dataesr/scientific-paragraphs-categorization huggingface dataset:
Furthermore, they demonstrated how to collaborate via Github (i. e. , authenticate and "push" the latest updates) as the final part of the workshop. The key takeaways from this workshop were consistent data generation and sharing for better research practices by taking advantage of free and open-source tools, being aware of reproducible principles right from the start of the project initiation, generating reproducible data analysis pipeline and integrating software analysis and textual reports for better reproducibility. Furthermore, the workshop material is freely available to participants and non-participants (https://iscbsc. github. io/2022-12-11-ASCSonline/).
Join us on this fascinating journey, and Let science break barriers and connect different Asian countries among themselves and with the rest of the great ISCB-SC ecosystem! The benefits of publishing with F1000Research: Your article is published within days, with no editorial bias • You can publish traditional articles, null/negative results, case reports, data notes and more • The peer review process is transparent and collaborative • Your article is indexed in PubMed after passing peer review • Dedicated customer support at every stage • For pre-submission enquiries, contact research@f1000. com.
Acknowledgments We thank the  ISCB leadership  and support staff and Nucleus maintainers, particularly  Diane Kovats ,  Seth Munholland ,  Catrina McDermott ,  Alexis Carpenter , and the  ISCB-SC Executive Team , for their support. We are truly grateful to  ISCB-SC  for sponsoring this event. Finally, we thank all organizers, speakers, presenters, and participants who made the 1st ASCS a success.
In Section 2, we present and describe the WR 140 observations and data reduction with Subaru/SCExAO/CHARIS, Keck/NIRC2+PyWFS, and Subaru/COMICS. In Section 3, we analyze the morphology of the IR emission from circumstellar dust around WR 140 and conduct a dust SED model analysis to investigate the dust properties. The dust SED analysis reveals the presence of very small nano-sized ("nanodust") grains around WR 140. Finally, in Section 4, we discuss the possible mechanisms that could lead to produce nanodust around WR 140 and the astrophysical implications of nanodust formation around WC binaries.
For astrometric calibration, we took four exposures with the artificial satellite spots  (Jovanovic et al. 2015b ) turned on and obtained our other observations without satellite spots. We observed the K0-star HD 194479 afterwards as a PSF reference star and for spectrophotometric calibration. We used the standard CHARIS pipeline  (Brandt et al. 2017 ) to extract CHARIS data cubes from the raw data. For subsequent data reduction, we used the CHARIS Data Processing Pipeline  (Currie et al. 2020 (Currie et al. , 2023)). For spectrophotometric calibration drawn from the HD 194479 data, we adopted a Kurucz stellar atmosphere model appropriate for a K0V star. Simple inspection showed that the "bar" and C1 emission features are bright (Figure  1 , top left-hand panel), especially at longer wavelengths, and detected with conservative PSF subtraction methods.
We then forward-modeled this image through our RDI/KLIP sequence to estimate signal loss. Forward-modeling showed that the flux from the bar is well preserved, with a throughput varying from 0. 90 to 0. 98 across the entire bar morphology and over the full range of CHARIS channels. We therefore conservatively adopt a 1σ photometric uncertainty of 10% across the CHARIS channels. Flux densities of the C1 and the bar were extracted from the CHARIS data cubes using a circular aperture with a 250 mas radius and a rectangular aperture with a size of 1480 × 300 mas, respectively. The rectangular aperture for the bar was tilted by 1°. 7 south of west to match the angle of the bar feature.
L′-band Imaging with the Keck/NIRC2 Vortex Coronagraph Keck/NIRC2 L′-band (λ c = 3. 8 μm) imaging observations of WR 140 were obtained on 2020 August 18 UT in the program C258 (PI-M. Hankins). The vector vortex coronagraph  (Vargas Catalán et al. 2016; Serabyn et al. 2017 ) was used to suppress the diffraction pattern of the star with an inner working angle of λ/D ≈ 80 mas at L′-band. The infrared PyWFS  (Bond et al. 2020 ) was used to obtain good adaptive optics correction because the star is much brighter in the infrared than at visible wavelengths due to extinction. Observations were taken using the narrow camera with a 10″ × 10″ field of view and a pixel scale of 9. 94 mas. QACITS, the standard focal plane wave front sensing technique for the vector vortex coronagraph, was used to obtain observations of the system while keeping the star aligned behind the coronagraph  (Huby et al.
2017). In total, we obtained 58 coronagraphic images, each consisting of 100 coadds of 0. 18 s exposures. As standard in the QACITS sequence, we also obtained sky background images and unocculted images of the star for calibration. In addition to WR 140, we used the same configuration to obtain 15 frames on two reference stars: the K5-star HD 181681 immediately before, and the K0-star HD 194479 immediately afterwards. We used the vortex preprocessing pipeline  (Xuan et al. 2018 ) to perform bad-pixel correction, flat fielding, thermal background subtraction, and co-registration of the images. The reference images from HD 181681 and HD 194479 were used to subtract off the stellar diffraction pattern of WR 140 using the KLIP-RDI implementation in the open-source pyKLIP package  (Wang et al. 2015).
The channels corresponding to 1. 37, 1. 42, 1. 87, and 1. 93 μm are likely telluric-dominated and were also omitted   1 )) presents the best fit to the shape of the CHARIS SEDs of both the bar and C1. Telluric-dominated channels (see Table  2 ) are omitted from the plots. 2 ) are omitted from the plots and SED fitting. from the SED analysis. The extracted near-IR flux densities were corrected for interstellar extinction using the average observed extinction curve of the Milky Way "G21_MWAvg" from the dust_extinction Python package  (Gordon et al. 2021). 22  A value of A v = 2. 21 23  was adopted for the interstellar extinction toward WR 140  (Rate & Crowther 2020). Figure  5  shows the near-IR SEDs of the bar and C1 from the CHARIS data cube before and after extinction correction. The shape of the near-IR SEDs of both the bar and C1 clearly demonstrates that the dust emission increases with increasing wavelength.
A log-normal grain size distribution with ( ) ( ( ) ) µ s - dn d a e log a a log 0 2 was adopted for the DustEM models, where the free parameters were the centroid grain size a 0 and the distribution width σ. Minimum and maximum grain sizes in the models were fixed at 9 × 10 -4 μm and 1. 0 μm, respectively, where the minimum grain size limit was defined by where the maximum dust temperatures exceeded a sublimation temperature of ∼1800 K when exposed to the WR 140 radiation field. To approximate the dust-heating radiation field from the WC7 and O5 stars in WR 140, we used synthetic spectra from model atmospheres computed with the PoWR code  (Gräfener et al. 2002; Sander et al. 2012; Hainich et al. 2019 ). The models were calculated to reproduce the spectral appearance of both stars (including the light ratio) using a detailed binary analysis similar to those described in  Shenar et al.
Acknowledgments R. M. L. thanks  Thiem Hoang  for the insightful discussions on grain disruption and the RATD mechanism. R. M. L. also thanks  T. Fujiyoshi , the  Subaru Observatory  staff, and the  Keck Observatory  staff for supporting our observations of WR 140. We also thank the anonymous referee for their valuable feedback on our analysis an interpretation. The work of R. M. L. is supported by  NOIRLab , which is managed by the  Association of Universities for Research in Astronomy   (AURA)  under a cooperative agreement with the  National Science Foundation. R. M. L. acknowledges the  Japan Aerospace Exploration Agency 's  International Top Young Fellowship  (ITYF). A. A. C. S. is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)  in the form of an  Emmy Noether Research Group  (grant No.
Participatory water resource management requires modeling techniques that are accurate and flexible yet stakeholder-friendly. While different modeling frameworks offer advantages and disadvantages, system dynamics (SDs) models have seen sustained use as a stakeholder-friendly approach for participatory water resource modeling. Physically based models (e. g. , SWAT+) have seen sustained use to model the hydrological components of water systems. Proposed as a way to combine the relative strengths of both modeling paradigms, model coupling allows researchers to, for example, build participatory SD models with stakeholders, while delegating the hydrological components of the overall model to an external hydrological model. Recently developed to facilitate model coupling, the Tinamït Python package presents an extensible, outward-facing application programming interface (API).
g. , Open Modeling Interface or OpenMI;  Gregersen et al. , 2007) ; however, socket-based approaches are another option  (Bulatewicz et al. , 2013). The latter approach is quite novel for this application and could provide potential benefits, e. g. , shorter execution time (see Sect. 2). Most existing wrapping approaches have not been or cannot be used to couple SD models. However, automatic SD model wrapping with external physically based models may be achieved through the Tinamït API  (Malard et al. , 2017). In this process, a physically based model wrapper is developed only once for every physically based model platform; thereafter, a few lines of code allow any model built upon the same platform to be coupled with any other SD model. Tinamït has been previously applied to the evaluation of policy-makers' decisions for salinity management in Pakistan, using a coupled SahysMod and SD model  (Malard et al.
, 2017) , and for agricultural management in predominantly indigenous rural communities in Guatemala, by coupling SD models and the Python Crop Simulation Environment (PCSE;  de Wit, 2022; Malard et al. , 2020 Malard et al. , , 2023)). However, Tinamït has not yet been applied to coupling an SD model with a hydrological model (e. g. , SWAT+) and, thereby, facilitating the integrated modeling of coupled human-water systems. The concept of using Tinamït to couple SD and hydrological models has been presented; however, details of these earlier conceptualizations were mostly changed in the process of development  (Harms et al. , 2020 (Harms et al. , , 2021)). The present paper will present (i) the development of a sockets and JavaScript Object Notation (JSON)-based data exchange Python package and its C/Fortran counterpart in SWAT+, (ii) the creation of a SWAT+ wrapper, using the functionality of the Tinamït API and the data exchange Python package, to allow SWAT+ models to be automatically coupled to SD models, and (iii) the coupling and application of a SWAT+ and a human-water SD model to holistically evaluate policy-makers' decisions and their potentially far-reaching effects in the Usa river catchment, Tanzania, based on a SWAT+ model provided by  Nkwasa et al.
Methodology A Tinamït (2. 0. 3)-compatible SWAT+ wrapper was created using the following steps: 1. A Python package (labeled "tinamit-idm") employing socket functionality and including a generic JSON protocol was developed to serve as the basis for data exchange between Tinamït wrappers and the SWAT+ model engine  (Malard and Harms, 2022 ; Python 3). 2. The SWAT+ engine was modified by adding C language sockets, thereby allowing communication via the JSON protocol used by tinamit-idm  (Harms and Malard, 2022a ; Fortran, C). 3. A SWAT+ wrapper was created using Tinamït 2. 0. 3 and tinamit-idm  (Harms and Malard, 2022b ; Python 3). 4. The case study model was coupled  (Harms and Malard, 2022b ; Python 3). A socket-based approach was chosen for the inter-process communication between the models instead of a pipe-andfilter-based approach (e.
tinamit-idm A generic socket-based Python package was developed to provide basic functions that any models interchanging information during runtime might require  (Malard and Harms, 2022). The functions "cambiar", "recibir", "incrementar", "finalizar", and "cerrar" define how to provide data, receive data, increment the model by a certain number of time steps, finalize the model, and close the model, respectively. The JSON protocol was of critical importance for these functions. Five distinct types of JSON message types were defined, corresponding mostly to the key functions provided by tinamitidm. The definition of this JSON protocol was kept as general as possible to give it the necessary flexibility to be implemented as a standard for all socket-based inter-model communication using tinamit-idm and Tinamït.
The JSON messages are detailed in Table  1. Keywords and variable names for the tinamit-idm code are written in Spanish. This is done to keep inter-operability with the existing Tinamït code, as tinamit-idm will be added to the next version of Tinamït. Code for the SWAT+ modifications are kept mostly in English, except for the parts needing to interface with tinamitidm, to keep easy usability for SWAT+ users that are used to English-based code.
Modification of SWAT+ To give SWAT+ the ability to exchange data via sockets, SWAT+ was modified as follows  (Harms and Malard, 2022a). Argument handling was initially added so that one might specify whether SWAT+ was to be executed alone or connected to Tinamït. Arguments can be added to the command line call of the swatplus. exe file; the execution file can be called with the command "swatplus [port] [host]" (where "port" specifies the port to which SWAT+ should connect and "host" specifies the host IP, usually 127. 0. 0. 1). One may still call "swatplus" to run only the SWAT+ model by itself. Second, a Fortran module implementing the methods required for communication with the tinamit-idm package was added. This module was named the "tinamit_module" and is called mainly from the "time_control" module that manages SWAT+'s main simulation loop.
The tinamit_module gives SWAT+ the ability to pause, receive messages from, and send messages to other models coupled via Tinamït. Furthermore, a mechanism is implemented here that allows SWAT+ to run as many time steps as the coupling code specifies before re-communicating with the Tinamït wrappers. This alleviates the need to unnecessarily pause the simulation of SWAT+ after every time step to communicate with Tinamït and allows for a more efficient execution of the simulation, depending on the data exchange interval chosen by the modeler. It also allows Tinamït to balance the varying time step lengths of the different models. The tinamit_module makes use of a C file ("socket. c"), which provides it with socket creation and reading and sending functions (hereafter referred to as the C client).
Creation of the SWAT+ wrapper A SWAT+ wrapper was created using the Tinamït and the tinamit-idm packages  (Harms and Malard, 2022b). This wrapper is openly available on GitHub, as are the other source codes for the work mentioned in this paper. Since SWAT+ is a physically based model, a subclass of the Tinamït wrapper class "ModeloBF" class was created, called "ModeloSWATPlus". The following methods were defined for the ModeloSWATPlus subclass: 1. __init__() creates an instance of the ModeloSWATPlus and initializes the socket connection in addition to the model variables. 2. unidad_tiempo() returns the unit of time of the model for SWAT+. This was set to occur daily. 3. iniciar_modelo() defines how the wrapped SWAT+ model will be called to start running, sets up a working directory for the model, and ensures that the other requirements for data exchange are met.
4. incrementar() defines how the model will be advanced during its run and how data exchange with the model may occur after a simulation step. 5. paralelizable() defines whether SWAT+ can be parallelized in different Python threads, which it can be, if run using the wrapper. 6. cerrar() ends the model run and stops the model engine. In this case, it is also responsible for ending the connection between the model and the Tinamït wrapper. 7. instalado() checks whether a SWAT+. exe or engine is installed and specified. Steps 1-7 must be implemented by any physically based model wrapper created in Tinamït  (Malard et al. , 2017). The following three are convenience functions that the authors deemed useful for any SWAT+ model in general and more specifically for the case study model execution: 1.
This was demonstrated in earlier work with Tinamït  (Malard et al. , 2017 (Malard et al. , , 2020 (Malard et al. , , 2023)). Through this method, the researchers were able to focus on representing the socioeconomic processes in the watershed, or in potentially involving further stakeholders, without requiring a re-implementation of location-specific hydrological processes. Additionally, since a generalized JSON protocol was used in concert with socket technology, inter-process communication was achieved between diverse languages (Python, Fortran, and C, in this case), without the need for writing and reading files to disk. Other coupling methods which have employed file-and pipe-based approaches  (Gregersen et al. , 2007; Inam et al. , 2017)  or translated the entire model into a single programming language  (Prodanovic and Simonovic, 2010)  have shown potential shortcomings, e.
g. , longer execution time, extensive implementation work, and a resultant lack of flexibility. Since no files were written or read during execution when the socket-based data exchange was in use, the model execution time was likely to benefit. This technology could furthermore be adapted to a multitude of other Fortran (or C)-based models without major modifications to the client part of the socket code (i. e. , the socket. c file), as the C socket client is as generic as the JSON protocol used by tinamit-idm. The server code in tinamit-idm, especially in conjunction with Tinamït, lays the groundwork for developing wrappers for models written in any language that can interpret JSON and will simplify the development of other physically based model wrappers.
Limitations Compared to OpenMI, Tinamït has neither the same status nor the history of use and trust and does not yet support a similar range of models. Therefore, the OpenMI standard may currently have an advantage when different physically based models are to be coupled for a project. However, Tinamït is unique in its ability to create wrappers for SD models, which are some of the most popular tools for integrated WRM models or, more broadly, participatory model building. Additionally, the work presented here is likely to improve the usefulness of Tinamït, not only through the possibility of easily integrating SWAT+ into a participatory WRM model but also because it provides standards, methodologies, and examples that simplify the addition of further models to Tinamït. Currently, the SWAT+-coupling-capable version is only available for Linux systems, although Windows and MacOS versions are in development.
During development, the Windows version of the socket code in the modified SWAT+ version created difficulties during compilation. These difficulties were exacerbated by differences between Windows sockets and C sockets. The MacOS version is nearing the end of its development, but at the time of writing, the Linux version of the modified SWAT+ was the only functional version available. However, all Python packages presented (i. e. , Tinamït and tinamit-idm) are functional on all current major operating systems. A selection of about 190 numerical-type SWAT+ variables have been made available for coupling, including some util-ity functions and variables specific to the case study; however, there are likely functions and variables that other modelers might find useful to couple that have not been included.
The use of sockets and the JSON protocol is a promising step, as it largely bypasses the need for language interoperability and potentially improves execution time compared to other model coupling platforms. Expansion of the abilities of Tinamït makes it more useful for participatory WRM and other participatory modeling work. In the case study presented here, the coupled model was able to portray the overall results of both the human, socioeconomic, and the physical resource systems at play with considerable ease. The modeler was able to obtain results for hydrological variables without having to define all the relationships manually in the SD model, thereby allowing a focus on representing socioeconomic processes. In closing, we hope that the code and technology presented in this paper will contribute to improving participatory WRM modeling work and make it easier to apply to real-world decision-making scenarios, while also providing developers with ideas and templates for the further development of Tinamït and other model coupling platforms.
Acknowledgements. This research has been supported in part by a  National Sciences and Engineering Research Council of Canada (NSERC) Undergraduate Student Research Award (USRA) , supplemented by the  Fonds de recherche du Québec (FRQNT) , held by  Joel Z. Harms. This research has further been supported by a grant from  NSERC  held by  Jan F. Adamowski. Ashutosh Sharma  has been supported by the  Shastri Indo-Canadian Institute (SICI)  under the  Shastri Research Student Fellowship (SRSF) scheme  to carry out this research at  McGill University. Financial support. This research has been supported by the  Fonds de recherche du Québec -Nature et technologies  (grant no. 297038 ), the  Natural Sciences and Engineering Research Council of Canada (USRA ; grant no. 552014-2020 ), and the  Natural Sciences and Engineering Research Council of Canada (NSERC ; grant no.
Code and data availability. The source codes of the software presented in this paper, including the case study, are available. The currently archived versions are cited in the text (https://doi. org/10. 5281/ZENODO. 6902755, Harms and Malard,  2022a; https://doi. org/10. 5281/ZENODO. 7630281, Harms and  Malard, 2022b; https://doi. org/10. 5281/zenodo. 6884988, Malard and Harms, 2022) , and any updated versions are available publicly on GitHub. The links to the GitHub repositories are as follows: tinamit-idm at https://github. com/joelz575/tinamit_idm (last access: 22 February 2023), SWAT+ (modified for Tinamït compatibility) at https://github. com/joelz575/swatplus (last access: 22 February 2023), and the SWAT+ wrapper and coupling example at https://github. com/joelz575/swatplus-tinamit-coupling (last access: 22 February 2023).
INCEFA-SCALE is a five-year project supported by the European Commission HORIZON2020 program. It is the successor to the INCEFA-PLUS project that ran from 2015 to 2020. Both projects try to address existing gaps between the fatigue behavior of stainless steels in the laboratory, real fatigue behavior observed in nuclear components during operating service, and provide guidance on how to account for the studied behavior in fatigue assessments. These programmes are contributing to a database with a large number of parameters (strain amplitude, strain rate, temperature, surface roughness, hold time periods, chemistry, etc. ). Once the International Fatigue Database Agreement is signed, this database will be augmented with fatigue data shared by international organisations from the US, Korea, Japan and Europe.