dataesr/scientific-paragraphs-categorization huggingface dataset:
| Functional diversity and forest resilience As a second example of rcontroll application, we revisited the question: does functional diversity improve the tropical forest resilience to disturbance, which has been previously addressed in a virtual experiment using TROLL  (Schmitt et al. , 2020). We replicated a scaled-down version of this experiment to demonstrate how the rcontroll interface facilitates the implementation of a simulated experiment such as this one (Supplementary Information SI4 and SI5). For three levels of species richness (5, 10 and 20), we simulated 10 random assemblages of communities whose composition from the default TROLLv3_species dataset included in rcontroll (resulting in 30 simulations). This was done using the stack function. Simulations were initialised from bare ground and run for 600 years to reach a mature forest state.
, 2020). The rcontroll package reproduces the analyses of Schmitt et al. (  2020 ) with only about 80 lines of R code, increasing transparency and replicability (Supplementary Information SI4 and SI5; Figure  4 ). F I G U R E 3 Sensitivity of TROLL to parameters using Morris analysis. Twelve parameters of TROLL were tested, with abbreviations found in Table  1. The level of grey of the label indicates parameters related to the same processes (from dark grey to white, respectively: carbon allocation, crown allometry, leaf ecophysiology, mortality and reproduction). The x-axis represents the absolute mean of elementary effect μ*, and the y-axis represents the variance of elementary effect σ. A high μ* indicates a factor with a heavy overall influence on model outputs; a high σ indicates heterogeneity of the sensitivity across the parameter space, which could indicate nonlinearities or interactions with other parameters.
In the second, we showed how rcontroll facilitates the replication of a previously published analysis  (Schmitt et al. , 2020)  by simplifying the code while increasing transparency and reproducibility. The reproducibility of studies can be further increased by the use of other R packages, such as tidyverse  (Wickham et al. , 2019)  essential for processing simulation results, analyses and graphs. rcontroll can be used to address a wide range of topical fundamental and applied ecological questions by means of modelling, such as the assessment of management scenarios  (Marechaux et al. , 2020). The rcontroll package is tightly linked to TROLL, so a specific discussion of the latter is in order here. As with any model, TROLL is built upon assumptions and care should be taken to interpret its results carefully.
rcontroll provides user-friendly functions for setting up and analysing TROLL simulations. Users specify floristic community composition, ecological parameters and climatic conditions, and default values are available where possible. rcontroll provides default data for demonstration runs, a climate data generator from a global dataset, visualisation tools as well as a generator of virtual LIDAR point clouds. Here, we demonstrate the flexibility of rcontroll by testing the sensitivity of TROLL parameters and replicating analyses from a previously published study using reproducible code examples.
cal TROLL simulation: (i) climate data, (ii) plant functional traits and (iii) global model parameters. Presimulation functions include global parameters definition (generate_parameters function) and climate data generation (generate_climate function). rcontroll also includes default data for species and climate inputs for a typical French Guiana rainforest site. The purpose of the generate_climate function with the help of the corresponding vignette is to create TROLL climate inputs from ERA5-Land (Muñoz-Sabater et al. , 2021), a global climatic reanalysis dataset that is freely available (see Supplementary Information SI1). The ERA5-Land climate reanalysis is available at 9 km spatial resolution and hourly temporal resolution since 1950, and daily or monthly means are available.
The rcontroll package is free and open source (version 0. 1. 0 with GPL3). It is available on the CRAN repository https://cran. r-proje ct. org/web/packa ges/rcont roll/index. html and can be installed in the R environment using the install. packages ('rcontroll') command. The project is hosted on GitHub (https://github. com/sylva insch mitt/rcont roll), which allows future users to openly contribute to the project. AUTH O R CO NTR I B UTI O N S Sylvain Schmitt and Guillaume Salzet conceived the ideas; Sylvain Schmitt led the package development; Sylvain Schmitt and Guillaume Salzet designed the examples and analysed model outputs; and Sylvain Schmitt led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication. ACK N O WLE D G E M ENTS This work was supported by the 'Amazonian Landscapes in Transition' project and by the 'Investissement d'Avenir' grants (CEBA, ref.
Ethical Considerations The study has been validated by national ethics committees (unique protocol ID number 2021-A03196-35; favorable opinion of the South Mediterranean Committee for the Protection of Persons I 03/02/2022) and the French Data Protection Agency. The study is registered on ClinicalTrials. gov (NCT05246774). The survey complies with the tenets of the Declaration of Helsinki. All patients will be informed that the data collected may be used for research purposes, and will be asked to provide their written consent.
Statistical Analysis As this is a pilot exploratory study, the sample size was not based on a statistical argument. As the variability and evolution of biomarkers over time and the history of the disease are not known, and in order to explore the links between biomarkers and the occurrence of radiation cystitis, based on the hypothesis that half of the patients initially included will develop cystitis, a sample size of 60 individuals-including 30 individuals with cystitis and 30 individuals without cystitis-seems acceptable. Statistical analysis will be carried out using SAS (version 9. 4; SAS Institute Inc) and R (The R Foundation)  [31]. Basic statistics will be used for continuous variables n, missing n (if applicable), mean, type of deviation, median, first and third quartiles, and minimum and maximum values, and for categorical variables, we will use frequency and percentage values.
Results and Evaluation We implemented our method in PyTorch and used a single NVidia A6000 GPU for training and motion synthesis. We will release all our code and data, which will be available at: URL will be updated upon acceptance. We built our implementation on top of on the TensoRF codebase and we use the original hyper-parameters for the static NeRF part: Adam Optimizer with an initial learning rate of 0. 02, training on 4096-pixel rays at each step, and using a small MLP with two fully-connected layers (with 128-channels) and ReLU activation for the view dependency. We jointly train TensoRF and the displacement of the particles, therefore we need significantly more iterations than what TensoRF uses for a static scene (120k iterations in our case, for approximately 5 hours). We found that the training time descreased if we delay the upsampling of the tensor grid so that the training spends more iterations on lower resolution radiance fields.
Ancillary imaging The HST WFC3/F105W calibrated image of GN20 was retrieved from the Mikulski Archive for Space Telescopes (PI: Faber, ID: 12442). This image was taken with an integration time of ∼2800 s, drizzled to a pixel scale of ∼0. 09 and with a resolution FWHM ∼ 0. 24. Archival Plateau de Bure Interferometer (PdBI) tuned to 340 GHz (i. e. , 880 µm), and Very Large Array (VLA) imaging of the CO(2-1) line with a final resolution of ∼0. 19  (Hodge et al. 2015)  is also included in the analysis. Details about these observations and their data processing can be found in  Carilli et al. (2011)  and  Hodge et al. (2012).
Star formation in GN20. The UV, near-IR, molecular gas and cold dust perspectives GN20 has been previously imaged with HST and radio interferometers at a similar angular resolution as the MIRI imaging. HST (rest-frame) 0. 2 µm imaging traces the unobscured, young star formation. VLA and PdBI imaging  (Hodge et al. 2012 (Hodge et al. , 2015) )  trace the cold molecular gas and dust emission, respectively (see Figs. 2  and 3 ). The stellar structure traced by the F560W/MIRI image combined with the ancillary data provide a unique picture of this DSFG with several new results:  (1)  there is a substantial offset of 0. 55 (i. e. , 3. 9 kpc) between the stellar nucleus and the UV-emitting regions. These UV-bright regions are located W-NW of the nucleus, in an arc-like structure in the outskirts of the galaxy; (2) the stellar nucleus perfectly coincides with the position of the far-infrared continuum emission peak; (5) the clumpy molecular gas is embedded in the stellar envelope and is similar in size; and (6) the stellar clumps (traced by the residuals in the two-component light decomposition, (see Sect.
Summary This Letter presents the first mid-infrared sub-arcsec imaging at 5. 6 µm of the dusty star-forming galaxy GN20 at a redshift of 4. 05, taken with MIRI/JWST. The image resolves for the first time the stellar structure by tracing the rest-frame 1. 1 µm light on scales of 1. 5 kpc. The new MIRI imaging is combined with existing multi-wavelength ancillary data tracing the rest-frame UV continuum and the cold molecular gas and dust with similar angular resolutions. This dataset yields a new picture of the stellar structure, its relation with the active star-forming regions (both obscured and unobscured) and its potential evolution. GN20 is a luminous galaxy (M 1. 1 µm, AB = -25. 01 uncorrected by internal extinction) with a stellar structure characterised by a luminous unresolved (<0. 8 kpc) nucleus and a diffuse extended envelope.
Acknowledgements. This Letter is dedicated to the memory of our colleague  Hans Ulrik Nørgaard-Nielsen ,  MIRI  European Danish coPI and co-lead of the European Consortium MIRI High-z team, R. I. P. Thanks to  Jackie Hodge  for providing detailed information about the positional accuracy of the VLA observations. J. A-M. , A. C-G. , L. C. , A. L. acknowledge support by grant  PIB2021-127718NB-100 , and P. G. P-G. by grant  PGC2018-093499-B-I00  funded by  MCIN/AEI/10. 13039/501100011033. A. A-H. is supported by grant  PID2021-124665NB-I00  from the  Spanish Ministry of Science and Innovation/State Agency of Research   MCIN/AEI/10. 13039/501100011033  and by "ERDF A way of making Europe". F. W. and B. L. acknowledge support from the  ERC Advanced  Grant  740246  (Cosmic_Gas), A. B. and G. Ö.
acknowledge support from the  Swedish National Space Administration (SNSA). O. I. acknowledges the funding of the  French Agence Nationale de la Recherche  for the project  iMAGE  (grant  ANR-22-CE31-0007 ), J. H. and D. L. were supported by a  VIL-LUM FONDEN Investigator grant  (project number  16599 ). K. I. C. acknowledges funding from the  Netherlands Research School for Astronomy (NOVA)  and the  Dutch Research Council (NWO)  through the award of the  Vici Grant   VI. C. 212. 036. J. P. P. and T. T acknowledge financial support from the  UK Science and Technology Facilities Council , and the  UK Space Agency. T. P. R. would like to acknowledge support from the  ERC  under advanced grant  743029  (EASY). The  Cosmic Dawn Center  (DAWN) is funded by the  Danish National Research Foundation  under grant No.
(2012)  because it represents a favorable compromise between various criteria: (1) it has few parameters; (2) it is relatively simple and thus keeps the entire framework complexity quite low; (3) it accounts for most neural phenomena (stochastic spiking, refractoriness, facilitation, latency and jitter); (4) it can be easily integrated with the other blocks of the chain; (5) it is reasonably fast to compute; (6) a MATLAB® implementation is available. This model takes the electrical current waveform received by the ANF as input and gives the timing of spikes (i. e. , a spike train) as the output. Goldwyn et al. (2012)  used a renewal point-process approach, and more specifically the framework of generalized linear models (GLMs). A point process considers spike timings as discrete events occurring over time.
Experimental data Amplitude-modulation detection. Chatterjee and Oberzut (2011) measured AM detection for ten adult CI users who were instructed to identify modulated from unmodulated pulse trains presented to a single electrode. Electrical pulses were biphasic, charge-balanced, and rectangular with a phase width of 40 μs and an inter-phase gap of 8 μs. Pulse trains had a rate of 20 0 0 pps (pulses per second), and were modulated in amplitude such that the n -th pulse had an amplitude of: A [ n ] = A 0 1 + m • cos 2 π f n 20 0 0 + π (3) where A 0 refers to the reference carrier amplitude, f refers to the modulation rate, and m to the modulation depth. An adaptive, three-alternative forced-choice (3AFC) method was used to measure AM detection thresholds by varying the value of m from trial to trial.
Simulations Auditory nerve spike trains were simulated by feeding the ENI stage of the model ( Fig. 1  ) with electrodograms generated as described by  Chatterjee and Oberzut (2011)  or  Brochier et al. (2018)  with a sampling rate of 1 MHz with a custom MATLAB® (v 9. 10, R2021a) program. Each experimental condition was simulated while varying the modulation depth ( m ) of the input envelope: 32 values approximately logarithmically spaced from 0. 0 0 01 to 1. 0 ( -80 to 0 dB) in the case of the Chatterjee and Oberzut (2011) study, and 28 values from 0. 001 to 1. 0 ( -60 to 0 dB) for the study of  Brochier et al. (2018). Because of the stochastic nature of the firing process in the ANF model, spike trains were likely different for different presentations of a given stimulus. Therefore, each simulation was repeated 50 times to account for this variability.
Effect of current spread Current spread was investigated here by considering a onedimensional exponential decay as a transfer function between the current delivered by the electrodes and that received by the fibers. Simulations were restricted to a fixed stimulus level and two values of current spread: 1 mm and 5 mm. The value of 1 mm was selected because it approximately reflects the spread of monopolar stimulation in Ringer's solution  ( Jolly et al. , 1996 ; Kral et al. , 1998 ) , while 5 mm was arbitrarily chosen as an extreme case of current spread. When simulating the data of  Chatterjee and Oberzut (2011)  and  Brochier et al. (2018)  , increasing current spread from 1 to 5 mm resulted in better (smaller) modulation detection thresholds. According to this prediction, more current spread would lead to better modulation sensitivity.
Acknowledgments We thank  Monita Chatterjee  for sharing experimental data and for interesting comments on this work. We thank  Attila Fráter  for constructive discussions. We also thank two anonymous reviewers for excellent suggestions. Work supported by  Oticon Medical , the  William-Demant Foundation ,  Junta de Castilla y León  (Grant  SA252P20 ), the  Spanish Ministry of Science and Innovation  (Grant  PID2019-108985GB-I00 ), and the  European Regional Development Fund.
RNA isolation, Real-Time Quantitative PCR (RT-qPCR) and analysis of transcriptomic data RNA was extracted from tissues using TRIzol ® (Invitrogen, Carlsbad, CA, USA), according to manufacturer's instructions. cDNA synthesis was performed using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems ® , Foster City, CA, USA), according to manufacturer's instructions. Target genes transcript levels were quantified by RT-qPCR. Expression levels were evaluated using either 4. 5µL of diluted cDNA, 5µL of TaqMan ® Universal PCR Master Mix No AmpErase ® UNG (Applied Biosystems ® ) and 0. 5 µL of specific TaqMan ® Gene Expression Assay (HPRT1 -Ref. ID Hs01003267_m1, VIM -Ref. ID Hs00185584_m1), or using Xpert Fast SYBER Mastermix Blue (GRiSP Research Solutions, Porto, Portugal) with specific primers for each target and reference genes, as described in Table  S2.
Each sample was run in triplicate under the following RT-qPCR conditions: 2 minutes at 50ºC, followed by enzyme activation for 10 minutes at 95ºC, and 45 cycles which included a denaturation stage at 95ºC for 15 seconds and an extending stage at 60ºC for 60 seconds. HPRT was used as reference gene for normalization. Relative expression of target genes tested in each sample was determined as: [Gene Expression Level = (Gene Mean Quantity / Reference Gene Mean Quantity) x 1000]. For the CIT cohort, VIM, CDH1, CDH2 and CDH3 expression levels were extracted from available transcriptomic Affymetrix U133Plus2. 0 data  [40, 41]. An EMT score for each tumor was also determined using these data and a previously published signature, combining 206 epithelial genes and 132 mesenchymal genes  [44]. EMT scores were calculated by subtracting the mean log2 normalized expression of the epithelial genes from that of the mesenchymal genes in each sample.
Membranes were blocked with 5% bovine serum albumin (BSA) in TBS/0. 1% Tween (TBS/T pH=7. 6) for 2h at RT. After incubation with VIM primary antibody (NCL-L-VIM-V9, Leica), membranes were washed in TBS/T and incubated with secondary antibody coupled with horseradish peroxidase, for 1h at RT. Binding was visualized by chemiluminescence (Clarity WB ECL substrate, Bio-Rad) and quantification was performed using band densitometry analysis from the ImageJ software (version 1. 6. 1, National Institutes of Health). β-Actin (A1978, Sigma-Aldrich) was used as loading control.
Immunofluorescence (IF) and Morphometric analysis SVHUC1, UMUC3 KD and UMUC3 CTRL cell lines were seeded on cover slips at 20,000 cells/well, overnight. Briefly, cells were fixed in methanol during 10min and then blocked with 5% bovine serum albumin (BSA) during 30min. After overnight VIM (1:150, #3195, Cell Signaling Technology) incubation at room temperature, cells were incubated with secondary antibody anti-rabbit IgG-TRITC (1:500, T6778, Sigma-Aldrich) during 1h at RT. Finally, after washing in 1X PBS, cells were stained with 4',6-diamidino-2-phenylindole (DAPI) (AR1176, BOSTER Biological Technologies) in mounting medium. Pictures were taken in a fluorescence microscope Olympus IX51 with a digital camera Olympus XM10 using CellSens software (Olympus Corporation, Shinjuku, Japan). Cell morphometric parameters -roundness and aspect ratio (cell length/ cell width) -were calculated for UMUC3 KD and UMUC3 CTRL cells using the ImageJ software, in three independent experiments.
Chorioallantoic membrane (CAM) Assay Fresh fertilized eggs (PintoBar, Lda, Portugal) were incubated at 37 °C in a humidified environment. After 6 days of embryonic development, a window was opened into the eggshell under aseptic conditions. On day 10, UMUC3 KD or UMUC3 CTRL cells suspensions in growth factor-reduced Matrigel (BD Biosciences) were seeded on CAM. On day 17, microtumor images were obtained, and tumors were dissected, formalin fixed and included in paraffin. Relative perimeter in ovo was assessed using CellSens software (version V0116, Olympus). Ex ovo microphotographs were obtained for blood vessels counting, using Image J software.
Statistical analysis All statistical analyses were performed using IBM ® SPSS ® Statistic software version 23 (IBM-SPSS Inc. , Chicago, IL, USA) and graphs were built using GraphPad Prim 7. 0 (GraphPad Software Inc. , La Jolla, CA, USA). Significance level was set at p<0. 05, and Bonferroni's correction was used when appropriate. Mann-Whitney U test (MW) was used to test for differences in VIM expression or methylation levels between NB and BlCa, pathological stages of cases divided into Ta-1 (non-muscle invasive BlCa, NMIBC) and T2-4 (muscle invasive BlCa, MIBC), and patients' gender, and to assess differences in UMUC3 KD and UMUC3 CTRL conditions. Kruskall-Wallis test (KW) was performed to test for differences among more than two groups of samples then followed by MW test when appropriate.
Funding This work is part of the project "P. CCC. :  Centro Compreensivo de Cancro do Porto" -NORTE -01-0145-FEDER-072678 , supported by  Norte Portugal Regional Operational Programme  ( NORTE 2020 ), under the  PORTUGAL 2020 Partnership Agreement , through the  European Regional Development Fund (ERDF). This research was funded by  Research Center of Portuguese Institute of Porto  ( CI-IPOP-27-2016  and  CI-IPOP-74-2016 ).
6  Although no worldwide estimate of emulsifier use in the food industry exists, a recent descriptive study of the NutriNet-Santé prospective cohort study revealed that seven of the 10 most consumed food additives among French adults were classified as emulsifiers (total modified starches, lecithins, xanthan gum, pectins, monoglycerides and diglycerides of fatty acids, carrageenan, and guar gum), and modified starches were consumed by more than 90% of the participants. 7  Additionally, more than 53. 8% of food or beverage industrial products contain at least one food emulsifier  5  as estimated from Open Food Facts, 8 a database that contains information and data on food products from around the world. Despite their evaluation of safety and acceptable daily intakes provided by the European Food Safety Authority, recent experimental studies suggested potential deleterious effects of food additive emulsifiers on the gut microbiota and gut inflammation.
study population This study was based on the prospective NutriNet-Santé e-cohort, launched in May 2009, with an open ongoing enrolment of volunteers and the main objective of investigating the associations between nutrition and health. 18  Participants are recruited from the general population of French adults (>18 years) through multimedia campaigns. To enrol, participants are required to create a personal account on the NutriNet-Santé web-based platform (https://etudenutrinet-sante. fr/). Upon enrolment, participants are invited to complete five questionnaires about their dietary intakes, health (eg, personal and family history of disease, prescribed drugs), anthropometric data (eg, height, weight),  19 20  physical activity (validated seven day assessment through the International Physical Activity Questionnaire),  21  lifestyle and sociodemographic data (eg, date of birth, sex, education level, professional occupation, smoking status, number of children).
Dietary data collection Usual dietary intakes were assessed at inclusion and then every six months, using repeated sets of three non-consecutive web-based 24 hour dietary records, randomly assigned over a two week period (two weekdays and one weekend day). The NutriNet-Santé web-based self-administered 24 hour dietary records have shown good performances when tested against an interview with a trained dietitian  23  and against blood and urinary biomarkers (showing appropriate estimates of true intakes of fruit, vegetables, fish, β carotene, vitamin C, omega 3 fatty acids, proteins, and potassium). 24 25  In this analysis, we calculated the usual baseline dietary intakes as the average of all 24 hour dietary records completed during the first two years of each participant's follow-up, with a mandatory requirement of having at least completed three valid days of 24 hour dietary records during this period to be included in the analysis.
At all times throughout their assigned dietary record period, participants had access to a dedicated interface of the study website to report all foods and beverages consumed during a 24 hour period: three main meals (breakfast, lunch, dinner) and any other eating occasion. The dietary assessments included details of commercial names and brands of industrial products, to determine individual additive intake. Participants were asked to estimate portion sizes either by entering the weight or volume of food consumed directly in the platform, or by using validated photographs or usual containers. 26  A French food composition database (>3500 items)  27  was used to estimate mean daily intakes of energy, alcohol, macronutrients, and micronutrients. These estimates included contributions from composite dishes using French recipes validated by food and nutrition professionals.