dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments This work was supported by the following: LILI-EQUIPEX-Lyon Integrated Life Imaging: hybrid  PET-MR ANR  project -11-EQPX-0026 , the  French National Agency for Research and Technology (ANRT) ,  CESAME -Brain and Mental Health ANR-10-IBHU-0003 program ,  Neurodis Foundation , and  Siemens Healthcare SAS France. We would like to thank  Siemens Medical Solutions, Knoxville, USA  for providing the PET reconstruction software e7tools. We thank our colleagues at the  CERMEP Lyon  for help in the acquisition and transferring of PET data; and  Marjorie Villien  for valuable advice on this work.
The resulting supernatant (cytosolic fraction) was precipitated with trichloroacetic acid and resuspended in Laemmli buffer. The pellet (mitochondrial fraction) was also directly resuspended in Laemmli buffer. Mitochondrial and cytosolic fractions were separated under reducing conditions on 14% SDS-PAGE gels. Immunoblotting was performed according to standard procedures using affinity-purified home-made antibodies raised in rabbits against the C-terminal segment of human MCU (residues 285-351) fused to maltose binding protein, and commercially available antibodies: MCU (Sigma-Aldrich, HPA016480), EMRE (Santa Cruz Biotechnology, sc-86337) and Aequorin (clone 6E3. 2, Merck/Millipore; MAB4405). Antibodies against YME1 and PKGa (Thermofisher/Novex, 459250) were used as markers for mitochondrial and cytosolic fractions, respectively.
, 2012; Vais et al. , 2016). Patch pipettes had resistances of 20 -60 MΩ when filled with (in mM): 130 TMA-OH, 100 HEPES, 10 glutathione, 2 MgCl 2 , 1. 5 EGTA, pH 7. 0/D-gluconic acid, osmolarity 330-350 mOsm/kg. Mitoplasts were initially bathed in (in mM): 150 KCl, 10 HEPES, pH 7. 2, osmolarity 300 mOsm/Kg ("KCl-DVF" solution). Voltage pulses of 350 -500 mV amplitude and 15 -50 ms duration, delivered by the PClamp-10 (Molecular Devices) program, were used to obtain the "wholemitoplast" configuration. Access resistance (30 -90 MΩ) and mitoplast capacitance C m (0. 2 -1 pF) were determined using the membrane test protocol of the PClamp-10 software. After the whole-mitoplast configuration was obtained, the KCl-DVF bath solution was exchanged with HEPES-EGTA (150 mM HEPES, 1. 5 mM EGTA, pH 7.
0/Tris-base) for baseline (control) measurements, followed by HEPES (no EGTA) solutions with 0. 1 and 1 mM CaCl 2 (with or without 10 μM mitoxantrone), successively. Finally, a HEPES-based solution with 1 mM CaCl 2 and 200 nM ruthenium red (RuR) was perfused to record the baseline (I RuR ) after complete block of MCU Ca 2+ currents. Osmolarities of all bath solutions were 297-305 mOsm/Kg, adjusted with sucrose. The voltage protocol, delivered by the PClamp-10 software with a DigiData-1550 interface (Molecular Devices), consisted in stepping from V m = 0 mV to -160 mV for 20 ms, followed by ramping to 80 mV for 860 ms, dwelling at 80 mV for 20 ms and return to 0 mV. Currents were recorded using an Axopatch 200-B amplifier (Molecular Devices). Data were acquired at room temperature with a sampling rate of 50 kHz and anti-aliasing filtered at 1 kHz.
Data analysis was performed with the PClamp-10 software. For quantitative comparisons, current densities were calculated with the formula: I Ca and I RuR being measured at V m = -160 mV, with 1 mM Ca 2+ in the bath. Isolation of Mouse Liver Mitochondria-Mitochondria were isolated from freshly collected livers of female NMRI mice. After cardiac perfusion, livers were excised and minced with 20 mL isolation buffer containing (in mM): 220 mannitol, 80 sucrose, 10 HEPES, 1 EDTA, and 0. 5% essentially fatty acid-free BSA supplemented with protease inhibitors (pH 7. 4/KOH). The tissue was homogenized with two strokes at 300 rpm using a loose-fitting Teflon homogenizer followed by nitrogen cavitation at 800 psi for 10 min. The homogenate was centrifuged at 600 g for 10 min at 4°C and the supernatant was further centrifuged at 4,000 g for 10 min.
Electrophysiological Measurements on Xenopus Oocytes-Oocytes were isolated from female Xenopus laevis (Xenopus One) and defolliculated with type IV collagenase (Worthington Biochemical) in OR2 medium (in mM: 85 NaCl, 2. 5 KOH, 1 MgCl 2 , 5 HEPES, pH 7. 6). Defolliculated oocytes were injected with 15 ng of Xenopus connexin-38 antisense RNA. 48 hr after injection, oocytes were incubated in OR2 medium in the presence or absence of 2 μM thapsigargin (dissolved in DMSO; DMSO did not exceed 1% in the working solution). Recordings were done at least 3 hr after incubation in 2 μM thapsigargin. Currents were recorded using a Warner OC 725-C voltage-clamp amplifier controlled via an ITC-18 interface (Instrutech) by Pulse software (Heka). Oocytes were placed in standard bath solution containing (in mM): 100 Na + , 100 Cl -, 2 K + , 1 Mg 2+ and HEPES (pH 7.
QUANTIFICATION AND STATISTICAL ANALYSIS Statistical Analysis of Primary Screens-Data analysis was performed using MATLAB software. The dynamics of mt-Ca 2+ -dependent luminescence was smoothed by the cubic spline function: where, p is a smoothing parameter, controlling the tradeoff between fidelity to the data and roughness of the function estimate, f is the estimated cubic spline function to minimize the above function, and x i and y i are the dynamical data points. Here, p is set at 0. 5. For each compound, two parameters were directly extracted: the maximal amplitude of the luminescence signal (peak) and the left slope of the bell-shaped kinetic trace (uptake rate). Based on these parameters an inhibition score, I drug , was assigned to each compound C i as follows: where, u i is the fitted value of the compound C i , and μ ̄ is the trimmed average of positive and negative controls.
Acknowledgments We thank  M. Jastroch  and  T. Misgeld  for helpful discussions,  U. Uhrig  for assistance on molecular docking studies, and  J. Lewis  and  B. Jehle  for assistance on drug screening. This work was supported by the  German Research Foundation (DFG)  under the  Emmy Noether Programme  ( PE 2053/1-1 ) to F. P. , J. W. , D. M. A. , and A. L. ; the  Bavarian Ministry of Sciences, Research and the Arts in the framework of the Bavarian Molecular Biosystems Research Network  ( D2-F5121. 2-10c/4822 )to F. P. , A. G. , C. G. -P. , and Y. C. ; the  Munich Center for Systems Neurology (SyNergy ;  EXC 1010 ) to F. P. ; the  NIH  grants  GM56328  to J. K. F. and  R01DC012538  to J. K. F. and Z. M. ; the  Spanish Ministerio de Economía y Competitividad  grant  BFU2014-53469P  and the  Instituto de Saludo Carlos III  grant  RD16/0011/0003  to M.
Data Analysis-All data are represented as mean ± SEM and the statistical details of experiments can be found in the figure legends. Differences between two datasets were evaluated by two tailed unpaired Student's t test. Statistical tests between multiple datasets and conditions were carried out using one-way analysis of variance (ANOVA) followed by Tukey's post hoc test. A P-value < 0. 05 was considered statistically significant. Statistical analyses were performed using GraphPad Prism version 5. 0 (GraphPad Software, San Diego, CA, USA).
No. HPA016480; Lot No. C0114358; RRID: AB_2071893 Cat. No. M2305005; CAS: 89991-52-6 N/A Rabbit polyclonal anti-EMRE -C22orf32 Disperse blue 7 p423GPD (plasmid) Santa Cruz Biotechnology Boc Sciences Mumberg et al. , 1995 Cat. No. sc-86337; Lot No. K0215; RRID: Cat. No. 3179-90-6; CAS: 3179-90-6 N/A (clone C-12) Daunorubicin hydrochloride p425GPD (plasmid) Sigma-Aldrich Mumberg et al. , 1995 AB_2250685 Cat. No. 30450; CAS: 23541-50-6 N/A Mouse monoclonal anti-Aequorin (clone 6E3. 2) Doxorubicin hydrochloride Software and Algorithms Merck/Millipore Sigma-Aldrich Cat. No. MAB4405; RRID: AB_94900 Cat. No. D1515; CAS: 25316-40-9 Mouse monoclonal anti-β-Actin (clone Epirubicin hydrochloride pClamp 10 Sigma-Aldrich Sigma-Aldrich Molecular Devices Cat. No. A2228; Lot No. 085M4754V; Cat. No. E9406; CAS: 56390-09-1 N/A AC-74) Idarubicin hydrochloride GraphPad Prism 5.
Statistical analysis Results are expressed as the mean ± standard error of the mean (SEM). Data were analysed with NCSS9 software (NCSS LLC, Kaysville, UT and GraphPad Prism software (version 5. 00 for Windows, GraphPad Software, San Diego, CA). For intergroup comparisons (smokers vs never-smokers), a non-parametric analysis of variance (ANOVA) was followed by Dunn's test for multiple comparisons. For comparisons of condition (i. e. Ach doseresponse curves in the presence and absence of another drug), a repeated-measures ANOVA was followed by a Tukey-Kramer test for multiple comparisons. Fischer's exact test or the Mann-Whitney test was used to compare categorical variables. To search for a correlation between 2 parameters, a non parametric correlation (Spearman) test was performed, followed by a linear regression.
Blot's images were analyzed with Image Lab ™ Software through 'Lane and Bands' method. The evaluation of the relative amount of each protein was performed relating the densitometric value of optical density (OD) units of each protein band to the OD units of the respective β-actin band and normalizing with respect to the samples control group. The phosphorylation level of AKT FoxO3a and Drp1 was determined relating the densitometric value of optical density (OD) units of each phosphorylated protein band to the OD units of the band of the total protein and normalizing with respect to the samples control group.
NOTE: Do not only check by looking at the specimen position on the CCD camera, move the specimen in the x-direction and make sure that the distance with the stage has not changed. 8. Move the stage to locate the specimen and verify that the beam is hitting the specimen at the position of interest (where the TKD scan will be performed) on the specimen using secondary electron imaging. 1. Select the secondary electron detector in the detector tab of the SEM control panel. 9. Turn on the EBSD software and insert the EBSD camera by pressing the "in" button on the control box of the EBSD camera to a distance of 15 to 20 mm from the specimen using the external controller or the software. 10. If required for the analysis, insert the EDS detector within the chamber by clicking the "in" button on the EDS camera control panel.
EBSD Software Parameters for Data Acquisition NOTE: The data acquisition parameters are different for specific commercially-available EBSD systems. This section is written as generally as possible, but some of the names and values of the parameters given here are only appropriate if one uses the EBSD software mentioned in the Materials List, and users of different systems will need to adjust these parameters according to their own system. Most of these steps are exactly the same as for a normal EBSD experiment. 1. Make sure that the specimen geometry in the EBSD software reflects the fact that the specimen is in horizontal position. Ensure that the total tilt value is 0°. If not, add a -20° pre-tilt value in the specimen geometry tab. 2. Select the phase(s) (which element or compound) to be analyzed as for a normal EBSD experiment in the phase tab.
Representative Results The data presented here have been collected using the SEM, EBSD system and software mentioned in the Materials List. Depending on the features of interest, scans were run with different step sizes and the specific step size is indicated for each specimen shown in this work. The two first examples of TKD application presented here are related to grain refinement of metallic alloys in order to increase their mechanical properties. Stainless steels and Cobalt-Chromium-Molybdenum alloys are commonly used for biomedical applications due to their high corrosion resistance, good mechanical properties under static loading and biocompatibility  23, 24. However, both these materials have drawbacks: stainless steels have low hardness and wear resistance while Co-Cr-Mo alloys can fail due to tribocorrosion phenomena.
Discussion All the data presented in this paper were obtained using a standard, commercial EBSD system. Such a system is available in many laboratories around the world, which means that this technique can readily be applied in these laboratories without having to make any further investment. No modification in the configuration of the SEM and no additional software are necessary to use the EBSD system to collect TKD data. Therefore the transition from traditional EBSD to TKD is very easy. The data acquisition rate for TKD is similar to that of EBSD, which currently reaches up to approximately 1,000 patterns/s 19. This high rate is partially due to the very high level of automation of the technique, including calibration for pattern center position and pattern center change during scanning 19.
Acknowledgements The authors acknowledge the facilities, and the scientific and technical assistance, of the  Australian Microscopy & Microanalysis Research Facility at the Australian Centre for Microscopy and Microanalysis, The University of Sydney. This research was partially supported by funding from the  Faculty of Engineering & Information Technologies, The University of Sydney , under the  Faculty Research Cluster Program , from the  Regional Council of Champagne-Ardenne (France)  through the  NANOTRIBO  project and from the  European FEDER program.
The glass samples from the SO193 expedition (ref. 4 and references therein) were re-analysed with electron micro-probe (EMP) and laser ablation inductively coupled plasma source mass spectrometry (LA-ICP-MS) using the same analysing conditions and standards for better data comparison. The sample SO225DR12-2 contained only small amounts of fresh glass material and thus it was not possible to replicate the radiogenic isotope composition. This sample shows slightly higher 143 Nd/ 144 Nd and 87 Sr/ 86 Sr ratios compared with the more-enriched glass sample compositions, plotting slightly off the estimated correlation line and therefore data for this sample have not been used to estimate the end member compositions. Whole-rock samples from the SO225 and SO193 cruise are fine-grained and show different degrees of seawater alteration from fresh to strongly altered samples (loss of ignition (LOI): 1-13 wt%, see Supplementary Table  2 ).
Sample mounts were mounted in a twovolume ablation cell  49  , and the ablated sample aerosol was transported with helium as the carrier gas and mixed with argon prior to introduction into the spectrometer. Glass shards were analysed with 60-80 mm crater size, 10 J cm À 2 laser energy and 10 Hz laser frequency. The total analysis time for each single analysis was set to 80 s (20 s background and 60 s counting time during laser ablation). The measured intensities were converted to concentrations in the Glitter software by using  43  Ca as internal standard and Ca concentrations from EMPA. The SRM NIST612 standard  50  was used for initial calibration. Matrix correction was applied by using data for KL2-G reference glass  51. Reference glasses GOR128-G and BCR-2G were analysed as unknown, and the data are listed in Supplementary Table  6c.
Consistency between EMPA and LA-ICP-MS data was checked using Ti contents, which agreed within 10% rel. between the two techniques. Analytical precision for multiple analyses was typically better than 3% rel. for most elements. Further details of the setup and calibration strategy can be found in ref. 52. The LA-ICP-MS data in Supplementary Table  1  are average trace element concentrations obtained from three to five spots for every sample. In addition, whole-rock powder of the sample SO225DR24-10 was analysed for trace elements using an Agilent 7500cs ICP-MS instrument following acid digestion as described in ref. 53. The trace element data generated by laser ablation ICP-MS on glasses and solution ICP-MS on the bulk sample show excellent agreement on p. p. m. to sub-p. p. m. concentrations, except for elements easily affected in bulk rocks by seawater alteration (for example, Cs, Sb, Rb, U).
Within-run mass bias correction used 146 Nd/ 144 Nd ¼ 0. 7219 and 86 Sr/ 88 Sr ¼ 0. 1194. NBS987 and La Jolla reference material was measured five to six times each turret to obtain a normalization value relative to our preferred values of 87 Sr/ 86 Sr ¼ 0. 710250 and 143 Nd/ 144 Nd ¼ 0. 511850, respectively. The normalization value was then applied to the sample data of each turret. Over the course of the study, the long-term machine drift compensated external 2s uncertainties (2SD) are ± 0. 000011 (n ¼ 25) for NBS987 and ± 0. 000007 (n ¼ 33) for La Jolla. Within-run 2 s. e. errors are equal or smaller than 2 s. d. of the reference materials. Total chemistry blanks were 10 to 30 pg for Pb and below 150 pg for Sr and Nd and thus negligible. Replicate analyses by means of a second sample digest were carried out for SO225 ROV-3-6 whole-rock chips.
Acknowledgements We thank  Captain Mallon , the  R/V Sonne  crew and the scientific team of the SO225 cruise for excellent cooperation. We are grateful to  M. Tho ¨ner ,  U. Westernstro ¨er  and  S. Hauff  for support with EMP, LA-ICP-MS and TIMS analyses respectively. Insightful comments of  R. Arculus ,  M. Jackson  and  M. L. Tejada  helped to substantially improve the manuscript. This study was funded by the  German Ministry of Education and Research (BMBF ,  Manihiki II  project; #  03G0225A ). This is a CRPG contribution  N°2444.
ACKNOWLEDGMENTS This work was supported by the  Polish National Science Centre  on the basis of the decisions No. DEC-2012/05/B/ST3/02516 ,  DEC-2011/03/B/ST5/02698 , and  DEC-2012/05/B/ST3/03113. This research was supported in part by  PL-Grid Infrastructure. The calculations reported in this paper were performed using computing facilities of the  Interdisciplinary Centre for Modelling of Warsaw University (ICM UW ) and on cluster Nostromo, i. e. a computing facility of  Center for Preclinical Research and Technology (CePT). We would like to thank  Prof. Piotr Boguslawski  for critical reading of the manuscript.
OASIS is coupling software developed primarily for use in the climate community. It provides the ability to couple different models 1 with low implementation and performance overhead. OASIS3-MCT is the latest version of OASIS. It includes several improvements compared to OASIS3, including elimination of a separate hub coupler process, parallelization of the coupling communication and runtime grid interpolation, and the ability to easily reuse mapping weight files. OASIS3-MCT_3. 0 is the latest release and includes the ability to couple between components running sequentially on the same set of tasks as well as to couple within a single component between different grids or decompositions such as physics, dynamics, and I/O. OASIS3-MCT has been tested with different configurations on up to 32 000 processes, with components running on high-resolution grids with up to 1.
Introduction OASIS is coupling software developed primarily for the climate community. OASIS was originally an abbreviation for "Ocean Atmosphere Sea Ice Soil", but the capabilities provided by OASIS are not restricted to just those kinds of models, so the name OASIS now represents a project to develop general coupling software. It is in relatively wide use, especially in European-based modeling efforts. It is one of a number of coupling infrastructure packages  (Valcke et al. , 2016)  that are focused on standard and reusable meth-ods to support coupling requirements like interpolation and communication of data between different models and different grids. OASIS is maintained and managed by the Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS) and the Centre National de la Recherche Scientifique (CNRS) in France.
It is a portable set of Fortran 77, Fortran 90, and C routines. Low intrusiveness, portability, and flexibility are key OASIS design concepts. The current version of the software, OASIS3-MCT, is a coupling library that is compiled and linked to the component models. Its primary purpose is to interpolate and exchange the coupling fields between or within components to form a coupled system. OASIS3-MCT supports coupling of fields on grid types commonly used in climate science via a put-get approach, which means components make subroutine calls to send (put) or receive (get) data from within the component code directly. A separate top-level driver to control system sequencing is not required to use OASIS3-MCT, but a handful of subroutine calls must be added to the code to initialize the coupling, define grids, define decompositions (partitions), define coupling fields, and put and get variables between components.
This paper describes the development of OASIS3-MCT from OASIS3 to the current 3. 0 release and also introduces some new features expected in the next 4. 0 release. The initial requirements of OASIS3-MCT were to improve the parallel performance of the coupling, implement an ability to read in mapping weights to mitigate the cost of weight generation, support next-generation grids such as high-resolution unstructured grids running on high processor counts, and to add those features while retaining the basic OASIS3 application programming interfaces (APIs) and namcouple file to support backwards compatibility. To meet these requirements, a number of changes were made. First, a portion of the underlying communication implementation was replaced with the Model Coupling Toolkit (MCT) software package  (Larson et al.
With the release of OASIS3-MCT_3. 0 in 2015  (Valcke et al. , 2015) , several new features were added to the coupler. OASIS3-MCT_3. 0 extends the ability to couple components running concurrently and adds support for coupling within a component for grids and fields defined on overlapping or partially overlapping sets of tasks, such as between physics and dynamics modules within an atmospheric model or to and from an I/O module. OASIS3-MCT_3. 0 also allows a component to define grids, partitions, and coupling fields on subsets of its tasks, and it comes with a graphical user interface (GUI) to generate the namcouple file. The next section, titled Implementation, describes these features in greater detail. Section 3 provides performance and memory scaling results from OASIS3-MCT_3. 0 as well as some initial results for features expected in OASIS3-MCT_4.
General architecture To accomplish these tasks efficiently and in a timely manner, the MCT developed by the Argonne National Laboratory  (Larson et al. , 2005)  was incorporated into OASIS3 to support parallel matrix vector multiplication and parallel distributed exchanges. Its design philosophy, based on flexibility and minimal invasiveness, is consistent with the approach taken in OASIS. MCT has proven parallel performance and is one of the underlying coupling software libraries used in the National Center for Atmospheric Research Community Earth System Model (NCAR CESM)  (Jacob et al. , 2005; Craig et al. , 2012). MCT handles two primary tasks in OASIS3-MCT: the parallel transfer of data from a source model to a destination model, and interpolation of fields between decomposed grids. At the present time, these two steps are independent and both are largely performance limited by MPI communication cost at moderate to high processor counts due to the data rearrangement in both.
Memory Figure  5  shows the memory use per core for the T799-ORCA025 test case on Curie, the same test case as in Figs. 2  and 3. Memory use was determined by calls into the gptl (http://jmrosinski. github. io/GPTL/) interface, included in the OASIS3-MCT release, which queries memory usage through C intrinsics. At 16 000 cores, the infrastructure uses a bit more than 1 GB per core, which while not tiny, is generally acceptable for many applications and hardware. Memory increases on a per core basis at higher core counts. It is possible that the MPI memory footprint accounts for most of this behavior  (Balaji et al. , 2008; Gropp, 2009) , but further investigation will be carried out in the future to better understand this behavior.