dataesr/scientific-paragraphs-categorization huggingface dataset:
7 L min -1 and sample uptake rate 1. 0 L min -1. The following atomic line wavelengths were used in the measurements: Ag I (328. 068 nm) and Te I (214. 281 nm). X-Ray Diffraction (XRD) analyses were carried out with a Bruker D8 Advance diffractometer using Cu Kα radiation (λ = 1. 5406 Å) at 40 kV and 40 mA. The samples were scanned in the 2θ range from 10° to 70° but only the reduced range 20° to 60° was analyzed, where all the main peaks of the Te-based phases were expected. The crystallographic phases were analyzed on the basis of the JCPDS databases with the EVA 5 software. (cFEG TEM/STEM) operating at 200 kV and equipped with a spherical aberration (Cs) probe and image correctors (point resolution 0. 12 nm in TEM mode and 0. 078 nm in STEM mode). The growth direction of the nanostructures was determined by imaging and Selected Area Electron Diffraction (SAED).
Acknowledgements This work was supported by the  Grand Est Region  under the  Nanohyb  project. Sebastien DILIBERTO  (from  Université de Lorraine, CNRS, IJL, F-57000 Metz, France ) and  Sylvie MIGOT  (from  Université de Lorraine, CNRS, IJL, F-54000 Nancy, France ) are acknowledged for their technical support.
08 kg/h. To better monitor the flame spread during combustion, an IR camera was set up to measure the surface temperature during whole combustion. A FLIR X6540sc IR camera calibrated from 20 • C to 1500 • C was used, equipped with a specific filter-eliminating wavelength corresponding to the flame. It allows the visualization of the surface of a material without the contribution of the flame. The data was collected and treated with FLIR ResearchIR software.
(20b) C. Numerical methods All the numerical analyses are performed using FreeFEM++ software  [27]  for axisymmetric cylindrical coordinates (r, z). The velocity, pressure and temperature are discretized with Taylor-Hood P2, P1 and P2 elements, respectively. The typical number of triangles is ∼ 10 4. The linear equations and the eigenvalue problem are solved using UMFPACK library and ARPACK shift-invert method, respectively. Starting with the initial radius R = 3. 5 mm, the nonlinear solution of (  4 ) is solved for the given water properties. Once the solution for one radius is found, it is used as the initial guess for the smaller radius. Within 5 iterations, the L2 norm residual becomes smaller than 1 • 10 -8. The zero normal velocity condition on the free surface is applied using the Lagrange multiplier method.
The tests were performed with the deformation control and the deformation increase per unit time was kept constant at 0. 05 mm/min. During the test, the value of the applied force was recorded. It was planned that the test would be stopped when the measured force dropped by 20% compared to the maximal value in the test. As described above, three concrete hollow cylinder specimens were subjected to testing two of which were prestressed: With regard to the assumptions concerning the specimens' boundary conditions and the technical conditions of the tests performed for the calculation, the tested elements were positioned between a rigid support at the bottom and a hinge joint suspended to the machine travers at the top. Data cables were placed through an opening in the steel plate for load transfer at the rigid support.
Acknowledgments: C. L. thanks  NIMS  for his internship support in Japan under the  NIMS-UR1 ICGP  agreement. C. L. , M. W. , N. O. , T. U. and F. G. wish to thank  Meng Zhou  and  David Lechevalier  of  Saint-Gobain KK (Tokyo, Japan ). The authors thank the CMEBA platform ( Francis Gouttefangeas  and  Loïc Joanny ) from  ScanMAT ,  UAR 2025 UR1-CNRS  for the FE-SEM images and EDX analyses. Raman investigations were performed using facilities available on  SIR Platform from ScanMAT ,  UAR 2025 UR1-CNRS. The authors are very grateful to  Bertrand Lefeuvre   ISCR UMR6226 CNRS-UR1  and  Alain Moréac  from  IPR   UMR6252 CNRS-UR1.
Here again, different magnifications have been used to take microscopic images. Surface analyses by XPS were carried out with a Thermo K-alpha spectrometer (ThermoFisher Scientific) operating under ultra-vacuum (10 -9 mbar). This device used the monochromatized Al-K radiation (1486. 6 eV) as X-ray source. An argon dry glove box is directly connected to the machine. The radiation is microfocused on the surface sample (ellipsoidal spot of 400 μm diameter). A charge compensation system based on low energy electrons was used. First, survey spectra were recorded from 0 to 1350 eV with a pass energy (PE) of 200 eV. Then core ionization spectra were recorded with a higher resolution at PE of 40 eV. All spectra were fitted with CasaXPS© software. Binding energy of the C 1s peak due to the presence of adventitious carbon has been set up to 285 eV.
Preparation of ZIF-67-Air. Remove the preparation process of calcination in N 2 ; the rest of the preparation process was consistent with the preparation process of Co 3 O 4 @CN. Evaluation of POD-like activity of Co 3 O 4 @CN. The exploration process of the enzymatic activity of Co 3 O 4 @CN was as follows. Totals of 20 µL of Co 3 O 4 @CN (2 mg/mL), 30 µL of TMB (10 mM) and 30 µL of H 2 O 2 (10 M) were sequentially added to buffer solution at pH = 5, and the total volume of the reaction system was 2 mL. The UV-Vis spectral data in the range of 550 to 700 nm were collected by UV-Vis spectrophotometer. This process can be used to analyze the POD-like activity of Co 3 O 4 @CN. In addition, the rest of the experimental procedure was the same as above except that H 2 O 2 was not added, which can be used to study the OXD-like activity of Co 3 O 4 @CN.
Kinetic analysis of POD-like activity of Co 3 O 4 @CN. To explore the detailed catalytic mechanism of Co 3 O 4 @CN, the enzymatic kinetic testing of Co 3 O 4 @CN was performed. First, the absorbance of the reaction system as a function of time was measured after the addition of the different contents of Co 3 O 4 @CN (Figure  S5A ). The data analysis results show that the specific activity of the material is 1. 781 U mg-1 (Figure  S5B ). Subsequently, a steady-state kinetic test was conducted on the POD-like activity of Co 3 O 4 @CN by chang-ing the concentration of a substrate (TMB or H 2 O 2 ) while retaining the concentration of another substrate (H 2 O 2 or TMB) unchanged. Figure  S5C  and Figure  S5D  describe the relationship between the initial reaction velocity and the concentration of TMB and H 2 O 2 , respectively.
It can be seen that both curves accord with the Michaelis-Menten curve. The maximum reaction velocity (Vmax) and Michaelis constant (Km) were determined by the Lineweaver-Burk equation. Generally speaking, the Km value can be used to evaluate the affinity of the catalytic material to the enzyme substrate. The smaller the Km value, the higher the affinity of this catalytic material for the enzyme substrate. The data analysis shows that the Km value of the material to TMB is 0. 06877 mM and the Vmax is 14. 4207 µM min-1, indicating that the affinity of the material for TMB is at least 6 times that of HRP, and the maximum reaction rate is about 3 times that of HRP. Moreover, compared with other peroxidase mimics, the affinity of Co 3 O 4 @CN for TMB still has great advantages (Table  S1 ). When H 2 O 2 was used as the substrate, Co 3 O 4 @CN had a significantly higher affinity than the single Co 3 O 4 NPs and other peroxidase mimics.
Chemosensors 2022, 10, x FOR PEER REVIEW 8 of 13 Kinetic analysis of POD-like activity of Co3O4@CN. To explore the detailed catalytic mechanism of Co3O4@CN, the enzymatic kinetic testing of Co3O4@CN was performed. First, the absorbance of the reaction system as a function of time was measured after the addition of the different contents of Co3O4@CN (Figure  S5A ). The data analysis results show that the specific activity of the material is 1. 781 U mg-1 (Figure  S5B ). Subsequently, a steady-state kinetic test was conducted on the POD-like activity of Co3O4@CN by changing the concentration of a substrate (TMB or H2O2) while retaining the concentration of another substrate (H2O2 or TMB) unchanged. Figure  S5C  and Figure  S5D  describe the relationship between the initial reaction velocity and the concentration of TMB and H2O2, respectively.
It can be seen that both curves accord with the Michaelis-Menten curve. The maximum reaction velocity (Vmax) and Michaelis constant (Km) were determined by the Lineweaver-Burk equation. Generally speaking, the Km value can be used to evaluate the affinity of the catalytic material to the enzyme substrate. The smaller the Km value, the higher the affinity of this catalytic material for the enzyme substrate. The data analysis shows that the Km value of the material to TMB is 0. 06877 mM and the Vmax is 14. 4207 μM min-1, indicating that the affinity of the material for TMB is at least 6 times that of HRP, and the maximum reaction rate is about 3 times that of HRP. Moreover, compared with other peroxidase mimics, the affinity of Co3O4@CN for TMB still has great advantages (Table  S1 ). When H2O2 was used as the substrate, Co3O4@CN had a significantly higher affinity than the single Co3O4 NPs and other peroxidase mimics.
Acknowledgements This work is based upon work of  COST Action CA18112 Mechanochemistry for Sustainable Industry  [20] supported by  COST (European Cooperation on Science and Technology). [21]  COST (European Cooperation in Science and Technology)  is a funding agency for research and innovation networks. Our Actions help to connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. C. B. and F. P. acknowledge the  German Research Foundation  (DFG; project  BO 823/16-1 ) and the aforementioned  COST Action  for financial support through a short-term scientific mission of F. P. We are also grateful to  Dr. N. Biliškov  and  Dr. B. Karadeniz  ( Ruđer Bošković Institute ) for technical assistance.
Experimental setup Tests are performed on a SOMAB Genymab 900 multitasking lathe (max cutting speed 30 m/min and max cutting force 10 kN), and four different configurations are tested on 3-mm-thick AA6082-T6 and AA7075-T6 sheets. The depth of cut is kept constant at 1 mm and the rake angle is set at 0 • , while the other parameters 130 are summarized in Table  3. Two tests for each configuration are performed, one with a high-speed camera   A sketch of the experimental setup and HSC and IR images (post-processed with MATLAB) are presented 135 in Fig. 6. The HSC images are used to measure the primary shear angle, while the mean temperature in the primary shear plane and the maximum temperature in the secondary shear plane are determined using IR camera images. Local heating of the plates is performed using a blowtorch.
CmXyn10B (recombinant endo-β-1,4-xylanase from Cellvibrio mixtus; Cat. # E-XYNBCM) and NpXyn11A (recombinant endo-β-1,4-xylanase from Neocallimastix patriciarum; Cat. # E-XYLNP) were obtained from Megazyme. TfXyn11A (recombinant endo-β-1,4-xylanase from Thermobifida fusca) was kindly provided by T. V. Vuong  [46]. All xylanases were purchased or recombinantly prepared as mono-component enzymes; protein purity was determined by SDS-PAGE (Additional file 1: Fig. S4 ). Bovine serum albumin (BSA) was obtained from Sigma-Aldrich (St. Louis, MO, USA; CAS# 9048-46-8). PcaLOOL2 (loosenin-like protein 2 from Phanerochaete carnosa, GenBank code EKM55357. 1) and Pca-LOOL12 (loosenin-like protein 12 from Phanerochaete carnosa, GenBank code EKM51974. 1) were recombinantly expressed in Pichia pastoris SMD1168H.
Briefly, codon optimized genes encoding PcaLOOL2 or PcaLOOL12 were obtained as subcloned in pPICZαA plasmids with a C-terminal 6 × His tag (GenScript, Piscataway, NJ, USA). Transformants were grown in shake flasks in buffered glycerol-complex medium (BMGY; 100 mM potassium phosphate buffer (pH 6. 0), 2% (w/v) peptone, 1% (w/v) yeast extract, 1. 34% (w/v) yeast nitrogen base, 4 × 10 -5 % (w/v) biotin, 1% (v/v) glycerol) at 30 °C and 100 rpm until an OD 600 of ~ 6 and then induced in buffered methanol-complex medium (BMMY; BMGY containing 0. 5% (v/v) methanol instead of glycerol). Secreted recombinant proteins were purified from culture supernatants by FPLC using a GE Healthcare His-Trap ™ FF Crude prepacked column (Thermo Fisher Scientific; Cat. # 11723219). Pm25 (Xyn10C, endo-β-1,4-xylanase from the termite Pseudacanthotermes militaris gut metagenome, GenBank code CCO21036.
Image analysis Dried composites were scanned at 600 × 600 dpi using Canon image RUNNER Advance C5250i system. The image processing was done with Fiji software  [54, 55]. The scanned RGB images were converted to Hue Saturation Brightness (HSB) color space. The strips were segmented from the background pixels in the saturation channel using "Threshold tool" by choosing pixels with minimum intensity value of 80 and maximum value of 255. The saturation channel was chosen for the analysis because it contained most of the tone loss due to the enzymatic reaction in comparison to the other channels. From Fiji function "Analyze particles" the minimum particle size was set as 1000 pixels to remove wrongly selected pixels from the background. Fiji function "save XY coordinates" was used to extract the x and y coordinates of each pixel, as well as their intensity value in each strip.
The data were stored as CSV files and imported to R studio  [56]  for further processing. X coordinates of the pixels were converted into percentages relative to full length of the strip and the split into four segments corresponding to turns of cellulose/azoxylan composites around the mandrel. Mean intensity values of each segment with the standard error of the mean from at least four replicated strips per treatment were plotted. Processing, analysis and plotting of the data were done using Tidyverse 1. 2. 1, ggplot2 3. 2. 1, dplyr 0. 8. 3 R packages  [56] [57] [58] [59]. Code for extracting pixel information using Fiji and processing the data in R is deposited in GitHub and available through the link https:// github. com/ mipav ici/ PACER assay.
Funding We thank the following granting agencies for their financial support: the  European Research Council (ERC)  (Consolidator Grant no. BHIVE -648925 ) (MM, EJ, VL and ERM);  Jenny and Antti Wihuri Foundation (Centre for Young Synbio Scientists) (TK) ;  Academy of Finland   Postdoctoral Researcher Grant  No. 331853  (TP); The  French national research agency (anr)  Grant No. ANR-18-CES43-DECO  (TE and CD).
Most of them are Mg-based materials, but the search for new systems involving 3d metals is in progress. All these newly discovered properties lead to intensive research works in the field of hydride-based electrochemical storage of energy. In the present paper, state-of-the-art results are presented addressing high-capacity anodes, new superionic fast conductors, and full SSBs combining these astonishing materials into practical devices. Operando neutron diffraction studies were applied to study the mechanism of transformations in the LaNdMgNi 9 AB 3 type anode. The electrochemical charge and discharge showed the formation of a saturated LaNdMgNi 9 D 13 deuteride. Deuterium isotope was used instead of H to improve the quality of the data and to observe the sequence of transformations in the anode electrode during step-by-step electrochemical charge and discharge  [17].
Acknowledgments This paper was realised within the framework of the  Hydrogen Technology Collaboration Programme (TCP)  of the  International Energy Agency (IEA) in Task 40  'Energy storage and conversion based on hydrogen'. Torben R Jensen  acknowledges funding from independent research fund Denmark for technology and production,  Solid-State Magnesium Batteries-SOS-MagBat  ( 9041-00226B ) and  Calcium Metal Battery-CaMBat  ( DFF-0217-00327B ), and the  Danish Ministry of Higher Education and Science through the SMART Lighthouse. Rana Mohtadi  is grateful for  Mr Ryuta Sugiura  and  Dr Oscar Tutusaus  at  Toyota Research Institute of North America  for the discussions and acknowledges the financial support from  Toyota Motor Corporation. Sabrina Sartori  acknowledges the financial support from the  European Union´s   Horizon 2020 research and innovation program , under Grant Agreement No.
Fundings NWO materials for sustainability ( 739. 017. 009 )grant; and  NWO ECHO  ( 712. 015. 005 )grant;  RCN ENERGIX (LiMBAT 244054/E20 );  JSPS KAKENHI  ( 17H06519  and  19K15666 );  JSPS KAKENHI  ( 19K15305 );  JSPS KAKENHI (Hydrogenomics ,  JP18H05513 );  Hydrogen Materials-Advanced Research Consortium (HyMARC)  of the  U. S. Department of Energy (DOE) ,  Office of Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office; U. S. Department of Energy (DOE) ,  Office of Energy Efficiency and Renewable Energy ,  Vehicle Technologies Office  under Contract  DE-AC52-07NA27344 ;  EU   Horizon 2020 program , Grant Agreement  778307-HYDRIDE4MOBILITY-H2020-MSCA-RISE-2017 ;  National Research Foundation of Korea  ( NRF-2020M1A2A2080881 );  ARC   Future Fellowship   FT160100303 ;  Carlsberg Reintegration Fellowship   CF19-0465.
The DCM units were calculated using PBE0 functional and the 6-311G+(d,p) basis set while the bridge connecting the DCM unit was treated using the semi-empirical PM6 method (see details in Figure  S1 ). The optimized geometries have been built and converged in an unfolded conformation for both (EZ)-2DCM and (EE)-2DCM structures, as shown in Figure  7  and Figure  S1. They were packed with 1500 THF molecule by Packmol (Figure  S2 ),  [12]  and MD simulations were performed with the GROMACS software package version 2020  [13]  using general AMBER force field (GAFF)  [14]  from AmberTools. [15] All the simulations for (EZ)-2DCM and (EE)-2DCM were performed in a sequence involving the energy minimization, the equilibrium isothermal-isobaric (constant particle number, pressure and temperature, NPT) ensemble, and the production NPT ensemble for 200 ns, which was validated by comparison with longer trajectories (Figure  S5  and Table  S1 ).
More interestingly, connections between the main conformations found by PCA of (EZ)-2DCM and (EE)-2DCM, can be revealed by the Markov State Model (MSM) method, as detailed below. Markov State Models (MSMs) of 2DCM. To further rationalize the conformational changes occuring during the trajectories produced by MD simulations, we built the MSM for both trajectories, corresponding to (EZ)-2DCM and (EE)-2DCM. The MSM reveals the important intermediate states from the MD simulation data and their mutual relationships. The analysis was carried out using the PyEMMA package. [16] The MD trajectories were taken into a time-lagged independent component analysis (tICA), and featurized by the software. The tICA maximizes the autocorrelation of the linearly transformed coordinates by a lag time , finding a maximally slow reaction in the MD simulation corresponding to the lag time of the input parameter as the first independent component (IC).
Experimental Section Materials. The synthetic protocols of DCM, 2DCM and 3DCM are given in the Supporting Information. All commercially available compounds and solvents are purchased from Sigma-Aldrich affiliated to Merck KGaA, Carlo Erba Reagents, TCI chemicals and Acros Organics affiliated to Thermo Fisher Scientific without further purifications. 1H-, 13C, COSY, HSQC NMR data were acquired by JEOL ECS-400 spectrometer with a broadband probe. Spectroscopic measurements were performed with spectroscopic grade solvents from Carlo Erba Reagents and Sigma-Aldrich affiliated to Merck KGaA. Steady-state spectroscopy. Absorption spectra at room temperature were recorded using Agilent Cary-4000 or Cary-5000 UV spectrometers. Fluorescence emission and anisotropy data were measured with Horiba Jobin-Yvon Fluorolog-3 spectrofluorometer equipped with polarizers in excitation and emission.
[14] The MD simulation was carried out using GROMACS software package version 2020. 2  [13]  trajectories of (EE) and (EZ) configured 2DCM were obtained. All trajectories were written every 5 ps for analysis. The production ensembles use the leapfrog integrator with the step size of 2 fs, a reference temperature at 298 K, a reference pressure at 1 bar. Molecular Dynamics (MD) analyses. The 2DCM trajectories were pretreated by GROMACS toolkit (principal components analysis, PCA). The covariance matrix and following eigenvalues, eigenvectors were generated and calculated by GROMACS toolkit or PyEMMA. The alltrajectory clustering was realized in VMD. [18] The MSM was obtained from the MD simulation data by analyzing with program PyEMMA. [16] The MD simulation data of 2DCM coordinates was estimated by computing a time-lagged independent component analysis (tICA).
Discussion In this work, we provide a large-scale digital gene bank of silkworm bioresources and find a high level of genetic diversity in silkworms. We have a larger sample size and a wider geographic distribution of sample set than in the previous publications that contain 40 strains (11 wild silkworms and 29 domestic silkworms) in 2009  41  and 144 strains (seven wild silkworms and 137 domestic silkworms) in 2018  22. We release 1078 high-depth NGS and 545 high-quality reference genomes and construct almost the entire pan-genome of silkworm with 7038 newly identified genes, more than fifty million short variants (SNPs and Indels), and over three million SVs. This dataset enables the functional investigation of many types of sequences. These include many coding genes absent from the existing silkworm reference genome, the core/ private genes in silkworms and the variable genes among populations, the complex SVs that are difficult to detect from NGS data, and the genomic variants in the non-coding regions that were rarely touched in previous studies using forward and reverse genetic approaches.
Short-read sequencing For NGS, a paired-end sequencing library of each sample of 1078 silkworms was constructed with insertion sizes ranging from 300 to 400 bp and sequenced through the DNBSEQ platform of BGI (China). SOAPnuke 54 v1. 5. 6 was used to filter out the low-quality reads (a read containing over 40% low-quality bases, base quality value less than 20 was considered as low-quality) and remove PCR duplication reads with parameters -n 0. 03 -l 20 -q 0. 4 -G -d -Q 2. The two prior resequencing projects of silkworms  22, 41  generated low coverage depths (only ~3× and ~13× coverage depth), limiting the utilization of those data in genome assembly and detection of structural variation. Thus, we sequenced all our samples in high depth ranging from 22× to 181× (approximately 65× on average).
Long-read sequencing For long-read DNA sequencing, 545 samples containing 39 wild, 162 local, 117 improved, and 227 genetic stock silkworms were selected to build Oxford Nanopore Technology (ONT) sequencing libraries in BGI (China). According to the standard procedure of library construction of the Oxford Nanopore Technologies Company, 20 kb DNA library of each sample was used to sequence on the PromethION platform with R9. 4 chemistry using the Ligation Sequencing Kit SQK-LSK109 (Oxford Nanopore Technologies). For the pooling library of two samples, reads of each sample must be split before filtering. Therefore, guppy_barcoder v3. 1. 50 (https://nanoporetech. com/) and qcat v1. 0. 1 (https:// github. com/nanoporetech/qcat) were applied to split reads and the intersection of the two results was used as split data.
The porechop v0. 2. 4 (https://github. com/rrwick/Porechop) program was used to find and remove adapters. We also removed the reads with length <5 kb and average quality <7. The final sequencing depth ranged from 48× to 277×. The N50 read sizes ranged from 13. 5 to 44. 9 kb with an average of 30 kb (Supplementary Data 2).