dataesr/scientific-paragraphs-categorization huggingface dataset:
Experimental data used for parameterisation and evaluation Measured data from five two-year experiments (Exp1, Exp2, Exp4, Exp5) conducted in five countries (Australia, Argentina, Canada, China and Ireland) were used for model development and evaluation. Exp1 was conducted under controlled conditions (Mt Pleasant Laboratories, Launceston, Tasmania, Australia) with four waterlogging treatments using six contemporary Australian barley genotypes differing in their waterlogging tolerance from 2019 to 2020 (see refs. 39, 40  ). In Exp2, barley yields were measured under five waterlogging treatments in the greenhouse and field conditions at the School of Agronomy, University of Buenos Aires, Argentina in 2010 (see ref. 68  ). In Exp3, barley genotypes were evaluated for waterlogging tolerance in controlled field conditions at Brandon Research and Development Centre, Brandon, Manitoba, Canada from 2016 to 2017.
Waterlogging treatments were initiated at tillering by adding the water to heights of 0. 5-1 cm above the soil surface (see ref. 69  ). In Exp4, barley yields were measured in field conditions carried out at Oak Park, Carlow, Ireland from 2017 to 2018. Waterlogging treatments were initiated at the tillering stage using a boom irrigator (see ref. 70  ). In Exp5, field experiments were conducted in 2003-2004 and  2005-2006 at Zhejiang University, Hangzhou, China. Waterlogging treatments were imposed at tillering (see refs. 71, 72  ). All experiments were carefully managed to provide adequate nutrition and control of biotic pressures. Original datasets used for model evaluation (e. g. , yield under ambient conditions and those subject to waterlogging) were compiled from a range of environments, including field experiments and environmentally controlled experiments.
Given the diversity in data origins and variation in units used for reporting (e. g. , g plant -1 , g m -2 , kg ha -1 ), we standardised grain yield dimensions to kg ha -1 before computing yield loss using Eq. (1): Y ield loss % ð Þ= ðY ield ck À Y ield W L Þ Y ield ck × 100% ð1Þ Where Yield CK is the yield (kg ha -1 ) obtained from control treatment and yield WL represents yield measured for the waterlogging treatments (kg ha -1 ).
After the adaptation stage, genotypes tolerant to waterlogging tend to exhibit similar photosynthetic rates compared with before waterlogging, analogous to plants that grow aerenchyma after waterlogging  39  , whereas genotypes sensitive to waterlogging can exhibit decreased growth after waterlogging events if y_oxdef_lim_photo remains less than unity. We did not mathematically transcribe a process for crop failure under waterlogging, because in the majority of cases, waterlogging is realised as a transient event (viz. Fig. 3 ) and our experimental work suggests that intolerant genotypes persist for up to two months of waterlogging without failing  40. These concepts were programmed into the source code of APSIM; the executable containing the modified source code and XML files are available online: https://github.
Waterlogging in later growth stages causes premature flag leaf senescence and shortens the grain-filling period  66. Reduced grain growth in waterlogged plants is due to decreased post-anthesis carbon assimilation and culm reserves remobilised to grains  84, 85. APSIM was initialised using the SWIM3 Module (soil water infiltration and movement; Supplementary Fig. 11 ). To examine the extent with which the new processes described above improved the ability to simulate crop growth and development under waterlogging, we also run a default (unimproved) version of APSIM-Barley with waterlogging. Simultaneous multi-objective optimisation  63  of oxdef_photo and oxdef_pheno for each genotype was performed for waterlogging treatments by minimising the sum of squared residuals across datasets. Evaluation of phenology, biomass and yield components under waterlogging have been described in our previous peer-reviewed literature  35, 39, 40.
Cross-sectional malaria prevalence surveys We used data from 5 cross-sectional surveys from 4 countries, i. e. Brazil, Thailand, Cambodia, and Solomon Islands. The study design and basic descriptions are summarized in Table  1. We included a cross-sectional survey in 17 villages in the high-incidence, rural province Mondulkiri, in North-Eastern Cambodia, in the dry season in December 2017 until April 2018 (as described in  (9) ). The 4,200 study participants were 2-79 years old and from randomly sampled households based on a census prior to the survey. We classi ed villages of residence into categories of proximity to the forest based on a forest cover remote sensing analysis  (49). In this and all following included studies, we tested nger-prick blood samples for P. vivax and P. falciparum infections by real-time PCR and collected GPS locations of households.
From Kanchanaburi and Ratchaburi provinces in western Thailand, we consider data from a cross-sectional survey in September-October 2012  (7). We enrolled 4,309 study participants aged 0-92 years. We added data from two cross-sectional surveys in a peri-urban part of Manaus, Amazonas State, Brazil from November 2012 until January 2013 (rainy season) and from August until September 2013 (dry season), respectively (6). After all inhabitants had been invited to the study, 2,010 and 2,073 participated in the two surveys, respectively (963 in both surveys). From Solomon Islands, we used data from a cross-sectional survey in several villages across Ngella, Central Islands province from May until June 2012 (48). From a representative household-based sample, 3,501 individuals agreed to participate.
Longitudinal cohort studies In addition to the cross-sectional surveys, we used data from two longitudinal cohort studies with similar design: Monthly active follow-up with nger-prick blood-sampling for P. vivax and P. falciparum real-time PCR testing and collection of household locations by GPS at baseline. One study was conducted in two villages in Kanchanaburi and Ratchaburi provinces, Thailand, respectively, in May 2013 until June 2014, enrolling 999 participants (Table  1 ) (8). The other study took place in the peri-urban part of Manaus, Brazil, from April 2013 until March 2014 with 1,274 enrolled participants  (47).
Funding This is part of the  International Centers of Excellence for Malaria Research program  " Understanding , tracking and  eliminating malaria transmission in the Asia-Paci c Region ", funded by the  National Institutes of Health, MD, US  (grant  1U19AI129392-01 ) and received additional funding by  NHMRC (Australia ,  GNT1092789 ). Some of the included studies were supported by the  TransEPI  consortium funded by the  Bill & Melinda Gates Foundation, USA  (www. gatesfoundation. org). IM is supported by an  NHMRC   Principal Research Fellowship  ( GNT1155075 ). MS is part of the  PhD program  of the doctoral school ED393 Pierre Louis de santé publique and was supported by the  Sorbonne Université  (contract  n°2695/2017 ). MW is supported by the  European Research Council  ( 852373 ). HS is supported by the  European Research Council  ( 804744 ).
We present the new version of BlackHawk v2. BlackHawk is a public code designed to compute the Hawking radiation (HR) spectra of (primordial) black holes (PBHs). In the version 2. , we have added several non-standard BH metrics: charged, higher dimensional and polymerized black holes, in addition to the usual rotating (Kerr) BHs. BlackHawk also embeds some additional scripts and numerical tables that can prove useful in e. g. dark matter (DM) studies. We will describe these new features and provide some examples of the capabilities of the code.
It is thus of utmost importance to be able to predict precisely the HR spectra of SM and beyond SM (BSM) particles. There was thus a need for an automatic program to compute the precise spectra for any BH mass and spin, with a wide choice of parameters that allow for any kind of HR study. This was the context of creation of the public code BlackHawk  [12]. Since its first release, the code has received some modifications and has reached version v2. 1  [13]. The code is publicly available on HEPForge: https://blackhawk. hepforge. org/ BlackHawk is used by many groups from very different domains of astrophysics and cosmology to perform striking studies, a complete list of which is given on the BlackHawk website. BlackHawk v2. 1 includes some primordial new features linked to the physics described above: dark sector emission (Section 2.
1), spin 3/2 greybody factors (Section 2. 2), BSM BH metrics (Section 2. 3), low energy hadronization (Section 2. 4). The updated version of the code is available on the BlackHawk website mentioned above, and an updated version of the manual is available on the arXiv  [12]  (v3). All the installation and run procedures, as well as the complete set of parameters and routines are described in the latter, while we focus here on the new features only (for a complete description see the release note  [13] ).
Low-and high-energy hadronization The AMEGO constraint discussed above raised an issue: PBHs in the mass range just above the evaporation limit 5 × 10 14 g have a temperature in the low energy QCD domain  ∼ 100 MeV. This represented a difficulty for BlackHawk v1. 2, which relied on PYTHIA  [21]  and HERWIG  [22]  to compute the hadronization of primary particles, valid for  GeV. There was a need for more careful treatment of this energy range, a work initiated by the study of Ref. [18]  based on the public package Hazma  [23]. We interfaced BlackHawk with Hazma to incorporate realistic hadronization tables that allow to go from the HR primary spectrum of Eq. (  2 ) to the final stable output of a BH d 2 Ñ 𝑗 d𝑡d𝐸 = ∑︁ 𝑖 ∫ +∞ 0 Br 𝑖→ 𝑗 (𝐸, 𝐸 ) d 2 𝑁 𝑖 d𝑡d𝐸 d𝐸 , (3) where Br →  are the branching ratios.
Engrafted MuSCs adopt quiescent-like morphologies that predict cell fate signature Qualitatively, the engrafted MuSCs in our cultures adopted an elongated morphology over time  5A ), reminiscent of quiescent MuSCs in vivo, and contrasting against with morphologies observed in 2D cultures (Supplementary Figure  7 ). 12, 34, 35 Therefore, we next overcame a significant data analysis bottleneck by establishing and validating a CellProfiler TM -based image analysis pipeline in order to segment and evaluate donor MuSCs in our phenotypic datasets (see Methods and Supplementary Figure  8 ). 50 The cytoplasmic elongation of mononucleated Pax7 + donor cell bodies was captured by applying a ratio of max/min feret diameter to segmented images of tissues immunostained for YFP, Pax7, and DAPI. The roundness of nuclei within mononucleated YFP + Pax7 + cells was evaluated using the measurement of eccentricity, whereby a value of 0 corresponds to a perfect circle, and a value of 1 to a straight line (Figure  5B ).
Image acquisition Confocal imaging was performed using the Perkin-Elmer Operetta CLS High-Content Analysis System and the associated Harmony® software. Prior inserting the 96-well plate into the Operetta, the PBS was removed from the wells of the plate to prevent tissues from shifting during imaging, and they were carefully positioned in the middle of the wells using tweezers. For stitched pictures, images were collected using the 10X air objective (Two Peak autofocus, NA 1. 0 and Binning of 1). For MuSC analysis, images were collected using the 20X and 40X water immersion objectives (Two Peak autofocus, NA 1. 0 and 1. 1, and Binning of 1). All images were exported off the Harmony® software in their raw form. Subsequent stitching, max projections, etc was performed using the ImageJ-BIOP Operetta Import Plugin available on c4science.
Bio-image analysis For SAA coverage, stitched images were used along with a previously published ImageJ macro. 79 SAA signal was put in red, the threshold set to 0-45 and the tissue outline selected using the oval tool. For fusion index, cell counting, cell morphology, YFP/GFP coverage and mean nuclear intensity, the CellProfiler TM software was utilized. CellProfiler TM version 4. 2. 1  50  was downloaded from source website (www. cellprofiler. org) and installed on a PC (Intel Core i9-11900 @ 2. 5GHz, 64. 0 GB RAM, and 64-bit Windows 11 operating system). Analysis pipelines were created for each of the above-mentioned metrics. Fusion index: 9 x 20X max projected images were taken per tissue. The channels were split, the fiber and nuclei signal individually identified and overlayed to calculate the percentage of nuclei in fibers.
Cell counting and morphology: 25 x 20X max projected images were taken per tissue. The channels were split, mononucleated DAPI + YFP + Pax7 + (or Caveolin-1 + ) objects extracted using the IdentifyPrimaryObjects module and counted. For object segmentation, the global minimum cross-entropy thresholding method 80 was selected. Pixel intensity and object shape were used as metrics to distinguish and segment clumped objects. Morphology measurements of the identified cellular objects were recorded using the MeasureObjectSizeShape module. For the proportion of c-FOS + , Ki67 + , MyoD + and/or CalcR + cells, this fourth channel was overlayed over the identified objects and divided. YFP/GFP coverage: 25 x 20X max projected images were taken per tissue. The channels were split, the YFP/GFP signal identified, and coverage calculated using the MeasureAreaOccupied function.
Acknowledgements This project was funded by a  CIHR  CGS-D scholarship to E. J. , an  Ontario Graduate Scholarship  to E. J. , a  Cecil Yip Doctoral Award  to E. J. , a Medicine by  Design Canada First Research Excellence Fund  grant to P. M. G. ( MbDC2-2019-02 ), and a  Canada Research Chair in Endogenous Repair  to P. M. G.
Navier-Stokes resolution Navier-Stokes simulation of the entire flow domain has two purposes: first, resolving the flow behaviour in the area compatible with continuous solution, and second, calculating the local rarefaction level to draw an interface delimiting continuous and rarefied areas. This section gives the detail of the numerical tools and inputs used to simulate the DLR experiment presented in Section 2. Onera code CEDRE is used to resolve NS equations. This tool is a 3D multi-physical code  [42]  developed to perform numerical studies of energetics and propulsion matters in a research context as well as for industrial use. CEDRE is able to simulate complex flow involving reactive, compressible, multiphase, acoustics or radiative physics that can be encountered during solid or liquid rocket propulsion simulations.
e. at least 10 to 20 particles per cells). The tool used in this study is SPARTA  [49] , an open-source code developed by Sandia National Laboratories. Simulations realised in the scope of this work used the Variable Soft Sphere (VSS) collisional model  [50]. Particles-wall interactions are modelled by a Maxwell wall condition such as the one presented in Section 3. 3 with an accommodation coefficient of 1. As for NS simulations, an axial symmetry is set and the box size is similar. The mesh is made of rectangles defined by 265 points over  direction (axial) and 162 over  (radial). The grid is automatically refined during the simulation according to the value of the numerical Knudsen number  , = ∕,  being the cell size. This ensures a spatial resolution matching particle mean free path in high-pressure regions (see Fig.
Model overview The NEOCARBSULF model is an extension of GEOCARBSULFOR  (2)  and is solved in MATLAB using an implicit variable-order ordinary differential equation (ODE) method  (66). The original GEOCARBSULF model  (38)  was solved using an Euler approach, but the differential equations used by the model are "stiff"; therefore, there is a high degree of numerical instability, which sometimes leads to model failure when using explicit methods with set step sizes  (48). GEOCARBSULFOR was built to use the ODE15s solver in MATLAB, which permits (among other things) a dynamic step size, allowing the model to adapt to areas of stiffness when solving the equations, and we continue to use this solver in NEOCARBSULF. The full set of model equations and information about the data used can be found in tables S1 to S7.
Rift and plate boundary modeling Plate boundary lengths from 1000 Ma to the present are analyzed using a full-plate model that combines existing models that discretely cover the past 1000 million years  (75). Rift events over the past 1000 million years were taken from prior work  (76)  for the Neoproterozoic as well as an earlier compilation (77) and digitized by others (78) for the Phanerozoic. These rifting events, which include failed rifts, are incorporated into the tectonic models as digitized polylines in GPlates (www. gplates. org). Subduction zone length was calculated using the pyGPlates python library  (76). We also obtained the mantle to crust flux data from a previous study (their figure  4 )  (79). Each dataset (i. e. , subduction zone lengths, rift lengths, and mantle to crust flux) is normalized to their present-day value, as per the original GEOCARBSULF (38) model, and the value for subduction zone lengths at 1000 Ma is extended back to 1600 Ma (1600 to 1500 Ma is the model spin-up time).
Acknowledgments: We thank two anonymous reviewers for their constructive comments which helped to significantly improve the manuscript. Funding: This work is supported by the  Natural Environment Research Council   SPHERES Doctoral Training Partnership   NE/ L002574/1  (A. J. K. ),  UK Natural Environment Research Council   NE/R010129/1  (B. J. W. M. and S. W. P. ),  UK Natural Environment Research Council   NE/S009663/1  (B. J. W. M. and S. W. P. ),  Royal Society   Wolfson Research Merit Award  (S. W. P. ),  Leverhulme Research Fellowship  (S. W. P. ),  Deep Energy Community  of the  Deep Carbon Observatory  (A. S. M. ),  Richard Lounsbery Foundation  (A. S. M. ),  MSCA-IF  project  893615  (A. S. M. ), and  UK Natural Environment Research Council   NE/P013651  (T. M. L. ) Author contributions: Research design: A.
J. K. and B. J. W. M. NEOCARBSULF modeling:  A. J. K. Tectonic  plate modeling: A. S. M. Writing: A. J. K. , B. J. W. M. , A. S. M. , T. M. L. , and  S. W. P. Competing  interests: The authors declare that they have no competing interests. Data and materials availability: The datasets required to run the model and the code for NEOCARBSULF, which is constructed in MATLAB, can be accessed via the DOI: 10. 5281/zenodo. 6954788or can be found at https://github. com/Alexjkrause/NEOCARBSULF. Submitted 13 October 2021 Accepted 25 August 2022 Published  14 October 2022 10. 1126/sciadv. abm8191Downloaded from https://www. science. orgon February 01, 2023.
Overview of Application of Blockchain in DNS Namecoin  [9]  is the first distributed DNS system based on blockchain technology. Its characteristic is that it does not require network censorship and can guarantee the free release of information. The purpose of its design is to realize the registration, management and resolution of domain names as a public chain that can replace the DNS system. Namecoin adheres to the idea of decentralization, but the security of the blockchain is low, because the network can accommodate fewer nodes and is vulnerable to attacks. Blockstack  [10]  overcomes the vulnerable characteristics of Namecoin, separates the control layer and data storage layer in the system, uses the underlying blockchain to process domain name data, and the domain name information is stored in the system's database.
Overview of Application of Cross-chain Technology in DNS DNSTSM proposed a multi-channel algorithm for DNS domain name caching resources, and designed a method to calculate the credibility of DNS resolution nodes to evaluate malicious nodes to avoid affecting the system and reduce the service delay of the system  [12]. However, DNSTSM did not solve the problem of low service speed caused by multiple nodes in the alliance chain. Duan et al. [13]  proposed a domain name resolution system model based on slave chains, provided a complete DNS system structure, designed a new domain name storage method and realized a complete solution for domain name application, modification and resolution services. However, DNSLedger uses a local database method, which cannot guarantee the uniqueness and legality of the domain name.
Domain Name Update After applying for a domain name, the domain registrar can modify the registered domain name information. The process of domain name renewal is the process of domain name transaction. The ownership and status of the domain name are changed. The specific process is: the user initiates a domain name modification request to the master node in the slave chain. After receiving the domain name modification request, the master node queries and checks the domain name information from the distributed database. After completing the transaction on the chain through the consensus algorithm, after the domain name information is updated, respond to the client.
Otherwise, the local domain name server sends a request to the slave chain. The local DNS service can be divided into different slave chains according to geographic location or node status. When the client queries, the default slave chain node is preferred. 3. After receiving the query request, the slave chain node searches the data index on the chain. If there is corresponding domain name information, initiate a database query request from the chain node to the distributed database, and send the queried destination IP address to the local domain name server. The local DNS server sends to the client, and the query ends. If the destination IP address is not found, the slave chain node will send feedback information to the local DNS server. 4. The local DNS server receives the feedback information and sends a query request to the master chain node.
In this manuscript, which is to appear in the proceedings of the conference "MathemAmplitude 2019" in Padova, Italy, we provide an overview of the module intersection method for the the integration-by-parts (IBP) reduction of multi-loop Feynman integrals. The module intersection method, based on computational algebraic geometry, is a highly efficient way of getting IBP relations without double propagator or with a bound on the highest propagator degree. In this manner, trimmed IBP systems which are much shorter than the traditional ones can be obtained. We apply the modern, Petri net based, workflow management system GPI-S in combination with the computer algebra system S to solve the trimmed IBP system via interpolation and efficient parallelization. We show, in particular, how to use the new plugin feature of GPI-S to manage a global state of the computation and to efficiently handle mutable data.
PoS(MA2019)004 Module Intersection Janko Böhm and Yang Zhang successfully used to obtain reduction for the non-planar 5-point topologies appearing at 2-loop order  [57, 65]. In this review paper, we also present a Mathematica interface for generating IBPs without double propagators (or IBPs with restricted propagator degree), via our module intersection method, see https://bitbucket. org/yzhphy/module-intersection/src This review is organized as follows: In Section 2, we present the intersection algorithm used to generate the IBP system. In Section 3, we describe our Gaussian reduction approach, introducing the GPI-S system and the Petri net formalism to formulate our workflow. We then present some examples and finish with some outlook on possible future directions.
The acquisition and analysis of these data are also very timely, as theoretical simulations of the turbulent multiphase ISM are starting to include chemistry, thereby allowing observations to be compared to specific model predictions for the first time. This paper presents an overview of the HyGAL program and the analysis of the first data collected from SOFIA Cycle 8 observations toward three of the targeted sources, W3(OH), W3 IRS5, and NGC 7538 IRS1. Section 2 details the main scientific goals of the HyGAL program, with the observations, use of archival and complementary data, while the data reduction strategies are described in Section 3. We present and discuss the results in Sections 4 and 5, and summarize our findings in Section 6.