dataesr/scientific-paragraphs-categorization huggingface dataset:
5 N (specimens number less than 50), (  3 ) P i = i N + 1 (specimens number higher than 50). (  4 ) For practical purposes, the shape and scale parameters are assessed by fitting the experimental data through the expression: Ln Ln 1 1 -P(σ ) = m Ln(σ ) -m Ln(σ 0 ). ( 5 ) But when failure is governed by different populations of flaws (assuming that they act independently), a multimodal function is needed. The two-parameter multimodal Weibull distribution function is  [10, 11] : P(σ ) = 1 -q exp - σ σ 01 m 1 -(1-q-k) exp - σ σ 02 m 2 -k exp - σ σ 03 m 3 • (6) Where m 1 , m 2 , m 3 , σ 01 , σ 02 and σ 03 are the shape and scale parameters of the three populations of flaws, respectively; q and k are the proportions of the most and less severe flaws respectively. In practice, a number N of identical specimens is loaded to rupture, the calculated strengths are then sorted and the probability of failure is calculated for each strength value (Eq.
Each point of view is calibrated from the known box  [14]. The relative positions of the joint centres and the metallic markers are calculated toward a frame attached to the cube using a classic triangulation algorithm. Then, the relative positions of the shell-scapula and shell-femur joints' centres are calculated toward the metallic markers attached to the shell. The Cartesian trajectories of these joints are obtained from those of the metallic markers. Each limb segment length is calculated as the distance between two consecutive articulations. Using the force measurements, the X-ray and video films, the frames corresponding to a gait cycle (stance and swing) of the right hind-and forelimbs are isolated. Then an acquisition of special points' Cartesian trajectories is done using a software developed using MATLAB.
The virtual robot From the data collected during the in vitro experiments, a virtual tortoise-like robot is created using the ADAMSView platform. TATOR II copies the kinematics and inertial properties of subject III. It is a linkage of 15 rigid bodies articulated by 22 degrees of freedom; it copies the mechanical design of subject III and the motion of subject I. The model consists of the shell imported from a 3D mechanical CAD program and four legs, as shown in Figure  -9. Each spherical joint is replaced by a kinematic equivalent compound consisting of three revolute joints that have concurrent and orthogonal axes.
Control of TATOR II Using the recordings of the contact forces and the motion, the Cartesian trajectories of the important anatomical points (joints' centres, metallic markers and claw contacts) are measured during a gait cycle of the right limbs. The acquisition of these points' trajectories is done frame by frame using custom software programmed using MATLAB. An automatic acquisition is not possible due to the quality of the X-ray films and the use of a video camera to film the motion of subject I in the lateral plane. To solve the inverse kinematics problem, two models for the right limbs are built using the ADAMS platform  [15]. Figures  10  and 11  show these models. q q 2. 8 radian   and the third joint angle 8 q is approximately constant (see Figure  -13 ). The interpolated joint angles are used to control TATOR II using a PD control law and to simulate its motion.
5. I ta p p e a r st h a t these variations can be expressed as xðNÞ¼A x logðNÞ 2 þ B x logðNÞþC x ð5Þ where N is the number of impacts, x is a geometrical parameter of the residual imprint, i. e. radius r and/or depth d. Let us note that the choice of Eq. (  5 ) was drawn from a large number of studies on indentation testing  [31, 32, 16]. A x , B x , C x are functions of [k, n, E impact ] and have been stored in two databases: one for the growth of depth (A d , B d , C d ) and the other for the growth of radius (A r , B r , C r ). To illustrate this, function B d ðK,nÞ corresponding to an energy of 8 mJ is plotted in Fig. 6.
Materials Repeated impact tests have been conducted on an annealed AISI1045 steel (200 HV) and an AISI316L stainless steel (150 Hv). The surface was mechanically polished with abrasive papers up to 1200 grit size. Surface finishing was achieved using diamond paste up to 3 mm grit before ultrasonic cleaning in ethanol. Two impact energies (8 mJ and 21 mJ) were used for each material. According to Eq. (  2 ), the nominal strain rate induced by these impacts belongs to the range [100 s À 1 ; 1000 s À 1 ]. According to literature data  [3, 34] , the stress difference for a strain of 0. 1 within this strain rate range is lower than 30 MPa for the AISI1045 steel and lower than 60 MPa for the AISI316L. For each residual imprint, the depth and radius have been measured using a 3D optical profilometer and an optical microscope.
Tomography acquisitions were carried on in 2010 July, in order to propose a higher resolution structural model of the landslide in the direct vicinity of the seismic observation systems. The tomography acquisition (grey colour dot lines in Fig. 2a ) consisted of two profiles of 80-90-m length crossing the landslide from the east to the west. Forty 14-Hz sensors were installed every 2 m and sources were located every 4 m. Data was acquired at 2000 Hz in order to observe the discontinuities of the first metres of sediments. Two models were obtained that indicate a first layer sliding on the bedrock. P-wave velocity of the upper and the lower profiles are presented in Fig. 3. They vary between 350 and 700 m s -1 in the first layer and between 2200 and 2300 m s -1 in the second layer and are significantly higher in the lower profile.
At Super-Sauze, only one seismic array was installed in the upper part at the interface between the most active zone of the landslide (in terms of surface displacement) and a stable zone; at Valoria, two seismic arrays were installed in the upper part of the landslide (Fig. 2c ). At both sites, the datalogger is a Képhren Agécodagis. The sensors are velocimeters with different characteristics for each landslide (Table  2 ). Data sampling rate has been set to 400 Hz, as the best compromise between signal resolution, data storage and V m -1 s -1 1920 V m -1 s -1 Sampling rate 400 Hz 400 Hz data transmission. For both sites, the ground motion is recorded with a flat frequency response in the frequency range [2-80] Hz simultaneously on all channels of each array. At the Super-Sauze landslide, additional observations consisted in surface displacements monitored ca.
2011). Semi-automatic detection was applied for the three acquisition periods. The number of seismic signals that were classified as noise is variable with the acquisition periods (Table  3 ), probably due to changes of anthropogenic activities and meteorological conditions. To define the robustness of the semi-automatic detection method, the SonoView package  (Joswig 2008; Sick et al. 2012) , was used to detect visually the seismic signals and propose a reference (e. g. manual) catalogue. Spectrograms are calculated for each vertical channel with a sliding window of 256 samples with an overlap of 50 per cent, so that each pixel on the time axis of the spectrograms corresponds to ∼[128 samples/400 Hz] seconds. A global spectrogram, also called 'super-sonogram', is obtained from the combination of the spectrograms of all vertical channels of the array, pixel by pixel.
Though this procedure, each pixel of the super-sonogram is made up with seven subpixels  (Sick et al. 2012) , extracted from the spectrograms of all vertical channels. The super-sonogram is then normalized by the noise spectrum. This enables a continuous clearer and more condense view of the variations for all vertical channels together. All seismic signals have to be considered manually individually, by observing the amplitude and frequency variations. HypoLine software, which is included in the SonoView package, enables us to determine further characteristics of the seismic sources such as the location in a layered velocity model (see section 3. 4. 3). The semi-automatic and manual catalogues were compared for the 2009 October and the 2010 May records. After manual control of the candidate seismic signals picked by the semi-automatic method, up to over 50 per cent more seismic signals were detected (Table  3 ).
Local events were classified as either 'quakes' or 'rockfalls/debris flows' based on their signal duration and other characteristics, but the distinction between these two types of events is not always trivial. Local seismic events were located using the beam-forming method of  Lacroix & Helmstetter (2011). This method was tested by comparing with the HypoLine manual location software  (Joswig 2008)  based on manual picking of first waves arrivals, and, in the case of Super-Sauze landslide, by performing shot tests. These shots enabled us to estimate a static time correction for each sensor. Local seismic events were concentrated in several clusters, essentially nearby the array on fractured and creeping zones for quakes and on scarp and unstable zones for events classified as rockfalls. At the Valoria landslide, only some of the events could be located due to the occurrence of a collapse and the progressive loss of several sensors.
A washing step was then achieved (3 × 5 min in PBS 10 mM + 0,1% tween 20). Fluorescence analyses were performed to quantify the adsorption of the target molecules onto the chip surface and evaluate the efficiency of the surface chemistry to minimize the background signal. f. Characterization technique Fluorescence quantifications were performed using an InnoScan 900 scanner, dedicated to microarrays measurements (Innopsys, France). This equipment composed of two wavelengths (λ= 532 nm, λ= 635 nm) exhibits a spatial resolution of 1 μm. We measured the surface fluorescence intensities, thanks to the image treatment software Mapix (Innopsys, France). The fluorescent signal between the antibodies spots (i. e. background) is measured and systematically compared after statistical analysis for the various surface chemistries tested in this work.
Acknowledgements We thank the clean room facility of  LAAS-CNRS  for the fabrication of silicon molds used for the printing process. We greatly thank  P. Colpo  from  JRC ,  Ispra Italy  for the fabrication of the plasma deposited PEO films used in this study. This work was financially supported by the  ERANET  project  DETECTMUNE  financed by the  Midi-Pyrénées regional council.
1) Functional simulation At this first stage of the design flow, the power part of WECS (DFIG, infinite electrical grid and fault tolerant converters topology) shown in Figure  1  and the sensors (mechanical and electrical) are modeled using the Matlab/SimPower Systems. The interfaces, RSC and GSC controls, the different PWM controls and the fault detection and compensation scheme, shown in Figure  7  have been modeled using Matlab/Simulink. The studied WECS is first modeled in the continuous-time mode and then in the discrete-time mode. In the functional simulation, the up-counter shown in Figure  6  is modeled by an integrator. The threshold value h in first comparator must be chosen equal to 3 at 5 % of DC bus voltage v dc in order to eliminate offset near zero of voltage sensors. For experimental tests with a real power part, the threshold value N t must be chosen regards on: -the time response of the voltage sensors used for the pole voltages measurements, -the characteristics and performances of the analog data acquisition, mostly analog to digital converter and interface electronics, -the dead time of the IGBTs' drivers.
However, in all simulations, sensors and interfaces of the power part are simulated with Matlab/SimPower Systems. Thus, the threshold value N t will be chosen as the lowest as possible. Thus, the values of the thresholds N t and h are chosen, respectively, to be equal to 10 (corresponding to 10 μs) and 50 V. After the validation of all WECS models by functional simulation in the continuous-time mode, the power part and the sensors of the WECS have been modeled with the Matlab/SimPower Systems in discrete-time mode with a time step equal to 1 μs. The interfaces, RSC and GSC controls and the fault-detection and compensation scheme have been modeled with Matlab/Simulink. The sampling period for RSC and GSC controls has been chosen to be equal to 1 ms. For different PWM controls and the fault-detection scheme, the sampling period is chosen to be equal to 1 μs.
3) HIL simulation The reconfigurable platform is based on a DSP S80 development board, which includes a Altera Stratix EP1S80B956C6 FPGA chip. This FPGA contains 79 040 programmable logic elements, 679 user I/O pins, 12 reconfigurable fast PLLs, and 7. 4-Mb RAM. The development board has also an on-board 80-MHz oscillator. To implement the fault detection and compensation scheme as well as the different PWM controls into the FPGA target, the following steps have been followed with Quartus II software: -generation of the synthesizable VHDL code, -logical synthesis, -fitting. At this step, all DSP Builder blocks have been replaced in the Matlab/Simulink environment by a single "HIL block" corresponding to the digital fault tolerant reconfigurable control implemented into the FPGA. The connection between the development board and the computer is done by using a ByteBlasterMV cable for FPGA programming.
While following the already generated path, the sensor onboard systems transfer the updated information about the environment to the planning algorithm. When the obstacles are detected, the algorithms has to be able to compute new maneuvers. In case of replanning a path de¦ned by waypoints to avoid the recently detected obstacles, the new path also has to reach the goal point. This is called planning waypoint navigation. In  [10] , waypoint navigation system introduced in a database from the current information of the environment is composed by three main units: Reactive Unit, Knowledge Base, and Deliberative Units. The Reactive Unit is the primary navigation when the vehicle is placed in the unknown environment. The information from the sensors is stored in the Knowledge Base. The already available waypoints are recorded over Deliberative Unit for preplanning, planning, or replanning.
Autoclave corrosion In order to record oxidation weight gain as a function of autoclave corrosion exposure, as well as generating samples that have experienced different durations of autoclave exposures, sets of four samples were introduced into the autoclave every 20 days. Corrosion experiments were conducted in static isothermal autoclaves operating at 360 °C in simulated primary water chemistry (Li and B were added in the form of lithium hydroxide and boric acid, Li = 2 wt. ppm, B = 1000 wt. ppm), at a saturation pressure of $18 MPa (360 °C). The tests were performed consistent with ASTM G2 standard and are discussed in detail elsewhere  [40]. The corrosion experiments aimed to provide samples and weight gain data from the early stage of corrosion until after the first transition.
It should also be noted that while APT data are shown here only for ZIRLO with 34 days, similar tests have been carried out on samples after 100 days (pre-transition) and 140 days (post-transition) autoclave exposure. The results from these samples also demonstrate tin to be evenly distributed between the metal and oxide relative to the Zr. In order to compare the percentages of niobium and tin in the matrix measured by 3DAP, to those expected for the bulk alloy, it is important to take into account the significant levels of oxygen present in solution near the metal/ oxide interface. However, even when this contribution is considered, the values shown here remain lower than suggested by the bulk alloy composition. For niobium, the bulk concentration exceeds the solubility limit in zirconium ($0.
Acknowledgements The authors would like to thank the  Engineering and Physical Science Research Council (EPSRC)  and  MoD in the UK  for funding the research as part of the Materials for Energy call (Research Code:  EP/E036171/1 ). The project would not have been possible without the strong support of our industrial project partners (in alphabetical order):  EDF ,  National Nuclear Laboratory, Rolls-Royce, Serco and Westinghouse , who have provided substantial in-kind and financial support, and our academic project partners from the  Open University. The provision of synchrotron beam time at the  BESSY II  facility (EU proposal  2010_1_90919 ) is gratefully acknowledged.
-Identifying seismic traces: Using advanced analytics based on Hadoop and distributed Database for storage, quick visualization and comprehensive processing and imaging of seismic data  (Seshadri, 2013)  to identify potentially productive seismic trace signatures previously  (Hems & al. , 2013). -Build new scientific models: By using high performance computing and based on combination between "historical data" and "Real Time Data Acquisition": Petabyte seismic data sets, Mud Logging, MWD, LWD, Testing, Gamma Ray  (Nicholson, 2013 ) &  (Seshadri, 2013).
Research & Development Oil & Gas companies should take advantage of their Research & Development Centers (CRD) or through close collaboration with existing independent centers to explore the potential of Big Data to resolve problems and technical difficulties they encounter in daily operations and capitalize knowledge to improve performance. They must in this case, taking into account the requirements of a shared collaborative environment that supports the flow of total production of the working groups. To solve problems, R&D workgroups should have permanent eye on the wealth of data contained in the patent databases to be inspired particularly as these databases are considered as Open Big Data. Patents are a unique and invaluable source for R&D because the information they contain, are generally not published elsewhere.
Characterization of Au nanoparticles Absorbance spectra were measured with a Varian Cary Win UV spectrometer (Varian Inc, Melbourne, VIC, Australia) and fluorescence spectra with a Varian Cary Eclipse fluorometer (Varian Inc, Australia). Fluorescence excitation and emission slits were 5 nm; measurements were taken in 1 cm path length quartz cells (Hellma, Müllheim, Germany). Particle size in the solution-aging study was measured using dynamic light scattering at a 90° scatter angle on a Nanoparticle Size Analyzer system (Brookhaven Instruments Corp, Holtsville, NY, USA). Data were acquired at 25°C, and sample solutions were prepared by diluting Au nanoparticles into deionized water. The results are given as the mean value of 10 measurements. An ultrasonic revival of the aged colloidal solution was accomplished in a Bandelin Sonorex RK 156 BH (Bandelin Electronic GmbH, Berlin, Germany) commercial ultrasonic bath operating at 35 kHz and with power of 215 W (8.
No agglomeration of colloidal nanoparticles was observed with an optical microscope at a resolution of ∼1 µm; if surface anchoring was not used, clustering of Au nanoparticles occurred and was discernable under optical observation. We show SERS data only for sample Number 1. Spectra were analyzed with Matlab (Math Works, Natick, MA, USA). The multiple reference and Rh6G spectra were averaged. The averaged reference was subtracted from the averaged Rh6G spectrum. However, due to a sample-induced change in the Raman background, the reference spectrum was shifted and warped slightly to provide a close fit for the subtraction. The background-corrected Rh6G data was smoothed with a Savitzky-Golay filter using a window size of 15 and a third-order polynomial. This method of smoothing is suitable as it minimally affects the shape and height of the peaks yet significantly improves the signal-to-noise ratio.
Acknowledgments RK acknowledges support via a fellowship funded by  European Union   Structural Funds project  " Postdoctoral Fellowship Implementation in Lithuania" within the framework of the Measure for Enhancing Mobility of Scholars  and  Other Researchers  and the  Promotion of Student Research  ( VP1-3. 1-ŠMM-01 ) of the  Program of Human Resources Development Action Plan. The project was in part supported by the  Australian Research Council   DP120102980  project,  VP1-3. 1-ŠMM-01-V-02-001funding  scheme, and  French National Research Agency (ANR)  grants  LASERNANOBIO  ( ANR-10-BLAN-919 ) and  BIONANOPLASMON  ( ANR-09-BLAN-0177 ).
Simulations In order to determine the parameters which are critical for the LED COB encapsulation performance, we have developed a simulation model which calculates the amount of light extracted from a blue light-emitting die depending on the shape and on the size of its encapsulation. We have used the Zemax software, which is based on the Monte-Carlo ray-tracing. The typical LED COB geometry includes a 1×1 mm 2 GaN LED die (refractive index:  = 2. 42 for a 450 nm incident wavelength) on a large board. Then, the die emission has been modelled as a lambertian intensity distribution. The light-emitting wavelength has been fixed equal to 450 nm, which is close to the typical wavelength of Royal Blue LEDs. For simplicity reasons, we have also chosen not to take into account the die roughness in these simulations.
DZjiD Where M and N are the number of data points in the X and Y direction, respectively, of the array, and Z is the surface height relative to the reference mean plane. R q represents the root mean square roughness, obtained by squaring each height value in the dataset, then taking the square root of the mean. The digital approximation for the three-dimensional R q is given by: Rq~ffi ffiffiffiffiffiffiffiffi 1 MN r X M i~1 X N i~1 Z 2 xi,yi ð Þ R q has statistical significance because it represents the standard deviation of the surface heights, and it is used in the more complex computations of skewness (briefly, R sk that measures the asymmetry of the surface about the mean plane) and kurtosis (briefly, R ku that measures the peakedness of the surface about the mean plane). In our work, we characterize the three-dimensional membrane waves for migrating single and collective cells and describe their propagation using a superresolution wide-field optical profiling technique as described by Reed et al  [48].
This work was supported in part by the '' Region Aquitaine '', the '' Agence Nationale pour la Recherche'' (ANR,  grant number  ANR-09-ETEC-001-01 ; www. agence-nationale-recherche. fr) and  Advanced Materials in Aquitaine (AMA, GIS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Dissection and Extraction Each nudibranch specimen was dissected into four parts: 1) inner organs (viscera), 2) mantle tissue devoid of MDFs, 3) MDFs, and 4) dissection residuals. The volume of the first three dissected parts was measured for each individual in acetone by displacement of the solvent in graduated glass tubes or micro syringes depending on their size. The obtained volumes of a given number of spheroidal MDFs from R. tryoni and C. gracillimum were also compared as a validation with the calculated volumes of spheroids with the same axes, just observing minute variations near to our limit of detection in the glass microsyringes (data not shown). Afterwards all dissected parts were extracted separately with acetone by crumbling the tissue with a small glass mortar and pestle and then treating it with ultrasound vibration for 1 minute.