dataesr/scientific-paragraphs-categorization huggingface dataset:
Therefore, the merging of both models into the CASTANEA-MAESPA model aimed to offer a relevant and extensive ecophysiological model for C and water cycles in eucalypt plantations, prior to the implementation of the K processes as described below. The modules of CASTANEA simulating light interception, water interception, carbon allocation and the growth of organs, and organ respiration were coupled with the modules of MAESPA simulating soil water dynamics, leaf photosynthesis, transpiration, and plant hydraulics (Fig. S1 ). More precisely, the coupled version includes the following points: 1. CASTANEA computes the diffuse and direct incoming radiation reaching sun and shade leaves of a canopy layer (25 canopy layers of varying surface). 2. This radiation is used in MAESPA to compute leafscale carbon and water processes (half-hourly time step), based on what is done usually at voxel scale in MAESPA.
f p was the flattening factor, meaning that if f p = 0, then leaf production was linearly related to height increase, and as f p increased, N tended towards a constant function. κ (n leaves m -2 ground m -1 height ) is a conversion factor from height increment to number of new leaves. The parameters used here were fitted using experimental data from the fully fertilised stand. The calibration was a systematic exploration of parameter space using multiple normalised RMSE (addition of the normalised RMSE for multiple variables; see Eq. S1) as a goodness-of-fit indicator. The data used for calibration were destructive leaf biomasses (eight trees and upscaling using a stand inventory at a yearly time step over the rotation), leaf area (same as leaf biomass), and leaf fall (12 L traps at a monthly time step over the rotation) measurements.
Leaf water content In non-limited nutrient conditions, leaf cell expansion in area was associated with a leaf water inflow in order to maintain an optimum leaf turgor. This water inflow was computed as W xylem→leaf = × S t , (5) where W xylem→leaf (mL d -1 ) was the water inflow into the expanding leaf (this was "structural" water associated to the creation of new tissues, not to be confounded with the water used for leaf transpiration), S the leaf area of the cohort (mm 2 ), computed in Eq. (  2 ), and (mL mm -2 ) was the surfacic water content, i. e. the amount of leaf water per leaf area at full turgor. was assumed to be a constant. Experimental data have shown that at the end of leaf area expansion, when the leaf has reached its maximum area, there was some water outflow, defined hereafter as water expulsion.
Branch and root sapwood volume were deduced from their biomass, considering that branches and root biomass are entirely composed of sapwood. Their volume were computed using the density of eucalypt sapwood. The lumen volume of the xylem (i. e. the xylem sap volume) was considered to be 13. 6 % of total xylem volume as reported in general for angiosperms  (Zanne et al. , 2010) , since no eucalypt-specific data were available. Following  Hölttä et al. (2013) , and considering the relatively similar lumen proportion between both xylem and phloem  (Nobel, 2005) , phloem sap volume was considered to be 2 % of the total xylem sap volume. Uptake of K from the soil by the trees was a function of demand by growing organs, remobilisation of K from senescent organs, and soil supply. The amount of K available for uptake was computed in Eq.
We focused on the modelling of the carbon-source activity on canopy processes and fluxes, starting with the demography of leaves and the impact of K availability on their functioning. In particular, we first considered the impacts of K on leaf development, photosynthetic capacity, and senescence. We included processes that we identified as central  (Cornut et al. , 2021)  regarding the K limitation of GPP in these plantations. While adding processes to a mechanistic model is pertinent from a realism perspective, one must consider if the implementation of new processes increases or decreases the predictive power of the model in a given context  (Famiglietti et al. , 2021). Here, the model additions were clearly necessary, since the CASTANEA model, into which we developed the K modules, was initially incapable of reproducing the effect of K limitation on GPP, and no mechanistic model of the effect of K on plant productivity at the stand level existed.
This development also broadly followed several of the guidelines posited by  Famiglietti et al. (2021)  in their paper addressing the question of models' structural complexity. These points are as follows: (1) we used datasets (here multiple experiments over multiple rotations) to constrain model parameters, (2) the new developments led to increased forecast ability (since no forecast of K deficiency was previously possible), and (3) we sought to calibrate unmeasured parameters. We adopted a reductionist approach, typical of the development of mechanistic model, by formulating and parameterising the model on dedicated experiments conducted at the organ scale. Only a few parameters were calibrated on carbon and water fluxes measured at the ecosystem scale. It is noticeable that the model was calibrated in a fully fertilised stand and then allowed to run in a virtual K omission stand with, as the only difference, a reduced amount of K fertiliser brought the first months after planting.
Disclaimer. Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Special issue statement. This article is part of the special issue "Ecosystem experiments as a window to future carbon, water, and nutrient cycling in terrestrial ecosystems". It is not associated with a conference. Acknowledgements. Ivan Cornut was funded by the ANR under the "Investissements d'avenir" programme and by the Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD). The data acquired on Eucalyptus stands at Itatinga station, Brazil, and partly re-analysed here, were funded by Universidade de São Paulo, CIRAD, Agence Nationale de la Recherche, the Agropolis Foundation, and from the support of the Brazilian state (Programa de Cooperacão internacional capes/-Fundacão AGROPOLIS 017/2013).
We are grateful to the staff at the Itatinga Experimental Station, in particular, Rildo Moreira e Moreira (ESALQ, USP) and Eder Araujo da Silva, for their technical support. The EUCFLUX 1 project was a cooperative programme with the participation of Arcelor Mittal, Cenibra, Bahia Specialty Cellulose, Duratex, Fibria, International Paper, Klabin, Suzano, and Vallourec Florestal, coordinated by the Forestry Science and Research Institute -IPEF (https://www. ipef. br/, last access: 16 March 2023). The data acquired on the response of photosynthesis to leaf K were funded and conducted by Suzano. We thank Daniel Goll and one anonymous reviewer for their very meticulous evaluation of the paper and relevant remarks that helped greatly in improving the article. Financial support. This research has been supported by the Agence Nationale de la Recherche (grant nos.
Analysis and numerical computations confirm the role played by intensity and frictions as key factors for sustainability by contrast with real gdp growth-as well as the interplay between resource scarcity, income inequality, and inflation. A more egalitarian society with moderate inflation turns out to be more sustainable than an unequal society with low inflation. Our approach is flexible enough to allow for various economic models to be embedded into our thermodynamic framework. Finally, we propose the open source EcoDyco software as a first complete realization implementing economic dynamics in a multi-resource environment. A prominent stream of economic literature considers Nature as an easy-to-overcome constraint for economic activities. Unlimited supply of energy and matter (hereafter E &M) and full-or, at least, partial-substitutability of production factors-to wit, labor L, capital K, matter, M, or energy E-are often assumed (see OFCE 1 and Nordhaus 2 ).
ADE-MS The ADE-OPI-MS system used during this study was a prototype based on an acoustic liquid handling comprising a modified EDB Biosystem Gen4+ where the rotary function of the receiver plate has been disabled and a proprietary open port probe interface mounted at 2 mm from the source plate (Figure  1 ). The OPI was centered over the acoustic transducer central axis within ±100 μm using the ATS-100 software and 5 nL droplets were generated using the water calibration and a pause of 1. 2 s was observed between injection of each sample. electrode/probe assembly. The ion source gas 1 and 2 pressures were fixed at 90 and 85 psi, respectively, with a temperature of 300 °C for both. The ion spray voltage, declustering potential and collision cell exit potential were adjusted to 4000 V, 80 V and 10 V, respectively.
The curtain and collision gas were set at 25 psi and "medium", respectively. to generate individual results for each sample. This splitting step was possible thanks to custom software developed by SCIEX. Briefly, the peak corresponding to the injection of the first sample was detected using a threshold based on the intensity of the most intense peak present. Then, the ADE report containing the time interval between two consecutive ejection events (i. e. two consecutive samples) was used to assign each data point of the chromatogram to a specific sample and finally to split the raw data into individual files. In this study, we chose to use 10% of the maximum peak intensity.
s between two consecutive injections To evaluate the process variability of the entire workflow (i. e. sample preparation and data acquisition), 60 wells of a 96-well plate were spotted with a pooled allantoic fluid sample and the plate was processed 4 times into the same 384-well plate. Over the 240 samples measured, the process variability presented a CV better than 6%. In addition, with a time delay of 1. 2 s between 2 consecutive injections and including the instrumental delay of the system check inherent to every plate analysis, it is possible to analyze 240 samples in 6. 5 min, so a throughput of 1. 63 s/sample.
4°C). We analyzed the subsequent 60 min of video recordings using the coding software BORIS  (Friard et al. , 2016). We coded activity as: (i) number of jumps and (ii) call duration (in s). The setup of the video cameras allowed us to monitor the entire space inside male terraria. It occasionally occurred that visibility of males was slightly obstructed by the vegetation, but in general male movements were unambiguously visible. Male calls were recorded at all times. In instances where males were neither visible nor audible for the entirety of the recording (e. g. , hiding under a shelter, N = 27/108 observations), we coded them with a value of zero for both number of jumps and call duration.
Assessment of boldness and exploration levels We collected data on individual levels of boldness and exploration using a novel environment test (NET) (cf. Carter et al. , 2013; Peignier et al. 2022 ). The setup (Figure  1 ) consisted of a cooler box (50 × 25 × 29 cm), with a 10 cm PVC tube attached on one side of the box (hereafter 'release tube'). The floor of the box was visually divided into 40 squares (5 × after entering the box. As temperature varied during the day, we noted the exact ambient temperature (in °C) at the beginning of each trial. At the end of a trial, the individual was put back in its home terrarium and the setup was cleaned to remove potential chemical cues. We analysed video recordings using the coding software BORIS  (Friard et al. , 2016). We coded (i) whether individuals entered the box (1) or not (0), (ii) the latency to leave the release tube (i.
All experiments were conducted at a constant temperature of 29°C. The first 30 minutes of the recordings were not considered in the analysis to allow individuals to acclimate to the new environment. We analysed only the subsequent 7. 5 h of video recordings. For the analysis, the setup was split in two equal areas  ('complex' versus 'non-complex' habitat) , and we used the software BORIS  (Friard et al. , 2016)  to code (i) the time spent in each habitat type (in s) and (ii) the number of times individuals crossed over from one habitat type to the other. The latter variable was used to identify if and how much individual males assess and compare the available habitat options.
e. , if time spent in a given habitat significantly deviates from what is expected by chance). Then, we investigated the influence of personality traits on males decision and movement in a territory settlement context. We built a generalized linear model and a linear model using the 'lme4' package  (Bates et al. , 2016). The generalized linear model followed a Poisson distribution and had the number of times individuals crossed over from one habitat type to the other as response variable. The linear model followed a Gaussian distribution and had the time spent in the complex habitat (transformed with the function transformTukey following a constant transformation) as response variable. For the fixed effects, we only used behaviours that were repeatable according to the repeatability estimations previously done (i.
Similarity Evaluation of Selected CAF Peptides with Human Proteins We performed the similarity evaluation of the three individual peptide repertoires to the human "personalized" proteome of 20,000 proteins/genes (20 K) by peptide-to-peptide mappings, which is an integrated application of the PepSimili bioinformatics modules. Again, applying the PAM30 threshold score at 0. 68, the peptides of the CAF1 repertoire were mapped to proteins encoded by 7169 proteins/genes, the peptides of the CAF2 repertoire to 7184 proteins/genes, and the peptides of the CAF3 repertoire to 1635 proteins/genes. Among these evaluations, 1578 proteins/genes were mapped by all the three CAF peptide repertoires, while the same 5370 proteins/genes were mapped by both CAF1 and CAF2 repertoires, 1600 proteins/genes were mapped by both repertoires CAF1 and CAF3 and 1606 proteins/genes were mapped by both CAF2 and CAF3 repertoires.
Discussion To address the question of effectively selected peptides or the randomness of positive selected peptides among selections of phage-displayed peptide repertoires, we used the data published by Brinton et al. [19]. In their study, the authors present data of the comparative selections of peptide ligands by in vitro biopanning phage display with a combinatorial library of cyclic 7-mer peptides on a cancer-associated fibroblast (CAF) cell line. The in vitro selections were performed in three independent experiments under identical conditions (same cell line, same culture conditions, same recombinant phage library, etc). The three selections were sequenced by NGS revealing three large peptide repertoires, which are each composed of several hundreds of thousands of unique peptides. The authors had already observed that the three repertoires CAF1, CAF2 and CAF3 contained only a relatively small number of peptides that were common to the three selections.
Indeed, the common fraction of peptides of the three repertoires represents about 5% of the selected peptides. By applying their developed PHASTpep software  [19] , the authors identified three potential CAF-selective peptide sequences as present in these three CAF peptides repertoires, but absent from peptide selections performed with other cell lines and under various other experimental conditions serving as controls. Finally, their study confirmed experimentally for two of these three identified peptides the binding to the tumor microenvironment in vitro and in vivo. This experimental observation is important to notice as indicative evidence that the selections were effectively producing valuable peptide ligands. On the other hand, the several hundreds of thousands of non-common peptides of the three CAF repertoires were not further studied.
Materials and Methods For the comparative evaluation of the three peptide repertoires that were generated on the CAF cell line study  [15] , we applied the elements of the PepSimili workflow  [21]  that is implemented as a tool in a Galaxy cloud platform  [26] , online available. The bioinformatics modules of the Galaxy platform allow manipulation of the raw fastq files including quality filtering, trimming of the sequences to isolate the variable part of the recombinant phages and DNA-to-protein translation. To obtain detailed information on the common and different compounds among the three NGS peptide selections, named CAF1, CAF2 and CAF3, the peptide lists were filtered and sorted for duplicates to obtain unique peptides in each of the lists by using the corresponding tools of the Galaxy platform.
These three lists of unique peptides were used as basis for further analysis (lists can be obtained open request). Further processing of data included the grouping or subtraction and sorting in demand of steps of the qualitative and quantitative analysis. All these applied tools were used online on the Galaxy platform  [26]. We first performed a comparison of the individual peptides of the three peptide lists to quantitate the number of peptides presenting the sequence identity among the three selections. In a second step, we performed the mapping of the peptides from each list to the peptides of the two others by using the module peptide-to-peptide mapping of PepSimili algorithm. The similarity between two peptides is calculated based on the implemented the PAM30 substitution matrix  [27].
Funding: This work was supported by  INSERM ,  ANR-French National Research Agency   2006-15  (KGP) and by the  Operational Program Competitiveness, Entrepreneurship and Innovation ,  EPAnEK   2014-2020 , under the call  RESEARCH CREATE INNOVATE , which is co-funded by Greece and the  European Union  (project code  T2EDK-03126 , MIS: 5129434, Acronym: BIOFOS).
A minimal installer package can be obtained from the site, and this will proceed to install the latest version of the suite. Updates are then distributed via a nondisruptive mechanism that was first introduced with CCP4 version 6. 3. 0 in 2012. Update reminders are generated automatically, although the update mechanism itself is, by design, initiated manually. As an indication of update frequency, the 7. 0 series, which was originally released in 2016, saw more than 70 updates until the 7. 1 series was released in 2020. Updates are not a one-way road: they may be rolled back if problems are encountered. Whilst every effort has been made to keep the suite streamlined and maintainable, the inclusion of large databases and toolkits has driven space requirements steadily upwards (Fig. 1 ). The last decade has seen some large transformations in the field of MX: new workflows have been created (for example phasing with AlphaFold2 models) and some old workflows have been optimized, while some others are on the verge of disappearing; this has often been the result of cross-pollination with other techniques in structural biology, for example electron cryo-microscopy (cryo-EM) in particular, through a synergistic collaboration with CCP-EM  (Burnley et al.
Although seemingly unconnected, most of these newer developments have one thing in common: the Python programming language as a platform for pipelining and program communication. While some Python scripts were already part of the CCP4 suite even before the time of the last general publication  (Winn et al. , 2011) , most of the recent source code committed to the CCP4 repositories involves Python in one way or another; for example, both the data-integration tool DIALS  (Winter et al. , 2018)  and its CCP4 graphical user interface DUI  (Fuentes-Montero et al. , 2016)  are Python-heavy software. Other CCP4 programs, encoded in a different language such as C++ for performance reasons, may also offer Python bindings; examples include Coot  (Emsley et al. , 2010) , Privateer  (Agirre et al. , 2015)  and GEMMI  (Wojdyr, 2022) , which is a crystallographic toolkit developed in collaboration with Global Phasing Ltd.
Both the Python language and its interpreter are now at the core of the CCP4 suite. Importantly, both new graphical user interfaces to the CCP4 suite (see below) make substantial use of the Python language. On the subject of graphical user interfaces, a large paradigm shift is also under way, with both CCP4i2 and CCP4 Cloud making extensive use of web technologies: HTML, CSS and JavaScript are used for both interface design and result presentation, with CCP4 Cloud making a strong case for the transformation of existing interactive model-building and illustration applications, for example Coot and CCP4mg, into apps that can be run within a web browser.
Graphical user interfaces The long-serving CCP4i interface (developed in Tcl/Tk) has recently been deprecated and replaced by a more modern, QT/PySide graphical user interface (GUI) named CCP4i2  (Potterton et al. , 2018). The CCP4i2 GUI, the main purpose of which is to provide a desktop-based experience, has introduced a number of architectural differences with respect to the first iteration. (i) A real database system, as opposed to a directory structure, provides traceability of files and jobs, and allows the automatic population of inputs to follow-on jobs with outputs from previous jobs. (ii) Large MTZ files are separated into important column sets defining particular data types and with predictable names, for example Miller indices (H, K and L columns) plus amplitudes and estimated standard deviations or e.
MrBUMP is an automated tool that will perform searches for templates and attempt molecular replacement with them, displaying comprehensive results that can be taken forward provided that the R factors are low enough. It can find structures of homologues using PHMMER  (Eddy, 2011)  or HHpred (So ¨ding, 2005) and place them using either Phaser  (McCoy et al. , 2007)  or MOLREP  (Vagin & Teplyakov, 2010). The template search code of MrBUMP can also be harnessed interactively in CCP4mg, allowing users to create composite models and ensembles for subsequent MR searches; this tool can be accessed from both CCP4i2 and CCP4 Cloud. MrParse  (Simpkin, Thomas et al. , 2022)  provides a convenient visualization of potential search models from the PDB and databases of new generation models such as the AlphaFold Protein Structure Database  (Varadi et al.
e. without turning them into amplitudes first, and can also use SAD data (for SAD and MR-SAD phasing). The voyager  (Sammito et al. , 2019)  automated procedure within Phaser presents a new architecture that allows more flexibility, guiding user decisions in creating ensembles. It also provides, alongside a plethora of new and reimplemented algorithms, code to make the best use of AlphaFold  (Jumper et al. , 2021)  and RoseTTAFold  (Baek et al. , 2021)  structure predictions, or high-confidence subsets of them, including the transformation of model confidence metrics (for example the AlphaFold pLDDT) into estimated B factors. Owing to the flexibility of the new design, tools for fitting models into cryo-EM maps have been included. An ad hoc graphical user interface is under development; this will allow easier navigation of the different solutions calculated during the search strategy, presenting the user with essential plots such as the self-rotation function.