dataesr/scientific-paragraphs-categorization huggingface dataset:
Adaptive smoothing 2D-SSA can be also used for adaptive smoothing of two-dimensional data. It was used for this purpose in  Golyandina et al. (2007)  for smoothing digital terrain models (DTM) and in  Holloway et al. (2011) ;  Golyandina et al. (2012)  for smoothing spatial gene expression data. Similarly to the example in  Golyandina et al. (2007) , we consider an image extracted from the SRTM database. The test DTM of a region in South Wales, UK, is extracted by the function getData of the package raster  (Hijmans 2013 ). The DTM is 80 × 100, and it includes the Brecon Beacons national park. The point (N x , 1) lies in a heighbourhood of Port Talbot, (N x , N y ) -in a neighbourhood of Newport, and (1, N y ) is near Whitney-on-Wye. In Fragment 22, we decompose the image with a small window, and plot the eigenvectors and the matrix of w correlations in Figure  24.
Acknowledgement The authors would like to thank the anonymous referees for their patience and thoughtful suggestions and comments that led to the significantly improved presentation of the paper. The paper was partly supported by the project  NG13-083  of the  Dynasty Foundation  in the area of computer science. Konstantin Usevich  was supported by the  European Research Council  under the European Union's  Seventh Framework Programme  ( FP7/2007-2013) / ERC Grant  agreements no. 258581  and  320594.
chordalis for the first time and of U. armoricana for extending the knowledge on its lipid composition where little is known about FA composition of individual lipid classes. The aim is the determination of the potential value of lipid composition (total lipid, glycolipid-GL, phospholipids-PL, sterol and unsaponifiable fraction) of these proliferative species, which may constitute a nutritional database for chemotaxonomy and anti-proliferative activity perspectives. So, for these two species, the present study was designed to clarify the content of lipid and glycolipid (GL) classes, and the FA composition from total lipids, phospholipids (PL), GL and compounds of unsaponifiable fraction. In addition, the GL fractions were evaluated for their anti-proliferative activity against human cancer cell lines (non-small cell lung cancer-NSCLC-N6).
Fatty Acid Composition of Phospholipids The PL FAs of U. armoricana and S. chordalis were identified by GC-MS analyses as FAMEs and N-acyl pyrrolidides (NAPs) as previously described for FAs of the TL. For many FAs, GC-MS data of the NAP derivatives allowed us to confirm their structures and to determine the location of double bonds, branching and hydroxyl groups  [50]. More than 35 FAs were identified in PL of U. armoricana and 19 FAs in PL of S. chordalis as showed in Table  5. The SFAs represented 64. 3% and 37. 5% of the PL from U. armoricana and S. chordalis, respectively. They ranged from C13 to C24 for U. armoricana and from C14 to C18 for S. chordalis. The major SFAs for U. armoricana were palmitic acid (53. 6%), and stearic acid (4. 6%). For S. chordalis, the main SFAs were myristic acid (2.
Acknowledgments The authors thank  Vony Rabesaotra  from  University of Nantes ,  Laboratory Mer-Molécules-Santé  (MMS), EA 2160-for her technical assistance;  Christophe Tomasoni  from  University of Nantes, IICIMED/ERATU, Cancer du Poumon et Cibles Moléculaires  for his technical assistance; and the PhD students  Anne Sophie Burlot  and  Kevin Hardouin  from  University of Bretagne-Sud  for collecting algae. This work is part of research conducted as Teaching and  Research Temporary Attaché (ATERs)  at the  Université de Bretagne-Sud, LBCM Laboratory.
Clinical data The patient was the second born child of unrelated healthy parents. Pregnancy and delivery were uneventful. Psychomotor development was initially normal. At the age of 18 months, concomitantly to an intercurrent viral illness, he lost the ability to walk, stand, sit, grip, he partially lost head control and spastic tetraparesis appeared. After this acute episode he partially recovered: one year later he was able to sit again and to stand alone but he never regained the ability to walk. He was first evaluated in our department at 17 years of age. Neurological examination showed a spastic paraparesis with mild cognitive impairment. Electrophysiological studies performed at 18 years of age (BAEP, VEP, ERG, SEP, EMG, NCV, EEG) were normal. Progressive scoliosis required spine surgery at 18 years of age.
, 2011). RWQM1 was selected because it belongs to a family of widely accepted models (e. g. the Activated Sludge Models (ASM)) which share the same presentation, notation and structure for compounds, processes, and kinetic constants  (Henze et al. , 2000; Sah et al. , 2011). Moreover, RWQM1 is the unique in the IWA family models because it considers microalgae activity. The model was implementedin the COMSOL Multiphysics TM software, which solves differential equations using the finite elements method (FEM). For calibration we used experimental data obtained from a culture medium simulatingtreated urban wastewater (i. e. secondary effluent). This model will provide new insight into the functioning of microalgae cultures, and will help to explore the simultaneous effects of factors affecting microalgae growth.
Model implementation and calibration procedure The modeldescribed in section 2was implemented in COMSOL Multiphysics TM v4. 3b software. A0D domain was used to represent the experimental reactor (mesocosms), which can be considered in perfect mixing, and therefore transport of aqueous phase species (i. e. dissolved and particulate) can be ignored. The model was calibrated using available data for the 9 days of experimentation. Manual trial and error adjustment of parameters was used to match measured data as much as possible using graphical representations. The concentrations of componentsin the mesocosmsmeasured at the beginning of the experiment are shown in Table  3. From the 31 parameters implemented in the model, 16 parameters were obtained from the existing River Water Quality Model  (Reichert et al.
, 2001). Those parameters related to transfer of gases to the atmosphere, temperature, photorespiration and carbon limitation on microalgae growthare not included into the RWQM1 and they were obtained from other literature cited in Tables. Morris's uncertainty method  (Morris, 1991)  was applied to screening which parameters had a greater influence on the simulation response. Based on a previous uncertainty analysis, the model was calibrated by adjusting the values of the maximum growth rate of microalgae (μ ALG ),the transfer of gases to the atmosphereand the photorespiration inhibition constant (K PR ). Calibration was conducted by comparing simulated and experimental data curves.
Monoclinic crystals with the usual P2 1 spacegroup with three hydrogenase heterodimers per asymmetric unit were typically obtained within 3 days (average cell dimensions: a, 62. 9 Å; b, 99. 6 Å; c, 182. 4 Å, ␤ 92. 2°). All crystals were cryoprotected in the reservoir solution used for crystallization supplemented with 20% glycerol before they were flash-cooled in liquid nitrogen or in liquid propane  (31). X-ray data were collected at the European Synchrotron Radiation Facility in Grenoble, France, and at the Swiss Light Source in Villigen, Switzerland. After data reduction and scal-ing with the XDS package  (32) , structures were solved by molecular replacement using PHASER  (33) , starting from the 1. 8 Å resolution structure of the S499A variant  (34). Next they were refined with REFMAC5 (35) using TLS bodies for the individual hydrogenase subunits.
The course of the reaction is monitored by using mass spectrometry to follow the concentrations of D 2 , HD, and H 2 as a function of time. The data can be analyzed to calculate the rate of H 2 diffusion from the active site (k out ) and the first order rate constant of HD exchange at the active site (k), which is an indicator of PT and H 2 splitting recombination at the active site  (19, 25)  (see Scheme 1). Table  2  shows that the value of k out is similar for the WT and T18S enzymes. The value of k out cannot be determined in the T18V and T18Q variants because the HDE activity is too low. The T18G mutation increases k out 1. 5-fold, and the T18D mutation decreases k out about 5-fold. The values of the rate constant k for the T18S and T18D variants are, respectively, ϳ100 and 10% that measured with WT.
Acknowledgments-We thank the  Pôle de Compétitivité Capénergies  and the  FrenchBIC research network  for support. We thank the staff at the used  SLS  and  ESRF  beamlines for assistance with x-ray data collections. We acknowledge the  Aix-Marseille EPR spectroscopy Facility Center  (national  TGE-RENARD network ,  FR3443 ) and the  HélioBiotec platform (Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA) ).
* This work was supported by the  CNRS , the  Agence Nationale de la Recherche  (HYLIOX and  HEROS  projects:  ANR-07-BIOE-010  and  ANR-14-CE05-0010 ), the  Aix-Marseille Université , and the  City of Marseilles. This work was also supported by grants from the  CNRS  and the  Région Provence-Alpes Côte d'Azur  (to A. A. -H. ), the  Spanish MINECO   CTQ2012-32448  project (A. L. D. L. ), the  Spanish FPI program  (to O. G. -S. ), the  Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA) , and the  CNRS  (to H. L. and A. V. ). The atomic coordinates and structure factors (codes  4UCW ,  4UCX , and  4UCQ ) have been deposited in the Protein Data Bank (http://wwpdb. org/.
Microarray profiling MIN6B1 cells were incubated for 48 h in full DMEM complemented with exosome-free FCS, in the absence or presence of cytokines. At the end of the incubation, the media were collected for exosome isolation and total RNA was extracted from both exosomes and cells. Global miRNA expression profiling was carried out at the Genomic Technologies Facility of the University of Lausanne using the Agilent Technologies miRNA Gene Microarrays. The microarrays included probes for 650 mouse miRNAs listed on http://www. mirbase. org/ (2010). For each condition, 100 ng of total cellular or exosomal RNA was analyzed. Computational analysis of optical signal-to-noise ratio was performed using the software Feature Extraction (version 10. 5. 1. 1). A miRNA was considered "not detected" if the optical signal was too low or too variable.
Statistical analysis Data are expressed as means ± SD. Statistical significances were determined using one-way ANOVA of the means, followed by post-hoc Dunnett's or Tukey's test (GraphPad Software, USA). For the microarray analysis, comparisons between groups were made using Student t test, with adjusted p-values based on the Benjamini-Hochberg false discovery rate procedure taking in to account all the 650 miRNAs included in the microarray.
Acknowledgements We thank  Bryan Gonzalez  and  Sonia Gattesco  for their technical expertise. This work was supported by grants from the  Swiss National Science Foundation  ( 310030-146138 ) and  European Foundation for the Study of Diabetes (RR)  and from the  Fondation pour la Recherche Médicale  ( DRM20101220456 ) and from the biopharmaceutical company AstraZeneca (SR). CG is supported by fellowships from the  Fonds de la Recherche en Santé du Québec , the  Société Francophone du Diabète  and the  Canadian Diabetes Association. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The model, developed in TRNYS, was validated for steady state and transient conditions. The aim of the work now is to assess the energetic and exergetic performance of systems integrating this new PV-T module. The PV-T prototype, as well as the entire domestic hot water system, and the complete TRNSYS model are presented in this paper. Model validation was performed using measurements taken under real conditions. The model allows a rapid energetic analysis of the domestic hot water system.
TRNSYS Model This SDHW system has been modelled with TRNSYS, following a similar arrangement to previous works  [1, [7] [8] [9] [10]. TRNSYS a dynamic simulation tool particularly dedicated to the modelling of energetic complex systems at the system scale. The software adopts an approach where a system is reduced to a set of interconnected subsystems modelled as TYPES. In our case, the entire system has been modelled using TYPES available in the TRNSYS standard library sumarised in table 1 and as illustrated in figure  3. The model includes the following numerical limitations and settings: the weather data and the consumption profiles allow minute-wise simulations; the TYPE used to simulate the PV-T modules does not work for a zero flow. A residual flow of 7 l/h was therefore imposed; mass conservation at pipe diameter shifts was ensured via "equation" components as shown in the diagram; 7 °C et 4 °C delimits the upper and lower bounds of the dead band ot the controller: is the set point temperature (55 °C in our case) and the water temperature at the bottom of the tank; temperature stratification in the tank was modeled in the TYPE 60d.
Conclusions An experimental domestic solar hot water system integrating hybrid PV-T module prototypes has been installed and monitored during 18 months on BESTLab site of EDF R&D. Its aim was to follow the behaviour of these prototypes within a complete system in order to evaluate its real performance the value added compared to more conventional solutions. In this paper, a TRNSYS simulation has been compared to monitoring data from the test rig at BESTLab. The thermal behaviour of each sub-system, PV-T modules and tank in particularly, have been validated, showing calculated temperatures in general agreement with the data. Comparing power and energy consumed by the auxiliary heating suggests the control systems has been correctly simulated by the model. Finally, this model allowed to point out the limitations of the PV-T model currently in use, (TYPE 50), in particular with regards electrical power generation and for close to zero glycol water flow rates.
IR spectroscopy and adsorption studies both confirm a direct accessibility of both Fe(III) and M(II) Lewis acid sites. Further studies will focus on the establishment of a library of mixed-metal MOFs and the analysis of their properties for various relevant applications. The research leading to these results has received funding from the European Community's Seventh Framework Program (FP7/2007-2013) under grant agreement no. 228862. The authors would also like to thank Antoine Tissot and Nathalie Guillou for their valuable help.
Acknowledgements We acknowledge support from  Foundation de l'Orangerie for individual Philanthropy  and its donors. This work was supported by the  French National Research Agency  ( ANR , Carbiored  ANR-12-BS07-0024-03 ) and the  French State Program 'Investissements d'Avenir' (Grants "LABEX DYNAMO ",  ANR-11-LABX-0011 ). N. E. acknowledges the  Direction Générale de l'Armement (DGA)  for a graduate research fellowship.
Nevertheless, these parameters and the diode reverse saturation current have been determined by some authors  [3] [4] [5] [6] [7] [8]. These authors measured the - characteristic of a PV module using a solar simulator instead of the normal operating conditions. Under the real weather conditions, it is difficult to have a constant irradiance and a constant temperature, particularly in the tropical climate. So, it is not evident to get the - characteristic of the PV module under the normal weather conditions. That is why this paper proposes a new method of the determination of photovoltaic parameters under the normal operating conditions. The irradiance, the temperature, the load current, and the load voltage have been recorded during a whole day. Then, the PV parameters have been calculated from these experimental data using a least square method in the PV parameters extraction algorithm.
The results confirm that the diode reverse saturation current   effectively depends on the temperature and the mathematical expression obtained in the literature has been validated  [6] [7] [8] [9]. The diode ideality factor, , changes less with the weather conditions. The series resistance   depends essentially on the irradiance. The mathematical expression of the series resistance has been obtained. In order to verify the effectiveness of these results, the PV module has been modeled with MATLAB/SIMULINK. The input parameters for the simulations are the recorded irradiance and surface temperature, the determined PV parameters (  ,   , and ). The recorded load current has been also loaded in the SIMULINK model for comparison. For the comparison with the literature results, the same PV module model has been simulated as inputs: the recorded irradiance and temperature, a constant diode ideality factor ( = 1.
The second one is the simulated current  sim with MATLAB/SIMULINK, using the extracted parameters (,   , and   ). And the last one is the simulated current  lit with MATLAB/SIMULINK, using the consideration of the literature. The results confirm the fact that the parameters such as series resistance and inverse saturation current cannot be considered as constant. If so, the simulated result will be too far from the real system as it is the case in Figure  19. With the extracted parameters, the module's electrical model used for the simulation with MATLAB/SIMULINK is really similar to the real one functioning under the same climatic conditions. So the results of the simulations will accurately be the behaviour of the real system under the normal climatic conditions.
Conclusion This paper presents a new method for extracting the different parameters of a monocrystalline silicon solar cell. Modeled by a one diode model with three parameters to be determined (the diode reverse saturation current, the series resistance, and the ideality factor of the - junction), a fitting based on the least square method is used to extract these parameters from experimental data. The results confirm that the diode reverse saturation current   effectively depends on the temperature and the mathematical expression obtained in the literature has been validated. The diode ideality factor, , changes less with the weather conditions. The series resistance,   , depends essentially on the irradiance. The mathematical expression of the series resistance has been obtained. For the verification of the effectiveness of these results, the PV module has been modeled with MATLAB/SIMULINK.
Ray-tracing model We used the ray-tracing software TracePro® to create a simple optical model of our test bench (see Figure  9A ). The solar disk sources can be set for any position in the sky with solid angle of the sun not being taken into account. Moreover, an isotropic semi-hemispherical background source is defined with an importance T = 25 + V OC (T, G) -V OC (25, G) ⋅ V OC (25, 1000)  sampling applied on the aperture area 3c × 3c. We limit the model to the opto-geometry of the system and do not take into account spectral effects. Additionally, we did not take into account the ground albedo in front of our test bench in order to be able to use the importance sampling tool. Also, the reflective losses, semi-transparency of the module as well as global irradiances below 10 W/m 2 have not been integrated in the model.
Note that Reich went down to 8 W/m 2  [12]  and Sprenger to 5 W/m 2  [13]. With this model, we can set any diffuse to global ratio and any sun position in order to simulate the spatial and angular distribution of hourly irradiance on the backside of the bifacial module. We defined a typical day for each season of the year as shown on Figure  9B. The input data is taken from PVsyst database  [14]  and averaged over ±1. 5 month around each solstice. Note that the number of rays have been chosen in order to ensure sufficient uniformity of the irradiance as well as limited time of simulation.
Bifacial power at real temperature In order to get the electrical power at real operating temperatures, we use a linear model based on outdoor data obtained for the monofacial module. Figure  11  shows the temperature difference T module -T ambient as a function of irradiance G front over the whole year in minute data. The linear approximation lead to a coefficient κ mono = 0. 035°C/(W/m 2 ) in Equation  2. Therefore, the module temperature can be evaluated using the ambient temperature and irradiance measured on site, and the real powers can be calculated. These front and back powers are summed to give the bifacial power. We ensured with double illumination indoor measurements that this hypothesis is valid for the level of total irradiance involved in our application (<1. 04 sun). (2).
Annual performance In the previous sections, we obtained experimental data in different configurations of our test bench at specific periods of the year. The model being validated, we can now extrapolate our results over the whole year. Figure  15  shows the bifacial module energy production simulated in watt-hour for each typical day as well as over the year (cumulating each typical day) according to the distance between module and reflector in the white reflector case. As in the monofacial case, we can see that the energy production is maximum near spring and autumn solstices independently of the distance (see Fig. 8 ). The annual energy production (black curve) clearly shows a maximum between distance 0. 5c and 0. 75c. Above these distances, the decrease is due to side effects of our test bench, namely the black side walls between the module and the reflector, which absorb the light diffused by the white reflector and prevent the ambient diffuse light from reaching the backside of the module.
Acknowledgments We thank  AGC Glass Europe  for providing the textured glass samples and for technical discussions. Bruno Soria 's work has been supported by a PhD grant from the  Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA). The resulting thesis is available online in French [19]. This article is dedicated to the memory of Yves Delesse who actively participated to the instrumentation of the test bench applied in this study.
Hydrolysis of the BH3 Group of Hydrazine Borane The Özkar's group (Middle East Technical University, Ankara, Turkey) have focused their efforts on the development of metal-based catalysts of different forms for hydrolysis of the BH3 group of hydrazine borane (Equation (  7 )). Systematic works were performed where, in addition to the characterization of the catalyst (in fresh and/or used states), the hydrolysis reaction was analyzed in terms of turnovers, turnover frequency, power law and thermodynamic data (apparent activation energy, activation enthalpy and activation entropy). The lifetime and isolability/reusability of the catalysts were also systematically considered. N2H4BH3 + 2H2O → N2H5 + + BO2 -+ 3H2 (7) Some catalysts were ex-situ prepared: e. g. , Rh/Al2O3, Ru/Al2O3, Rh(0) or Ru(0) nanoparticles supported on the zeolite Y  [30] ; Rh(0) supported on hydroxyapatite Ca10(OH)2(PO4)6  [34].
Structural and morphological characterization Transmission electron microscopy (TEM) images were obtained using a Jeol JEM-2100 with a LaB 6 filament. Highangle annular dark-field (HAADF) imaging and electron energy loss spectra (EELS) were collected using a Jeol J2010F (S)TEM operating at 200 kV and coupled to a GIF spectrometer and in an FEI Titan operated at 80 kV fitted with a CEOS Probe Corrector and a Gatan Tridiem Energy Filter. EEL data were acquired at about every 1 nm along the diameter of the nanoparticles at an energy range containing the Fe-L 2,3 and O-K edges with an energy resolution of 0. 8 eV. Fe/O quantification was performed using Gatan Digital Micrograph commercial software. The Fe oxidation state was obtained from a homemade script ("Oxide Wizard") for Gatan Digital Micrograph software,  8  where the required iron oxide reference data were obtained from Schmid et al.