dataesr/scientific-paragraphs-categorization huggingface dataset:
Season EC 1. 0 ± 1. 1 0. 2-8. 2 0. 04 ± 0. 1 < dl-0. 5 1. 0 ± 1. 1 0. 2-8. 3 OC 2. 3 ± 1. 6 0. 9-12. 1 1. 2 ± 0. 6 0. 5-5. 3 3. 5 ± 1. 8 1. 6-13. 7 OC prim 0. 4 ± 0. 4 0. 1-2. 9 n. a n. a 0. 4 ± 0. 4 0. 1-2. 9 OC sec 2. 0 ± 1. 3 0. A concentration value C nm attributed to a grid cell (n, m) represents the average concentrations measured at the receptor site when air masses come from the geographical area defined by the grid cell (n, m). A large dataset is necessary to ensure the statistical significance of the results. A scale of 5 colours from light yellow to brown is used for the representation of different groups of median concentrations in µg m -3. Grid cells in white correspond to grid cells with less than 20 trajectory endpoints.
The results for particulate sulphate and chloride data give confidence in the CFMM results since chloride is an indicator of maritime origin and sulphate is an indicator of aged air masses. Cells showing slightly elevated levels to the extreme west of the sulphate map correlate with elevated chloride and may reflect sea salt sulphate. In the case of the nitrate, the main potential sources are also located in continental Europe, (Fig. 3b ). Concentrations larger than 4 µg m -3 are associated with the European areas with strong NO x emissions. This is confirmed by a highly significant correlation between the map and the EMEP emissions database (Spearman rank correlation r = 0. 67; p < 0. 001). Note that this correlation coefficient shows the agreement between the cells of the entire European domain and as a consequence is a representation of the importance of the regional contribution.
Acknowledgements. Atmospheric measurements derive from the UK air quality data archive and the work of  Bunthoon Laongsri. Air temperature and air masses backward trajectories were supplied by the  British Atmospheric Data Centre (BADC). European emissions were supplied by the  Centre on Emissions Inventories and Projection (CEIP). The authors are also grateful to  IFSTTAR  for financial support through a  Master grant  to  Céline Degrendele. Edited by:  X. Querol.
ACKNOWLEDGMENTS We thank  Région Rhône-Alpes  for  Jordan Vacheron's Ph. D. fellowship and acknowledge funding from the  ANR  projects  SymbioMaize  ( ANR-12-JSV7-0014-01 ),  AzoRiz  ( ANR-08-BLAN-0098 ) and  Azodure  ( ANR-12-AGRO-0008 ), and the  FW6   STREP  project  MicroMaize  ( 036314 ) from the  European Union.
2009; Newman et al. 2012, and references therein)  in the  Extended Groth Strip (EGS). This paper is structured as follows. We describe the data sets, photometry and photometric redshift estimation in §2. Our ERO samples are defined and our ERO separation technique is described in §3. In §4 we present our clustering analysis and results, followed by a discussion and summary in §5. Throughout this paper, unless otherwise specified, all magnitudes are in the Vega magnitude system. Spitzer IRAC and MIPS magnitudes are quoted using square brackets  (e. g. , 3. 6 µm is [3. 6] ). We introduce the following nomenclature for our ERO samples: (R -K s ) > 5. 0, (I -K s ) > 4. 0 and (I -[3. 6]) > 5. 0 selected ERO samples are respectively referred to as the ERO RK , ERO IK and ERO I3. 6 samples. We assume a standard ΛCDM flat cosmology, with Ω m = 0.
The 24 µm fluxes were measured using PSF photometry on the MAGES images  (Jannuzi et al. 2010)  for each source in the 4. 5 µm-selected catalogue, with uncertainties determined using a Monte Carlo method. The NEWFIRM K s catalogues are described in  Gonzalez et al. (in prep. ). We used an exposure time-weighted map to exclude poor photometry in the K s -band and we only use photometry from regions where the exposure map was greater than 40% of the maximum for the NEWFIRM images. Aperture diameters for the NEWFIRM K s data were determined as described above. To test some of the techniques used in this paper, we also employ 6,285 galaxies observed through identical B w RI  (Dey et al. 2007) , K s  (Bundy et al. 2006) , IRAC  (Barmby et al. 2008 ), MIPS (FIDEL;  Dickinson & FIDEL team 2007)  filters and with DEEP2 DR3 spectra  (Yan et al.
Finally, owing to the 10 ms integration time of the CMOS camera, the 2D-ST image is acquired with a 100 Hz acquisition rate. The transverse resolution along the line projection attains the diffraction limit of the imaging system  [16]. The pixel number in the vertical direction of the 2D-ST image is 232 pixels, which provides a pixel rate of 2320 pixels/s. This is much faster than conventional THz imaging system where pixel rate is usually from 1 to 100 pixels/s. However, as for 3D CT it is important to limit the amount of data storage, we arbitrarily reduced the size of the 2D-ST image to 116 × 116 pixels. Data storage and total acquisition time of our 3D THz CT system will be presented into more details in Table  1. To perform fast 3D THz CT, the sample is horizontally scanned along the X-axis with a translation stage at a constant speed of 2 mm/s whereas the THz beam is vertically linefocused along Y-axis of the sample so that a series of 2D-ST images can be acquired for a given projection angle.
Finally, for each projection angle and at every horizontal and vertical sample positions, the pixel value is extracted by measuring the peak-to-peak value of the THz electric field in temporal waveform. Similarly, after FFT of temporal data, the spectral amplitude at a given frequency could also be extracted for spectral imaging  [30]. Then, the application of the wellknown FBP algorithm implemented in the ImageJ software will numerically provide the multiplanar slices of the sample in order to finally reconstruct the 3D volume  [33]. It is wellknown that FBP suffers from several drawbacks such as beam hardening, which can induce cupping, streaks and blurring because rays from some projection angles are hardened to a differing extent than rays from other angles, confusing the reconstruction algorithm.
Finally, using the ImageJ software, the 3D reconstruction of the sample can be obtained, as shown in Fig. 5(c ) which corresponds to one still picture from the 3D movie (available in Media 2). We have to notice that inhomogeneities in thickness over the complete length of the bars can be visible in Figs. The second test sample is a plastic box (section 10 × 10 mm 2 ) with a wooden toothpick inside. Similarly, Fig. 6 (a) shows one of the 36 frontal views (video in Media 3), Figs. 6(b1) and 6(b2) give the two axial views at the position of the red horizontal lines, and Fig. 6(c ) is the final 3D reconstruction including a picture of the sample as inset (video in Media 4). First, we can notice that we are able to determine the position of the toothpick inside the plastic box in all figures. Then, especially from the axial views, we observe that the shape of the rectangular plastic box is not perfectly reconstructed.
Experimental devices Heating trials have been done using a continued Laser Nd-YAG Trumpf HL2006D (l ¼ 1064 mm). The laser is power-controlled to obtain 70 W at the exit of the focusing lens (Fig. 1a ). Non-coated carbide inserts (6% Co-94%WC) have been used. The insert geometry is TCMW1608: triangle form; clearance angle ¼ 7 ; cutting edge length ¼ 16 mm; nose radius ¼ 0. 8 mm; without a chip-breaker (plane faces). The tool-holder designation is STFC L2020 K16. It is composed of a steel body and a carbide shim. In order to focus the study on the thermal resistance between the insert and the rest of the toolholder, the carbide shim has been stuck on the tool-holder steel body using heat conductive metallic glue. These different parts of the turning device are presented Fig. 1. The temperatures were measured on accessible locations of the insert, the shim and the tool-holder by using a type K thermocouple and a Frontacq data acquisition system with a PC-controlled voltmeter.
6D ). In contrast, CpG did not activate TApDC thus confirming our in vitro data. Specific activation of TApDC was confirmed, as neither TA-CD8a þ dendritic cell nor TA-CD11b þ dendritic cell displayed increase in MHC-II (nor CD80, CD86, data not shown) expression upon TLR7 triggering (Fig. 6D ). Finally, changes in gene expression were analyzed in NEU15WT tumors 8 hours post-intratumoral injection of TLR7L by TaqMan low-density array (TLDA) mouse immune assay (Supplementary Materials and Methods). Data are presented as fold changed over the nontreated conditions and displayed as a heat map (Fig. 6E ) and detailed in Supplementary Fig. S5. Genes that displayed fold changes higher than 10 were selected to highlight the most significant changes in gene expression upon TLR7 intratumoral injection.
This work is supported by The  BCRF, Ligue Contre le Cancer, Institut National du Cancer (INCa   ACI-63-04 ,  METESCAPE ,  ANR-10-LABX-0061 ,  ARC 3364 , EML 2009, LYRIC,  INCa_466 ), and  Lyon Biopole. The costs of publication of this article were defrayed in part by the payment of page charges.
Experimental data In order to assess the efficiency of the proposed method, we propose to localize buried objects in a real-world environment. The experiment is carried out in an acoustic tank under conditions which are similar to those in an underwater environment. The bottom of the tank is filled with sand. The experimental device is presented in Figure  11. The tank is topped by two mobile carriages. The first carriage supports an issuer transducer and the second supports a receiver transducer managed by the computer. The observed signals come from various reflections on the objects being in the tank. In this experiment, we have recorded the reflected signals by a single receiver. This receiver is moved along with a straight line with a step d = 10 cm in order to create a uniform linear array of N = 5 sensors.
The buried objects are P = 6 small cylindrical shells, buried at the same depth in sand, with DOA {32°, 33°, 34°, 35°, 36°, 37°}. The wave speed in the water v 1 = 1,500 m/s and in the sediment v 2 = 1,700 m/s. Figure  12  sums up the experimental set-up. For each experiment, the transmitted signal is a short pulse with a duration of 15 μs, the frequency band is [150,250] kHz. At each sensor, time-domain data corresponding only to target echoes are collected with SNR equal to 20 dB. To simulate different SNR values, we add a simulated white Gaussian noise. In this study, the received signal from direct path of propagation is used to fulfil matrix. The estimation of RMSE and NRMSE as given in Eqs. (47) and (  48 ) is presented versus SNR values in Figures  13  and 14. From Figures  13  and 14 , it can be seen that the proposed method could effectively estimate the bearings and ranges of the buried objects in the real-world data since the RMSE and NRMSE are low.
Acknowledgements The authors would like to thank the editor and two anonymous referees for their comments and suggestions which improved the article greatly. This work was supported by the  French Armaments Procurement Agency (DGA). The authors would like to thank also  Dr. J. P. Sessarego , from the  LMA (Laboratory of Mechanic and Acoustic), Marseille, France , for providing us with experimental data. Received: 10 October 2012 Accepted: 13 July 2013 Published: 26 July 2013.
Sleep apnoea is associated with significant daytime functioning impairment and marked cardiovascular morbidities, leading to a significant increase in mortality. Sympathetic activation, oxidative stress and systemic inflammation have been shown to be the main intermediary mechanisms associated with sleep apnoea and intermittent hypoxia. There are now convincing data regarding the association between hypertension, arrhythmias, coronary heart disease, heart failure, increased cardiovascular mortality and sleep apnoea. This has been evidenced in sleep apnoea patients and is supported by experimental data obtained in intermittent hypoxia. Whether treating sleep apnoea enables chronic cardiovascular consequences to be reversed is not fully established as regard coronary heart disease, arrhythmias and heart failure.
Epidemiological aspects From OSA to HF Cross-sectional data from the Sleep Heart Health study in 4442 patients (mean age 62 years, males 44%) demonstrated that the adjusted risk of prevalent self-reported heart failure in patients with OSA (AHI. 10) was almost 2. 4 times higher compared to patients with AHI f10  [118]. Prospective data  [17]  from the same cohort (mean follow-up 8. 7 years) showed that patients without self-reported heart failure at baseline and AHI. 30 as compared to those with AHI,5, had a 58% higher rate of incident heart failure during the follow-up period. Additionally for every 10-unit AHI increase, the incidence of heart failure augmented by 13%, thus the higher the severity of OSA at baseline, the greater the incidence of heart failure. Finally, incident heart failure was associated with baseline OSA in males but not females.
Those with at least moderate sleep apnoea received either CPAP or ASV and were observed for 4 years. The primary end-point was the event-free survival time to first appropriate cardioverter-defibrillator therapy. Both CSA and OSA were independently associated with a shorter eventfree survival time period, awaiting first monitored ventricular arrhythmia and appropriate cardioverterdefibrillator therapy. While evidence may support the possibility of progression from OSA and CSA to heart failure, no data is available on the possibility that CSA might lead to heart failure development. These data taken together suggest that diagnosis and treatment of OSA and CSR-CSA are mandatory. This is underlined in international guidelines mentioning a higher morbidity in heart failure patients presenting with sleep apnoea and recommending sleep apnoea specific treatment  [141].
Ongoing studies using assisted servo-ventilation will elucidate the exact benefit that might be expected in terms of survival  [167]. Also, aiming to reduce the severity of CSA with different treatments of heart failure is promising but not definitive. Among heart failure treatments, resynchronisation therapy reduced the severity of CSA-CSR more effectively compared to other therapies. A semi-quantitative score grading the weight of evidence for all directions of ''cause-effect'' relationships between sleep apnoea and heart failure is reported in table 1. Currently, the available evidence suggests that heart failure can be considered as ''cause'' and sleep apnoea as ''effect''. Data in favour of an inverse relationship are significant but limited regarding OSA and almost absent in the case of CSA-CSR.
, 2002; Fedak, 2004]. While their principle intent was to improve understanding of seal foraging strategies  [Biuw et al. , 2007; Fedak, 2013] , they have also provided as a by-product a viable and cost-effective method of sampling hydrographic properties in many regions of the Southern Ocean  [Charrassin et al. , 2008]. [4] Within the "Marine Mammals Exploring the Oceans Pole to Pole" (MEOP) program, several international teams agreed to share their CTD-SRDL data sets to produce a single, uniformly calibrated, homogeneous database of hydrographic profiles. Here we present the MEOP-CTD database, a quality-controlled collection of most seal-derived hydrographic data obtained in the period 2004-2010 (publicly available at http://people. su. se/~froqu), and we provide an objective assessment of its contribution to improving the existing observing system.
The MEOP-CTD Database [5] The MEOP-CTD database includes 349 CTD-SRDLs, representing 165,000 TS profiles (see Figure  1  and Table  S1  in the supporting information). The majority of loggers were deployed on elephant seals, with a lesser number on Weddell and crabeater seals. On average, profiles are 500 m deep, although some seals occasionally reach 2000 m or more. The MEOP-CTD collection of profiles produces near circumpolar coverage, although some regions such as the Weddell and Ross Seas remain poorly sampled. More than 60% of TS profiles were obtained south of the southern limit of the ACC, where few Argo data exist. The migration distance of seals depends highly on the deployment location and time of the year, ranging from 100 km to more than 5000 km, while the life span of a CTD-SRDL varies from 1 to 10 months (5 months on average).
The ECCO model grid is global, with an approximate 1°× 1°horizontal resolution and 50 vertical levels  [Forget, 2010]. [11] Two 1. 5 year long state estimates were carried out for the period 2007 to mid-2008. The reference state estimate (here denoted as REF) was constrained with Argo profiles only (166,000 T + S profiles, see Figure  1b ), while the so-called SEAL state estimate was constrained with both Argo and seal data. All CTD-SRDL profiles from the MEOP-CTD database were used to constrain the SEAL state estimate, pooled as if they were all obtained during the simulation period, to obtain an upper limit on the effect of seal data while simultaneously decreasing the computation time. Some inconsistencies between seal and Argo data from different years are possible, but they should be limited given that the main contribution of seal data is expected to occur south of the ACC where few Argo profiles are available.
Nevertheless, improvements already seen in the crucial region of sea ice formation are expected to be of growing importance as more seal data become available. [19] The MEOP-CTD database is constantly expanding, as more CTD-SRDLs are being deployed every year. New sites of deployments are being used, or will be soon, such as the Ross, Weddell, and Amundsen seas, thus improving the spatial coverage around Antarctica. Improvements to the CTD-SRDL technology are underway, in terms of sensor accuracy, life duration, storage capacity, and satellite transmission. The challenge now is to broaden coverage by extending the methods to new sensors, such as fluorometers  [Guinet et al. , 2013] , and using more diverse animal types. Miniaturization techniques are improving at a fast pace, and the true potential of animal-borne instruments is yet to be revealed.
As a case study to demonstrate the effect of ADC catabolism on ADC toxicity, Dr Schutten presented results showing increase in toxicity of trastuzumab-mc-vc-PAB-MMAF ADC by increasing the DAR. She also presented data from Junutula et al. 16  comparing THIOMAB-drug conjugates (TDC) with ADC, where it was shown that TDC resulted in slower catabolism of antibody compared with ADC, resulting in better toxicity profile for TDC conjugate. To explain the unwanted ADC-mediated cytotoxicity, Dr Schutten first focused on the toxicity resulting from targeted binding of ADC to normal tissues expressing antigen. She presented a case study with the ADC-targeting leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5), which is a marker for colon stem cells and postulated marker for colon cancer stem cells.
It was observed that the LGR5-targeting ADC resulted in an on-target (intestinal stem cell-targeted) toxicity, leading to blunted or fused villi. She also presented data from CD22-targeting ADCs, where target-dependent depletion of replicating B cells by anti-CD22-vcMMAE ADC was observed in the monkeys. Using anti-CD22 ADCs, it was also shown that the targeted toxicity on B-cell depletion was more profound when drug mechanism of action was independent of cell proliferation (i. e. , DNA damaging agent) compared with cell cycle-specific microtubule inhibitors like MMAE. Dr Schutten also mentioned that off-target (cross-reactive) binding of ADC to normal tissues and non-antigen-mediated ADC uptake (e. g. , Fc-mediated uptake, pinocytosis) can also result in unwanted ADC-mediated cytotoxicity.
October 16, 2013: ADC Development Approaches In this session, Jan Pinkas (ImmunoGen) gave a talk on advancing preclinical development of ADCs, and Dave Colcher (City of Hope) discussed use of radiolabeled antibodies and antibody constructs for preclinical and clinical Applications. Paul Parren (Genmab) then presented a case study on advancing toward the clinic as soon as possible based on the pre-clinical development of a therapeutic ADC targeting tissue factor. William Olson (Progenics) showcased biomarker strategies for selecting patients and tracking treatment response in prostate cancer, Barbara Hibner (Takeda) discussed progress toward developing more predictive preclinical ADC Models, and Jiang He (University of Virginia) reported data on tumor-targeting single-chain antibody fragments for cancer imaging and targeted therapy.
He showed detailed data on the effect of aldehyde tags on physical properties of proteins. The data indicated that aldehyde tags can be placed on a broad region of mAb with minimum/no effects on aggregation, antigen binding, internalization, melting temp, and FcRN binding. He then discussed the advantages of using the new linker, which enabled new conjugation chemistry through formation of C-C bond using a proprietary HIPS chemistry. This new chemistry provided enhanced plasma stability that can be applied to a variety of payloads. Finally, he discussed the in vitro cytotoxicity and in vivo efficacy data for SMARTag TM HER2 ADCs. Potent in vitro cytotoxicity was observed with various linkers and payloads with little positional dependence and significant tumor growth inhibition was observed with payload placement at selected positions for this ADC.
Acknowledgements. The authors are grateful to  Sergio Vicente-Serrano  for providing the software used for the calculation of the Standardized Precipitation Evaporation Index and for his helpful comments on the first draft of this article. Thanks are also due to the AMAZALERT  FP7  project for supporting this study, as well as to  Aurélien Ribes  and  Julien Cattiaux  for helpful discussions and to the reviewers for their constructive comments. Edited by:  S. Seneviratne The publication of this article is financed by  CNRS-INSU.
Acknowledgments We are grateful to  Ben Allanach ,  Thomas Hahn ,  Sven Heinemeyer ,  Sabine Kraml , and  Michael Spira  for useful discussions and correspondence. FM would like to thank  Alexandre Arbey  and  Marco Battaglia  for useful discussions and comments on the manuscript. UH would like to thank  Babis Anastasiou  for an invitation to "The  Zurich Phenomenology Workshop, Higgs Search Confronts Theory" , which triggered the present work. He also acknowledges travel support from the  UNILHC network  ( PITN-GA-2009-237920 ). FM acknowledges partial support from the  European Union   FP7 ITN INVISIBLES (Marie Curie Actions ,  PITN-GA-2011-289442 ).
Data analysis. From the two individual calibrated eyes position signals we derived the disconjugate signal (left eye -right eye). The eye velocity of either conjugate (saccades) or disconjugate (vergence) signal was computed using a symmetrical twopoint differentiator after low-pass filtering with a Gaussian FIR filter with a cut-off frequency of 33 Hz. The initial ('I') and ending position ('e') of the vergence eye movements were defined as the time point when the vergence velocity exceeds or drops 5u/s (Figure  3 ). This criterion is standard  [35, 36]. The process was performed automatically by the computer, and the verification was made by visual inspection of the individual eye position and velocity trace. For both convergence and divergence, we measured the latency, i. e. the time between target onset (0 ms) and vergence initiation (marker 'I' in Figure  3 ), accuracy (gain), i.
Data analysis. We evaluated the Quotient of Romberg (QR) as the ratio of values in the conditions eyes open fixating at 150 cm versus eyes closed; the QR was estimated for each of the parameters listed above. Then we performed a non-parametric analysis U Mann Whitney Test for each postural parameter, comparing the QR of the patients and the controls group. To evaluate the effects of distance (far, near) and of vergence, we run a two way mixed ANOVA design with the viewing condition (Near 40 cm, Far 150 cm and Vergence movement) as the main factor, and the group (patients and controls) as the intersubject factor.