dataesr/scientific-paragraphs-categorization huggingface dataset:
The expressions given in the table were obtained by fitting to the reported data. (j) Time dependent HCl uptake coefficients measured in a cylindrical flow tube with H 2 SO 4 contained in a boat were analysed to derive values of H * D 1/2 l. Direct measurements of H * were done by static vapour pressure measurements. The parameters listed in the table were obtained by fitting to the tabulated datasets given by  Hanson and Ravishankara (1993). Initial uptake coefficients were not reported. (k) Static vapour pressure measurement using a mass spectrometer over a stirred H 2 SO 4 /HCl/H 2 O solution (0. 01-5 wt % HCl). The expression given in the table was obtained by fitting to the reported data. (l) Vapour pressure measurement over ternary and quaternary solutions in a wetted wall flow tube.
The carrier gas flow was humidified to maintain the H 2 SO 4 concentration. The time dependent HOBr signal was used to derive values of H D 1/2 l at different temperatures and H 2 SO 4 concentrations (59. 7-70. 1 wt %). The uptake to fresh H 2 SO 4 surfaces was found to be as much as a factor of two larger than to surfaces previously exposed to HOBr. Only data from fresh surfaces is reported. Values of H D 1/2 l were converted to H HOBr using diffusion coefficients calculated as described by  Klassen et al. (1998). The temperature dependence of the solubility yields a heat of dissolution of -38 (±4) kJ mol -1. (e) Rotating CWFT with stirring of the H 2 SO 4 film (58-70 wt %). HOBr (typically 10 -10 atm) was generated by reacting BrONO 2 with water and detected using SF - 6 chemi-ions. H HOBr was determined by measuring the equibrium amount of HOBr taken up to a known volume of H 2 SO 4.
H was extracted using diffusion coefficients for HBr in H 2 SO 4 as described by  Williams et al. (1995)  (see comment (a)). Only the result for H D 0. 5 at 210 K (59. 6 wt %) was listed though data were obtained over the temperature and concentration range indicated. The solubility listed was calculated using temperate and concentration dependent diffusion coefficients of  Klassen et al. (1998). (c) Equilibrium concentrations of HBr were measured above cold, HBr-containing H 2 SO 4 samples of known HBr concentration composition and wt % (40. 3-60. 5 %). Solubility data at room temperature were obtained by bubbling N 2 through a HBr/H 2 SO 4 solution of known composition and analysing the HBr mole fraction in the gas by re-dissolution in H 2 O with electrical conductivity measurement of ion concentrations.
The data listed also contain a parameterisation of measurements (at 59. 6, 64. 4 and 69. 8 wt %) reported in  Abbatt (1995) , and described in comment (b). (d) Head space above stirred, bulk solutions of known composition was analysed by tuneable diode laser absorption spectroscopy of HBr. H 2 SO 4 solutions of 53-75 wt % were used. (e) Modified diaphragm cell method. The value of the parameter c in the Stokes-Einstein expression for the diffusion coefficient, D = cT /η, was independent of the H 2 SO 4 concentration and agrees well (within 5%) with calculations using the  Wilke and Chang (1955).
Uptake coefficients obtained by gas-analysis using MS. The enthalpy and entropy of solution were determined as -66 kJ mol -1 and -249 J mol -1 K -1 , respectively. The solubility data (180-195 K) can be described by: H * = exp {(T * 216. 7 -66000)/8. 314 * T )} for 70 wt % H 2 SO 4. (b) Rotating WWFT generally at ≈100 mbar with MS detection of acetone at high concentrations ((1-5) × 10 -5 atm). The experimental uptake coefficient, γ ss , was observed to increase with [acetone]. Reactive uptake observed at [H 2 SO 4 ] > 70 wt % and reversible uptake at lower concentrations. Uptake coefficients were corrected for gas diffusion. (c) Knudsen reactor using 48-68 wt % H 2 SO 4 at 210-240 K. Solubility determined by measuring the time dependence of the acetone uptake and using liquid-phase diffusion coefficients calculated from viscosity data.
The error limits are reported to be (+100 %, -50 %) except for the 40 and the 60 wt % solution. The uptake of ClONO 2 in the presence of HCl is not accelerated compared to experiments without HCl. A number of experiments were performed at high HCl concentrations with the result that γ is significantly enhanced at comparable ClONO 2 concentrations: for a 60 wt % solution γ was 2 × 10 -4 (215 K), 0. 006 (215 K) and ∼0. 01 (238 K) for gas phase HCl concentrations of 2 × 10 10 , 7 × 10 12 and ∼5 × 10 12 molecule cm -3 , respectively. M. Ammann et al. : Evaluated kinetic and photochemical data for atmospheric chemistry (c) Liquid H 2 SO 4 (46. 6 wt % to 65 wt %) was applied as a cold liquid to the inner wall of the flow tube. The HCl was either added to the liquid (46. 6 and 51 wt %) or taken up from the gas phase  (55.
Uptake coefficients determined from both kinetic curves were within 10 %. γ increased with p(HOBr) 1/2 at 65-70 wt %. Bimolecular rate constants for the HOBr + HCl reaction derived from the uptake data using H * (HOBr) determined in the same study were in the range of (1. 6-270) × 10 5 M -1 s -1 , increasing strongly with wt % H 2 SO 4 and less so with temperature (213-228 K). The [H 2 SO 4 ] dependence was attributed to an acid catalysed mechanism and the temperature dependence to diffusion limitation. (d) Rotating CWFT with stirring of the H 2 SO 4 film (58-70 wt %). HOBr (typically 10 -10 atm) was generated by reacting BrONO 2 with water and detected using SF - 6 chemi-ions. First order loss of HCl was measured in the presence of excess HOBr (0. 2-2. 0) × 10 -10 atm. b was extracted assuming α b = 1.
Acknowledgements. We thank  I. U. P. A. C. for the financial help which facilitated the preparation of this evaluation. We also acknowledge financial support from the following organisations:  EU Framework Program 6 and 7, ACCENT network  of excellence; the  European Science Foundation  ( INTROP program ), the  UK Natural Environmental Research Council ; the  Swiss National Science Foundation  (Projects  200020 125204  and  200021 130175 ), and the  Deutsche Forschungsgemeinschaft  ( SFB 357 ). We have appreciated valuable comments by  H. Herrmann ,  D. Knopf  and an anonymous reviewer. Edited by:  W. T. Sturges M. Ammann  et al. : Evaluated kinetic and photochemical data for atmospheric chemistry Langenberg et al. (1998) provide an upper bound of the reactive uptake coefficient consistent with these values.
Previous studies on loiasis in Kokodo In January 1996, the village was included in a study aiming at identifying the risk factors associated with post-IVM SAEs  [4]. Detailed data on Kokodo currently presented, though part of the study by Gardon et al. [4]  in the Lekie division, were not previously published. A total of 453 persons aged 15 years and above participated in the study. All individuals were first asked whether they had already received IVM treatment, and 107 (23. 6%) declared they had so  (3 in 1993, 72 in 1994 and 32 in 1995). This relatively high proportion of persons already treated was due to the fact that largescale IVM treatments were organized since 1993 by the Ministry of Public Health and the non-governmental development organization (NGDO) Helen Keller International (HKI) in the neighboring sub-division of Monatele.
Regarding loiasis specifically, several studies showed that a single dose of IVM brings about a marked and long-standing decrease in Loa microfilaremia, lowers the prevalence of loiasis  [10, 11] , and reduces the infective rate of the Chrysops to low levels when given on a large scale at 3-monthly intervals  [15]. large-scale administration of IVM was demonstrated to be an efficient means to control Loa transmission, it was hypothesized that CDTI would have had such a result in the Lekie division after several years of annual distributions. At the launching of CDTI in this division, entomologic data on the transmission of loiasis were recorded over 1 year, and distribution of IVM has been conducted annually, every year, with various therapeutic coverage rates. To evaluate the impact of this drug coverage on the transmission of loiasis, entomologic data were collected over a 4-month period from March to June 2012 and compared with the baseline data.
Acknowledgements This study was partly funded by the  Filariases and other Tropical Diseases Research Center (CRFILMT)  supported by  Mectizan Donation Program (MDP). It was also funded by  APOC  through financial support for the training of MKK in entomology in Benin. Dr Raceline Gounou  is duly acknowledged for providing some dissecting materials. Mr. Guerin Moudze  and  Mrs. Sintiche Madjo Amougou  are very much appreciated for their logistic help. The support of the chief, volunteers and the entire population of Kokodo are highly acknowledged.
Data Data from more than 2000 lakes from 22 European countries were used to develop the eutrophicationrelated metrics (Table  1 ). The data are stored in a central database and are further described by  Moe et al. (2012). The above listed papers focus on the individual BQEs, including the datasets underlying the regressions presented in this synthesis. Within-lake variability in metrics has been assessed from new WISER data collected from 26 to 51 lakes in 2009-2010 (Table  2 ).
Macrophyte response to water level fluctuations (winter drawdown) The dataset used in the water level fluctuation analysis included winter drawdown data as an indicator of water level regulation amplitude (see  Hellsten, 2001). Winter drawdown was calculated as the average difference between the highest water level during October-December and the lowest level during the following April-May. The macrophyte data included in total 67 lakes; 29 Finnish lakes, 25 Norwegian lakes and 13 Swedish lakes. The data were used to establish the water level drawdown index (WIc) based on the sensitivity of aquatic macrophytes to winter drawdown of water level. A further regression was developed by selecting only lakes under hydropower production, leading to regulation amplitudes between 1 and 6 m. All details are presented in  Mjelde et al.
Littoral macroinvertebrate response to shoreline modifications A sampling campaign of benthic invertebrates was conducted in the eulittoral zone of 51 lakes in order to produce a methodologically homogeneous dataset. The sampling campaign included lakes in seven countries sampled at shoreline sections representing three levels of hydromorphological degradation (unmodified, moderately modified and highly modified)  (Miler et al. , 2012). More specifically, benthic invertebrates were sampled in Germany (9 lakes), Denmark (2 lakes), Ireland (9 lakes), United Kingdom (3 lakes), Sweden (9 lakes), Finland (4 lakes) and Italy (15 lakes with eight lakes in the subalpine and seven lakes in the Mediterranean region). Hydromorphological pressures on lake shores were parameterised using the Lake Habitat Survey (LHS) method  (Rowan et al.
Littoral macroinvertebrate responses to morphological shoreline modifications The multimetric index LIMCO (based on the composite invertebrate samples) was significantly correlated with the stressor index on shoreline modifications in all the four biogeographic regions covered by the dataset (Table  4b ). The strongest correlation was shown for the region of Germany and Denmark (q = -0. 69), followed by the Irish/UK region and the Italian region (q = -0. 47 and -0. 49, respectively), whereas the correlation for the Northern region with Sweden and Finland was the weakest (q = -0. 39). The multimetric index LIMHA (based on habitat-specific samples) showed the strongest correlations for stony habitats for the regions Germany and Denmark (q = -0. 73) and Ireland and United Kingdom (q = -0. 71), intermediate correlation strength in habitats with macrophytes for Germany and Denmark (q = -0.
Also, the fish metrics are largely affected by a series of other environmental factors, such as lake morphometry, as well as availability of substrate feasible for spawning, in addition to other human pressures, such as climate change (temperature) or stocking and fishing  (Jeppesen et al. , 2010; Argillier et al. , 2012). An additional reason for the different performance of the various metrics and BQEs is variation in the length of the pressure gradient in the separate BQE datasets, especially if data in the lower or upper ends of the gradient are few, or missing. Variation in the lake types or regions covered by the dataset may be another reason, rendering some metrics more applicable for certain types or regions. For example, the Fish multimetric index for the Northern region (NLFI) performs better than the European Lake Fish Index (ELFI), which can be due to a more heterogenous dataset used for the ELFI index, having larger variability of other environmental factors, thereby obscuring the TP pressure signal.
Thus, the metric developed in WISER based on available data from previous years should be further developed taking hydropeaking into account. Data from Alpine reservoirs should also be included. The benthic invertebrate multimetric indices LIM-CO and LIMHA show good correlations with the morphological stressor index  (Table 4b, Miler et al. , 2012) , especially for the LIMCO index in the biogeographical region of Germany/Denmark (q = -0. 69), and for the LIMHA index for stony habitats in two regions: Germany and Denmark (q = -0. 73) and Ireland and United Kingdom (q = -0. 71) (Table  4b ). Effects of morphological alterations to lake shores on benthic invertebrates can be assessed at whole-lake level by interpolation of site-specific biological scores using physical habitat surveys of the lakeshore sections in-between the biological sampling sites.
For macrophytes, further work is needed to explore the consequences of hydropeaking in hydropower reservoirs, as well as the consequences of water level stabilisation in more productive lakes expanding the gradient of impact. Furthermore, macrophyte metrics should be developed to assess the impacts of morphological shoreline alterations to complement the benthic invertebrates multimetric indices. For benthic invertebrates, the influence of other environmental factors on the two metrics LIMCO and LIMHA and on their correlation with the morphological shoreline modification pressure should be further investigated based on more extensive datasets also covering other countries in Europe. Moreover, these indices should also be linked with the MMI, which was used for the intercalibration in the CB-GIG and proven to respond to hydromorphology and eutrophication in 11 countries.
Acknowledgments The paper is a result of the project  WISER (Water bodies in Europe: Integrative Systems to assess Ecological status and Recovery ) funded by the  European Union  under the 7th  Framework Programme, Theme 6  ( Environment including Climate Change ) (contract No. 226273 ). We would like to thank  Birger Skjelbred ,  Jannicke Moe  and  Bernard Dudley  for assistance with data management and extraction, and a special thanks goes to all the data providers, as stated also in the individual BQE papers in this issue. We also thank the reviewer for helpful comments to the manuscript. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
ACKNOWLEDGMENTS We acknowledge support from the  EU   Seventh Framework Program  ( EU-FP7 ITN Herodot , Grant No. PITN-GA-2008-214954 ). Calculations were performed at the IDRIS supercomputing center, Orsay (Proj. No. 091827 ). Technion laboratory was supported by the  EU-FP7   SANS (Self-Assembled Nanostructure System ) project,  Israel Science Foundation  Project No. 1009/07  and  1425/04 , and  USA-Israel Binational Science Foundation  (Project No. 2006-225 ).
These factors require the not trivial calculation of vector intersection volumes which calculation is presented in the paper. Intersection volume is defined by superimposing the building model to be tested with the reference one. The multi-dimensional vector assessment approach has been applied to evaluate the building models produced with three different reconstruction processes created from different types of datasets. The datasets are obtained by photogrammetry (UltraCam-X and Zeiss LMK cameras), by LiDAR, and also by integration of photogrammetric and LiDAR datasets. The 1D, 2D or 3D assessment approach allows highlighting the source of deviations in the tested buildings. The error budget affecting the final product is not only composed of errors due to the reconstruction algorithm. Also errors due to the quality of the raw data, the processing of LiDAR data, of aerial data and the shape of the produced buildings should be considered.
INTRODUCTION Photogrammetric and LiDAR data are used since many years for the 3D reconstruction of objects such as buildings. These applications need accurate data and methods in order to produce good results. Quality assessment is critical for 3D data production and is important for several reasons. Firstly, it may give important information about deficiencies of an approach and may take place to help in focusing a further research activity. Secondly, accuracy evaluation is needed in order to compare the results of the different approaches and to convince a user  (Schuster and Weidner, 2003). Several methods were presented in order to evaluate photogrammetric and LiDAR datasets. Calculation of Root Mean Square Errors (RMSE) for analyzing the precision of the complete 3D building is an interesting process.
1D assessment Point accuracy assessment allows to evaluate fully 3D geometry datasets by comparing points to points  (Rottensteiner and Briese, 2002). Calculations are performed to compare two different 3D building models. This is done by computing RMSE based on the deviations between both models (reference and test), in X, Y and Z directions. Deviations are not calculated between homologous nodes, but between centers of gravity of homologous planes that compose the tested and respectively the reference building.
Volume calculation In order to compute the volume of 3D objects, one has to solve two tasks; firstly determine the convex hull of the given boundary, then, calculate the volume of the resulting 3D polyhedron. Convex hull is the boundary of a closed convex surface generated by applying Delaunay triangulation on the corner points. In three dimensions, the convex hull corresponds to a closed polyhedron. Convex hull calculation is a hard process in computational geometry  (Barber et al. , 1996). A large class of algorithms that compute the exact volume of a convex object is based on triangulation methods  (Büeler et al. , 1997). The result of convex hull calculation for a gable roof building is shown in Figure  3 (a). The convex hull of a set of points in two or three dimensions is given by Matlab built-in function (convhull in 2D or convhulln in 3D) as presented in Equation (  2 ).
Test site and datasets The study area is located in the city of Strasbourg, France. Digital aerial images from UltraCam-X (4 images) and frame Zeiss LMK (6 images) of the same area were available. Table  3  shows characteristics of the photogrammetric data. Moreover, LiDAR data of the same are has been captured in 2004 (Table  4 ). 14 ground control points were measured by GNSS. The digital aerial photographs have unknown imaging orientation parameters. Using bundle block adjustment, the exterior orientation parameters of the images have been calculated by KLT software. In our application, the camera information was taken from the calibration sheet given by the camera owner. 3D reference buildings models have been created based on the photogrammetric processing of images acquired with UltraCam-X stereo-pairs.
After relative and absolute orientation of the images, an accuracy of about 16 cm in X,Y and 25 cm in Z can be estimated for a point digitized in the stereo-pairs. It is satisfactory, considering that the accuracy of the LIDAR point clouds used here is lower (around 30 to 40 cm in X, Y, Z). So, it has been decided that the 3D buildings from UltraCam-X stereo-pairs will be used as references for assessing the 3D buildings reconstructed a) from Zeiss LMK stereo-pairs (75 buildings), b) from LiDAR data (8 buildings), and c) from integration of LiDAR and UltraCam-X stereo-pairs (26 buildings). For illustration purposes, only 8 buildings are shown in Figure  7. The reconstructed buildings in the test site have three types of roofs: flat, hip and gable roofs.
3D models from LiDAR datasets In this part, a model-driven building reconstruction method using airborne LiDAR data is presented. This method has been carried out by Yong Xiao from the Chinese Academy of Sciences (China). This semi-automatic reconstruction process comprises 3 steps. At first, the point cloud covering the building is segmented to isolate building roofs. Then, a topological graph is constructed to recognize the shape of the buildings. Finally, once simple roof types are determined, building models are reconstructed with predefined models. Outlines of the buildings are first estimated with the minimum area bounding rectangle while the other key vertices and segments are obtained through the roof-topology graph. More details are given in  (Verma et al. , 2008). Figure  7 (d) shows the results.
3D assessment The results of the quality analysis based on volumetric quality factors are shown in Table  7. The mean values of V ρd and V ρq are about 0. 9, while the other three indices are close to 0 for 75 models of aerial images. The mean values of volume quality indices, V ρd and V ρq are about 0. 8. The other three indices are about 0. 1 for 8 models created from LiDAR datasets and 26 models of integration of optical and LiDAR datasets. This means that the models reconstructed from aerial images are more accurate than the other models. The 3D assessment provides more information than the 2D assessment, because it takes into account the shift which might exist in the third dimension between the two 2D surfaces. This occurs for the quality indices obtained for the models reconstructed from the LiDAR dataset.
Western blot experiments and analysis Proteins were separated by SDS-PAGE (12. 5% gels), transferred to nitrocellulose membranes (Millipore, France) and immunoblotted with the appropriate primary and horseradish peroxidase-conjugated secondary antibodies (Immunotech, France). Immune complexes were revealed by Enhanced Chemiluminescence (Supersignal Femto/Pico chemiluminescence susbtrate, Thermo Scientific) and images were acquired with the Gene Gnome imaging system (SynGene). Band intensities were quantified using the ImageJ software (NIH).
HIV-1 infection significantly reduces the uracil excision capacity of host cells Next, endogenous UNG2 expression was analyzed over time in total extracts from HIV-1-infected MAGIC-5B cells (HIV-1 replication was demonstrated by intracellular p24 expression) (Figure  1E ). UNG2 was significantly decreased at day 7 post-infection, and SMUG1 expression was significantly reduced in HIV-1-infected cells in comparison with uninfected (UI) cells. Uracil excision analysis using our enzymatic assay with the PEG-U9 probe showed that at day 7 post-infection, the uracil excision activity of HIV-1-infected cells was $40% of that of UI cells (Figure  1F ). These data indicate that HIV-1-induced depletion of endogenous UNG2 results in a decrease of the host cell uracil excision capacity. To discriminate the respective contribution of UNG1, UNG2 and SMUG1 in the residual uracil-DNA glycosylase activity, fluorescence levels were recorded in the presence of UGI or after preincubation with anti-SMUG1 antibodies.