dataesr/scientific-paragraphs-categorization huggingface dataset:
To conclude, besides its strong local radioenhancing effect, one of the main properties of AGuIX nanodrug that makes it such strong candidate as a radiosensitizer is its ability to pass through the blood brain barrier selectively in brain metastases leading to the possibility of a differential response between the tumour and dose-limiting normal tissue. The NanoCOL clinical trial (NCT03308604) has been accepted recently by French regulatory office. NanoCOL is a Phase Ib clinical trial ongoing in Gustave Roussy institute (Villejuif). 78 It is aimed to treat advanced cervical cancer by RT and brachytherapy in association with AGuIX NPs and cisplatin (CDPP) (Figure  14 ). During the protocol, three injections of AGuIX NPs will be delivered before the first irradiation at Week 1, at the beginning of Week 3 and before brachytherapy.
In this work, to analyze the studied area potential, application of a cadastral dataset was proposed. Thanks to this approach, the obtained results may be related to specific plot borders, which is optimal for greenway construction. To automatize the process of analysis, the TBM was implemented into an ArcGIS toolbox. The result of using this toolbox is a tree belt functions geodatabase. This database contains information about the available functions in the analyzed lines that are potential sites for afforestation. This solution, both at the methodological and technological levels, may significantly increase the effectiveness of greenway planning and thus contribute to more effective activities for sustainable development.
, 2012). Furthermore, this approach was used for the analysis of quantified functional relationships over a landscape using GIS  (Papadimitriou, 2002)  in order to assess the significance of a forest patch within a larger landscape  (Papadimitriou, 2013). Presently, the available GIS software more and more often provides programming tools and graphical interfaces that allow users to design their own methods of geoprocessing. One such toolset is Model Builder (MB) for ArcGIS (ESRI) e a system of analysis programming. MB facilitates the construction of spatial models without the necessity of combining the typical developing software programs and advanced programming skills of a user  (Lee et al. , 2008). This programming tool finds application in many different areas, e. g. , automatic landslide susceptibility analysis  (Jim enez-Per alvarez et al.
, 2009)  or flood threat recognition  (Schr€ oder et al. , 2015). When the available standard tools limit the possibilities of spatial analysis, MB can be supported by the Python programming language. This open source programming language allows to create from scratch or develop and combine existing components in a computing environment, including the GIS software  (Neuwirth et al. , 2015). It should be emphasized that the ArcGIS structure makes it easy to compile many Python scripts and Model Builders into one toolset that can be easily distributed and included in other software. This aspect makes python scripts available to both programmers and GIS users. The use of scripts and MB enables their integration with other GIS tools  (Brown, 2014) , improves computing processing efficiency and facilitates their implementation  (Rahmati et al.
The obtained results will aid in answering the question of whether the structure of a given area will satisfy local requirements for LWF that will cover different landscape functions -the aim of this work. For the needs of this spatial performance was to create a conceptual model for the analysis of potential LWF location availability at the level of cadastral plots (1) for a properly defined input dataset (2) that will make it possible to create a toolbox for the modeling of a potential LWF network with diverse functions (3).
Input data Taking into account different forms of greenways (such as the presence of tree belt gaps) and diverse ranges of natural and economic functions, the selection of proper spatial data was vital to prepare a conceptual model of tree belt function modeling. Aside from the determination of the thematic scope of data essential for multicriteria analysis, an important issue was also to adjust these data to spatial details. However, the national resources of topographic and thematic data are often prepared in different scales, which makes the analyses that combine both types of data into one input set difficult. To prepare such a dataset, the following resources were used: -digital topographic database (accuracy: 1:10 000) -digital cadastral database (accuracy: 1:5000) -digital hydrographic database (accuracy: 1:10 000) -ALS data (density of point cloud: 4e6 points/m 2 ).
GIS toolbox development To implement the prepared conceptual LWF model, ArcGIS 10. 3, supplemented with the Model Builder (MB) toolbox, was used. MB was chosen for this study because it enables the creation of a user's own automated geoprocessing applications of often complicated and multi-layered algorithms for multicriteria analysis. Using MB enabled the ongoing modification and development of a constructed model, which finally resulted in a higher work efficiency thanks to the automation of analytical processes and input data preparation. Furthermore, additional programming functions of MB based on the Python language increased the analytical possibilities of this toolbox. Scripts written using ArcPy (Python site package) were subsequently used for the modification of ArcGIS tools and defining new ones.
C3 -mapping of the spatial distribution of tree belt functions (TBF) (integrated level of output data). The selection of input data (A) was based on the analyzed LWF functions and included those environmental variables that affect the presence or absence of individual functions. To define the structure of the multicriteria analysis (B), LWF functions were divided into three main groups existing in the agricultural area (C2), which are composing from six basic functions (C1): -the first group was connected to the effect of the LWF network on the modification of microclimate and water conditions (among others, the more favorable balance of insolation and ground waters); -the second, took the minimization of soil erosion (by water and wind) into account; -the third was connected to the improvement of geo-and biodiversity.
To evaluate the terrain structure in terms of the availability of the greenway functions defined above, this terrain was also analyzed in terms of light conditions depending on the line orientation relative to world directions and greenway area aspects. Additionally, the connections between the greenway layout and prevailing wind directions, topographic slopes, level of plot mosaicity and differentiation of landforms in relation to the spatial distribution of potential LWF network were analyzed. To enable the grouping and comparison of the results for individual greenway functions, a uniform scale was used in each analysis. Multicriteria analysis results (C1, C2, and C3) were recorded in geodatabases at three levels: elementary (analysis results for each greenway function), semi-integrated (analysis results divided into three groups of function) and integrated (the general level of function availability).
Input data preparation To define potential places for tree belts, a polyline layer was created (all_lines). This layer comprised the boundaries of record plots (balks), including watercourses and roads that were distinguished as separate record plots. Other roads and watercourses (usually small in size), which were not distinguished as separate record plots, were added to the layer from the digital topographic database (DTD). Next, all polylines were divided into basic segments at the vertices using the Split Line at Vertices tool (Data Management Tools). This enabled us to carry out the evaluation of LWF function availability for the basic fragments of plot boundaries. Each polyline that forms one of the plot boundaries may differ considerably in relation to their direction. Because one of the plot boundaries often consisted of several segments (irregular course), before polyline division into basic parts, all lines were smoothed using the Simplify Line tool with a simplification tolerance of 1 m (Cartography Tools).
Based on the digital topographic database (DTD), a polygon layer (land_cover) was prepared. Because of the complex topographic structure of the studied area in the DTD, the reclassification process was conducted into the following classes: industrial areas, arable land, orchards and plantations, running and standing waters, forests, built-up areas, meadows and wasteland. To conduct analyses that require topographic information, a digital elevation model (DEM) was prepared. For its preparation in ArcMap, ALS data was used for the filtering of the point cloud to bring out the points representing the ground and next for converting to raster data. 3. 2. 2. Multicriteria analysis 3. 2. 2. 1. Solar conditions analysis. To conduct the light conditions analysis within the studied lines, the MB system, partially based on the Python code, was prepared.
Then, all lines were classified into two possible groups e perpendicular and parallel to the aspect/sunlight direction. For the last stage of MB preparation, the Python script was written. It was used to evaluate the effect of each line on light conditions in the area of a potential tree belt impact zone. The proposed evaluation scale of the studied lines depended on the availability of sunlight in a given place. Thus, during the preparation of the evaluation system, the location of lines in the specific type of area aspect, and their orientation in relation to the slope gradient and incidence angle were considered (Fig. 3 ). Based on these factors, a 5-point scale was defined, where the highest value was attributed to the lines with the best location in relation to light conditions. The lines that received the highest score were situated on southern slopes, while the lowest were on northern slopes.
However, to determine the other prevailing wind directions, we implemented the possibility to define a user scoring scale depending on local conditions into the tool. To use the standard Calculate Field tool for the evaluation of line set in terms of availability of discussed functions, the Python code was prepared. The MB system for the prevailing wind direction analysis tool is presented in App. B. 3. 2. 2. 3. Slope conditions analysis. The first stage of the analysis of line orientation relative to the slope defined in the third MB (App. C), implemented into the slope conditions analysis tool, was the calculation of slope based on the digital elevation model. Next, the mean value of slope degree of each individual line (from the all_lines layer) was added to this line. The areas recognized as not threatened with water soil erosion were excluded from analysis, i.
Preparation of output data The results of five spatial analyses formed three levels of the tree belt functions (TBF) geodatabase. First, the elementary level contains information on the availability level of each analyzed greenway function for the studied line. Fig. 8  presents the result of prevailing wind direction analysis (the presence of windbreak and snowbreak functions and reduction of wind erosion within the studied lines). Nearly half of the 1023. 12 km of analyzed lines were qualified to the fourth and fifth class (43,66% and 5,14%, respectively). This result indicates a very high availability of the described function within a potential LWF network. The results of the other four analyses are shown in Table  2. To prepare a geodatabase at the semi-integrated and integrated levels, the tree belt functions geodatabase tool was prepared.
To date, these types of linear structures have not been used in other works describing the methods of LWF design. We expect that tree belt modeling will be a significant contribution to the development of greenway planning both at the method (the possibility to evaluate available greenway functions to an accuracy of situational maps) and technology (preparation of the TBM toolbox) levels. The prepared TBM toolbox may initiate the preparation of consecutive toolboxes that will be based on existing conceptual models of other greenway planning stages. However, the application of the TBF geodatabase results at one of the detail levels (elementary, semi-integrated or integrated) will make it possible to check to what degree the current area structure enables the design of an optimal greenway network, i.
e. , the network comprising specific functions that will improve environmental conditions, economic effectiveness and human comfort. Such a precise determination of the studied area potential in relation to the available environmental and economic functions (through the indication of specific places in the field) may aid the decision making in spatial planning. The TBF geodatabase makes it possible for a user to select lines in the analysis range of one or several functions, function groups or a general function potential of the considered area. Thus, it enables an easy delimitation of areas with high or low potentials of selected functions. This type of information should be one of the essential factors that decides the way of area development. For instance, in a given area with an available soil erosion reduction function, there is no current need of its implementation (meadow areas), and the greenway network in this area should be developed in the way that will enable the later initiation of this function, e.
This hinders using the TBM toolbox for other latitudes because of the different sunlight incidence angles. Thus, it might be essential to prepare the score scale that refers to other latitudes. This emphasizes the need for adding a new module to the solar condition analysis tool, enabling the selection of latitude, which will decide about the light conditions modified by the lines of potential tree belts. Additionally, a low slope gradient does not affect the amount of sunlight reaching the ground. In solar analyses, such areas may be treated as flat. Thus, it might be advisable to supplement the toolbox with an option defining a gradient threshold above which an analysis may be conducted based on the adopted score scale and with an option defining a time range for which light conditions will be evaluated.
Thus, taking into account that TBM is destined for spatial planning, the future development of the solar condition analysis seems justified. For the analysis of a terrain gradient relative to lines, the toolbox provides the possibility of area selection above a given value of gradient, i. e. , all soils prone to water erosion. It might also be useful to complement the toolbox with an option enabling one to define several gradient brackets. Furthermore, the availability of detailed information about the susceptibility of soils to water erosion would make it possible to include this information in the delimitation stage of areas for which analyses are conducted. Additionally, during the preparation and interpretation of an obtained tree belt function geodatabase, the lines within forest plots that are not suitable as a tree belt location should be removed.
In the current version of the TBM toolbox, there is no formula defining forest area input data that enables an automatic elimination of forest lines. Thus, in future work on the TBM toolbox, information about the existing greenway network should be included within the input dataset. This will enable one to adapt the TBM toolbox to the valorization of existing greenways in terms of the functions they serve. The analysis of vertical vegetation in tree belts would make it possible to precisely verify the effectiveness of these functions, e. g. , as a snow-and windbreaker, or a barrier against the wind erosion of soil.
These I/O requirements obviously affect performance: the more data to output and the slower the file system, the larger the effect. To simulate tsunami hazard for a large number of scenarios is computationally expensive, so VOLNA has been replaced in past studies by a statistical emulator, i. e. a cheap surrogate model of the simulator. To build the emulator, input parameters are varied in a design of experiments, and the runs are submitted with these inputs to collect input-output relationships. The output of interest could for example be the waveforms, free surface elevation, and velocity, among others. The increase in flexibility in the definition of the region over which the earthquake source of the tsunami is defined reduces the size of the series of files used as inputs: this is really helpful when a set of simulations needs to be run.
On a single node with pure MPI, running the largest mesh, 9% of time was spent in the RK stage, achieving 182 GB/s throughput on average, 40% of time was spent in the gradients stage, achieving 108 GB/s, 25% of time was spent in the fluxes stage, achieving 142 GB/s, 12% of time was spent in the dT phase, achieving 65 GB/s, and 12% of time was spent in the applyFluxes stage, achieving 221 GB/s thanks to a high degree of data reuse. The maximum bandwidth on this platform is 189 GB/s as measured by STREAM Triad. The time spent in MPI communications ranged from 23% on the smallest mesh to 10% on the largest mesh. When scaling to multiple nodes with pure MPI, as shown in Figure  9 (a), it is particularly evident on the smallest problem that the problem size per node needs to remain reasonable, otherwise MPI communications will dominate the runtime: for the N U 0 mesh, at 32 nodes 251 seconds out of 308 total (81%).
A natural response to increased language complexity is to define subsets of the language designed for a better programming experience. For instance, a subset can be easier to teach (e. g. , "Core" ML 1  , Haskell 98 as opposed to GHC Haskell, Scala mastery levels 2  ); it can facilitate static analysis or decrease the risk of programming errors, while remaining sufficiently expressive for the target users' needs (e. g. , MISRA C, Spark/Ada); it can enforce a common style within a company; or it can be designed to encourage a transition to deprecate some ill-behaved language features (e. g. , strict Javascript). Once a subset has been selected, it may be the case that users write whole programs purely in the subset (possibly using tooling to enforce that property), but programs will commonly rely on other libraries that are not themselves implemented in the same subset of the language.
If users stay in the subset while using these libraries, they will only interact with the part of the library whose interface is expressible in the subset. But does the behavior of the library respect the expectations of users who only know the subset? When calling a function from within the subset breaks subset expectations, it is a sign of leaky abstraction. How should we design languages with useful subsets that manage complexity and avoid abstraction leaks? We propose to look at this question from a different, but equivalent, angle: instead of designing a single big monolithic language with some nicer subsets, we propose to consider multi-language programming systems where several smaller programming languages interact together to cover the same feature space. Each language or sub-combination of languages is a subset, in the above sense, of the multi-language, and there is a clear definition of abstraction leaks in terms of user experience: a user who only knows some of the languages of the system should be able to use the multi-language system, interacting with code written in the other languages, without have their expectations violated.
If we write a program in Java and call a function that, internally, is implemented in Scala, there should be no surprises-our experience should be the same as when calling a pure Java function. Similarly, consider the subset of Haskell that does not contain IO (input-output as a type-tracked effect): the expectations of a user of this language, for instance in terms of valid equational reasoning, should not be violated by adding IO back to the language-in the absence of the abstraction-leaking unsafePerformIO. We propose a formal specification for a "no abstraction leaks" guarantee that can be used as a design criterion to design new multi-language systems, with graceful interoperation properties. It is based on the formal notion of full abstraction which has previously been used to study the denotational semantics of programming languages  (Meyer and Sieber 1988; Milner 1977; Cartwright and Felleisen 1992; Jeffrey and Rathke 2005; Abramsky, Jagadeesan, and Malacaria 2000) , and the formal property of compilers  (Ahmed and Blume 2008, 2011; Devriese et al.
Acknowledgments. We thank our anonymous reviewers for their feedback, as well as  Neelakantan Krishnaswami ,  François Pottier ,  Jennifer Paykin ,  Sylvie Boldot  and  Simon Peyton-Jones  for our discussions on this work. This work was supported in part by the  National Science Foundation  under grants  CCF-1422133  and  CCF-1453796 , and the  European Research Council  under  ERC Starting Grant   SECOMP (715753 ). Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of our funding agencies.
The development of density functional theory and the tremendous increase of compute power in recent decades have created a framework for the incredible success of modern computational materials engineering (CME). CME has been widely adopted in the academic world and is now established as a standard tool for industrial applications. As theory and compute resources have developed, highly efficient computer codes to solve the basic equations have been implemented and successively integrated into comprehensive computational environments leading to unprecedented increases in productivity. The MedeA software of Materials Design combines a set of comprehensive productivity tools with leading computer codes such as the Vienna Ab initio Simulation Package (VASP), LAMMPS, GIBBS and the UNiversal CLuster Expansion code (UNCLE), provides interoperability at different length and time scales.
Introduction Since the turn of the millennium, industrial exploitation of computational materials research has seen a tremendous development. Atomistic simulations have become established as an integral part in research and development processes in many industrial sectors including automotive, aerospace, energy, chemicals, electronics, oil and gas, metals and alloys, glass and ceramics, and polymers. In all these sectors, computations help the process of finding new materials with unprecedented properties as well as tailoring and improving existing materials to make them better suited for their desired purpose. Atomistic simulations complement experimental investigations by providing detailed mechanistic understanding and systematic materials property data, thus reducing the number of candidates in screening studies, by contrasting measured data for mutual checks and by enlarging the databases of materials properties.
Beginning with the 1980s, integrated software environments such as Biosym's Insight integrating Discover and DMol, Quanta/Charmm of Polygen, ACACS of NEC and Sumitomo Chemical, UniChem of Cray Research and Cerius of Molecular Simulations/Accelrys emerged. Later, these early integrative concepts were further advanced by second generation environments such as the MedeA software of Materials Design  [1] , combining experimental databases and highly efficient simulation engines with a modern infrastructure for fully automated and high-throughput computations. Related efforts are QuantumATK of Synopsys, the Atomic Simulation Environment (ASE)  [2] , the Materials Project  [3] , the Open Quantum Materials Database (OQMD)  [4, 5] , NoMAD  [6]  and Aiida  [7] , just to mention a few. These tools are now well established and have a tremendous impact on the daily work of industrial researchers since they free them from routine work and allow them to focus on the scientific and technological problems to be solved.