dataesr/scientific-paragraphs-categorization huggingface dataset:
Tefor BrainBase: Database of Registered Images As a performance test of our registration algorithm, we registered the published data of the Janelia Farm Gal4 collection (http:// flweb. janelia. org/cgi-bin/flew. cgi, Jenett et al. 2012 ) into the coordinate system of our inter-sex template. Over 3,350 3D images of expression patterns were processed and their metadata imported into PostgreSQL database using the BrainBase storage framework (http://braingazer. org).
BrainBaseWeb 2. 0: Lightweight Database Webinterface The BrainBaseWeb interface of VRVis (http://vrvis. at) was widely redesigned and functionally enhanced to access the registered images stored in the Tefor database. BrainBaseWeb is the primary user interface to efficiently browse and retrieve confocal microscopy data and related metadata like annotated anatomical structures of imaging and registration parameters from the BrainBase (http://braingazer. org) storage framework. It provides the user with reactive client side slice viewers as well as 3D visualization of the expression patterns in a standard web client as Chrome, Firefox or Safari. Employing intelligent caching techniques, data are loaded and temporarily stored on demand only, which accelerates data access and visualization. Besides a traditional semantic search engine, BrainBaseWeb 2.
Group-Wise Atlases Outperformed Individual Atlases At least four of the most popular adult Drosophila templates are brains of single individuals  (Rein et al. , 2002; Jenett et al. , 2006 Jenett et al. , , 2012;; Chiang et al. , 2011). The brains in individual templates are frequently chosen for their apparent or objective representativeness of a whole population of specimens. Here, we evaluated quantitatively to what extent the arbitrary selection of a reference brain potentially affects the performance of the template in registration and segmentation tasks. In addition, we also evaluated how using group-wise templates built by pooling several individuals may improve these performances. We exploited the Würzburg dataset (see section 2. 1), composed of male and female brain images containing each a nc82 intensity channel (reference channel; Figures  1A, B ) and the corresponding anatomical region labels delineated by human experts  (Rein et al.
Comparison With Publicly Available Templates After demonstrating the superiority of our group-wise strategy with respect to individual brain templates, the next step was to evaluate its performance against publicly available wholebrain templates. We tested our median-intensity group-wise inter-sex template against five alternatives: the FlyLight template (JFRC2010, single female brain, stained with nc82)  (Jenett et al. , 2012) , an average inter-sex template from the FlyCircuit database (FCWB,  Chiang et al. 2011)  constructed by Gregory Jefferis's lab (Dlg staining)  (Ostrovsky and Jefferis, 2014)  and the three new average, artificially-symmetric templates from this same lab (DmelF, female-specific; DmelM, male-specific; DmelIS, inter-sex; all three with nc82 staining)  (Ostrovsky et al.
Robustness to Image Acquisition Conditions All evaluations of our group-wise atlases reported above have been against test brains belonging to the same "Würzburg" dataset, thus raising two questions. First, can the success of our strategy compared with alternative templates be explained by the common origin of template and test brains? Second, what is the robustness of our strategy to changes in the image acquisition conditions? To examine these issues, we  constructed a new template (GifM) using ten male nc82-stained samples acquired in this study (the "Gif " dataset) and checked its performance by co-registering independent "Würzburg" male individuals. We used the same twelve male brains that were used as a test set in the above comparison with other templates. The results obtained by evaluating registration using the Dice coefficient showed a partial sensitivity of template performance to image acquisition conditions (Figure  7 , Middle).
Biological Validation of Registration-Based Predictions As a performance test of our registration algorithm, we registered over 3350 3D images from the published Janelia Farm Gal4 collection (http://flweb. janelia. org/cgi-bin/flew. cgi, Jenett et al. 2012 ) into the coordinate system of our Median inter-sex template. The registered images and their associated metadata were imported into a database (the Tefor database, publicly accessible at http://fruitfly. tefor. net). In addition, we registered the anatomical labels of the Ito et al. (  2014 ) atlas onto our template (Figures  1G, H ; Supplementary Movie 1) and integrated them into the database, thus providing a comprehensive anatomical annotation of our statistical template. Therefore, the Tefor database is able to support a wide variety of atlas-based queries.
We tested the efficiency of our inter-sex template and registration procedure to retrieve gene expression profiles that intersect with each other. We used the anatomical 3D space query tool in BrainGazer software  (Bruckner et al. , 2009)  to search the ∼3,000 images of the Janelia Farm lines in the Tefor database with the typical axonal tracts of the PDF-expressing small ventral Lateral Neurons (sLNvs)  (Beckwith and Ceriani, 2015). The search pattern was restricted to the most central part of the axonal tract in both hemispheres. Five individual pdf-gal4 UAS-gfp profiles were used independently to take into account the interindividual variability of the axonal tracts (Figure  9 ). For each of the five sLNv profiles, 57-90 lines were recognized with more than 20% of overlap (arbitrary threshold) between the probe and the target profiles (Supplementary Table  1 ).
DISCUSSION Our study provides several new insights on the building of atlases of Drosophila adult brain. Based on an objective evaluation methodology, we first quantitatively established the importance of relying on group-wise atlases and provided guidelines for generating them. We then showed that state-of-the-art atlases, many of which have been built using the same computational procedure based on an affine transform followed by B-spline deformations, can be out-performed using alternative image registration algorithms that provide increased spatial accuracy. Lastly, we provided a web-based resource to access and query more than 3,000 GAL4 lines of the Janelia Farm FlyLight collection that we have registered onto a new average intersex atlas. The possibility of searching this database with the BrainGazer software allows to find axonal projections that are similar to any registered brain expression pattern and thus represents a unique tool to analyze neuronal circuits in the Drosophila brain.
In addition, the median intensity template almost systematically ranked first compared to the average intensity template. Hence, using group-wise strategies not only brings robustness with increased accuracy and precision for each task, but it also brings more consistent performance across different tasks. The availability of robust and consistent atlases is relevant not only for the analysis of image collections, but also for the bridging between different atlases, which is required for comparing and integrating complementary data across different databases  (Manton et al. , 2014). Several studies have evidenced sexual dimorphism in the organization of the adult Drosophila brain. On average, neuropil structures are larger in females than in males  (Rein et al. , 2002) , which is assumed to be related to the overall larger body size of female flies, though localized regions involved in courtship behavior have been shown to be specifically enlarged in males  (Cachero et al.
, 2010). At a smaller scale, sex-specific organization has also been shown in neuronal circuitry  (Cachero et al. , 2010). Several sex-specific templates have been built  (Jenett et al. , 2006, FIGURE 7  | Comparison with other templates (registration task). Dice coefficient obtained with our proposed group-wise templates (Median and Mean) and with other publicly available templates evaluated by registering female brains (Left), male brains (Middle), or both female and male brains (evaluation in template space). The male test set (Middle) was also used to evaluate the performance of an additional male-specific template (GifM) built using newly acquired nc82-stained samples. JFRC2010: single female template from the FlyLight database; FCWB: an inter-sex template that combines female and male brains from the FlyCircuit database; DmelF, DmelM, and DmelIS: symmetric group-wise female-specific, male-specific, and inter-sex templates, respectively, from Jefferis' lab.
This was much above the increase observed for the other structures (average = +5%). For females, all structures but the protocerebral bridge (+2%) were smaller in the inter-sex atlas. The decreased sensitivity of the Dice coefficient to registration error when structure size increases could thus explain the structure-and sex-specific improved performance of the inter-sex template. We conclude that at least comparable performance is achieved by using an inter-sex rather than a sex-specific template. Our study thus objectively establishes the efficiency of using inter-sex templates for spatial normalization of Drosophila brain expression patterns and comparison between sexes. This result opens the perspective of simplifying the current landscape of Drosophila brain databases by removing the need of bridging sex-specific templates  (Manton et al.
Although several online databases are available to look for specific expression patterns in the brain  (Bruckner et al. , 2009; Chiang et al. , 2011; Jenett et al. , 2012; Milyaev et al. , 2012) , only the Virtual Fly Brain (VFB) website (http://www. virtualflybrain. org/site/vfb_site/home. htm;  Milyaev et al. 2012)  allows to analyze and compare GAL4 expression patterns through a brain atlas. A nice feature of VFB is the possibility of searching patterns that are similar to those of the FlyCircuit collection of single neuron labelings  (Chiang et al. , 2011; Costa et al. , 2016). Our BrainBaseWeb 2. 0 interface allows to analyze and compare more than 3000 GAL4 lines of the Janelia Farm FlyLight project that have been registered in our brain template. Importantly, the desktop version of BrainGazer allows to select in 3D any segment of an axonal tract or arborization that is displayed by a GAL4 line of our database and search the FlyLight collection for other lines sharing these particular axons or arborizations, as we describe here for the PDF-expressing small lateral neurons.
Users can also perform similar searches through the BrainBaseWeb 2. 0 interface, thanks to the newly added free form spatial query tool, which allows direct requests on image data without requiring prior segmentation into predefined anatomical regions. Providing superior flexibility in the definition of a query, this tool promises to become a very powerful feature in atlas-based research. In the near future, new collections of GAL4 (or other) lines will be added to our database. Future developments will allow users to switch expression patterns between brain templates (see  Manton et al. , 2014)  and benefit from the tools developed by different projects to analyze specific neuronal populations and circuits.
ACKNOWLEDGMENTS We thank  Gerry Rubin  for providing the Janelia Farm dataset of confocal images,  Martin Heisenberg  and  Kornelia Grübel  for their help obtaining the Würzburg data set,  Elisabeth Chélot  for help with immunolabeling experiments, and  Eric Biot  and  Lionel Moreira  for their help with storage and computing facilities at  Institut Jean-Pierre Bourgin and at Institut des Neurosciences Paris-Saclay. IA-C, TM, NM, FS, and AJ were funded by the  Tefor Infrastructure  under the  Investments for the Future program  of the  French National Research Agency  (Grant # ANR-11-INBS-0014 ). FR was supported by  INSERM. Work at Institut des Neurosciences Paris- Saclay was supported by ANR Infrastructure Tefor and by ANR ClockEye (# ANR-14-CE13-0034-01 ). JI was supported by the  Spanish Ministry of Economy and Competitiveness  ( TEC2014-51882-P ), the  European Union 's  Horizon 2020 research and innovation programme  ( Marie Sklodowska-Curie  grant  654911 , project  THALAMODEL ), and the  European Research Council  ( ERC Starting Grant  no.
677697 BUNGEE-TOOLS ). VRVis (KB, FS) is funded by  BMVIT ,  BMWFW ,  Styria ,  SFG and Vienna Business Agency in the scope of COMET -Competence Centers for Excellent Technologies  ( 854174 ) which is managed by  FFG. The Institut Jean-Pierre Bourgin benefits from the support of the  LabEx Saclay Plant Sciences-SPS  (# ANR-10-LABX-0040-SPS ).
Symmetries play an important role in modern theories of gravity. The strong equivalence principle (SEP) constitutes a collection of gravitational symmetries which are all implemented by general relativity. Alternative theories, however, are generally expected to violate some aspects of SEP. We test three aspects of SEP using observed change rates in the orbital period and eccentricity of binary pulsar J1713+0747: 1. the gravitational constant's constancy as part of locational invariance of gravitation; 2. the post-Newtonian parameter α3 in gravitational Lorentz invariance; 3. the universality of free fall (UFF) for strongly self-gravitating bodies. Based on the pulsar timing result of the combined dataset from the North American Nanohertz Gravitational Observatory (NANOGrav) and the European Pulsar Timing Array (EPTA), we find G/G = (-0.
METHOD AND RESULTS PSR J1713+0747 is a millisecond pulsar orbiting a 0. 29 M ⊙ white dwarf. The pulsar's short spin period (4. 5 ms) and narrow pulse profile enable us to measure its pulse time of arrivals (TOAs) at submicrosecond precision. This pulsar is monitored by both the North American Nanohertz Gravitational Observatory (NANOGrav), the European Pulsar Timing Array (EPTA) and the Parkes Pulsar Timing Array (PPTA) for the purpose of detecting nHz gravitational waves. A major part of the data used in this work come from the NANOGrav 2  and EPTA programs. The EPTA 3  is a collaboration of European institutes to work towards the direct detection of lowfrequency gravitational waves and the running of the Large European Array for Pulsars (LEAP). These data were taken between 1993 and 2014 using observatories including William E.
Gordon Telescope of Arecibo observatory, Robert C. Byrd Green Bank Telescope, Effelsberg Telescope, Lovell Telescope of Jodrell Bank observatory, Nançay Radio Telescope, and Westerbork Synthesis Radio Telescope. Splaver et al. (2005)  published the early dataset for J1713+0747 from Arecibo and Green Bank Telescope (GBT). Subsequently,  Zhu et al. (2015)  published the combined J1713+0747 data from  Splaver et al. (2005)  and NANOGrav 9yr data release  (Arzoumanian et al. 2015). Desvignes et al. (2016)  published the data and timing analysis for the EPTA pulsars including J1713+0747. This work presents the first timing analysis of the combined J1713+0747 data published in  Zhu et al. (2015)  and  Desvignes et al. (2016). We are able to model very accurately the binary system's orbit through various time-delaying effects like Römer delay, Shapiro delay, and annual-orbital parallax.
This analysis is conducted using the PAL2 software package 5   (Ellis & van Haasteren 2017). The second approach is similar to the first one excepts that it models DM variation as a power-law Gaussian process  (Lentati et al. 2013 ). This analysis is conducted using the T N 6  software package  (Lentati et al. 2014). We find consistent results in the best-fit timing and noise model from both approaches. In this paper, we are mostly interested in testing theories of gravitation. Therefore, we choose to base our GR tests on the result from the first approach (presented in Table  1 ) because it yields slightly more conservative uncertainty on e. We use the solar system ephemeris DE421  (Folkner et al. 2009)  in the timing analysis instead of the more recent DE436  (Folkner & Park 2016). Arzoumanian et al.
7 ± 0. 4) × 10 -17 s -1 along the line of sight, likely coming from the periastron advance of the orbit. After removing the contributions of periastron advance ( e PN x = -0. 07 × 10 -17 s -1 , e PN y = -1 × 10 -17 s -1 ) according to the measured system masses and orbital parameter (Table  1 ) and eq. (  14 ), the resulting excess eccentricity change rate [ e exc x = (0. 4 ± 0. 4) × 10 -17 s -1 , e exc y = (0. 7 ± 0. 4) × 10 -17 s -1 ] is consistent with zero. We perform a Monte-Carlo Markov Chain (MCMC) simulation that simultaneously fits both the timing model and the dispersion, jitter and red noises, using the PAL2 software. The MCMC allows us to obtain a large sample of possible timing parameter values along with their likelihood. We then use these MCMC results to calculate the ∆ needed to account for the residual e excess.
DISCUSSION In this paper, we present new tests of the constancy of G, and the violations of UFF, Lorentz invariance, and conservation of momentum in gravitation. These violations of gravitational symmetries lead to changes in the orbital period and eccentricity particularly in binaries such as pulsar-white dwarf systems like J1713+0747. We conduct these tests through the measurement of an excess change in the orbital period and eccentricity from the timing analysis of PSR J1713+0747. We repeat the combined G/G, κ D test presented in Zhu et al. (  2015 ) by incorporating more PSR J1713+0747 timing data from EPTA and find the result improves [ G/G = (-0. 1±0. 9)×10 -1  yr -1 and κ D = (-0. 7 ± 2. 2) × 10 -4 ]. The improvement on G/G could be attributed to the inclusion of EPTA data which increased the number of TOAs used in the experiment, whereas the changes in κ D limits are mostly due to the change from using a fiducial sensitivity function that scales linearly with neutron star mass to using a more realistic non-linear neutron star sensitivity function.
ACKNOWLEDGEMENTS WWZ is supported by the  Chinese Academy of Science Pioneer Hundred Talents Program  and the  Strategic Priority Research Program  of the  Chinese Academy of Sciences  Grant No. XDB23000000. Pulsar research at  UBC  is supported by an  NSERC   Discovery Grant  and  Discovery Accelerator Supplement , and by the  Canadian Institute for Advanced Research. GD, MK and KL acknowledge financial support by the  European Research Council (ERC)  for the  ERC Synergy Grant BlackHoleCam  under contract no. 610058. GJ and GS acknowledge support from the  Netherlands Organisation for Scientific Research NWO  ( TOP2. 614. 001. 602 ). JAE acknowledges support by  National Aeronautics and Space Administration (NASA)  through  Einstein Fellowship grant   PF4-150120. Some computational work was performed on the Nemo cluster at  UWM  supported by  National Science Foundation (NSF)  grant No.
All computations were made using custom written MATLAB software (The Mathworks, Inc, Natick, MA). Criterion whole-body mass was determined using a calibrated set of scales and recorded to the nearest 0. 01 kg. Whole-body center of mass, along the long axis, was determined using the reaction board technique. 16 Subjects lay supine with palms of the hands flat against the proximal side of the thighs. Whole-body volume was measured using the hydrostatic weighing technique. Participants were familiarized with the water tank and the procedure and were allowed to practice the technique until they felt comfortable. Underwater weight was measured when the subjects were fully submerged, had breathed out, were motionless, and the load cell display stabilized on a value. Three measurements were taken with the maximum value taken as the underwater weight.
Adjustments were made for water temperature. Residual lung volume was estimated using height and age, and intestinal gases were assumed to be 100 ml. 17 Whole-body volume and density were calculated using the equations from Siri. 18 articipants underwent a whole-body DXA scan (Hologic Discovery; Hologic UK Ltd, Sussex, UK). The system had a scan pixel resolution of 1. 2 mm × 1. 8 mm, and a mass resolution of 0. 01 g/mm 2. The scan was performed with the subjects lying supine on the table with forearms pronated so that the palms of their hands were facing the lateral side of their thighs. The output from each scan was the distribution of mass of the whole body. Each scan was digitized in order to locate bony landmarks and section the body segments to correspond with the anthropometric data collected, giving the mass of each segment.
One trained operator performed all of the segmentation of the scans. Whole-body volume, whole-body mass, and whole-body center of mass were determined for each of the geometric solid models. These measures were compared with whole-body mass measured with scales, whole-body center of mass location measured via a reaction board, and whole-body volume measured via underwater weighing. Whole-body density was computed and compared with the whole-body density calculated from the hydrostatic weighing procedure. Segmental volumes and masses were compared with those estimated from DXA scans. Normality of the data was assessed using an Anderson Darling test of normality. All variables were normally distributed. The segment mass data for each method was normalized by dividing by the DXA-derived whole-body mass.
Percentage root mean square errors (RMSE) are reported for the normalized estimates from each model compared with the normalized DXA data, and for direct measures of whole-body mass, whole-body volume, and center of mass location compared with estimates from each model. The method of Bland and Altman  14  was used in assessing each comparison. Where applicable, 95% confidence intervals for the percentage deviation between methods are reported. All statistical analysis was performed in Minitab v17 (Minitab© Statistical Software, State College, PA, USA).
5% of the whole-body mass reported by the DXA software. This issue has previously been reported by Wicke and Dumas 26 and Chambers et al,  27  who found that DXA-derived segment masses and lengths do not sum to whole-body mass and height determined using traditional scales and stadiometers, respectively. It is likely that this is due to pixels at segment boundaries being included in both bordering segments. At the segmental level, a likely source of discrepancies between DXA and geometric model derived data is due to differences in soft tissue distribution when lying down compared with standing upright. In many sporting and daily activity situations, the soft tissue distribution is more likely to reflect that in the upright position. Furthermore, there is an inherent difference between the 2 techniques in that the anthropometric measurements predict volume, from which mass is calculated via an assumed density.
Set-up To record eye movements, we used a FaceLAB 5 eyetracker at 60Hz without head constraint on a 17-inch screen set to a resolution of 1920X1080. Instructions and websites were displayed in Google Chrome maximized with a resolution of 1920X955. To record Mouse movements we developed a plug-in using WebExtensions 1  standard. form of an ON/OFF button on the browser top bar and has only been used by the operator. The extension monitored the following metrics: time-stamp, event type (click, movement or scroll), mouse's coordinates, offset induced by the scroll, URL and screen size. The plug-in developed in Javascript was uploading all mentioned metrics on the fly or every 50-60ms to a NodeJS 2  server via a socket connection. The same server inserted in real time the data in a MySQL database without further processing.