dataesr/scientific-paragraphs-categorization huggingface dataset:
Glacier meltwater excess The effect of glacier mass balance on river discharge is assessed using two discharge datasets of Naryn (Tien Shan) and Gunt (Pamir) rivers (Fig. 1a ). For each catchment, three monthly time-series were obtained (Table  S4 ): long-term average discharge, one extremely negative  (2009 ( for Gunt, 2003  for Naryn) and one positive  (2008 ( for Gunt, 2006  for Naryn) mass balance year. The long-term discharge is the periods 1999/00-2017/18 (Naryn) and 1999/00-2012/13 (Gunt). The Naryn and Gunt catchments have 8% and 5% glacier cover. Discharge estimates are based on annually calibrated stage-discharge rating curves and stage readings. Both catchments drain higher parts of the respective mountain ranges so that runoff is not impacted by water resource management (e. g.
Accepted Article This article is protected by copyright. All rights reserved. S5 ). The remaining 773 (39%) were excluded due to insufficient transient snowline observations or disagreement with geodetic surveys. According to our multi-data assessment, we found an area-weighted average glacier mass balance of -0. 23±0. 37 m water equivalent (w. e. ) yr -1 from 1999/00-2017/18 for Tien Shan and Pamir. Glaciers in Eastern Tien Shan and Dzhungarsky Alatau showed the most negative mass balance rates at almost -0. 50±0. 37 m w. e. yr -1 (Fig. 1a ). Glaciers in Northern/Western Tien Shan, Pamir-Alay and Western Pamir showed mass balance rates between -0. 25±0. 37 m w. e. yr -1 and -0. 32±0. 37 m w. e. yr -1. A moderately negative mass balance rate of roughly -0. 13±0. 37 m w. e. yr -1 was observed for Central Tien Shan and Eastern Pamir.
Climatic forcing has been previously identified as dominant driver for the heterogeneous mass balance sensitivity over High Mountain Asia, explaining up to 60% of its spatially contrasting glacier response  (Sakai & Fujita, 2017). Glacier morphology was found to explain up to 36% of the spatial mass balance variability for Tien Shan and 20% for Pamir-Alay, but only 8% for Western and Eastern Pamir  (Brun et al. , 2019). The influence of glacier surge activity is so far poorly understood  (Goerlich et al. , 2020). Although our results provide new estimates to revisit these analyses, prevailing large uncertainties in current meteorological datasets  (Zandler et al. , 2019 ) require a more detailed approach than can be provided here. 6 Relevance of glacier mass loss to river runoff The most important impact of changing glacier runoff dynamics for Central Asia is the uncertain timing and duration of high or low meltwater contributions to river systems during dry summer months  (Varis, 2014; Chen et al.
Conclusions We provide annual mass balance time-series with low sensitivity to meteorologi- The excess glacier meltwater release for two catchments representative for Central Asia can highly vary between years (1-16%). The difference in meltwater production can relate strongly to early summer snow depletion (up to six times more melt than average) or follow air temperature changes during the end of summer (up to three times more melt than average). Large uncertainties in meteorological datasets remain a major hurdle for our understanding of processes governing changes at the climate-glacier-runoff nexus. Ongoing monitoring efforts coupled with mass balance and runoff models are essential to understand the impact of climate upon future glacier mass balance and discharge patterns, and in turn, to develop policy responses to rapidly increasing water demands in Central Asia.
Acknowledgments We thank to the project  CICADA (Cryospheric Climate Services for improved Adaptation ), with contract no. 81049674  between  Swiss Agency for Development and Cooperation  and the  University of Fribourg. The  CAWa (Central Asian Water)  project (http://www. cawaproject. net)was supported by the  German Federal Foreign Office  (contract no. AA7090002 ) as a part of the  Berlin Process. This study was also supported by the  Swiss National Science Foundation  (SNSF) by the following two projects: Snowline observations to remotely derive seasonal to sub-seasonal glacier mass balance in the  Tien Shan  and  Pamir Mountains , grant  155903 , and Changing glacier firn in Central Asia and its impact on glacier mass balance, grant  169453. Funding for parts of this work comes from the  BMBF (Federal Ministry of Education and Research)  research programme  PAMIR  ( FKZ 03G0815 ) within the  CAME (Central Asia and Tibet: Monsoon dynamics  and geo-ecosystems) project.
2019). Recent observations and re-analyses of earlier ALMA data have now led to a different possible scenario: a significantly larger scatter in L  [CII]  at high-redshift compared to the local SFR-L [CII] relation, instead of a [CII] deficit (see e. g. ,  Carniani et al. 2018; Matthee et al. 2019). Additionally, surface brightness dimming could affect the detectability of [CII] emission  (Carniani et al. 2020). However, the current datasets are still limited in size and, furthermore, most of the early galaxies that have been observed with ALMA were selected as Lyα emitters (such that they had a previously known redshift), which can lead to a bias toward young, metal-poor, dust-free systems (see e. g. ,  Smit et al. 2018). The ALMA large program ASPECS provides the first full frequency scan in band 6 of the Hubble Ultradeep Field (HUDF;  Decarli et al.
2019; Aravena et al. 2019; González-López et al. 2019 ). These observations enable the unbiased search for emission lines, both molecular (CO) and atomic ([CI])  (Decarli et al. (2020)  and  Boogaard et al. (2020) ) and  [CII]  (this paper). The HUDF was chosen as it represents the deepest dataset available across all wavelengths. By design, this field does not include very massive and highly star-forming systems (such as submillimeter galaxies or quasars), but traces the field galaxy population that is most representative at each cosmic epoch (L and sub-L galaxies). The HUDF has been particularly important in the discoveries of the most distant galaxies known, from early studies of the z > 6 galaxy population (e. g. ,  Bouwens et al. 2010; McLure et al. 2010; Oesch et al. 2010 ) to consecutively higher redshifts (now extending to z∼10-12; e.
g. ,  Ellis et al. 2013; Oesch et al. 2013). The frequency setup of the ASPECS band 6 scan covers the redshifted [CII] emission line from 6 < z < 8, ideally matched to some of the most distant galaxies known in the HUDF. In the pilot observations of ASPECS, a number of potential [CII] line candidates were reported  (Aravena et al. 2016). However, as discussed in detail below, none of these candidates could be confirmed (at 5σ) in the deeper and more uniform observations obtained through the ASPECS large program. This is in line with other recent [CII] detections and upper limits that have been reported in other sources in the meantime. In this paper, we exploit these deeper data from the ASPECS large program over the HUDF to constrain the [CII] emission from galaxies at z = 6 -8. In particular, we search for [CII] emission of previously identified LAEs and LBGs in this field, also exploiting recent, very deep MUSE spectra  (Inami et al.
(2020) ). For reference, imaging of the ASPECS Pilot data cube resulted in an average RMS level of 0. 42 mJy per beam over the same channel width  (Aravena et al. 2016). Combining both data sets results in a marginal increase-by only a factor ∼ 1. 14-in sensitivity over the relevant area over-1 v FWHM /v chn = 1. 6 at band center  (242 GHz). lapping between the LP and Pilot survey fields. We thus decided to proceed with the independent datasets. Additionally, we use the 1. 2 mm continuum map (without PB correction) with a mean RMS of 9. 3 µJy beam -1 presented in  González-López et al. (2020)  to search for continuum emission in targeted opticallyselected galaxies (described in the following Section 2. 2) and in positions returned by the blind search algorithm described in Section 3. 2.
Ancillary Datasets To enable a targeted  [CII]  search in the ASPECS Band 6 data cube, we exploit existing galaxy catalogs in UDF with reliable photometric or spectroscopic redshifts. Lyman-α emitters (LAEs) -The MUSE Hubble Ultra Deep Field survey  (Bacon et al. 2017 ) provides accurate spectroscopic redshifts for ∼ 1500 galaxies in a 9 arcmin 2  field encompassing the full ASPECS footprint. With its wide instantaneous bandwidth, spanning 4650-9300 Å, the MUSE IFU spectrometer provides continuous coverage of the Lyman-α (Lyα) emission line from z = 2. 8-6. 7; we refer the interested reader to, e. g. ,  Boogaard et al. (2019)  for more information on observational details of the MUSE survey and complementarities with ASPECS. We consider sources located within the ASPECS HPBW and which have secure spectroscopic redshifts within the ASPECS [CII] redshift coverage.
Lyman-break galaxies We have extracted single-pixel spectra in the ASPECS Band 6 data for the 45 Lyman-break selected sources described in Section 2. 2. For consistency with the noise estimation on the LAE spectra, we extract spectra in a local bandwidth of 8 GHz, centered at the expected observed frequency for [CII] based on the peak redshift, z peak , from the p(z) for a given LBG. In cases where the 1-σ uncertainty on z peak is greater than 8 GHz, we use the upper and lower 1-σ limits to determine the appropriate frequency range. No detections are reported. Upper limits on [CII] line luminosity are presented in Table  2  for a subset of the LBG sample containing 5 of the brightest objects with derived SFR 10, roughly corresponding the average 5σ depth in SFR for the ASPECS [CII] survey (cf.
1. 1 and 3. 1. 2, and/or spectroscopic redshift from the ASPECS 3 mm dataset); or, when a line candidate failed to match to a catalog position, the line redshift was assigned on a probabilistic basis, taking into account the cosmic volume sampled by each possible line and various empirical weights reflecting the expected relative strength of the emission line to CO(1-0). ID z RA Dec SFRSED L [CII] [deg] [deg] [M yr -1 ] [10 8 L ] (1) (2) (3) (4) (5) The fidelity of a line candidate is quantified using a probabilistic approach that compares the number of positive and negative fluctuations, N pos and N neg , in the data for a given SNR and convolution kernel width σ kernel : fidelity = 1 - N neg (SNR, σ kernel ) N pos (SNR, σ kernel ) , (1) where the allowable fidelity range from 0 to 1 implies a 100% to 0% chance, resp.
2013), we follow the reasoning in, e. g. ,  Willott et al. (2015) , and argue that-with a single flux density measurement-these competing effects of the CMB background are poorly constrained. (Walter et al. 2016). As the precursor to the Large Program, ASPECS Pilot shared the same survey strategy (e. g. , array configuration, frequency setups, comparable survey depth) as ASPECS LP, but targeted a smaller, 1 arcmin 2 patch of sky within the UDF. The final mean rms noise achieved was 0. 42 mJy beam -1 per 62. 5 MHz channel, roughly constant across the survey bandwidth, which is a factor 1. 4 higher than the mean rms of 0. 30 mJy beam -1 per 62. 5 MHz channel for ASPECS LP due to more favorable weather conditions in the latter campaign. The blind line search in the lower sensitivity AS-PECS Pilot data cube returned 14 [CII] line candidates down to lower signal-to-noise threshold (∼ 4.
Statistical approaches applied to existing ALMA datasets, such as the power spectrum analysis (as demonstrated in  Uzgil et al. (2019)  and  Keating et al. (2020) ) provide efficient tools for probing low fidelity emission from faint galaxies below survey detection thresholds. Line intensity mapping datasetstailored to this statistical approach-will also be available from ongoing and future experiments using large field of view instruments on single dish telescopes (e. g. , EoR-Spec  (Cothard et al. 2020) ; SuperSpec  (Karkare et al. 2020; Redford et al. 2018) ; CONCERTO  (Lagache et al. 2018) ; TIME  (Sun et al. 2020 )) to probe aggregate [CII] emission at the highest redshifts.
The authors thank the anonymous referee for a constructive report. We thank  Takuya Hashimoto  for sharing equivalent width data for the MUSE LAEs in AS-PECS. BDU would like to thank  Andrea Ferrara  and the cosmology group at  Scuola Normale Superiore , where part of this work was done, for their hospitality and useful discussions. DR acknowledges support from the  National Science Foundation  under grant numbers  AST-1614213  and  AST-1910107. DR also acknowledges support from the  Alexander von Humboldt Foundation  through a  Humboldt Research Fellowship for Experienced Researchers. TD-S acknowledges support from the  CASSACA  and  CONICYT  fund  CAS-CONICYT Call 2018. HI acknowledges support from  JSPS KAK-ENHI  Grant Number  JP19K23462. Facility: ALMA data:  2016. 1. 00324. L. ALMA is a partnership of  ESO  (representing its member states),  NSF (USA)  and  NINS (Japan) , together with  NRC (Canada) ,  NSC  and  ASIAA (Taiwan) , and  KASI (Republic of Korea) , in cooperation with the  Republic of Chile.
2011 ) and radius  (Petigura et al. 2013 ) between that of Earth and Neptune. Moreover, the observed orbital architecture is such that mutual inclinations are small, typically in the region of 1 • to 2 •  (Fabrycky et al. 2014) , while eccentricities are also found to be small, on average ē ≈ 0. 04  (Xie et al. 2016). An archetypal example of these systems, albeit containing six planets, is Kepler-11  (Lissauer et al. 2011 ). Exoplanet systems with orbital spacings much greater than that required for stability are also present in the Kepler data set. It is a favoured hypothesis that this orbital architecture is a result of dynamical instabilities in much more compact systems leading to ★ E-mail: p. bartram@soton. ac. uk close encounters and orbital reconfiguration  (Pu & Wu 2015). Understanding of the stability and evolution of compact exoplanet systems is therefore not only important for making sense of observations but also for understanding the planetary formation process as a whole.
Stopping criteria and integration packages We have opted to use the Terrestrial Exoplanet Simulator (TES) 1 package to perform our integrations  (Bartram & Wittig 2021). TES is a new numerical integration package written in C++ for propagating exoplanet systems. This package combines an integrator that follows Brouwer's law  (Brouwer 1937)  with a new special perturbation method to allow for reduced run-times and decreased numerical error resulting in, e. g. , improved energy conservation. Additionally, this tool has been designed to allow for integration all the way to collision of terrestrial mass planets to machine precision. TES can be run using C++ directly, or through a python interface allowing for ease of use and for multiple integrations to be performed in parallel. Throughout our simulations we have opted to use TES with a non-dimensional tolerance of 1 × 10 -8 which has ensured that the relative energy error in all simulations, even after collision, and for the longest lived systems, is maintained below 1 × 10 -13.
To validate our own results, we also repeated all of our standard suite integrations making use of IAS15  (Rein & Spiegel 2015)  within the REBOUND package  (Rein & Liu 2012). The results from this comparison can be found in Appendix A. As mentioned before, time is measured by periods of the innermost planet in the system throughout this work, meaning that all times are specified in units of orbits or dynamical periods. Integrations run until either a collision is detected or the simulation reaches a maximum time of 10 8 or 10 9 dynamical periods, depending on the experiment. In order to detect an orbital crossing, the orbital elements of each planet are calculated at every step within each integration. These are then compared to determine the time at which the apoapsis of a planet crosses the periapsis of the exterior adjacent planet.
Models fitted to the crossing and impact times according to Eq. 4 are shown as a dashed black and a dashed red line, respectively. that the system persists without a collision after the point of orbital crossing: 𝑡 𝑠 ≡ 𝑡 𝑖 -𝑡 𝑐. All encounters closer than any experienced previously are recorded such that it is possible to generalise the collision results to systems with planetary radii greater than that of the Earth or, equivalently, initial orbital radii closer than 1 AU. We use this generalisation to consider systems at 0. 25 AU and 1 AU for all integration suites. We also define the time of closest encounter prior to collision as the closest encounter time,. To ensure bit-wise identical initial conditions as in  Lissauer & Gavino (2021) , initial conditions are specified as orbital elements which are then entered in to the MERCURY (Chambers 1999) integration package in order to generate an initial state vector which is then provided to either TES or REBOUND.
Inclined integration suite The final integration suite is the inclined suite and is composed of 16, 800 integrations. Of these, 15 did not complete in the available CPU time and have been excluded from the dataset. This is equivalent to 0. 09% of inclined integrations, and we therefore do not believe this will have biased the dataset in any meaningful way. We choose initial conditions across a subset of the available parameter space manually rather than randomly and perform integrations for a maximum simulation time of 1×10 8 orbital periods of the innermost planet. To make best use of computational resources we limit this study to the range  = [3. 5, 6. 3] and perform experiments uniformly spaced in  with fifty values per unit. At each value of  we perform one hundred Cumulative sum of integrations with a collision before orbital crossing for various initial values for semi-major axis of the innermost planet.
We fit models of the form of Eq. (  4 ) to both the long-lived population and the population in its entirety, we call these datasets long and all, respectively. The model coefficients  and  can be found in the top two rows of Table  2. Similarly, we also fit linear models to the two datasets present in Fig. 5  for log 10 (  ) against log 10 (  ). The model coefficients  and  can be found in the bottom two rows of Table  2. In all cases, we calculate the Pearson correlation coefficient (PCC) and also calculate the standard deviation, , of the Blue dots indicate the same pair both crossed orbits and collided; orange indicates the pair that collided was not the pair that crossed; green indicates a collision between the inner and outer planets. The   model (bold dashed black) is fitted to all data points with a survival time greater than two orbits.
One notable difference between the two studies is in the initially wider spaced systems. In the regions  = [5. 0, 5. 999] and  = [6. 0, 6. 33] we find roughly double the number of initial orbital spacings where the standard and perturbed suite integrations experience orbital crossing times within 10% of one another. Given the precise orbital evolution required in order for standard and perturbed suite systems to experience a crossing at the same time it is unlikely that numerical error would ever cause an increase in this statistic. We therefore take this as an indication that TES has maintained a higher precision than the symplectic Wisdom-Holman  (Wisdom & Holman 1991)  scheme within MERCURY. To further validate TES in this setting we have also repeated the standard suite integrations with IAS15 from the REBOUND package for comparison.
Fitted model coefficients for   against  and. Plotted models are fitted to the long-lived population, long, only but fitted models for the full dataset, all, are included as well. is the Pearson correlation coefficient. is the standard deviation of the dataset from the fitted model. -intercept upon the slope. We fit this model to three data sets such that  =   ,   or   and state explicitly which at the time of use. Unless otherwise stated, we only include data points in the region  =.
ACKNOWLEDGEMENTS We would like to acknowledge the funding provided by the  Engineering and Physical Sciences Research Council (EPSRC)   Centre for Doctoral Training in Next Generation Computational Modelling grant   EP/L015382/1  that has made this research possible. Additionally, we would like to acknowledge the use of the  IRIDIS High Performance Computing Facility , and associated support services, at the  University of Southampton. JJL was supported through  NASA 's  PSD ISFM program. We would like to thank an anonymous reviewer for their detailed comments that helped improve this manuscript.
The neutron transport in nuclear fuels depends on the crystalline structure of materials when neutron energies lie below a few eV. For that purpose, the theoretical formalism that describes the neutron elastic and inelastic scatterings by crystals has been implemented in the CINEL processing tool in order to provide temperaturedependent neutron cross sections usable by the Monte-Carlo code TRIPOLI4 ®. The performances of the Monte-Carlo calculations are illustrated with the analysis of neutron powder diffraction data on UO 2 measured up to 1664 K with the D4 and D20 diffractometers of the Institute Laue-Langevin (Grenoble, France). The comparison of the experimental and simulated pair distribution functions confirms the unusual decrease of the U-O atomic distances with increasing temperature when an ideal fluorite structure (Fm 3m space group) with harmonic atomic vibrations is assumed over the full temperature range.
The flexibility of the CINEL code allowed to explore disorder or anharmonic oxygen vibrations in the Fm 3m space group by using either a foursite model with a relaxation term or a structure factor equation with a non-zero anharmonic third-cumulant coefficient. As none of these models succeeded to improve the agreement with the experiments, recent works that propose other local crystalline symmetries for UO 2 at elevated temperatures were investigated with the CINEL code. The case of the Pa 3 symmetry is briefly discussed in this paper.
Indeed, if the fluorite structure (Fm 3m space group) of UO 2 is well established at room temperature, the understanding of the unusual relaxation with the increasing temperature of the oxygen atoms from their regular positions is still under discussion. Among the few neutron diffraction measurements on stoichiometric uranium dioxide reported in the literature, we have selected the works of Ruello  [3]  and Ma  [4] , whose data are still available at the Institute Laue-Langevin (ILL) of Grenoble (France). The experiments were performed on the D20 and D4 diffractometers, respectively. They consisted in measuring the temperature-dependent neutron scattering yield   exp () as a function of the scattering angle. The two data sets cover a wide temperature range from room temperature to 1664 K. The originality of our work relies on the use of the Monte-Carlo code TRIPOLI4 ®  [5]  to simulate the experimental diffraction patterns by taking into account the multiple neutron scattering effects and the multiphonon contribution.
The experimental corrections, which are not introduced in the Monte-Carlo simulations, are the background correction, the angular offset and the angular response function of the diffractometer. They are deduced from the data by applying a Rietveld-type structure refinement  [6]  on the neutron scattering yields simulated with the TRIPOLI4 ® code. Final results mainly depend on the neutron scattering cross sections of uranium and oxygen in UO 2 which were introduced in the simulations. The low-energy neutron cross section formalism is well documented  [7]. The theory was implemented in dedicated processing codes, such as NJOY  [8]  and FLASSH  [9]. They provide neutron application libraries for Monte-Carlo and deterministic neutron transport codes  [10, 11]. For demonstrating the performances of the TRIPOLI4 ® code, we have developed a Python code, namely CINEL, which can be virtually applied on various solids, liquids and gases of interest for the nuclear industry.