of the rotational constraints imposed from exact DNA turns. The DNA sequences of the two trinucleosomes are detailed in the Suppl. Mat. Table  2. In both systems, the protein octamers were replaced by copies of the canonical human H3/H4 and H2A/H2B complete with full histone tails, from PDB file 1KX5. 59  Since this hybrid experimental structure is built with human DNA wrapped around Xenopus proteins, we manually substituted the human protein sequence in CHIMERA ("swapaa" command). A comparison of the human vs. frog sequences is given in Suppl.
Mat. Table  3 , showing that only very minor differences exists between the two. Notably, the largest sequence difference in the more mobile histone tails is observed for the H2A histone. However, the H2A dimer is arranged parallel to the dyad axis, the N-terminal tails remaining always close to the superhelical positions +4/À4, and the C-tails close to the dyad. Given the negligible deformations observed in the nucleosome core, such differences are expected to have a minor dynamical effect, if any. Where needed, the primary structure of the histones was completed for the missing aminoacids with the Swiss-Model utility of SwissProt. 60  All molecular dynamics (MD) simulations were run with the GROMACS-2020 package. 61, 62  Proteins were described with the AMBER14 force field database,  63  including the PARMBSC1 extension for nucleic acids.
Mechanical stress calculation Continuous stress fields at the molecular scale [66-68] were extracted from MD trajectories by the so-called covariant central-force decomposition scheme (CCFD) for the intra-and intermolecular forces, which ensures conservation of linear and angular momentum of the molecular systems under very general conditions. 65  The method is implemented in a special-purpose patch to the old GRO-MACS 4. 6 version, which reads (all or part of) a MD trajectory for the selected subset of atoms for which stress is to be computed, and performs the entire analysis. Since the patch (called GROMACS-LS) constrains the code to run in serial rather than in parallel, care must be taken to define properly the atomic subset of interest, in order to avoid prohibitive computing times. Comparing stress fields from different MD runs requires an extra care, since the structures need to share exactly the same box size and center, to avoid numerical artefacts; when averaging a sequence of frames from a simulation it is important to subtract any translation or rotation with respect to the first frame.