dataesr/scientific-paragraphs-categorization huggingface dataset:
Tools For this study, the FALCON platform (Fellowship in Anatomic deLineation and CONtouring) from ESTRO (European SocieTy for Radiotherapy and Oncology) and the software EduCase™ from RadOnc eLearning Center, Inc. Fremont, CA, USA was used. This is a web-based contouring and analysis tool that has a graphical user interface for the management, storage and publishing of contouring of the clinical cases. The software allows image fusion of the simulation CT scan with MRI, as well as an integrated analysis on contouring proficiency. EduCase contour similarity metric tools allows computing metrics that score a participant contour relative to the reference contour. For evaluation, the participants' contours were tested against the original DICOM structures. EduCase similarity metric includes an Area Domain metric and statistics expressed as areas in units of square centimetres.
Statistical evaluation All the delineations of the relevant ROIs were used for evaluation. The EduCase software counts the voxels in each reconstruction plane that contained both the reference contours and participant contours for a selected structure providing a calculated DICE index (DI) defined as  (12). DI= 2 x AI/(AC+DA) For the target volumes, i. e. CTV of the prostate and SV, the contours of a radiation oncologist (CS) were used as reference images. For the rectum the contours of the radiologist were set as reference images. The set of reference images was not similar for targets and organ at risk. It was agreed on that the contouring of CTV of the prostate and SV differed between radiationoncologist, taking into account the oncological microscopic spread when contouring the clinical target volume, and radiologist, mainly focusing on anatomical barriers.
The overall process is detailed in Algorithm 2, in which the function generateFrom() is the one detailed in Algorithm 1. Concerning the stopping criteria of the iterative process, it must include the detection that no new code has been produced at the last iteration. Also, as soon as the dimension of the N-cube is greater than 5, the number of potential generations becomes very large and the stopping criteria must include a limitation of the number of generations. As for the previous algorithm, the lists lst and nl must be sorted according to the canonical forms in order to obtain fast searches and insertions. The complexity of that algorithm is deduced by analyzing the nested loops. Although the number of iterations of the global while loop is variable, we can compute the total number of iterations of inner loops on i (line 9) and on j (line 11).
Performance of Gray Codes Generation Algorithms The first series of experiments is devoted to the performance of the GC generation algorithm. The execution times shown below have been obtained on a desktop machine with two Intel(R) Xeon(R) CPU E5-2640 v2 @ 2. 00GHz containing eight cores each and 128GB RAM. The OS is Linux Debian 3. 16. 43 and the program is written in C/C++ and uses the OpenMP multi-threading library. Indeed, the implementation of our algorithm is multi-threaded and takes advantage of the available cores in the machine. This reduces the execution times but does not change the overall complexity of the algorithm. Also, different compilers have been tested (GCC, Intel, PGI) and although slight variations may be observed, the executions times are quite similar. Times given below are averages of a series of executions.
Long-slit spectroscopic data The spectroscopic data were obtained at the ESO La Silla observatory with EFOSC2 attached to the 3. 6 m Telescope during the nights of 7 -9 March 2000. A 2048 x 2048 CCD detector with a pixel size of 15 µm was used. The field of view is 5. 4 x 5. 4 with a pixel scale of 0. 316 /pixel. With the two different grisms #7 (3270 -5240 Å) and #9 (4700 -6700 Å) we were able to detect the important lines in the optical. The slit had a length of 5 and a width of 1. The seeing varied between 0. 71 and 0. 74 (see Table  2 ). The total integration time was split into two exposures of 20 minutes in each grism (see Table  1 ). In Fig. 1  the slit position with a position angle of 92 • is shown superimposed on an Hα image of NGC 4634. The data reduction was carried out using the image reduction and analysis facility (IRAF,  Tody 1986 Tody , 1993)).
HST imaging NGC 4634 was observed with the Advanced Camera for Surveys (ACS) at HST as part of program #10416 (PI: Rossa) in the HST-ACS r-band (F625W) and the Hα filter (F658N) using the the Wide Field Channel (WFC) for 2308s and 6888s, respectively. Earlier results from the program were reported by  Rossa et al. (2008) ,  Dettmar et al. (2010), and Rossa et al. (2012). v [km s -1 ] D [Mpc] i [ • ] PA [ • ] Size Galaxy mass [M ] [1] [2] [3] [4] [5] [6] [7] [8] [9] NGC 4634 12 h 42 m 40. 9 s(1)   We retrieved the imaging data for NGC 4634 from the Space Telescope Science Institute (STScI) HST archive, using on-thefly reprocessing using the latest calibration files. The pipeline included the new, improved treatment of charge transfer efficiency (CTE) correction, and drizzling the subexposures to cosmic-ray cleaned, astrometrically improved image, as discussed in the ACS Data handbook V9.
GMRT data In May 2013 NGC 4634 and its companions were observed for 5. 5 hrs with the GMRT. To calibrate the flux and the bandpass, 3C286 was observed for 15 min at the start and the end of the run and 1264+116 was observed every 30 min in order to calibrate the phases throughout the run. The correlator was set up with 4 MHz bandwidth and 512 channels centered at 1419. 3 MHz. The data were reduced with a range of data reduction packages. The raw data, in lta format, is first converted into a fits file through the use of listscan (v2. 0) and gvfits (v2. 0) as provided by the observatory. The produced fits file is then loaded into the data reduction package MIRIAD  (Sault et al. 1995)  where RFI is flagged in an automated manner. The data are then further flagged and calibrated through the use of the package  FLAGCAL (v0.
989, Chengalur 2013). After this initial calibration the data is loaded into CASA  (McMullin et al. 2007 ). We first visually inspect all the baselines for any residual RFI and then self-calibrate the data through the standard CASA procedures. After the self-calibration we subtract the continuum in the uv-plane from the dataset with UVCONTSUB by fitting polynomials of order one. The 8. 1 kHz channels were combined into 24. 3 kHz channels with the task SPLIT, and TCLEAN was used to transform the visibilities into a data cube. The visibilities were weighted according to a Briggs weighting scheme with Robust = 0. The dirty cubes were cleaned with the TCLEAN multiscale clean algorithm, at scales corresponding to 1 and 4 beams. The cleaning was performed in an iterative process where we first cleaned the cube to a threshold of 6σ, created a mask with SoFiA  (Serra et al.
3. 4). To compare the calculated L-Z relation for the dwarf galaxy candidate we show in Fig. 10  the L-Z relation for five different datasets. The data of  Richer & McCall (1995)  of dwarf irregular galaxies (dIs) are shown as red squares. The fit to that data by  Richer & McCall (1995)  is shown as the red line. The relation of the data of blue compact dwarfs (BCDs, blue triangles) from  Zhao et al. (2010)  is similar to the relation of the  Richer & McCall (1995)  sample. The location of the dwarf galaxy candidate of NGC 4634 is shown with the orange star. Clearly, the region analyzed here does not follow the relation of the dIs or the BCDs. We therefore use the data of tidal dwarf galaxies (TDG) from  Duc & Mirabel (1999)  (dark circles) and the data from  Weilbacher et al. (2003)  (green diamonds).
The high oxygen abundance and the other characteristics of the dwarf galaxy candidate could be explained by the tidal dwarf scenario. It is therefore possible that the dwarf galaxy was formed in the spur as a result of tidal interactions with the neighboring galaxy, namely NGC 4633. However, the low-resolution Hi image of the NGC 4634 and NGC 4633 does not show any cold gas between the two galaxies. This might be due to sensitivity limits (1σ ∼ 3 × 10 19 cm 2 ; see also Section 3. 7); a comparison between single-dish data  (Haynes et al. 2011 ) and our GMRT observations indicates we are missing a significant amount of emission. However, both disks are clearly detected and show little to no signs of being disturbed. On the other hand, the F625W image (Fig. 7 ) shows clear signs of the stellar disk being disturbed, indicating past interactions.
Summary and conclusion In this paper we present multifrequency data of a dwarf galaxy candidate and its edge-on host NGC 4634. With optical longslit spectra we calculate the oxygen abundances of one disk Hii region and of a dwarf galaxy candidate's Hii region. The comparable oxygen abundances hint at the material of the dwarf galaxy candidate being pre-enriched and that it originates from the disk of NGC 4634. This is confirmed by its location in a L-Z diagram, which shows that its metallicity is much higher than expected for a dwarf galaxy that evolved in relative isolation. The images of r-band, B-band, and the Hα-luminosity show that the dwarf galaxy candidate is star forming and approximately 550 pc in diameter. The heliocentric velocities of the dwarf galaxy and its host NGC 4634 are similar and indicate that the galaxies are connected.
The Hi data give the hint that a spur of NGC 4634 is located at the same position as the dwarf galaxy candidate. We furthermore determined the total dynamical mass of NGC 4634 to be 1. 3 ×10 10 M from the GMRT data analyzed here. With the above discussion one possible origin is the tidal dwarf scenario where the dwarf galaxy candidate formed in the spur of NGC 4634 from disk material. However, the data presented in this paper cannot rule out other forces that separated the gas in the star-forming region from the disk of NGC 4634. In any case, it is clear that the halo of NGC 4634 contains a star-forming object of significant size that is formed from gas stripped from NGC 4634, which is an excellent laboratory for further studies in terms of galaxy evolution.
Acknowledgements. We thank the anonymous referee for the helpful and constructive comments. Furthermore, we thank  Pierre-Alain Duc  for interesting discussions about this work. We thank  Anika Beer  for helping perform the pPXF. This research was suported in part by the  DFG (German Research Foundation ) research unit  FOR1048. This research has made use of the "Aladin sky atlas" developed at  CDS, Strasbourg Observatory, France , and has made use of IRAF, the  NASA's Astrophysics Data System Bibliographic Services , the GOLDMine Database, and the  NASA/IPAC  Extragalactic Database (NED) which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration. This research has used data provided by the GALEX mission, the SDSS, and UKIDSS.
Statistical analysis Statistical analysis was performed in SPSS 23 (IBM SPSS Statistics, version 22, Armonk, NY). To investigate each of the hypotheses set out in the introduction, multiple twoway repeated-measures analyses of variance (RM ANO-VAs) were performed to compare knee laxity to the knee state across different flexion angles. When differences were found between successive knee states, post hoc paired t tests with Bonferroni correction were applied at individual flexion angles. Significance level was set at p < 0. 05. Post hoc power analysis of paired t tests indicated that, when comparing laxities with the standard deviations calculated in eight knees, significant changes of 3. 2 mm could be detected with 80% power and 95% confidence. Separate analyses were performed for anterior laxity with no axial load; anterior laxity with 710 N axial load; posterior laxity with no axial load; and posterior laxity with 710 N axial load.
Compliance with ethical standards Conflicts of interest Professor Amis declares that he acts as an expert advisor, holds research grants at  Imperial College London , receives royalties from a patent licensed through  Imperial Innovations , and has received payment for lecturing from Smith & Nephew Ltd. Dr Athwal declares that his salary is supported by a research grant to  Imperial College London  from  Smith & Nephew Ltd. The other authors declare that they have no conflict of interest. Ethical approval This study was approved by  REC   Wales 12/WA/0196.
Unstained macrophages were included as negative control for staining. Data were analyzed with Flowing Software (Turku Centre of Biotechnology, Turku, Finland), after gating on the myeloid population in the FSC/ SSC plot with 10,000 events recorded. Results were expressed as the relative values of the median fluorescence intensity (MedFI) of each fluorochrome normalized to the respective value of unstained control. The percentage of cells expressing a specific phenotype was calculated according to the number of cells in the dot plot quadrants after gating.
In the majority of patients (91), no histological examination was performed and there was no evidence for an aggressive tumour. In 16 patients, however, a biopsy was performed owing to the conspicuous MRI despite negative FET PET. Histopathology yielded an astrocytoma WHO grade II in four cases, astrocytoma WHO grade III in six cases, oligoastrocytoma WHO grade II in two cases, oligoastrocytoma WHO grade III in one case and oligodendroglioma WHO grade II in one case. In two cases, histology revealed no evidence of tumour. For each subject, data of age, gender, weight and height were collected. Subsequently, BMI [kg/m 2 ] was calculated by dividing the weight [kg] by the square of the height [m 2 ]  (Gorber et al. , 2007). BSA [m 2 ] was calculated using weight and height and the Gehan and George formula  (Gehan and George, 1970).
SPM analysis Whole-brain statistical analysis was performed at voxel-level using SPM8 software (Wellcome Department of Imaging Neuroscience, University College, London, UK). PET images were spatially normalized to an in-house adaptive template derived from MR and 18 F-FET PET images of 14 scans performed in the hybrid PET/MR system  (Gispert et al. , 2003). Briefly, the in-house PET template was built on the basis of previous MRI-aided spatial normalization of 14 subjects (39. 8 ± 15. 6 years old, 12 women). PET scans of each subject were initially co-registered to its corresponding MRI using the co-registration algorithm included in the SPM8 package. After this step, the MR images of the subjects were normalized to the Montreal National Institute (MNI) MRI template, also using the algorithm provided with SPM8, and the resulting deformation field was applied to the PET scans.
| Proteomic analysis Two independent clones of human proximal TECs (HK-2 cell line) stably overexpressing calreticulin in similar levels and 2 control clones were studied with proteomic analysis. From each clone, 2 biological and 2 technical replicates were analysed with 2D electrophoresis. From each sample, 100 lg of protein was applied onto immobilized pH gradient strips of non-linear pI 3-10 (BioRad). Isoelectric focusing was performed in BIORAD PROTEAN IEF cell. Strips were reduced and alkylated, placed onto 12% acrylamide gels and electrophorised at 180 V. 15  2D gels were incubated in fixation buffer (30% methanol, 10% acetic acid), stained with Coomassie Colloidal Blue and destained with double distilled water. Gels were scanned with GS-800 calibrated densitometer and analysed with PDQuest 8 image processing software (BioRad).
Normalization of spot intensities was conducted according to total OD in the gel. Spots exhibiting quantitative differences between the gels were excised and placed into 96-well plates. Spots were distained and following reduction and alkylation they were dried in MAXI DRY PLUS, and digested with 3 lL trypsin (10 ng/lL) overnight. Peptides were extracted with 10 lL 50% ACN, 0. 1% TFA. Peptide mixtures were analysed with a matrix-assisted laser desorption/ionization-time-of flight/time-of-flight (MALDI-TOF/TOF) mass spectrometer (Ultralfex II MALDITOF/TOF-MS, Brucker Daltonics, Bremen, Germany). Peaklists were created using Flexanalysis v2. 2 software (BruckerDaltonics). Peptide matching and protein searches were performed automatically by the use of MASCOT Software (Matrix Sciences, London, UK).
For peptide identification, monoisotopic masses were used and a mass tolerance of 0. 0025% (25 ppm) was allowed. Cysteine carbamidomethylation and methionine oxidation were set as fixed and variable modifications, respectively. One miscleavage site was allowed. The peptide masses were compared with the theoretical peptide masses of all available proteins from Homo sapiens using Swiss-Prot database. The probability score with P <. 05 identified by the software was used as the criterion for the affirmative protein identification. The identified proteins were categorized according to their function and gene ontology using UniProt database (Universal Protein Resource). 16 Protein-protein interaction networks were created with the Ingenuity Pathway Analysis software (IPA) 17 using the accession number of the identified differentially expressed proteins.
| Proteomic analysis reveals alterations in proteome of TECs stably overexpressing calreticulin To investigate how the cellular phenotype of renal TECs is altered during calreticulin overexpression, we performed proteomic analysis in 2 independent clones of human proximal TECs stably overexpressing calreticulin in similar levels and 2 control clones. Protein spots were matched in 2D electrophoresis gel images obtained from each clone and their intensity was compared after normalization (fold change > 2). From 81 differentially expressed spots, 74 differentially expressed proteins were identified (Figure  1A , Figure  S1  and Table  S4 ). Initially, calreticulin overexpression was confirmed in the cell lines studied (Figure  1B ). The identified differentially expressed proteins were categorized using Uni-Prot database according to their cellular function and gene ontology, and classified in 13 categories (Figure  S2A ).
More specifically, calreticulin overexpression in TECs was associated with alterations in abundance in proteins involved in inflammation, cytoskeletal rearrangement, collagen production, extracellular matrix deposition, cellular metabolism, apoptosis, cellular redox homeostasis, protein folding and proteasomal degradation. Moreover, differences were observed in the levels of chaperones, heat shock proteins, cell cycle proteins and of proteins involved in mRNA alternative splicing. To identify protein-to-protein interaction networks among the differentially expressed proteins, the Ingenuity Pathway Analysis software was used. The proteins that are affected by calreticulin overexpression were organized in 4 networks; in three out of these 4 networks at least 1 member of the family of 14-3-3 proteins was present, indicating an involvement of this family in renal pathology (Figure  1C , Figure  S2B ).
| Confirmation of 14-3-3 proteins up-regulation in vitro To validate the results of proteomic analysis, we performed western blot analysis in the studied cell lines using a pan antibody for all 7 isoforms of the 14-3-3 family of proteins. The results confirmed that in the presence of calreticulin overexpression, 14-3-3 proteins are up-regulated (Figure  2A ). To study each of the 14-3-3 family members separately, we performed RT-qPCR with primers specifically designed for each of the seven 14-3-3 genes. The results showed that with the exception of 14-3-3b and 14-3-3s isoforms, the mRNA coding for the other isoforms of 14-3-3 proteins is significantly upregulated upon calreticulin overexpression (Figure  2B ). To support these results, RT-qPCR data were also normalized against RPL32 and GUSB housekeeping genes (Figure  S3  A and B).
ACKNOWLEDGEMENTS This study was supported by  ARISTEIA  I grant # 2681  from the  General Secretariat of Research and Technology of the Greek Ministry of Education  to  A. Charonis , by  EMBO  ( STF 7050 ) to  Myrto Rizou , by  Inserm  to  C Chatziantoniou. The authors thank  Dr. Panagiotis Politis  and  Ms. Valeria Kaltezioti  for advice and support during these studies and  Ms Sandrine Placier  for her advice with the I/R experiments.
But this disadvantage of a higher uplink loss (by roughly 10 dB) is accompanied by the advantage of a lower photon detection rate on board of the satellite and therewith a significantly smaller amount of data to be stored and exchanged with the OGS via a classical (RF or optical), authenticated but non-secure communication channel. In addition to its principal scientific aim of demonstrating ground-to-space QKD with a CubeSat, the NanoBob mission has the technological aims of: (a) Accurate clock synchronization between the ground-based station and the flight platform. (b) Fine attitude determination and control to ensure correct pointing of source and receiver under dynamic conditions. (c) The use of eye-safe laser beams at 1550 nm on the ground station and the space segment as laser tracking beacons, at the same time as they are used for fast classical optical communication using pulse position modulation, potentially at rates up to roughly 1 Gbit/s.
As the primary ground station location we use the ESA OGS at Tenerife on the Canary Islands (28. 30086N, 16. 51172W, 2410 m asl). However, as we want to be free to use other OGSs in order to demonstrate trusted-node, global QKD, and need to download data to RF ground stations located elsewhere, we conclude that a Sun Synchronous Orbit (SSO) at a height of 550 km and a local hour of 22h30 appears a near optimal choice. With an orbit time of 96 min, the satellite will make an average of 15 full orbits per day. Depending on the exact weight and the effective drag area (i. e. , the product of the drag coefficient and the cross-sectional area perpendicular to the direction of motion), the expected lifetime is between 3 (10 kg, 0. 11 m 2 )and7years(15kg,0. 08m 2 -the surface area of one side panel).
Additionally, the specified low dark count rate of 25 cps was demonstrated at a temperature of -5 • C, much higher than the -30 • C targeted in our system. We expect to receive prototypes of these detectors shortly for radiation testing in Grenoble. We note that the DCR requirement has obvious implications for the detector operating temperature. However, the stability of the detector temperature is not very critical for the QKD experiment, but may limit the precision and accuracy that can be attained if the space segment is to be used in light pollution mapping mode (see Sect. 1). High doses of radiation in space may cause the DCR to increase over time. For this reason the detectors are shielded by housing them in an aluminum module with walls of minimally 10-mm thickness, as well as by other satellite components around it (batteries, electronics, the Figure  5  The effect of radiation shielding by the aluminum detector housing on the total cumulative radiation dose for exposures of 1 and 3 years as calculated by the Omere software package  [43].
The satellite is assumed to be in a 550-km SSO starting September 2020 aluminum CubeSat structure, and solar panels). Using the OMERE software package  [43]  we calculated the cumulative total radiation dose received by the detectors as a function of the thickness of the aluminum shielding provided by the mounting structure. The satellite was assumed to be in an SSO at 550 km with a launch date in September 2020. The results for a 1-year and a 3-year exposure are shown in Fig. 5. The total incident radiation dose includes contributions from electrons trapped in Earth's magnetic field, solar and trapped protons, and Gamma photons (in order of decreasing radiation level). Kodet et al. [44]  determined that gamma radiation has no detrimental effect on Si-APD performance, and in any case in our mission scenario the gamma radiation dose accounts for just 1❤ of the total.