dataesr/scientific-paragraphs-categorization huggingface dataset:
For example, clade 4B species have type 3 fibulae, though this type is also found in other clades. In our dataset, the only species with type 5 fibulae are Simonsenia species and Tryblionella debilis. Fibula morphology thus separates T. debilis from the two other, unrelated groups of Tryblionella (the T. apiculata group in clade 5B and the T. compressa group in clade 8B), both of which have rather small solid fibulae. SEM observations of T. gracilis  (Mann, 1978, fig. 721, as "Nitzschia tryblionella")  indicate that this species has somewhat similar fibulae to T. debilis and can be predicted to be related to it. There are also similarities between T. debilis fibulae and the hollow fibulae that  Sims and Paddock (1982)  discovered in T. circumsuta (classified in a different section to T. debilis by Grunow in Cleve and Grunow, 1880; Table  1 ), which they referred to as 'fenestral fibulae'.
Problems of GenBank sequences The sequences in GenBank are a precious source of data, even if they are not identified beyond family or genus, and any sequences of Bacillariaceae can potentially help to detect how the group has evolved molecularly. However, taxon identifications in GenBank are not peerreviewed but rely on the expertise of depositors and, even if identifications are correct when the sequences are submitted, they may become incorrect later, as a result of changes to the classification. Hence interpretation of molecular phylogenies based on GenBank sequences needs to be cautious, especially in a family like the Bacillariaceae, where the taxonomy is often contentious. An example where incorrect identifications could easily have led to misleading conclusions about non-monophyly is given by some of the 'Bacillaria' sequences in GenBank.
The identities of the other two nSSU sequences of 'Bacillaria II' are also doubtful and are discussed, together with the Xmm clones of the four species mentioned earlier (section 3. 2: N. dubiiformis, N. palea, N. capitellata and N. epithemioides) in Supplementary file 10. Such examples, and the 'Pseudo-nitzschia' clone A2ni mentioned in section 2. 2, show the need for careful evaluation of the identifications assigned to GenBank sequences and in some cases the accuracy of the sequence itself (for example, whether a protein-coding sequence is implausible because of indels or 'wrong' amino-acids or extra stop codons). We refer to these two checks as 'curation' of the sequences, following e. g. del  Campo et al. (2018)  and  Rimet et al. (2019). Curation is especially important for nSSU, which was the first DNA marker to be used for microalgal classification (e.
Options for a revision of the Bacillariaceae Although Nitzschia is very clearly paraphyletic (consistent with previous findings, e. g. by  Lundholm et al. , 2002a; Rimet et al. , 2011; Stepanek et al. , 2016; Lobban et al. , 2019; Mucko et al. , 2020, in press) , we consider that it would be premature to suggest formal changes to the genera, subgenera and sections of the Bacillariaceae until : 1. there has been further opportunity to check (curate) the sequences already available, to minimize misidentifications. Curation of rbcL sequences is already undertaken annually to incorporate new GenBank accessions into the Diat. barcode database  (Rimet et al. , 2019) , though this exercise is arguably more rigorous for freshwater diatoms, given the primary use of Diat. barcode to support to river biomonitoring through metabarcoding.
g. 'group Z' in the rbcL tree (comprising N. umbonata, N. lorenziana and N. cf. palea TCC886: Fig. 4  and Supplementary Fig. 2 ), and 'Bacillaria sp. ' SH349. These groups, like Cymbellonitzschia, may not contain many species, although very recently  Mucko et al. (2020, in press ) have described a new species (Nitzschia inordinata) that is related to 'Bacillaria' SH349. The two species have a similar valve and raphe structure (our unpublished data for SH349) but N. inordinata has sigmoid frustules (SH349 is straight:  An et al. 2017). Kociolek and Williams (2015)  suggested that diatomists have been overcautious in erecting new genera, noting that 64000 fish taxa are grouped into 12000 genera, whereas roughly the same number of diatom taxa are grouped into only 1200 genera. This comparison is arguably not a good basis for guiding taxonomic decisions in diatoms, because in fish there are many easily recognizable morphological characteristics available for classification and identification (see also below, 'Cryptic clades').
Markers to be sequenced. The lack of robust support for any of the basal nodes within the Bacillariaceae, even in the four-gene analysis, suggests that a wider sampling of the genome may be needed before the deeper relationships can be established. Other chloroplast genes (psaA, psaB, psbA, and atpB) have phylogenetic information profiles much more closely resembling that of rbcL and psbC, suggesting that the plastome should be explored further as a source of the necessary data  (Theriot et al. , 2015). Within each of the main clades (i. e. in each of the genera and putative genera in option D of Table  2 ) the present range of genes may be sufficient to solve most taxonomic problems. Indeed, the rbcL+nLSU combination seems to approach the fourgene set in terms of resolution and support and could be an economic way to characterize and place new isolates.
In most cases, what makes a phylogeny interesting is what it implies about how the properties of the organisms have evolved -their morphology, ecology, metabolism, etc -but, as we have already noted, for many of the sequences in Bacillariaceae in GenBank, there is little information about the diatom from which they were obtained, apart from a species or genus name. It is important, therefore, that new sequences for phylogeny reconstruction are accompanied by ancillary data on organisms' properties, including as full a documentation as possible of morphology. For the Bacillariaceae it would be helpful to expand the list of characters that diatomists routinely survey. In particular, our data (e. g. Figs 4, [6] [7] [8]  suggest that details of the raphe canal and the structure of the girdle deserve more attention.
Acknowledgements AW and ChL acknowledge funding from  Polish National Science Centre (NCN) in Cracow  [grant no. N2012/04/A/ST10/00544 ]. Thanks are due to  Dr. Przemysław Dąbek ,  Ewa Górecka  and  Marta Krzywda ,  Nickolai Davidovich  and  Olga Davidovich  for isolations and for help with lab work. AW also acknowledges support from  Chinese Academy of Sciences President's International Fellowship Initiative (PIFI)  and is grateful to  Dr. Rinat Gogorev  for providing.
Li psbC four-gene, psbC Cylindrotheca sp. SZCZCH50 SZCZCH50 MN920674 C. Li rbcL four-gene, SSU+rbcL, LSU+rbcL, rbcL Cylindrotheca sp. SZCZCH50 SZCZCH50 MN943995 C. Li SSU four-gene, SSU+rbcL, SSU Hantzschia abundans HANT025-11 Hantzschia cf. amphioxys HANT015-11 HANT025-11 HANT015-11 [BOLD [BOLD] LSU rbcL LSU+rbcL, LSU LSU+rbcL, rbcL Hantzschia sp HANT009-11 HANT009-11 database] [BOLD] rbcL rbcL Hantzschia abundans HANT025-11 Hantzschia sp. HANT001-11 HANT025-11 HANT001-11 [BOLD] [BOLD rbcL LSU LSU+rbcL LSU+rbcL, LSU Hantzschia abundans HANT026-11 HANT026-11 [BOLD] database] rbcL rbcL Hantzschia amphioxys HANT011-11 Hantzschia sp. HANT001-11 HANT011-11 HANT001-11 [BOLD [BOLD] LSU rbcL LSU+rbcL, LSU LSU+rbcL, rbcL Hantzschia sp. HANT002-11 HANT002-11 database] [BOLD LSU LSU+rbcL, LSU Hantzschia amphioxys HANT011-11 HANT011-11 [BOLD] database] rbcL LSU+rbcL, rbcL Hantzschia amphioxys HANT017-11 Hantzschia sp.
HANT002-11 HANT017-11 HANT002-11 [BOLD [BOLD] LSU rbcL LSU+rbcL, LSU LSU+rbcL, rbcL Hantzschia sp. HANT005-11 HANT005-11 database] [BOLD LSU LSU+rbcL, LSU Hantzschia amphioxys HANT017-11 HANT017-11 [BOLD] database] rbcL LSU+rbcL, rbcL Hantzschia amphioxys HANT018-11 Hantzschia sp. HANT005-11 HANT018-11 HANT005-11 [BOLD [BOLD] LSU rbcL LSU+rbcL, LSU LSU+rbcL, rbcL Hantzschia sp. HANT006-11 HANT006-11 database] [BOLD LSU LSU+rbcL, LSU Hantzschia amphioxys HANT018-11 HANT018-11 [BOLD] database] rbcL LSU+rbcL, rbcL Hantzschia amphioxys HANT019-11 Hantzschia sp. HANT006-11 HANT019-11 HANT006-11 [BOLD] [BOLD] rbcL rbcL rbcL LSU+rbcL, rbcL Hantzschia amphioxys HANT028-11 Hantzschia sp. HANT021-11 HANT028-11 HANT021-11 [BOLD [BOLD LSU LSU LSU+rbcL, LSU LSU+rbcL, LSU database] database] Hantzschia amphioxys HANT028-11 Hantzschia sp.
HANT021-11 HANT028-11 HANT021-11 [BOLD] [BOLD] rbcL rbcL LSU+rbcL, rbcL LSU+rbcL, rbcL Hantzschia amphioxys TCC901 Hantzschia vivax TCC940 TCC901 TCC940 MN696780 MN696730 F. Rimet F. Rimet rbcL SSU rbcL SSU Hantzschia amphioxys TCC901 Nitzschia acicularis Nit56 TCC901 Nit56 MN696729 MN734045 F. Rimet C. SSU SSU Cylindrotheca sp. SZCZCH690 Hantzschia cf. amphioxys HANT012-11 SZCZCH690 HANT012-11 MN944005 [BOLD C. Li LSU LSU four-gene, LSU+rbcL, LSU LSU+rbcL, LSU Cylindrotheca sp. SZCZCH690 SZCZCH690 MN920685 database] C. Li psbC four-gene, psbC Cylindrotheca sp. SZCZCH690 Hantzschia cf. amphioxys HANT012-11 SZCZCH690 HANT012-11 MN920676 [BOLD] C. Li rbcL rbcL four-gene, SSU+rbcL, LSU+rbcL, rbcL LSU+rbcL, rbcL Cylindrotheca sp. SZCZCH690 Hantzschia cf. amphioxys HANT013-11 SZCZCH690 HANT013-11 MN943996 [BOLD C.
Li SSU LSU four-gene, SSU+rbcL, SSU LSU+rbcL, LSU Hantzschia abundans HANT024-11 Hantzschia cf. amphioxys HANT013-11 HANT024-11 HANT013-11 [BOLD database] database] [BOLD] LSU rbcL LSU+rbcL, LSU LSU+rbcL, rbcL Hantzschia abundans HANT024-11 Hantzschia cf. amphioxys HANT015-11 HANT024-11 HANT015-11 [BOLD] [BOLD rbcL LSU LSU+rbcL, rbcL LSU+rbcL, LSU database].
The Ir L 2,3 edge was probed at the APS beamline 4-ID-D (hard X-rays), where the partial fluorescence yield and reflectivity signals were measured. DFT calculations. First-principles DFT calculations were performed using the generalized gradient approximation  55  and the projector augmented wave (PAW) pseudopotentials  56  as implemented in the Vienna ab initio Simulation Package (VASP) code  57, 58. To better describe the strong correlation effect, the local Hubbard repulsion  59  with U = 2 eV is included for Ir d states  60. The spin-orbit coupling (SOC) is also turned on. To minimize the complexity arising from the interface with LSMO, we considered bulk SIO with the experimental lattice constants, a ¼ 5:5617A, a ¼ 5:5909A, and c ¼ 7:8821A with corrections  61, 62. The proximity coupling with LSMO is simulated by performing constrained magnetic moment calculations.
Here, the direction of Ir moments is fixed along the crystallographic z direction and their size is varied. Following a self-consistent calculation with total energy convergence of 10 À5 eV, the maximally localized Wannier functions  63  were constructed using the WANNIE90 code  64  from the ab initio ground-state wave function. In the disentanglement process, 112 Wannier functions were chosen as initial projections including the d orbitals of Ir atoms and the p orbitals of O atoms. Finally, the AHC was calculated by computing the Berry curvature using the Wannier interpolation approach which is also implemented in the WANNIER90 code  64, 65.
Acknowledgements The authors acknowledge received funding from the projects  Quantox of QuantERA ERA-NET Cofund in Quantum Technologies  (Grant Agreement No. 731473 ) and To2Dox of the  Flag ERA ERA-NET  implemented within the European Union's  Horizon 2020 Programme. This work was supported by  Spanish MINECO  through grants,  MAT2017-87134-C02 , J. S. thanks  Scholarship program  Alembert funded by the  IDEX Paris-Saclay ,  ANR-11-IDEX-0003-02. Work at  CNRS/Thales lab  supported by  ERC  grant  N°647100  " SUSPINTRONICS" and French ANR  grants  ANR-15-CE24-0008-01  " SUPERTRONICS " and  ANR-17-CE24-0026-03  "OISO". J. S. thanks  Maria Varela  for helpful discussions. L. F. L. was supported by the  China Scholarship Council. The research at ORNL was supported by the  US Department of Energy (DOE), Office of Science, Basic Energy Sciences ,  Materials Sciences , and Engineering Division.
In the companion paper  [1]  we have derived the short-ranged potentials for the Teukolsky equations for massless spins (0, 1/2, 1, 2) in general spherically-symmetric and static metrics. Here we apply these results to numerically compute the Hawking radiation spectra of such particles emitted by black holes (BHs) in three different ansatz: charged BHs, higher-dimensional BHs, and polymerized BHs arising from models of quantum gravity. In order to ensure the robustness of our numerical procedure, we show that it agrees with newly derived analytic formulas for the cross-sections in the high and low energy limits. We show how the short-ranged potentials and precise Hawking radiation rates can be used inside the code BlackHawk to predict future primordial BH evaporation signals for a very wide class of BH solutions, including the promising regular BH solutions derived from loop quantum gravity.
We present in details three examples as illustrations, namely charged BHs, higher-dimensional BHs, and polymerized BHs. The important point we wish to emphasize is that most of the previous studies on HR were performed with heavy use of numerical methods due to the lack of a general derivation of the short-ranged potentials. Here we take advantage of the analytical results derived in  [1]. As a consistency check, we also compare our results at low and high energy with analytical limits, some of which are derived for the first time here. This gives strong support for the robustness of our numerical method based on short-ranged potentials, which can then be used to predict HR radiation signals for other BH metrics for which there is no analytical results yet. During this study, we have also modified the public code BlackHawk  [51] , written by a subset of the present authors, to produce the Hawking spectra of BHs with the new metrics.
The spherical symmetry reduces the sum on m in Eq. (1. 7) to a factor 2l + 1. To compute these greybody factors, we have used the same kind of Mathematica scripts that are given with the public code BlackHawk  [51]. Finally, we also define the cross-section σ i for a particle i by σ i ≡ π E 2 Γ i. (1. 13) We emphasize here that the new HR results obtained in this paper will be part of a forthcoming update of BlackHawk, where the aforementioned scripts and tabulated greybody factors will be publicly available.
Thus, the most striking result from this Section is that we expect the window for light PBHs to represent all DM to be reopened in the case of high values of ε, down to smaller PBH masses than in the Schwarzschild case. In order to illustrate this proposal, we have chosen to compute the prospective evaporation constraints from MeV to GeV photons as will be measured by AMEGO, whose expected sensitivity can be found in  [67]. There are two reasons for this choice: i) this limit lies among the most stringent ones in the disputed mass range where PBHs may represent all DM (see  [8] ), ii) some of the authors of this paper are also authors of the public code BlackHawk, which has been updated to compute precisely the secondary low energy photon spectra and obtain robust constraints in the considered mass range  [8] , as well as to compute the primary emission rates for photons in the polymerized metric.
Following the shutdown of the CEA Valduc experimental facilities, where, for more than 50 years, IRSN used to perform experiments related to criticality safety, IRSN initiated a new project named PRINCESS (PRoject for IRSN Neutron physics and Criticality Experimental data Supporting Safety). The objective is to continue collecting experimental data necessary for the IRSN missions in nuclear safety. For this purpose, collaborations with various national and international laboratories have been established. The PRINCESS project covers various nuclear physics fields from nuclear data to criticality-safety and reactor physics providing information to both differential and integral data improvements.
INTRODUCTION In the frame of its missions, IRSN performed various experimental programs related to criticality-safety in collaboration with the CEA Valduc. Following the shutdown of the Valduc facilities, IRSN has initiated a new project named PRINCESS  [1]  for "PRoject for IRSN Neutron physics and Criticality Experimental data Supporting Safety". The aim is to continue gathering experimental data necessary for criticality safety by the mean of collaborations with various national and international laboratories and to extend them to reactor physics. The PRINCESS project covers the acquisition of new experimental data, but also old ones that are not freely available. This paper presents an overview of the status of the IRSN PRINCESS project.
J-PARC is a proton accelerator facility operated by JAEA and KEK in Tokai-Mura. Neutron capture cross section and transmission measurements were performed on natural molybdenum with ANNRI (Accurate Neutron-Nucleus Reaction measurement Instrument) in MLF (Material Life and science Facility for the purpose of using neutrons to investigate material properties) of J-PARC. Five metallic natural molybdenum samples with various thicknesses of 0. 1 mm, 0. 5 mm and 2 mm for capture and 0. 5 mm and 5 mm for transmission were considered. Additional measurements were performed to determine the background and the normalization factors. A NaI detector (flight length of about 28 m) was used for capture measurements and a Li-glass detector (flight length of about 28. 7 m) for transmission measurements. After the data reduction process, the measured data are being analyzed in order to produce more accurate cross sections and associated uncertainties.
Criticality risk prevention The objective is to contribute to criticality calculation packages and nuclear data validation. The experiments of interest are mainly slightly sub-critical approaches extrapolated to critical conditions using split-tables, pool tanks or sub-critical experiments dealing with noise measurement techniques. Within the PRINCESS project, IRSN continues its long-standing collaboration with US Department of Energy (DOE) laboratories on various experimental programs under the auspices of the US Nuclear Criticality Safety Program (NCSP). Additionally, the long term collaboration established with JAEA has been strengthened notably with the study of neutronic characteristics of fuel debris in the new STACY Facility.
CONCLUSIONS IRSN initiated a project named PRINCESS (PRoject for IRSN Neutron physics and Criticality Experimental data Supporting Safety). The objective is to collect experimental data necessary for its missions in nuclear safety. The PRINCESS project covers various nuclear physics fields from nuclear data to criticality-safety and reactor physics providing information to both differential and integral data improvements. It concerns the acquisition of new experimental data, but also old ones that are not freely available. Strong bilateral collaborations have already been put in place with DOE/NCSP, JAEA and SCK-CEN, allowing IRSN to maintain its capabilities in nuclear criticality-safety and reactor physics. Collaborations with other institutes and other countries are foreseen in the next years.
Thanks to the versatility of the automatic code infrastructure provided by FEniCS, the code is well-suited to newcomers to finite element methods interested in modelling biological systems. To test the new framework, we address complex cell geometries in two and three dimensions and compare the method to the standard finite element method in terms of accuracy. The results obtained with the new method CutFEM are as accurate as the finite element method (FEM) whilst CutFEM disentangles the cell morphology from its discretisation, enabling to deal with arbitrarily complex morphologies, including kinks and triple junctions, in two and three dimensions. A thorough understanding of brain metabolism is essential to tackle neurodegenerative diseases  [2, 3]. Astrocytes are glial cells which play an important metabolic role by supplying neurons with energy  [4].
Moreover, we use the libCutFEM library, which is a cut finite element extension of the open-source framework of the FEniCS Project  [15] [16] [17] 47]. FEniCS offers a highly flexible and easy way of transforming models expressed as partial differential equations into numerical methods based on the finite element method through the Unified Form Language (UFL)  [52] , a domain-specific programming language for writing the weak form of partial differential equations. The UFL specification of the finite element problem is then automatically translated by the other components of the FEniCS Project (DOLFIN  [16]  and the FEniCS Form Compiler (FFC)  [15] ) into high-performance specific C++ code with little or no user intervention. Solution scheme To solve the set of coupled, time-dependent and non-linear PDEs, we first discretise in time using a standard implicit time stepping scheme.
Usability and extensibility of the framework Thanks to the flexibility of FEniCS, the framework is generic and usable by biologists without a background or specific training in Computational Sciences or Applied Mathematics. The code used to create the two of the examples is freely online accessible (see "Availability of data and materials") and can be adapted to other problems straightforwardly. The paper is organized as follows. In "The problem formulation" section, we present the biological model for energy metabolism followed by the governing equation and its weak form. The FEM and CutFEM discretization can be found in "Discretization" section. In "Implementation" section a detailed explanation of how implement our model in CutFEM is presented. Our numerical results are introduced in "Numerical results" section and the conclusions follow in "Conclusion and discussion" section.
Instead we aim show a precise derivation of the discrete weak forms and then in the subsequent section we show their translation into the FEniCS Project domain specific language, called the Unified Form Language (UFL)  [52]. In practice, if the user can convert their problem into a discrete weak formulation then the the FEniCS Project and the libCutFEM library can automatically perform all of the subsequent discretization steps. For full details of how this process takes places the reader is referred to  [16, 47].
Implementation The finite element method discretization has been implemented using Python with the open source finite element solver DOLFIN from the FEniCS Project, see  [15, 16]. The Cut-FEM discretization has been implemented using Python using the libCutFEM library  [47]  which builds on top of DOLFIN and the rest of the FEniCS Project. In this section we show parts of the code for the libCutFEM example that highlight the close link between the mathematics and the concrete computer implementation. The standard FEniCS Project implementation is similar so we have chosen to show only the libCutFEM implementation for reasons of brevity. The reader should refer to the free online repository for two full working examples that are around 250 lines of code each. The precise problem setup and results from this example are shown in "Two-dimensional non-Lipschitz domain" section.
We import the dolfin and cutfem Python modules. These two modules contain all of the functionality we need to solve the problem using the CutFEM approach. We create the background mesh and then define a level set function describing the heart-shaped domain. In the next part of the code, we use two special libCutFEM methods to 1. create a special cut mesh, and 2. a mesh_cutter that intersects the mesh with the level set and computes the distinct sets of cells (i. e. those that are on the inside of the level set and those that are outside). With these special objects in hand we can define special CutFEM-specific UFL Measure objects that will subsequently allow us to write the residual and the stabilisation weak forms. Simply put, a measure defines regions of the problem mesh (cells, edges, parts inside the level set, and parts outside etc.