dataesr/scientific-paragraphs-categorization huggingface dataset:
The arm length is 7. 1cm, the weight is 70g and the carrying capacity 32g. On the other hand, a manipulator arm was designed and built for this project, whose length links are 5cm for the first one and 3cm for the second one and its weight 28g. The total weight of the system is 98g and its carrying capacity is about 4g. The attitude control law (20) for the hexacopter was programmed in a Microwii Copter board. The Vicon Tracker system  [16] , MATLAB/Simulink and the xPC target toolbox  [17]  are used to implement the position control. Fig. 3  shows an overview of the whole hardware architecture.
Numerical implementation The numerical simulation of the mathematical model, presented in the previous sections, was implemented by the use of the open source DuMuX  [15]  as the base platform. DuMuX is a DUNE  [3]   The fugacities are the primary variables in this model. The phase appearance/disappearance criteria are implemented through additional complementarity equations on the sum of the molar concentrations in each phase and saturation of each phase. We implemented a new module for microbial population dynamics and bio-chemical reactions and new equations for the components that do not participate in overall thermodynamic equilibrium, such as SO 2- 4 and Fe III 2 O 3. A 2D unstructured grid was used in the format of ALU-Grid data  [11]. For spatial discretization, the Box-method (vertex-centered finite volume method  [20] ) was used.
Even longer spin-up times are needed for coupled ocean models. In coupled GCM ocean models, deep ocean layers require hundreds of years to adjust while the upper ocean only requires about 50 years  [Kantha and Clayson, 2000]. Methods such as data assimilation (observations are used to derive initial conditions) [e. g. ,  Carton and Giese, 2008]  could help to reduce the spin-up time. None of the reviewed CPM climate simulations uses a coupled ocean model. Instead, sea surface temperatures are taken from the coarse-scale driving models (reanalysis or GCM). The effects of the resulting scale difference between the highly resolved atmosphere and the coarsely resolved ocean or the consequences of the missing ocean-atmosphere interactions on CPM climate simulations is unexplored.
1002/2014RG000475 Figure  6. Example of real-data strong scaling studies with WRF RCM on a massively parallel IBM BG/Q HPC system (blue) and a standard Linux cluster with Infiniband interconnects (red) for different pan-European Coordinated Regional Downscaling Experiment (CORDEX) model domains at about 48 km resolution (EUR-44, circle), 12 km (EUR-11, cross), and a 3 km CPM domain (squares). For the individual scaling experiments, the parallel efficiency (E) is given in relation to the number of parallel tasks (or CPU cores). E is defined as the reference runtime with a specific number of parallel tasks (Tref ) divided by the runtime with an increased number of tasks (Tp) and divided by the fractional increase in task number (p). A linear speedup (i. e. , Tref/Tp = p) would lead to a sustained efficiency equal to 1.
However,  Langhans et al. [2012a]  found no significant differences in precipitation magnitudes in a 550 m run in comparison to a 2. 2 km run in Switzerland. In addition, the microphysics might not be well tuned for CPMs   (c, d ) daily maximum 1 h precipitation as a function of threshold, expressed relative to the total number of days shown in Figures  9a  and 9c  and relative to the number of wet days shown in Figures  9b  and 9d  for the data at 24 Swiss stations. The distributions have been calculated for June, July, and August (JJA) in the period 1998-2007  [Ban et al. , 2014]. The CPM simulation with Δx = 2 km reproduces the observations very well, while the LSM simulation with Δx = 12 km underestimates the frequency of daily maximum 1 h precipitation. ©2014. American Geophysical Union.
Figure9. Cumulative distributions of (a, b) daily precipitation and (c, d) daily maximum 1 h precipitation as a function of threshold, expressed relative to the total number of days shown in Figures9a and 9cand relative to the number of wet days shown in Figures9b and 9dfor the data at 24 Swiss stations. The distributions have been calculated for June, July, and August (JJA) in the period 1998-2007 [Ban et al. , 2014]. The CPM simulation with Δx = 2 km reproduces the observations very well, while the LSM simulation with Δx = 12 km underestimates the frequency of daily maximum 1 h precipitation. ©2014. American Geophysical Union. All Rights Reserved.
The emission spectrum of a sample, recorded on a spectrofluorimeter or in an image from a spectral confocal microscope, is used to calculate the real and imaginary components (the amplitude and phase, respectively) for the first harmonic Fourier transformed spectrum (X and Y, called G and S, respectively). The data are then plotted in a phasor scatter plot, termed the spectral phasor plot. The spectral phasor is based on the Fourier transformation of the spectral information obtained from a cuvette or each pixel in a spectral image. The basic calculation is as follows: (2) (3) where I is the intensity at each step of the spectrum (each λ interval or bandwidth in an image spectral phasor), n is the number of the harmonic, and L is the length of the spectrum taken as the final minus the initial wavelengths, in our case 600-400 nm).
Acknowledgments The authors would like to thank the  Biochemistry and Proteomic Unit at the Institut Pasteur  to allow us access to their facilities, in particular to  Drs Carlos Batthyany  and  Rosario Duran. LM wassupported by a I + D-2012 grant from the  Comisión Sectorial de Investigación Científica, Universidad de la Reptiblica-Uruguay. EG is supported by  National Institutes of Health  grant  P41-GM103540  and  P50-GM076516.
Methods 59 patients with newly diagnosed HL were retrospectively included. [18F]FDG-PET was performed before any treatment. Four sets of TMTV0 were calculated with Beth Israel (BI) software: based on an absolute threshold selecting voxel with standardized uptake value (SUV) >2. 5 (TMTV0 2. 5 ), applying a per-lesion threshold of 41% of the SUV max (TMTV0 41 ) and using a per-patient adapted threshold based on SUV max of the liver (>125% and >140% of SUV max of the liver background; TMTV0 125 and TMTV0 140 ). TMTV0 41 was also determined with commercial software for comparison of software tools. ROC curves were used to determine the optimal threshold for each TMTV0 to predict treatment failure.
5) and found a different cut-off (198 ml)  [7]. The comparison of these two studies is limited by differences in the MTV methodology used and in patient characteristics (all Ann Arbor stages versus early stage only). The high prognosis value shown in these two studies underlines the clinical importance of TMTV0 and could be useful for patient management in further clinical studies. Before implementing TMTV0 in clinical trials, methodological data are needed to determine the best methodology for TMTV0 calculation. Without the availability of an adapted gold standard, only a comparative study with a single dataset of patients could be used to find the best prognosis value of different TMTV0 methodologies. The choice of the software tool is also a potential source of bias in the determination and reproducibility of TMTV0, given the fact that available commercial software includes different shapes of volume of interest (VOI) drawing (predefined or irregular) and different levels of display and visual control of TMTV0 calculation.
Material and Methods Patients Using a previously published dataset of patients  [6] , we retrospectively analyzed 59 consecutive patients with a first diagnosis of classical HL, excluding nodular lymphocyte-predominant lymphoma, referred to Dijon University Hospital between January 2007 and January 2010. All the patients provided a written informed consent. The study procedures were in accordance with the ethical standards of the committees with responsibility for human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. In case of a minor patient, the written consent of the legal guardian and the oral consent of the patient was required (the written consent of the minor patient was not mandatory according to the French legislation). The oral consent was reported in the medical record.
PET acquisition PET was performed at baseline (PET0) in accordance with the policy of the Hematology Department of Dijon Hospital since 2005, which requires systematic PET evaluation for [18F] FDG avid lymphoma. Whole-body PET was acquired sequentially using a dedicated PET/CT system (Gemini GXL or Gemini TOF, Philips Medical Systems, Eindhoven, The Netherlands). CT scans were used for anatomic registration and also for attenuation correction. Emission data were corrected for dead time, random and scatter coincidences and attenuation before reconstruction with the RAMLA iterative method. The image voxel counts were calibrated to activityconcentration (Bq/mL) and decay-corrected using the time of tracer injection as the reference. All of the patients were instructed to fast for at least 6 hours before the injection of [18F] FDG.
Serum glucose levels were measured using the hexokinase method. Whole-body emission and transmission scans were acquired in the 3D mode, 60 minutes after the i. v. administration of 3 (Gemini TOF) or 5 (Gemini GXL) MBq/kg of [18F]FDG. Non-contrast-enhanced CT images were acquired before PET data acquisition. The CT, PET, and co-registered PET/CT images were reviewed in the axial, coronal and sagittal planes along with maximum intensity projection (MIP) whole-body images.
Software tool We developed a new software tool based on Beth Israel plugin for FIJI  [10]. This shareware from the Beth Israel Deaconess Medical Center, Division of Nuclear Medicine and Molecular Imaging is available at http://sourceforge. net/projects/bifijiplugins/ as a free plug-in for FIJI  [11]  (Image J distribution). This software handles PET/CT fusion and display (multi-planar reconstruction and maximum intensity projection). We added MTV calculation capability based on absolute SUV threshold (ex >2. 5 SUV) or relative threshold (ex >41% SUVmax). This software is available under General Public License and can be used with all operating systems (Windows, OSX or GNU/Linux). For software validation, blinded calculation of TMTV0 was made with Beth Israel plugin and compared to the TMTV0 results to a commercial software, using Keosys software (FDA 510k clearance) as reference.
p values <0. 05 were considered statistically significant. For the software validation we compared the values of TMTV0 41 obtained with Beth Israel plugin for FIJI with those obtained with the commercial software on the NEMA IEC body phantom and the dataset of 59 patients. Statistical analysis compared the quantitative data and the prognosis strength of the two determinations of TMTV0. To compare TMTV0 assessment of each methodology, TMTV0 were also compared with a quantitative and prognosis analysis. Reproducibility analysis was made using a quantitative comparison of TMTV0 calculations (Pearson coefficient and Bland-Altman analysis) and kappa coefficient to calculate inter observer agreement using the optimal TMTV0 cut-off. For each methodology, survival functions of subgroups of patients defined by the TMTV0 were estimated using the Kaplan-Meier product limit method and compared using the logrank test; Progression-free survival (PFS) was analyzed according to the TMTV0 values.
Discussion In Hodgkin lymphoma, baseline total metabolic tumor volume (TMTV0) as determined by [18F]FDG PET has been recently demonstrated to have a strong prognosis value  [6, 7, 15] , and could be implemented in clinical trials to introduce risk adapted strategy for patient management. However, the choice of TMTV0 calculation methodology is still being debated and needs to be standardized before reaching a clinical protocol. The two available studies about TMTV0 in Hodgkin lymphoma were based on different TMTV0 methodology (SUV>2. 5 and 41% threshold). Thus, we designed this new study to compare different methodologies for determination of TMTV0 in the same dataset of patients and to calculate their impact on the prognosis value and cut-off determination. The absolute threshold using SUV>2.
The differences in TMTV0 41 values in the patient datasets are probably related to changes in VOI definition due to differences in software design. In our new software, we simplified VOI definition, added visuals controls and implemented a management of VOI overlapping. Using Beth Israel plugin, we were able to draw more VOIs to avoid underestimation of TMTV0 41 in cases of heterogeneous uptake. This study illustrates the importance of software design in the TMTV0 calculation that need to be simplified and optimized to reach a routine use. Beth Israel plugin for FIJI provides an accurate free tool for TMTV0 calculation that could be used for many purposes and could implement new features and optimizations to build a collaborative software tool for PET/CT processing. This study also presents some limitations: First, other TMTV0 methodologies have been proposed and were not evaluated in this study, in particular the most sophisticated methods like fuzzy locally adaptive Bayesian  [25].
Data Analyses Salivary concentrations of testosterone, cortisol, and IgA and AA activity were determined using a spectrophotometer Dynex MRXe (Magellan Biosciences, Chelmsford, USA) and standard assay kits (Salimetrics, State College, PA, USA). Chromogranin A was assayed using a kit from Yanaihara Institute (YK070 Human CgA EIA, Yanaihara Institute, Shizuoka, Japan). Salivary concentrations were determined from duplicates of the samples obtained during the preparation, resulting in an intra-assay coefficient of variation below 5% for all salivary markers (4. 5 ± 2. 1% on average). Subsequent analyses (pre-competitive phase) were thus performed in simple measurement. Measurements performed during both periods were averaged to obtain a representative value for each period (3 values for preparation period, 6 values for pre-competitive period).
The islands of this region are major breeding sites for terns (order Charadriiformes) as well as species in the orders Phaethontiformes (tropicbirds), Procellariformes (petrels and shearwaters), and Suliformes (boobies and frigatebirds). Several of these seabird species aggregate at very high densities in breeding colonies that may involve hundreds of thousands, occasionally millions, of birds  [13] , generating local conditions highly conductive for virus transmission. Because of de La Réunion"; and the National Institute of Allergy and Infectious Diseases, National Institutes of Health (contract no. HHSN266200700007C). CLe, AJ and MD post-doctoral fellowships were supported by the "Run Emerge" European Union's Seventh Framework Program (FP7/2007-2013; grant agreement no. 263958). The funding agencies did not have any involvement in the study design, implementation, or publishing of this study and the research presented herein represents the opinions of the authors, but not necessarily the opinions of the funding agencies.
Phylogenetic analyses A preliminary phylogenetic analysis was performed with all IAV H2 HA nucleotide sequences available in the Influenza Sequence Database (  [25] ; N = 618). Briefly, the coding region of nucleotide sequences was aligned with CLC 6. 6. 2 (CLC bio, Aarhus, Denmark). Maximum-likelihood analyses were performed using the software PhyML 3. 1  [26] , with the general time reversible (GTR) evolutionary model, an estimation of the proportion of invariable sites (I) and of the nucleotide heterogeneity of substitution rates (α). The phylogenetic tree obtained from this preliminary analysis is presented in S1 Fig (the detailed phylogenetic tree is available upon request). A Bayesian Markov Chain Monte Carlo coalescent analysis was then conducted to investigate the recent evolutionary history of the genetic lineage that included Reunion Island viruses (red branches on S1 Fig; N = 106).
Acknowledgments We are thankful to the  Island Conservation Society as well as Nature Seychelles  organising transportation and providing field work support from their teams (both staff and volunteers) on Aride and  Cousin Islands , respectively. We are also very grateful to  Marie-France  and  Guy Savy  for their warm hospitality and support in the field work and sample collection on Bird Island. We thank the " Brigade Nature Océan Indien " for the logistic support provided on  Reunion Island. Mélodie Bancal ,  Eric Buffard ,  Sophie Bureau ,  Licia Calabrese ,  Amélie Demosthenes ,  Jacques Fayan ,  Laurence Hoareau ,  Sébastien Lefort ,  Becky Poulson ,  Aurélien Prudor ,  Bernard Rota  and  Julie Tourmetz  are thanked for their assistance in the field or in the laboratory. We also thank  Scott Krauss  for providing the H15 IAV isolate and for attempting virus isolation of our samples.
g. ,  Thiollay 2001; Rondeau & Thiollay 2004; Virani et al. 2011; Murn et al. 2013; Kr üger et al. 2014). Collectively, these reports suggest that there may be a continental-scale problem, similar in extent-though more protracted-than the Asian situation, and as yet poorly documented. As representatives of the IUCN Vulture Specialist Group, we present published and unpublished data on Africa's vulture populations, to provide the first comprehensive assessment of their conservation status. We review the major threats to Africa's vultures, identify important knowledge gaps that need to be addressed, and suggest policy-level actions required of governments if they are to ensure the long-term survival of Africa's vultures.
Data for specific countries or regions were searched during June-July 2012 using the name of the country/region followed by the term "and vulture. " The data collected included: habitat change, timeframe, survey size, methods used, assessment criteria, species surveyed, percent decline, general trends, and threats. These data were collected using a range of methods, including road counts, foot and aerial surveys, and bird atlas records. We eliminated data sets that we judged to be speculative, if they were based on too few survey days, or the majority of species historically present in the country had not been assessed.
Panel process The typical RUAM process consists of individual rating rounds and plenary face-to-face discussions  [12]. The large size of our panel and the involvement of people from all over the world necessitated some practical adaptations, such as web conferences for the plenary meetings (Fig. 1 ). Panellists used an online programme to individually rate the appropriateness of referral for 1296 different scenarios. The appropriateness scale ranged from 1 (extremely inappropriate) to 9 (extremely appropriate) with 5 being 'uncertain' or 'equivocal'. Ratings had to be based on medical considerations only, and economic aspects had to be disregarded. Instructions to the ratings were accompanied by an overview of key peer-reviewed publications regarding DBS therapy for PD. After the ratings had been completed, data were analysed for patterns of appropriateness in relation to the clinical variables used.
Compliance with ethical standards Funding This study was supported by  Medtronic. Conflicts of interest Elena Moro received honoraria from Medtronic for consulting service and lecturing. Michael Schu ¨pbach received lecture fees from  Medtronic  and travel reimbursements from  Merz Pharma, Boston Scientific , and  Medtronic , received research grants from  ''Parkinson Schweiz'', Boston Scientific , and  Medtronic  and has been serving as a consultant for  Medtronic, Aleva , and  Lundbeck. Tobias Wa  ¨chter received honoraria from  Medtronic, Pharm-Allergan and Ipsen Pharma  for consulting service, lecturing and travelling. Niels Allert received honoraria from Medtronic for consulting service and lecturing. Roberto Eleopra  reported no conflict of interest. Christopher R. Honey  received research funding from  Medtronic  and  St.
Simulation Results The SimPower Systems and S-Function of MATLAB are used for implemented the three phase four wire four leg shunt active power filter controlled by nonlinear sliding mode technique Fig. 3. The components, parameters, and conditions considered for simulation are listed in Table  1  and 2 R s L f R f L 1 s i 2 s i 3 s i 1 l i 2 l i 3 l i 1 l v 2 l v 3 l v 1 f v 2 f v 3 f v 1 f i 2 f i 3 f i dc i dc V   Three Dimensional Space Vector Modulation 3D SVM * dc V 123 l i fn i C ld i abc dq * fd v sn i ln i fn v dc V Four Leg Inverter l R l L ch R ch L L R 123 l v  PLL * lq fq i i  * l f i i    LPF * ld fd i i   Sliding Mode Control 1 S 2 S 3 S n S dc V dqo   * fq v * fo v * f v  * f v  * fo v 123 f i fdq i .
The hypothesis of this study is that additional usage of space-borne SAR data combined with QuikSCAT and ASCAT can increase the accuracy of the offshore wind resource estimates. In this study Envisat ASAR images are processed from raw data to 10 m wind speed using three geophysical model functions (GMFs) and the results are tested against the high-quality in-situ wind data. Maps of wind resource statistics from the Northern European Seas (50°N to 64°N and 6°E to 22°W) are presented from each of the satellite sources, Envisat ASAR, ASCAT and QuikSCAT, and also combined. The diurnal wind variation is investigated and the synergetic use of wind observations from all three sensors is demonstrated. The combined wind resource statistics are compared to in situ results at two sites. This is novel and progress beyond state of the art in offshore satellite-based wind resource mapping.
Envisat ASAR, ASCAT and QuikSCAT The present analysis is based on SAR data from the Envisat 10-year archive from 2002 to 2012, and gridded ocean surface vector wind products from the 2-year archive of ASCAT from 2007 to 2008 and the 10-year archive of QuikSCAT from 1999 to 2009. Common to the three satellite instruments being used in this work is that they are active sensors based on microwave technology. One of the advantages of radar is that observations are obtained in all weather conditions, day and night. Thus all types of offshore wind conditions may potentially be observed. Each retrieved wind field is a snap-shot of the conditions at the time of observation. All instruments are on-board sun-synchronous satellite platforms and this gives a regular time of observation in ascending and descending mode.
Rain scatters and attenuates the radar signal and modifies the ocean surface. It has been found that, on average, rain contaminated scatterometer winds are biased towards higher wind speeds  (Hilburn, Wentz, Smith, & Ashcroft, 2006). The QuikSCAT satellite swath was 1800 km wide and most of the entire ocean was mapped twice per day. At 55°N the observational frequency is over 60 per month. The spatial grid is 25 km. The spatial resolution is low but the temporal resolution is high. In the present study QuikSCAT JPL (v4) GMF Ku-2011 is used  (Ricciardulli & Wentz, 2011 , 2013)  and data are the gridded wind product at grid resolution 25 km by 25 km from Remote Sensing Systems  (RSS, 2014). The wind products contain rain-flags and users can discard these data. This is done in the present analysis.
Satellite data extraction and processing In this study Envisat SAR images are processed from raw data to 10 m wind speed. The SAR data are calibrated and SAR-derived winds are retrieved using three GMFs: CMOD-IFR2  (Quilfen, Chapron, Elfouhaily, Katsaros, & Tournadre, 1998) , CMOD5  (Hersbach, Stoffelen, & de Haan, 2007) and CMOD5N (CMOD5N, 2013). The spatial grid is 1 km by 1 km. For SAR wind retrieval it has been suggested to remove hard targets using SAR-based ship detection methodology to identify ships and then omit these values before wind inversion  (Longépé, Hajduch, Pelich, Habonneau, & Lebras, 2013). This pre-processing has been applied at very high resolution (75 m) to filter out non-geophysical backscatter contributions before deriving the wind at kilometre scale. In addition, SAR wind measurements are considered as valid when they are more than 1000 m offshore to avoid contamination by the coast in the backscatter.