dataesr/scientific-paragraphs-categorization huggingface dataset:
A) Heatmap representing global gene expression in eWAT adipocytes of WT and GPS2 AKO mice after 12 weeks of HFD (n = 3). Gene enrichment analyses of the top-upregulated pathways enriched in the datasets. (B) Heatmap representing the ''remodeling'' genes upregulated in eWAT adipocytes of the GPS2 AKO compared with WT mice after 12 weeks of HFD (n = 3). RT-qPCR analysis of Col1a1 and Col3a1 in isolated adipocytes and eWAT from WT and GPS2 AKO mice after 4 and 12 weeks of HFD (4 weeks HFD, n = 12; 12 weeks HFD, n = 13). (C) Representative picrosirius red staining images and collagen quantification in eWAT from WT and GPS2 AKO mice upon normal CD and after 1, 4, and 12 weeks of HFD (CD, n = 8; 1 week HFD, n = 7; 4 weeks HFD, n = 12; 12 weeks HFD, n = 13). Scale bars, 100 mm. (D) Network analyses of biological processes deregulated in eWAT adipocytes of GPS2 AKO mice after 12 weeks of HFD.
ACKNOWLEDGMENTS We acknowledge  Ozgene Pty Ltd. for generating floxed GPS2 mice. E. T. was supported by grants from the  Swedish Research Council , the  Swedish Cancer Society , the  Swedish Diabetes Foundation , the  Novo Nordisk Foundation , the  European Union   FP7 Marie Curie ITN NR-NET , and the  Center for Innovative Medicine (CIMED)  at the  Karolinska Institutet. N. V. was supported by grants from the  French National Agency of Research (CONRAD and PROVIDE) ,  Region Ile de France (CORDDIM) ,  Paris city (EMERGENCE) , the  French Foundation for Diabetes (SFD) , and the  European Union   H2020  framework ( ERC-EpiFAT 725790 ). The clamp studies in humans were performed at the  Clinical Investigation Center (Groupe Hospitalier Saint-Louis/Lariboisie  `re, Paris) and were supported by  Assistance Publique des Hôpitaux de Paris (APHP ;  PHRC AOR09087 ; J.
( A) Heatmap representing global gene expression in eWAT adipocytes of WT and GPS2 AKO mice after 12 weeks of HFD (n = 3). Gene enrichment analyses of the top-upregulated pathways enriched in the datasets. (B) Heatmap representing the ''remodeling'' genes upregulated in eWAT adipocytes of the GPS2 AKO compared with WT mice after 12 weeks of HFD (n = 3). RT-qPCR analysis of Col1a1 and Col3a1 in isolated adipocytes and eWAT from WT and GPS2 AKO mice after 4 and 12 weeks of HFD (4 weeks HFD, n = 12; 12 weeks HFD, n = 13). (C) Representative picrosirius red staining images and collagen quantification in eWAT from WT and GPS2 AKO mice upon normal CD and after 1, 4, and 12 weeks of HFD (CD, n = 8; 1 week HFD, n = 7; 4 weeks HFD, n = 12; 12 weeks HFD, n = 13). Scale bars, 100 mm. (D) Network analyses of biological processes deregulated in eWAT adipocytes of GPS2 AKO mice after 12 weeks of HFD.
). Several particular trajectories are also shown. dead zones or to improve pond designs especially for lowering agitation costs  [33, 34]. However its impact on light access and biomass productivity still remains open to study. Often, models are built using commercial software such as Fluent ® which offers automated schemes for three-dimensional resolution of the Navier-Stokes equations. Given the numerical difficulties and the computational cost to approximate the Navier-Stokes solutions with standard finite volume approach, especially in the presence of a free surface, we use a recent approach based on a more efficient discretization of the Navier-Stokes equations  [35, 36]. This multilayer model applies Galerkin-type approximations along the vertical axis of the Navier-Stokes system yielding a set of partial differential equations with hyperbolic features.
EXPERIMENTAL MODEL AND SUBJECT DETAILS All experimental procedures were approved by the ethics committee of Radboud University Nijmegen (Nijmegen, The Netherlands). Data from two adult male macaque monkeys (macaca mulatta) were collected for this study. Parts of the data have been used in other publications  (Bastos et al. , 2015a; Bastos et al. , 2015b; Bosman et al. , 2012; Brunet et al. , 2015; Brunet et al. , 2014a; Brunet et al. , 2014b; Hindriks et al. , 2018; Lewis et al. , 2016a; Lewis et al. , 2016b; Pinotsis et al. , 2014; Richter et al. , 2015 Richter et al. , , 2017;; Rubehn et al. , 2009; Spyropoulos et al. , 2018; Vinck et al. , 2015).
All analyses performed in this study were done on the sites that showed highest (top 1/3) visually induced gamma-band activity within areas V1 and V4 (Figure  2A, B ), resulting in a subset of 26 recording sites from area V1 (monkey K: 10; monkey P: 16), and 11 from area V4 (monkey K: 6; monkey P: 5). All signal processing was conducted in MATLAB (MathWorks, USA) using the FieldTrip toolbox (http://www. fieldtriptoolbox. org/) (Oostenveld et al. , 2011). Line noise was removed by subtracting the 50, 100, and 150 Hz components estimated through a discrete Fourier transform. Trial epochs for each site were demeaned by subtracting the mean over all time points in the epoch. Epochs with any site having a variance of greater than 5 times the variance based on all data from that same site in the same session were rejected.
In addition, epochs were manually inspected, and epochs with artifacts were rejected. Subsequently, per recording site, the signals from all remaining epochs of a given session were divided by the standard deviation of the signal across all those remaining epochs, and the resulting ztransformed signals were combined across sessions. Stimuli and Task. -Stimuli were presented on a CRT monitor (120 Hz non-interlaced) in a dimly lit booth and controlled by CORTEX software (https://www. nimh. nih. gov/labs-atnimh/research-areas/clinics-and-labs/ln/shn/software-proiects. shtml). The paradigm is illustrated in Figure  1. Upon touching a bar, a fixation point was presented, and the monkey's gaze was required to remain inside the fixation window throughout the trial (monkey K: 0. 85 deg radius, monkey P: 1 deg radius).
QUANTIFICATION AND STATISTICAL ANALYSIS All statistical tests were based on the combined data from both animals, constituting a fixedeffect analysis that results in inferences limited to the investigated sample of two animals. To lend equal weight to each animal, data were first combined within each animal (across sites, site pairs, trials) and subsequently averaged over the two animals. All significance thresholds were computed using non-parametric permutation statistics  (Maris and Oostenveld, 2007). For the median split analysis, the observed PPC spectra were derived by 1) calculating PPC spectra across all epochs of a given condition in a given animal, separately for all V1-V4 site pairs, 2) averaging PPC spectra across those site pairs, and 3) averaging across the two animals after aligning the peaks of the respective frequency bands.
ACKNOWLEDGEMENTS We thank  Craig Richter  for preprocessing the data,  Julien Vezoli  for help with assigning electrodes and sites to brain areas, and  Martin Vinck  for helpful advice on data analysis. PF acknowledges grant support by  DFG  ( SPP 1665 ,  FOR 1847 ,  FR2557/5-1-CORNET ,  FR2557/6-1-NeuroTMR ),  EU  ( HEALTH-F2-2008-200728-BrainSynch ,  FP7-604102-HBP ,  FP7-600730-Magnetrodes ), a  European Young Investigator Award ,  NIH  ( 1U54MH091657-WU-Minn-Consortium-HCP ), and  LOEWE (NeFF).
The Meso-NH software Meso-NH is maintained by computer and research scientists from LA and CNRM. The code is written in Fortran 90. Running scripts are in shell and use makefiles. Much of the Meso-NH model has been parallel since 1999  (Jabouille et al. , 1999). The domain decomposition is 2D, i. e. , the physical domain is split into horizontal subdomains in the x and y directions, and the communication between multiple processes is achieved via the Message Passing Interface (MPI). In 2011, it was necessary to extend the model parallel capabilities to new computers, e. g. , the first PRACE (Partnership for Advanced Computing in Europe) petaflop computer, on issues concerning the I/O and the pressure solver. As a result, a sustained performance of 4 TFLOPS (tera floating-point operations per second) was obtained using a grid with 500 million points  (Pantillon et al.
, 2011). Meso-NH can adapt to most machine architectures from Linux PCs or clusters to Macs or supercomputers with an excellent scalability. Figure  1  shows the results obtained on MIRA, a Blue Gene/Q system at Argonne National Laboratory and HERMIT, a Cray XE6 at HLRS, the High Performance Computing Center Stuttgart. The sustained TFLOPS gradually increases with the number of threads while remaining close to the optimal speedup. When using four OpenMP tasks instead of one, a speedup of more than 30 % can even be obtained. This results in a sustained performance of 60 TFLOPS using two billion threads. The required libraries to run Meso-NH are NetCDF because the output files are in nc4 format, MPI and the GRIdded Binary (GRIB) Application Programming Interface (API) to use the European Centre for Medium-Range Weather Forecasts (ECMWF) datasets.
, 2007; Barth et al. , 2007a). Pinty et al. (2013)  realistically simulated the electrical aspects of a heavy precipitation event over the Cevennes area in the South of France in the HyMeX experiment. More recently, a few cases have been under investigation over Corsica taking advantage of the lightning-observing network SAETTA. This network, made up of 12 Lightning Mapping Array (LMA) stations, has been deployed in Corsica to monitor the 3D lightning activity within a range of approximately 350 km from the center of Corsica. The SAETTA dataset can therefore be used to assess in details the functioning of CELLS for multiple events. As an example, Meso-NH was able to reproduce the electrical properties of a local convective development in the afternoon of 25 July 2014 over northern Corsica.
Field campaign evaluations Measurements of atmospheric fields from intensive campaigns at specific locations of interest and for limited time periods are an important source of data used to evaluate Meso-NH. Of the more recent campaigns, the modeling of clouds and convection has been extensively evaluated during the African Monsoon Multidisciplinary Analysis (AMMA) (e. g. ,  Arnault and Roux, 2010; Couvreux et al. , 2012) , the Convective and Orographically induced Precipitation Study (COPS)  (Richard et al. , 2011) , CHUVA  (Machado et al. , 2014) , and HyMeX (e. g. ,  Defer et al. , 2015; Bouin et al. , 2017). Stable boundary layer schemes have benefited from SABLES98  (Cuxart et al. , 2000b). Numerous campaigns dedicated to air quality, such as ESCOMPTE  (Drobinski et al. , 2007) , EUCAARI  (Aouizerats et al.
Other systematic evaluations As described earlier, since 2008, Meso-NH physics has been used in the operational model AROME and has benefited from systematic evaluations based on the French operational observation network and the forecasters assessment. The performance of Meso-NH has also been evaluated on sites offering long-term statistics, such as the optical turbulence applied to ground-based astronomy for a statistically rich sample of nights above the European Southern Observatory (ESO) sites  (Lascaux et al. , 2013; Masciadri et al. , 2013 Masciadri et al. , , 2017)) , Arizona  (Turchi et al. , 2017) , and Antarctica  (Lascaux et al. , 2010 (Lascaux et al. , , 2011)). Another important aspect is that new versions and bug fixes of the code are systematically validated with a series of test cases including numerous diagnostics covering a wide range of settings, from idealized scenarios including linear mountain waves (compared to the analytic solution), a density current test case, convective supercells with chemistry and electricity, 1D simulations, and LES intercomparison cases of cumulus, stratocumulus, and fog to real cases of heavy precipitating events, dust outbreaks, and tropical cyclones.
(2008)  for the ice cloud effective radius and that of  Yang et al. (2013)  for the scattering properties should be implemented. Regarding aerosols and radiatively active gases, efforts should be made to provide realistic 3D initial and boundary conditions and to improve the prognostic schemes. This will be done within the microphysics scheme LIMA, using analyses from CAMS or MOCAGE. In addition to these structural upgrades, a photovoltaic (PV) module will be implemented to respond to the solar industry's need for improved PV production forecasts. LESs could benefit from a better representation of turbulence during stable conditions. Another issue is the introduction of anisotropy in convective clouds or around steep gradients. Parameterizing the turbulence at the cloud-clear air interface is also a difficult and promising challenge that will be dealt with by Meso-NH, depending on the relative magnitudes of the mixing and the phase change time scales and impacting the particle size distributions.
Code and data availability Since version 5. 1 was released in 2014, Meso-NH has been freely available under the CeCILL-C license agreement. CeCILL is a free software license, explicitly compatible with GNU GPL. The CeCILL-C license agreement grants users the right to modify and re-use the covered software. The Meso-NH software and its documentation can be downloaded at http://mesonh. aero. obsmip. fr.
Model Dev. Discussion started: 8 January 2018 c Author(s) 2018. CC BY 4. 0 License. second-generation. Global databases at 300 m (land cover, plants functional types, urban local climate zones (Stewart and Oke, 2012) , vegetation parameters as leaf area index) and 1 km resolution (soil composition, lake depths,. ) are available on the Meso-NH website. All parameters can also be prescribed separately by the user, as can the surface fluxes in an idealized configuration.
using a time splitting technique to compute the sedimentation fluxes. Emissions for the model domain are complied from a prescribed emissions database or can be parameterized. The surface model can process the raw prescribed emission data from any inventory of primary gases or aerosols. Emissions can include urban and industrial, biogenic, biomass burning, and volcanic sources from the most recent emissions databases. Desert dust emissions are parameterized following the Dust Entrainment and Deposition model (DEAD, Zender et al. , 2003)  based on the pioneering work of Marticorena and Bergametti (1995). The dust emission scheme was incorporated into Meso-NH-SURFEX by Grini et al. (2006)  and modified by Mokhtari et al. (2012)  to better account for the size distribution of erodible material.
Methods The measurements inside the rainforest at site T0t were performed over 3 years from September 2011 to January 2014. The second measurement site (T3) was part of the Green Ocean Amazon (GoAmazon2014/5) experiment  (Martin et al. , 2016). The GoAmazon2014/5 experiment operated from 1 January 2014 to 31 December 2015. The experiment included two intensive operation periods (IOP1 and IOP2). IOP1 extended from 1 February 2014 to 31 March 2014 and IOP2 from 15 August 2014 to 15 October 2014  (Martin et al. , 2016). The ion spectrometer measurements were conducted from 28 January to 13 October 2014. Figure  1  shows the locations of both measurement sites. Table  1  shows an overview of the available dataset presented in this study.
Open pasture measurement site The open pasture site, T3, is influenced by the Manaus pollution plume typically once per day or every second day, especially in the afternoon  (Martin et al. , 2010b, Supplement; Thalmann et al. , 2017; de Sá et al. , 2017). A mobile facility from the Atmospheric Radiation Measurement (ARM) Program  (Mather and Voyles, 2013)  of the United States Department of Energy was deployed at the T3 site close to Manacapuru, about 70 km downwind of the city of Manaus (3. 2133 • S, 60. 5987 • W), and included an ARM Mobile Aerosol Observing System (MAOS). The site also hosted numerous instrument systems from other GoAmazon2014/5 participants  (Martin et al. , 2016).
For the measurements reported here, a similar setup with a 60 m sampling line was used. The DMPS data should be used in a qualitative rather than quantitative manner as the losses due to diffusion in the sampling line are not precisely known and therefore not considered. In addition to the ion spectrometer measurements, the measurement hut hosted an automated weather system (Vaisala; WXT-520) for acquiring meteorological parameters. The auxiliary data from the T3 site presented in this paper include measurements from an ultrafine CPC (TSI Inc; 3010), with a 50 % activation diameter of 10 nm and an SMPS with a lower cutoff of 20 nm. The meteorological data were also retrieved from an automated weather station (Vaisala; WXT-520). Those datasets are available at the ARM data browser.
This increased level in the positive polarity of the natural ions continued when the NAIS was redeployed at the T3 site. The cause was the same (too-low current in the sheath air filters). We consider the positive polarity of the natural charged ions in the NAIS at the T3 site unreliable; therefore, the data regarding the absolute concentrations using the positive channel for the T3 site are not shown in this study. Additionally, the ion data from 9-26 September 2014 at the T3 site were considered unreliable and also excluded from our analysis. Rain-induced ion events were selected as the times when an ion burst coincided with the onset of precipitation. The median and the maximum (99th percentile) ion concentrations were calculated during periods when the rain intensity was > 0 mm h -1. In the case of more than one rain event per day, two separate rain events were classified as such if the start of the second one occurred more than 1 h after the end of the first one.
Any fluctuations in the rain intensity for a time period shorter than 1 h were considered to be part of a single rain event. We classified 962 rain events at the T0t site and 221 rain events at the T3 site. The new particle formation event analysis from the ion spectrometer data, including the event classification and formation and growth rate calculations, followed the already well-defined guidelines  (Kulmala et al. , 2012). In the data analysis, the first step was to classify all available days into NPF event and nonevent days according to methods introduced earlier by  Hirsikko et al. (2007)  and  Manninen et al. (2010). The days that do not fulfill the criteria of an event or nonevent day are categorized as undefined days. However, no days were classified as undefined in this study. The classification was performed manually through a visual inspection of daily contour plots of particle size number distributions.
The second step in the analysis was to define the characteristics related to each NPF event, such as the particle growth rate (GR) and formation rate (J ). The GRs were calculated for two different size bins (2-3 and 3-7 nm in particle diameter) using both ion and neutral particle data from the NAIS. The particle growth rate was determined by find-ing the times at which the maximum concentrations of ions and/or particles in each of these size ranges occurred. A fit between the points was then applied to resolve the growth rates. The particle formation rate was determined for the lower end of each size bin (2 and 3 nm) by taking the particle growth rate, condensation sink, and coagulation sink into account.
This difference is most likely due to the enhanced biomass burning during the dry season. The average temperatures and the average relative humidity were very similar in both seasons. The PSM measurements were performed during the dry season only. In total, 38 days of PSM data were included in this study and the results are shown in Fig. 4. The PSM was used in scanning mode but, due to the challenging environmental conditions, only data measured at the highest supersaturation (total particle concentration at > 1. 5 nm) are shown. The PSM data showed a similar diel pattern as the cluster ion concentrations measured by the NAIS (see Fig. 9 ), with higher median concentrations observed during the early morning (03:00-06:00), a dip in concentrations during the early afternoon (12:00-15:00), and then elevated median concentrations again in the evening (18:00-24:00).
The rain events were also evident in the total particle concentration measured by the NAIS, as depicted in Fig. 8. In this example, the rain intensity peaks twice, about 40 mm h -1 at ∼ 09:00 followed by a second peak of 10 mm h -1 at ∼ 11:00. The ion and particle concentrations measured by the NAIS increased and decreased almost simultaneously with the increase and decrease in the precipitation rate. Additionally, the DMPS data showed an appearance of nucleationmode particles between 6 and 10 nm, also following the onset of the rain. Please note that the DMPS was sampling at a height of 60 m, which is well above the rainforest canopy. The concentration of 6-10 nm particles increased by a factor of 4 during the rain event compared to a background concentration of 5 cm -3 in the absence of precipitation.
Summary and conclusions We performed direct measurements of atmospheric new particle formation (NPF) events in the Amazon region with state-of-the-art aerosol instrumentation. The measurement campaigns were performed at two observation sites (T0t and T3) in the vicinity of Manaus in Brazil. One site was located within the rainforest (T0t), providing long-term (September 2011 to January 2014) measurement data to complement data from a pasture site (T3, January to October 2014). No NPF events were observed at the T0t site during the long-term measurement period. However, we observed raininduced ion and particle burst events (rain events) inside the rainforest during 264 of the 384 days. Concentrations of 2-4 and 4-12 nm ions and total particles were enhanced by up to 3 orders of magnitude during such rain events (∼ 10 4 -10 5 cm -3 ) at the T0t site.
, 2016). The back-trajectory calculations using HYSPLIT did not show any clear difference between the days with high and low growth rates. Nevertheless, there was a clear difference in air mass origin between the days with NPF events when Table  4. The growth rates (GR, nm h -1 ) and nucleation rates (J ; cm -3 s -1 ) determined from the NAIS ion and particle data for each nucleation event are presented. Both the GR values and the nucleation rates present median values for positive and negative ions. Also, the median values for the calculated condensation sink values (CS; s -1 ) for each event are shown. The condensation sink parameter is calculated from the SMPS size distributions. The last line of the table shows the median values for GR and J for all the nucleation event days, except the ion GR at 2-3 nm of 19.
3 compared to nonevent days. The condensation sink was also lower on the NPF event days (0. 0016 s -1 ) than on nonevent days (0. 003 s -1 ). There were no NPF events observed during the dry season, when it is likely that the condensation sink is too high for new particle formation. Data availability. The data sets for the T3 site used in this publication are available at the ARM Climate Research Facility database for the GoAmazon2014/5 experiment (https://www. arm. gov/research/campaigns/amf2014goamazon, last access: 11 June 2018). The data from the T0t site can be made available upon request from the corresponding author. Author contributions. DW analyzed the data, conducted the measurements, and wrote the paper. SBM analyzed the data and wrote the paper. HEM and VMK provided scientific guidance and wrote the paper.
Acknowledgements. We acknowledge the  Academy of Finland Centre of Excellence program  (grant no. 272041 ). We acknowledge the  Atmospheric Radiation Measurement (ARM) Climate Research Facility , a user facility of the  United States Department of Energy, Office of Science , sponsored by the  Office of Biological and Environmental Research , and support from the  Atmospheric System Research (ASR) program  of that office. Daniela Wimmer  wishes to acknowledge the  Austrian Science Fund (FWF ; grant no. J-3951 ). Paulo Artaxo  acknowledges  FAPESP  project  2013/05014-0  and  CNPq  for funding. We appreciate field support from  Alcides Ribeiro ,  Bruno Takeshi , and  Fabio Jorge. We acknowledge logistical support from the  LBA Central Office  at the  INPA -Instituto Nacional de Pesquisas da Amazonia.