dataesr/scientific-paragraphs-categorization huggingface dataset:
Analogical and numerical simulation tools The software Autodesk Ecotect Analysis © offers many features to assess the performance of daylighting and passive solar heating. The mirror box type of artificial sky (GRAP, 2010a) and the heliodon (GRAP, 2010b), two analogical simulation tools, do the same. SketchUp Pro 2013 © is a CAD software used by students to model and present their project design. It also allows them to study the cast shadows on their 3D model like the analogical heliodon. Findings from the analysis of the proposed housing complexes confirm that 6 teams out of 7 made use of one of the Ecotect Analysis © applications to assess the performance of the proposed solutions (Table  2 ). In contrast, while only one presentation addressed the contribution of the analogical helidodon towards the development of the project, none addressed the contribution of the mirror box type of artificial sky.
However, all projects without exception proposed drawings in which cast shadows were shown as simulated by the software SketchUp Pro 2013 ©. The execution stage of the final projects was a factor that may have contributed to the wide use of the Ecotect Analysis © , which can only be applied during the advanced design stage. The results of the web-base questionnaire enabled us to conclude that the features of the Autodesk Ecotect Analysis © software were well appreciated by architecture students and allowed them to improve their skills. The following question was asked: "do you feel that the Autodesk Ecotect Analysis © software was useful for you in developing your project in the course of the design studios?" In all, 10 out of the 13 students found it "extremely useful" or "very useful". Figure  2  Indicators that may be represented graphically.
However, the results are less conclusive for the analog simulation tools. In this respect, students considered the mirror box type of artificial sky and the heliodon less helpful: 6 considered them "rather useful" and 1 "barely useful". We were able to gain a deeper understanding of these results from the statements made by some of the students during both focus groups. The Autodesk Ecotect Analysis © software was highly valued by students for its capacity to fully validate the project's performance and thereby help justify the conceptual choices. It fits easily within the design process; students are accustomed to building a virtual scale model of their project. In contrast, it is clear from focus groups that the time required to build a real scale model, mandatory to use the mirror box or the heliodon is not justified by the precision of the results.
The architect has to momentarily interrupt the design process in order to use these analogical tools, which is seen as an irrelevant interruption. It follows that the creation of a virtual scale model is pursued on a more fluid and continuous basis. In addition, although it requires a considerable amount of time to build, the interest in the virtual scale model lies in the fact that it can be used during several stages  (design, validation, presentation, etc. ). However, for a number of students, the time needed to properly operate the software acted as a barrier. Some called into question the validity of the results obtained, and admitted not having a firm command of all the software parameters. However, given that all projects developed in the course of the architecture workshop included software analysis, that the results of the survey clearly demonstrated its utility and that the majority of statements recorded during focus groups were positive, it is reasonable to say that the Autodesk Ecotect Analysis © software has several features that improve the skills of students.
Numerical simulations With the aim of computing R in different resonant photonic systems, we have studied the electric field on the surface of different structures using the software RETICOLO  [11]. This free software, written in Matlab 7. 0, implements a frequency-domain modal method (known as the Rigorous Coupled Wave Analysis, RCWA)  [12] [13] [14]. The goal of the simulations was to find the most suitable system for the present application, i. e. to reach a good compromise between strong enhancement on the surface, low incident field transmission and less than 200 nm penetration depth into the upper medium (as in TIRFM). Two types of systems were considered, all of them on glass substrates: either dielectric nanostructured planar waveguides or metallic nanostructured layers supporting surface plasmon resonances (SPR).
In this study, we identify ARF6 together with c-Jun NH 2 -terminal kinase-interacting protein 3 and 4 (JIP3 and JIP4) effectors as critical regulators of this process. Silencing ARF6 or JIP3/JIP4 in breast tumor cells results in MT1-MMP endosome mispositioning and reduces MT1-MMP exocytosis and tumor cell invasion. JIPs are recruited by Wiskott-Aldrich syndrome protein and scar homologue (WASH) on MT1-MMP endosomes on which they recruit dynein-dynactin and kinesin-1. The interaction of plasma membrane ARF6 with endosomal JIPs coordinates dynactin-dynein and kinesin-1 activity in a tug-of-war mechanism, leading to MT1-MMP endosome tubulation and exocytosis. In addition, we find that ARF6, MT1-MMP, and kinesin-1 are up-regulated in high-grade triple-negative breast cancers. These data identify a critical ARF6-JIP-MT1-MMP-dynein-dynactin-kinesin-1 axis promoting an invasive phenotype of breast cancer cells.
Finally, coverslips were incubated with Cy3-conjugated IgGs to detect a Duolink signal. JIP4-p150 Glued Duolink signal staining was measured by counting the number of red dots for each cell from 3D deconvoluted images with a "find maxima" plugin of ImageJ software and compared with control conditions in which JIP3 + JIP4 was depleted (siJIP3 #3 + JIP4 #4 ) or one of the primary antibodies was omitted.
To assess the ability of the cells to form invadopodia and degrade the matrix, 7 × 10 4 cells per 12 wells were plated on fluorescent gelatin-coated coverslips and incubated at 37°C for 12 h (MCF10DICS. com cells), 5 h (MDA-MB-231 cells), or 2 h (MDA-MB-231 cells stably expressing MT1-MMPmCh and KIF5B-YFP). Cells were then prepermeabilized with 0. 5% Triton X-100 in 4% PFA for 90 s, fixed with 4% PFA for 20 min at RT, quenched with 50 mM NH 4 Cl for 10 min, and processed for intracellular IF labeling with Alexa Fluor 594-phalloidin or paxillin as indicated. Cells were imaged with a 63× objective (NA 1. 40 differential interference contrast [DIC] oil) of a wide-field microscope (DM6000 B/M; Leica) equipped with a CCD camera (CoolSNAP HQ) controlled by MetaMorph software (Molecular Devices).
Spheroids were fixed in 4% PFA immediately after polymerization of the matrix (T0) or after 2 d of invasion (T2). After fixation, cells in spheroids were permeabilized for 15 min in 0. 1% Triton X-100/PBS and labeled with Alexa Fluor 594-phalloidin and DAPI. For quantification of invasion in 3D type I collagen matrix, phalloidin-labeled spheroids were imaged at RT with a confocal microscope (A1R) using a 10× CFI Plan objective (NA 0. 25 working distance [WD] 7-mm DIC Dry), steered by NIS Elements software (Nikon) and collecting a stack of images along the z axis with a 10-µm interval between optical stions. The spheroid mean diameter was measured from azimuthal averaging of intensity profile along a line centered on the spheroid using a homemade plugin in ImageJ software  (Rey et al. , 2011).
2 mg/ml  (Elsdale and Bard, 1972). H2B-EGFP images were acquired at 37°C from each well at the beginning (T0) and 48 h after invasion (T2) using a microscope (TE2000; Nikon) equipped with a CFI 4× objective Plan Fluor (NA 0. 13 WD 30-mm DIC Dry) controlled by MetaMorph software. This microscope was equipped with a cooled CCD camera (HQ2; Roper Scientific). Image analysis was performed using MetaMorph software. The invasion index was determined by thresholding the area occupied by H2B-EGFP nuclei in the detection zone of each well after 48 h of invasion. This index is defined as the total area occupied by H2B-GFP nuclei in the unseeded area (detection zone) at the end of the assay (T2) by subtracting the area occupied by H2B-GFP nuclei at the beginning of the experiment (T0). This area of invasion was normalized, and the results from three independent experiments are represented.
Quantification of pericellular collagenolysis Cells treated with 50 nM of indicated siRNAs were trypsinized and resuspended in 0. 2 ml of 2. 2 mg/ml collagen I solution (2. 5 × 10 5 cells/ml) loaded on a glass coverslip. After gelling for 30 min at 37°C, a complete L15 medium was added, and collagen-embedded cells were incubated for 24 h at 37°C in 1% CO 2. After fixation in 4% PFA in PBS at 37°C for 30 min, samples were incubated with 2. 5 µg/ml anti-Col1-3/4C antibodies for 2 h at 4°C, washed extensively with PBS, and counterstained with Cy3-conjugated anti-rabbit IgG antibodies, DAPI, and Alexa Fluor 488phalloidin to see the cell shape. Image acquisition was performed at RT with a confocal microscope (A1R) with a CFI 40× Plan Fluor objective (NA 1. 3 WD 0. 65 DIC oil) controlled by NIS Elements software.
TIRF microscopy and live cell spinning disk confocal microscopy For live cell TIRF microscopy, MDA-MB-231 cells stably expressing MT1-MMPmCh and KIF5B-YFP were plated on glass-bottom dishes (MatTek Corporation), coated with cross-linked gelatin, and imaged with a 100-ms exposure time at 2-s intervals for 30 s through a 100× 1. 49 NA TIRF objective on an inverted microscope (TE2000; Nikon) equipped with a QuantEM EMC CD camera (Roper Scientific), a dual output laser launch that included 491-and 561-nm 50-mW DPSS lasers (Roper Scientific), and driven by MetaMorph software. A motorized device driven by MetaMorph allowed the accurate positioning of the illumination light for evanescent wave excitation. For live cell confocal spinning disk microscopy, MDA-MB-231 cells stably expressing MT1-MMPmCh and YFP, KIF5B-YFP, or KI-F3A-GFP were plated on glass-bottom dishes (MatTek Corporation) coated with cross-linked gelatin and kept in a humidified atmosphere at 37°C in 1% CO 2.
The movement of MT1-MMPmCh vesicles was monitored by acquiring 3D time-series images by confocal spinning disk microscopy (1 z stack/2 s for a period of 1 min, or 1 z stack/3 s for a duration of 3 min) using a spinning disk microscope (Roper Scientific) based on a CSU22 head mounted on the lateral port of an inverted microscope (TE-2000U) equipped with a 60× 1. 45 NA oil-immersion objective, a PIF OC Objective stepper, and a dual output laser launch that included 491-and 561-nm 50-mW DPSS lasers (Roper Scientific). Images were acquired with a CCD camera (CoolSNAP HQ2) and steered by MetaMorph software. To quantify the motility of MT1-MMP endosomes, we determined a displacement index  (Quintero et al. , 2009)  obtained by dividing the area over which the MT1-MMPmCh endosomes moved in a 1-min time lapse (as a result of the time-lapse projection of the 31 frames recorded every 2 s) by the area occupied by MT1-MMP endosomes in the first frame of the time sequence (see Fig.
IHC analysis of breast cancer TMA Analysis of human samples was performed in accordance with French Bioethics Law 2011-814, the French National Institute of Cancer Ethics Charter, and after approval by the Institut Curie Review Board and Ethics committee (Comité de Pilotage du Groupe Sein), which waived the need for written informed consent from the participants. Women were informed of the research use of their tissues and did not declare any opposition to such research. Data were analyzed anonymously. Samples of primary breast tumors surgically removed before any radiation, hormonal, or chemotherapy treatment at Institut Curie from 2005 to 2006 have been analyzed. Alcohol formalin acetic acid-fixed paraffin-embedded samples comprised all of the TNBC and HER2 tumors available, as well as an equal number of consecutively treated luminal tumors.
9 , A-D) and multiplied by the percentage of positive cells (H score). The average H score of duplicate tissue cores was calculated. Distribution of H-score values for each marker according to breast cancer subtype and tumor grade was compared by an analysis of variance test and plotted using the ggplot2 R package. IHC H scores were scaled and analyzed by unsupervised hierarchical clustering using the Ward linkage-clustering algorithm with euclidean distance as the similarity metric using R Software (version 3. 1. 1). H-score variables were discretized either in low or high expression in order to perform the association test (Table  S2 ). Cut-off values for IHC H scores were calculated using normal mixture modeling (Mclust R package). For MT1-MMP and ARF6, we used membranous H scores with a threshold estimated at 100.
Acknowledgments Dr. G. M. Griffiths  is acknowledged for critical reading of the manuscript. We thank the  Breast Cancer Study Group  and patients of  Institut Curie  for breast tumor samples and the  Nikon Imaging Centre at Institut Curie-Centre National pour la Recherche Scientifique (CNRS) ,  CNRS  and  Cell and Tissue Imaging Facility of Institut Curie , and members of the  France Bio Imaging national research infrastructure  ( ANR-10-INSB-04 ) for help with image acquisition. Dr. A. Soltani  is acknowledged for contributing to pilot experiments,  Dr. C. Laurent  for help with IHC dataset analysis,  Dr. P. Paul-Gilloteaux  for help with endosome position analysis, and  A. Kawska  ( IlluScientia. com ) for artwork in Fig. 7 (F andG). Dr. A. Houdusse  is acknowledged for help with the  ARF6/JIP4 3D  structure used in Fig.
The large uncertainties inherent in photometric redshift estimation make the identification of cluster members based upon their spatial separation, as is the case for the friends-of-friends  (Huchra & Geller 1982)  and Voroni-Delaney methods  (Marinoni et al. 2002) , much more challenging (e. g. Zandivarez et al. 2014). A more favourable approach for photometric datasets is to identify cluster members based upon whether they lie on the cluster RS in the colour-magnitude relation (CMR). Under the assumption that early-type galaxies dominate the cluster galaxy population and that this population follows a tight relation in colour-magnitude space, then, when imaged in two photometric bands bracketing the 4000 Å break, the cluster galaxies will be the brightest, reddest objects  (Stanford et al.
At low redshift this can be done with spectroscopic datasets, but at higher redshifts, where the spectroscopic data is sparse, one must turn to using synthetic 'mock' catalogues based upon the latest galaxy formation models  (Baugh 2008). Due to their rarity, generating a population of galaxy clusters requires very large volume cosmological N-body simulations, which due to limitations in computational resources are typically dark matter only simulations. Several techniques are available for populating the halos from N-body simulations with galaxies. A common approach is to use empirical methods, such as the halo occupation distribution (HOD,  Berlind & Weinberg 2002)  or subhalo abundance matching  (Vale & Ostriker 2004 ). These methods have the benefit that they are tuned using observations to ensure that the luminosity function and colour distribution of the galaxies are correct by construction.
Halo merger trees are constructed using particle and halo data stored at 62 fixed epoch snapshots, which are spaced approximately logarithmically in expansion factor. Details regarding construction of the halo merger trees can be found in  Merson et al. (2013)  and  Jiang et al. (2014). The MS-W7 simulation uses 2160 3 particles to represent the matter distribution, with the requirement that a halo consists of at least 20 particles for it to be resolved. This corresponds to a halo mass resolution of M halo,lim = 1. 87 × 10 10 h -1 M , significantly smaller than expected for the Milky Way's dark matter halo.
Modelling dust attenuation The attenuation by dust of the starlight from galaxies is modelled in GALFORM using a physically motivated method based upon the results of the radiative transfer code of  Ferrara et al. (1999). The method assumes the dust to be distributed in dense molecular clouds embedded in a diffuse component. In this model the dust attenuation varies self-consistently with other galaxy properties, such as size, gas mass and metallicity, which are predicted by GALFORM (see also  Fontanot et al. 2009b; Fontanot & Somerville 2011). The V-band optical depth when looking face-on through the centre of a galaxy, τ 0 V , is assumed to be, τ 0 V ∝ M cold Z cold r 2 disc , (3) where M cold is the mass of cold gas in the galaxy (both atomic and molecular), Z cold is the metallicity of the cold gas content of the galaxy and r disc is the radius of the galactic disc.
OBSERVATIONAL DATASETS Here we briefly introduce the observational datasets against which we will compare the model predictions. Observations of clusters at high redshift, z > 1, are still limited to of the order of a few tens of clusters, often with masses exceeding 10 14 h -1 M. Here, we consider a compilation of clusters at redshifts between z ∼ 1. 2 and z ∼ 1. 6, for which multiband photometry is available. In particular, we focus on clusters for which photometry is available such that they could be identified by the Euclid mission. The clusters that we consider are listed in Table  1. Typically, the colours used to examine cluster galaxies are chosen such that the pairs of photometric bands bracket the redshifted 4000 Å break, the strength of which is typically used as a proxy for the age of a galaxy and as a way of distinguishing passively evolving galaxies from those that are undergoing star formation when combined with other indexes  (Kauffmann et al.
g. Angulo et al. 2012). In the remainder of this section we provide further details on each of the galaxy cluster datasets. RX J0848+4453, which together make up the Lynx Supercluster, located at z ∼ 1. 2. Applying the colour selection 0. 8 < (i775 -z850) < 1. 1, the flux selection 21 < z850 < 24 and an aperture selection of 120 , left 40 galaxies, of which 14 are confirmed cluster members and 26 are cluster member candidates. Galaxy colours were measured within the effective radii of the galaxies. Mei et al. assumed  reddening due to dust to be described by a  Calzetti et al. (2000)  extinction law of E(B -V) = 0. 027 with Ai 775 = 0. 054 and Az 850 = 0. 040. •  Strazzullo et al. (2006) : Strazzullo et al. present Ks-band imaging for the clusters RDCS J0910+5422 (Ks < 21. 5) and RDCS J1252.
They present estimates for the CGLF of the cluster in z850, H160 and Ks, with 10σ completeness limits of z775 < 25. 3, H160 < 25 and Ks < 23. They also apply an aperture and select only those galaxies within 83 of the cluster centre. The photometry was corrected Table  1. High redshift observational galaxy cluster datasets used for comparison with model predictions. Columns show: (i) Reference and cluster ID, (ii) estimated cluster redshift, (iii) photometry available, (iv) aperture used to identify cluster members, (v) estimated mass of cluster from X-ray measurements, (vi) estimated mass of cluster from weak lensing measurements. Cluster mass estimates are provided where known, with values converted to units of 10 14 h -1 M , using the values of h specified by the original authors. Note that cluster RX J0848+4453 is listed twice.
Cluster Cluster Photometry Aperture X-ray Mass Lensing Mass Redshift (Arcseconds) (10 14 h -1 M ) (10 14 h -1 M )   1  of  Hilton et al. (2009)  for Galactic extinction using the dust emission maps of  Schlegel et al. (1998). Strazzullo et al. argue that for their dataset the population of brightest galaxies in the inner region of the cluster can be considered to be quite well established, with about seventy per cent of these galaxies having measured spectroscopic redshifts. Eisenhardt et al. 2008). They provide photometry for these clusters in the H160-band and one of the I814, i775 or z850 bands. They report that the detection catalogues for each cluster are more than 90 per cent complete for H160 < 23. 5. To identify cluster galaxies lying on the red sequence, they subtract from the colour of each galaxy a fiducial evolved CMR model for the Coma cluster and apply a selection based upon the residual.
2. 1, changing the aperture size has a greater impact at the faintest magnitudes). We find that our CGLF estimates from the Snyder et al. data are consistent within error with the estimates from Strazzullo et al. When constructing their dataset, Snyder et al. identified galaxies as cluster members based upon the likelihood of the galaxy lying on the cluster RS. For a subset of the galaxies these authors were able to confirm that they indeed are on the RS of the clusters. In Fig. 2  and Fig. 3  we plot the Snyder et al. estimate for the CGLF using only the confirmed RS galaxies and can see that this is in excellent agreement with the estimate using the full Snyder et al. dataset, suggesting that our CGLF estimates are not being significantly biased by possible interloping non-member galaxies.
At z ∼ 1. 2, there are no existing estimates of the CGLF in the H or z-bands against which to compare ours. In the these bands our estimates from the Snyder et al. dataset show a bright-end fall off similar in shape to the CGLF estimates at z ∼ 1. 4. At the faintest magnitudes, however, the CGLFs show a down-turn. Snyder et al. report 5σ detection limits of 26. 0-26. 3 in the z-band and 24. 4 -24. 8 in the H-band, with 90% completeness at H ∼ 23. 5. It is possible therefore that the observed down-turns may be a result of incompleteness. When determining their samples of cluster galaxies, Snyder et al. place a selection limit of H ∼ 22 -23, determined for each cluster by evolving the characteristic brightness of the Coma cluster to the redshift of each cluster. This selection may also be contributing to the down-turns.
In the z-band, our estimate for the CGLF from the Mei et al. shows good agreement with the Snyder et al. estimate for magnitudes bright-wards of z ∼ 22. 2. Faint-wards of this value, however, the estimates diverge. We note that these estimates are based upon galaxies from only one or two clusters, so discrepancies are indeed possible due to cosmic variance across the cluster populations. Another possible cause could be due to the i -z colour selection that Mei et al. place in order to identify early-type galaxies. We note, however, that the uncertainties on our CGLF estimates are simple Poisson errors and so may well be underestimates of the true uncertainties. If this is the case, then it is possible that our estimates for these two datasets are consistent within error. Our estimates for the z and K-band CGLFs from the Hilton et al.
dataset are generally consistent with the other estimates presented, though there are one or two bins for which the counts are higher than the other estimates, for example at z ∼ 23. 2 and K ∼ 21. 2. Just under two-thirds of galaxies in the Hilton et al. data have photometric redshifts only and so this variation could be caused by interlopers. In addition, variation due to cosmic variance between CGLF measurements for different clusters would be expected. Figure  5. H-band CGLFs at z ∼ 1. 4 as predicted by GALFORM assuming different apertures for selecting the member galaxies of each halo, as indicated in the legend. For each choice of aperture a halo mass limit of M halo 1. 2 × 10 14 h -1 M was adopted. The data points are the same as in the right-hand panel of Fig. 3.