dataesr/scientific-paragraphs-categorization huggingface dataset:
Finally, each spectrum is corrected for geometry, including the laserto-sample distance, and the spectral resolution of each detector element. The spectrum is divided by the approximate area of the plasma (πr 2 , where r = 0. 1 mm), solid viewing angle (π(h/d) 2 , where h is half the aperture of the telescope, 54. 2 mm, and d is the distance to the target), and Δλ, obtained by fitting a second-order polynomial to the derivative of the wavelength vector. Following the processing steps outlined above, the units of the LIBS spectral data are spectral radiance, photons/shot/mm 2 /sr/nm. Continuum emission is typically removed from the spectrum during LIBS data processing to improve visibility of the spectral lines and prior to fitting peak areas for quantitative calculations. This is justified because unlike the spectral lines, continuum emission consists of Bremsstrahlung and recombination radiation from electron-ion interactions and does not provide direct information regarding elemental abundances  [Cremers and Radziemski, 2013].
Line Selection To compare the spectral emission of different samples quantitatively, the integrated areas of emission lines of Cl, C, and S were measured. A selection of emission lines in the NIST Atomic Spectra Database  [Kramida et al. , 2015] , representing elements relevant to the Martian surface with ionization levels I and II, were considered and accessed via the ChemCam Quick Element Search Tool (C-QuEST, http://pds-geosciences. wustl. edu/workshops/ChemCam\_Workshop\_Mar15. htm). For line identification, peak centers were allowed an uncertainty Journal of Geophysical Research: Planets 10. 1002/2016JE005164 from the reference wavelength within ±1. 0× the ChemCam spectrometer resolution (~0. 2 nm for wavelengths <470 nm and ~0. 65 nm for wavelengths >470 nm). All emission lines in the C-QuEST database for the element of interest (C, S, or Cl) were searched for in the LIBS data from a mixture suite by using an algorithm that checked for increasing line intensity with concentration as indicated by a positive slope between the intensity at the reference wavelength and the mole fraction of the element (χ element ).
Fitting of Spectral Peaks For lines identified according to the criteria outlined in section 2. 3, the local spectral region was fit, using a Levenberg-Marquardt algorithm  [Gill et al. , 1981]  as part of the LMFIT Python package  [Newville et al. , 2014]  to model a spectrum composed of Lorentzian functions for all observable peaks and an underlying linear continuum. The local region to be fit was selected to include any nearby peaks of the same element, any peaks that interfered with or contributed to the peak of interest, and a local region where the continuum could be reasonably approximated by including a linear function (Figures  1a  and 1b ). Simplified peak and continuum shapes were chosen to limit the use of excess free parameters. The number of peaks included in the model and their locations were determined based on those visibly present in the spectrum combined with knowledge provided in the C-QuEST data.
Cl Lines Sixteen potential Cl lines are observed in the spectra of the chloride salt + basalt mixtures that met the initial criteria provided in section 2. 3 (Table  3  and Figures 4, 5,  and S3 ). Of the 16 selected lines, one appears in the range of the VIO detector, whereas the rest are in the VNIR. The nine lines at wavelengths shorter than 546 nm result from transitions of singly ionized Cl, whereas those above 725 nm are from neutral Cl. [2011]  and NIST spectral line database as described in the text. The remaining columns provide the results of this analysis: the detection limits determined based on the methods described in section 2. 5, the concentration at which a monotonically increasing trend in peak area with salt concentration began (or an "X" if the peak area did not monotonically increase), and whether the peak area displayed unreliable behavior among the mixture compositions tested.
Detection of Salt Anions Table  3  summarizes the results of the quantitative analysis. Ten Cl lines met our complete criteria for being useful for quantitative analysis of chloride + basalt mixtures. Chlorides were detectable at ~5-10 wt % in Journal of Geophysical Research: Planets 10. 1002/2016JE005164 the basaltic background using select lines. The line at 837. 8 nm appears to be the most promising for quantification with this univariate method based on its low detection limit, sensitivity to concentration, and reliable behavior in all mixture compositions. Of the detected Cl lines, this line also has the lowest upper state energy and a relatively high transition probability (Einstein A coefficient) based on values from the NIST database  [Kramida et al. , 2015]. Interference from Fe emission complicates the detection of S.
Unexpectedly, the C line at 883. 7 nm and Cl lines at 725. 9, 754. 9, 774. 7, 809. 1, and 833. 6 nm from the NIST database were detected and identified as useful in the salt + basalt mixtures but not previously by  Cousin et al. [2011]. These differences in line detections may be due to the significantly improved spectrometers used for ChemCam. The most effective lines for the analysis of unknown Martian materials will likely be those that appear consistently in samples with various chemical compositions. Compared to the number of identified lines in pure elements and compounds, those found in the salt + basalt mixtures are more limited. However, there are emission lines of Cl, C, and S that appeared across multiple samples and may be promising for use in geologic targets. and  Schröder et al.
Acknowledgments Thanks to  Mike Baker  for supplying the K1919 end-member and  George Rossman  for end-member acquisition advice. Thanks to the entire MSL ChemCam team for feedback throughout this project. Thanks to the anonymous reviewers for their valuable suggestions that have improved this document. This work was supported by a  NASA   MSL Participating Scientist Program  grant to B. L. Ehlmann, a  National Science Foundation Graduate Research Fellowship  under grant  DGE-11444469  to  D. E. Anderson , and by contract from  NASA 's  Mars Exploration Program  to  R. C. Wiens  and  S. M. Clegg. Supporting data are included as supporting information; any additional information may be obtained from  D. E. Anderson  (e-mail: deanders@caltech. edu).
Wang et al. [17]  have simulated coal CLC in a circulating fluidized bed reactor via a 3D approach. Alobaid et al. [18]  have used a 3D approach to simulate a 1 MW CLC pilot plant. For this, they have used Fluent software to model 3D momentum, mass and heat balances in a fluidized reactor. Studies relative to the numerical study of packed bed reactors  [10]  are fewer because the technology and the operation are more complicated than the fluidized bed reactor from an industrial point of view (operation in batch process). But from an academic point of view, this technology is very interesting owing to the simplification of the mathematical modelling  [19, 20] , especially the fluid and OC dynamics. In this work, different kinetic models are used to simulate experimental results of chemical-looping combustion of carbon monoxide in a fixed-bed reactor.
1 to 1 vol % in nitrogen. After the reduction step, the oxygen carrier was re-oxidized under air at the same operating conditions than the reduction ones. The gases coming out from the reactor (CO, CO 2 and O 2 ) were continuously analyzed by an NG2000 infrared analyzer (for CO and CO 2 , concentration inferior to 1 vol %, Edinburgh Instruments Ltd, Livingston, UK) and by a paramagnetic Rosemount X-stream analyzer (for oxygen, range 0-20 vol %, Rosemount Analytical Inc, Anaheim, CA, USA). A data acquisition system recorded in real time the experimental data.
In terms of computing power, the Knights Hill is expected to be between 3. 6 teraFLOPS and 9 teraFLOPS, while the NVIDIA Volta is expected to be around 10 teraFLOPS. And yet, taking a wider perspective, the challenges are severe for software developers who have to extract performance from these systems. The hybrid computing model seems to be here to stay, and memory systems will become even more complicated. It is clear that support for parallelism is going to have to dramatically increase, going up by at least an order of magnitude for the CORAL systems and achieving billion-way parallelism at exascale. The PULSAR project attempts to tackle these challenges with a simple programming model, based on the systolic processing model, augmented with virtualization. The programming model is simple and so is the runtime implementation.
The DARPA's HPCS program introduced three more languages into the space: Fortress  [2, 33] , X10 [59], and Chapel (Cascade High Productivity Language)  [12, 13]. The last two are still maintained by IBM and Cray, respectively. A recent resurgence of activity around shared memory programming resulted in the OpenSHMEM  [14]  project that borrows some ideas from the PGAS model, but is much more library-centric, as opposed to requiring a completely new programming language. The other approach to achieving good performance on the current Petascale and future Exascale hardware designs is to use software runtime systems. Two notable projects in this category are Charm++  [36]  and PaRSEC  [9] , which deal with algorithms and their implementation represented as a Direct Acyclic Graph (DAG) of tasks connected with edges that communicate data between them -a concept clearly related to the dataflow paradigm.
This is an important distinction, because the code of a CPU VDP has synchronous semantics, while the code of an accelerator VDP has asynchronous semantics. In other words, for a CPU VDP, actions are executed as they are invoked, while for an accelerator VDP, actions are queued for execution after preceding actions complete. In the CUDA implementation, each VDP has its own stream. All kernel invocations have to be asynchronous calls, placed in the VDP's stream. Similarly, in the case of an accelerator VDP, all channel operations have asynchronous semantics.
Threads and Devices Threads and devices are internal PULSAR objects not directly accessed by the user. The user only deals with them indirectly by providing formulas for mapping of VDPs to threads and devices. Threads and devices know their local (within a node) and global ranks, and maintain lists of VDPs. The main reason for the distinction between CPU threads and GPU devices is the synchronous behavior of the former and asynchronous behavior of the latter. While the code of a CPU VDP is expected to have the usual synchronous nature, the code of a GPU VDP is expected to be fully asynchronous. The reason is the asymmetry in the programming models for CPUs and GPUs, in which GPUs are not fully autonomous devices. Most of their actions have to be initiated by a CPU thread, and synchronous GPU code locks up the controlling thread.
Software Engineering Although being an experimental project, PULSAR has a quite robust implementation. PUL-SAR is coded in C in a fairly object-oriented manner, and would be very suitable for a C++ implementation. PULSAR is very compact with only 21. c files, 22. h files and 6,600 lines of code. The compactness and clear structure is mostly thanks to the very crisp abstractions established in the design process (VDP, VSA, channel, packet, etc. ) PULSAR has very few software dependencies. At the minimum, it requires Pthreads, and can be optionally compiled with MPI support and/or CUDA support. The build process involves compiling the sources and creating a library from the object files. Using MPI requires providing  PULSAR only depends on the most basic data structures: a non-thread-safe double-linked list, a thread-safe double-liked list (implemented by protecting the non-thread-safe one with Pthread spinlocks), and a hash table.
The basic linked list and hash table are implemented themselves as dependency-free, stand-alone structures. PULSAR contains its own tracing routines, based on recording time of different events and writing an SVG file at the end of execution. PULSAR records computational tasks on CPUs and GPUs (VDP firings), MPI communications, and CUDA data transfers. CPU timestamps are taken using get time of day, GPU timestamps are take using cudaEventRecord. PULSAR code, including the runtime (PRT) and examples, is available on the project website (https://bitbucket. org/icl/pulsar), which also contains extensive documentation, including: installation instructions, users' guide, reference manual, etc. The code is documented using Doxygen and the reference manual is produced automatically from Doxygen annotations.
All channels are initially inserted as inactive, so that each VDP can be launched without any data in the input channels, compute the local part of the product, send its local tile of A to the right, and send its local tile of B down. Figure  8  shows a complete code of a VDP implementing the Cannon's algorithm. It starts with the declarations section, where tile size (nb) and matrix size (nt) are retrieved from global store, the location of the VDP tile in the matrix (m, n) is retrieved from the VDP tuple, an alias is created to the local store. The done variable is declared because the cuBLAS calls require passing of the constant by reference. The first half of the code handles the first step, when the VDP's counter equals to the size of the matrix. If the VDP is a device VDP (is assigned to a GPU), then cuBLAS initializations are handled in the first step (creating cuBLAS handle and associating it with the VDP's stream).
Then the local tile A is pushed to the right and the local tile of B is pushed down. Then the local product is computed, either using a cuBLAS call or a CBLAS call, depending on the VDP's location. Finally, the input channels are activated to provide data for the next step. In the followup steps, a tile of A is read from the left and passed to the right, unless it is the last step of the algorithm (VDP reaches one). Tiles of B are handeld in the same manner, passing downwards. Then the product is computed using an appropriate call (either cuBLAS or CBLAS), and finally the transient packets, used for transfers of A and B, are released. In the CPU case, MPI communication is completely overlapped with computation, resulting in no gaps in the trace and almost idea scaling. In the GPU case, the DMA transfers do not keep up with the speed of execution, and the MPI transfers do not keep up with the DMA transfers, resulting in large gaps in the trace and poor scaling.
Conclusion This paper has presented the PULSAR system. PULSAR combines the key paradigms of systolic arrays (regularity, extensive data re-use and multilevel pipelining) with virtualization techniques, in order to provide a simple yet efficient programming model to design parallel algorithms on complex multicore systems with attached accelerators. After detailing the nuts and bolts of the system, we have provided a comprehensive description of a PULSAR instance, namely the canonic Cannon's algorithm for matrix product. We have shown convincing performance results on Titan, which nicely demonstrate that a limited programming effort, as required by PULSAR, is not incompatible with an efficient implementation. Achieving a good trade-off between the ease of programming and the quality of the results was the primary objective of PULSAR.
Acknowledgements This work has been supported by the  National Science Foundation , under grant  SHF-1117062 , Parallel Unified Linear algebra with Systolic ARrays (PULSAR). The authors would also like to thank the  National Institute for Computational Sciences , the  Georgia Institute of Technology  and the  Oak Ridge National Laboratory  for generous computer allocations on their supercomputers. Yves Robert  has been supported by  Institut Universitaire de France. This paper is distributed under the terms of the Creative Commons Attribution-Non Commercial 3. 0 License which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is properly cited.
Image analysis Although the Zen software we used for acquisition of images on the Zeiss microscope allows extensive and convenient image analysis, including spectral decomposition (called 'linear unmixing' in the Zen software), this commercial software is not widely available. We have therefore chosen to base all the image analyses reported in this paper on ImageJ software (current version 1. 48V, Java 1. 6. 0_65) complemented with various plugins, which are all open code software and freely available. The PoissonNMF plugin (https://github. com/neherlab/PoissonNMF) ) performs nonnegative matrix factorisation to allow spectral decomposition without knowing the initial spectra  (Neher et al. , 2009). Here, we used it to perform spectral decomposition analysis of reference spectra acquired separately on MLVs of defined composition.
In the process of assembling practical examples of the procedure with step by step instructions for an updated version of our manuscript, we came to realize that this pitfall can be avoided by simply relying on the default spectral values of PoissonNMF (min 480nm, max 560nm). The allocated wavelengths will then be erroneous, but this will have absolutely no influence on the unmixing results. For more information, see the step by step instructions provided as Supplementary material. The Fraction Mapper plugin (see Software and data availability) was developed specifically for this study. This plugin converts the two-image stack obtained through spectral decomposition into fractional intensities by dividing the unmixed images by the total intensity image. The summation of fractional intensities is always 1 and since we only unmix two components, the fractional intensity can be indexed with only one number.
The emission curves extracted using ImageJ software on the MLV images acquired on the biphoton microscope were remarkably similar to those obtained from the same MLVs in cuvettes in the spectrofluorimeter. Thus, the spectral analyser of the biphoton microscope can be used to analyse emission spectra in two dimensions at the submicrometer scale. We then tried our decomposition approach on the most challenging task available to us, i. e. we performed spectral decomposition into four different channels on stacks of 29 images acquired after double staining with laurdan and Nile Red (Figure  6 ). By using the four emission curves obtained with each probe on either DPPC-cholesterol (Lo) or DOPC (Ld) MLVs to perform spectral decomposition with the PoissonNMF plugin, we obtained a very convincing separation of the signals, where laurdan was found to be in an apolar, water-poor environment in lipid droplets and at the PM, whilst being much more exposed to water in the intracellular membranes.
Source code for the Fraction Mapper plugin: https://github. com/ farzadf58/FractionMapper/tree/1. 0 Archived source code as at time of publication: doi, 10. 5281/ zenodo. 581815 (Fereidouni, 2017) License: MIT Dataset 1: Intermediary flow cytometry data for Figure 8: Using flow cytometry (FACS) to quantify staining intensities at 450 and 530 nm, as well as the ratio between the two. doi, 10. 5256/ f1000research. 11577. d162294 (Mazeres et al. , 2017).
Acknowledgments The authors thank  Laurence Salomé  and  Evert Haanappel  for enriching discussions,  Andrey Klymchenko  and  Rodrigo de Almeida  for their constructive criticisms of the manuscript in preparation,  Carol Featherstone  for her comments and corrections on the manuscript,  Richard Neher  for writing the PoissonNMF plugin and for his advice on its use, the  TRI  platform for providing us access to the biphoton microscope, spectrofluorimeters and flow cytometer,  Laure Gibot  ( Toulouse ) for the HFF cells,  Vanessa Gobert  ( Toulouse ) for the Drosophila Kc cells,  Francois Letourneur  (Montpellier) for the Dictyostelium AX2 cells.
Objectives This study was to develop a model to predict the CApmc based on previous ultrasound measured parameters. Methods Thirty-two patients who were diagnosed with adolescent idiopathic scoliosis and had at least two consecutive clinic visits with ultrasound scans were recruited. Twenty-six datasets were used to build the prediction model while the other 6 were used for preliminary validation. The six parameters used for the prediction model included the CApmc, AVR, LDpmc, the number of curves (NC), and torsion of the first visit, and elapsed time between the two visits. Meanwhile, the CApmc of the second visit was the output of the prediction. The establishment of the prediction model was based on the linear regression. Each predictor and their combinations were analyzed to find the correlation with the output.
Objectives The objective was to characterize intraoperative pressures at the patient cushion interface and examine the effect of BMI and duration of the surgery on the incidence of LFCN injury. Methods Twenty-three patients with adolescent idiopathic scoliosis, two male and twenty-one females, age range 9-18 years, were recruited from the University of Alberta Stollery Children's Hospital. A set of four FSA pressure mats (Vista Medical, Winnipeg), are used to measure intraoperative pressure. Data collection began after patient positioning on the surgery table and continued during the screw replacement, rod insertion and until closure. At the end of operation, pictures were taken of the redness on both hips. A post-operation follow-up form including: age, gender, BMI, weight, height as well as light touch sensation exams around the iliac area to detect numbness or tingling.
Objectives To assess the effects of low-dose ketamine infusion as an adjuvant analgesic for children undergoing scoliosis surgery. Methods With the permission from the lead investigator of the larger Post-Operative Recovery following Spinal Correction: Home Experience (PORSCHE) study, and with local institutional ethics approval, we analyzed data from study patients recruited locally. Data were collected prospectively from 51 pediatric patients with AIS undergoing posterior instrumentation and fusion. Included were patients who received or not receive a postoperative ketamine infusion as part of their pain control regimen. All patients received patient-controlled analgesia (PCA) morphine/hydromorphone as part of their analgesic plan. Data, including method of analgesia, side effects, and patient satisfaction with pain control, were recorded.
Results and discussion Data from 47 patients were analyzed. Four patients were excluded: one did not receive surgery, and three withdrew. Thirty patients received ketamine postoperatively, while 17 received PCA only. Mean patient age was 14. 7 ± 1. 6 years old, and mean patient weight was 53. 8 ± 11. 0 kg. On average, ketamine infusions were run for 2. 1 ± 2. 0 days. Comparing ketamine and non-ketamine groups, outcomes were not significantly different with respect to total days on bowel medications (p = 0. 05), PCA use (p = 0. 20), total days on anti-emetics (p = 0. 69), or total days in hospital (p = 0. 68). The non-ketamine group reported significantly higher satisfaction with pain control on postoperative day one (p = 0. 03), but patient satisfaction was similar between groups on post-operative days 2-6.
Objectives The aim of this study was to evaluate the basic knowledge of idiopathic scoliosis in physiotherapy students trained in the UK. Methods A previously designed and tested 10-question survey, including knowledge of SOSORT Guidelines, 2011 was transcribed onto an onlinesurvey platform. Questions were designed to analyse knowledge of: definition, cause, development, prevalence, diagnosis, treatment and bracing of scoliosis. All physiotherapy-based UK universities were invited to participate, with the programme lead of each institution asked to distribute the questionnaire among the target population of final and penultimate year physiotherapy students (Master's and Bachelor's Degrees). The final number of students who received the study invitation is unknown. The survey link closed after 8 weeks of data collection.