dataesr/scientific-paragraphs-categorization huggingface dataset:
Image analysis: All image analysis scripts developed in the context of this study, can be made available upon request. Cell Wall thickness measurement: The analysis pipeline to compute CW thickness used was fully automated with a manual check option for each step. All the analyses were performed using custom scripts written in MATLAB (Mathworks, R2013a equipped with Image Processing and Statistics toolboxes). Initial cell segmentation was performed using either fluorescent membrane or lectin signals. The signal was first binarized using a threshold determined with the graythresh function. The cell contour was defined as the most outer pixels of the binarized signal. The coordinates corresponding to the points along the cell contour were then equally spaced with an interval of 1 pixel using a spline function.
This map is finally used as an input in the cell wall thickness measurement scripts described above (Figure  S1C ). To assess the chromatic shifts in Z, we imaged a 3 µm deep Z stack with 10 nm spacing between slices of the same 200nm beads in 5 different positions in the field of view in two wavelengths channels. To reproduce the distance of the cell center from the cover glass (about 2 m), beads were embedded in 2% agar pad, and only beads at about 2 m from the glass surface were imaged. For each stack the fluorescent peaks were detected using a Gaussian fit, and the shift computed from the distance between the peaks. We found that this shift ranged typically from 0. 1 to 0. 4 m, which corresponds to a projected shift in thickness smaller than 30nm that we neglected for the measurement (Figure  S1B ).
Generation and analysis of simulated images: Simulated images were generated as described in  (Clark et al. , 2013) , using custom scripts written in MATLAB. The simulation starts with two dimensional data, corresponding to a simple spherical cell shape of 3 m diameter, drawn with a 5 nm resolution. The simulated cell has a cell membrane thickness of 15 nm and a cell wall thickness of 200 nm. To best represent the experimental imaging conditions, the cell membrane was assumed to be uniformly stained, and only 5 nm of the most outer part of cell wall was uniformly stained in another color. To account for the experimental noise and finite background signals inside and outside of the cell, two different Gaussian noises, were added. The mean and standard deviation of the noise was determined so that the noise in the final image matches typical experimental signals.
The original image was then convoluted with a Gaussian function with a standard deviation of 200 nm corresponding to the point spread function. The smoothed data were sampled at 40 nm to generate the final pixelized image. To systematically test for the effects of finite signals in the cytoplasm, we kept the standard deviation of the noise and changed only its mean values. The generated images were analyzed using the same scripts as for the experimental data described above. The simulation results suggest that the inside-outside difference in the background signal could potentially influence cell wall thickness measurement (Figure  S1D ). By running a systematic modification of background difference between inside and outside, and signal/noise ratio in simulations, we thus computed the influence of those parameters on the error in thickness measurement (Figure  S1E ).
Those results defined a region in which the predicted error is below 30 nm, which is less than 20% of the typical experimental thickness. We thus used this simulation result as a criterion for image quality, and discarded images or regions of images where the predicted error is out of this accepted region (Figure  S1E ). TEM and CLEM images: The full cell wall in electron microscopy images was detected using custom scripts written in MATLAB, by using a threshold value for the signal intensity. In some images with inhomogeneous contrast, the results were manually updated. The edge of the binarized signal were traced to define the inside and outside boundaries of the cell wall. The normal direction was defined based on the inside cell wall boundary, and the cell wall thickness was defined as the distance between inside and outside boundaries along the normal direction.
To compare EM and light microscopy images in CLEM analyses (Figure  1B   Cell shape, growth and polarity factor concentration measurements: Cell length was generally measured using lectin signals in ImageJ. To compute old end elongation rates visible birth scars were used as fiducial reference landmarks. Tip curvature was computed from the lectin contour defined for cell wall measurements, by fitting a local circle in Matlab  (Bonazzi et al. , 2015). To analyze changes in cell shape, growth rates and localization of polar factors following turgor reduction by sorbitol addition, we developed dedicated Matlab scripts. We first segmented cells using the signal from the lectin-labelled cell wall. To this aim, we first smoothed the image with median and Gaussian filters and detected cell edges using the Laplacian of the Gaussian filter.
ACKNOWLEDGEMENTS The authors acknowledge  P. Perez ,  Y. Sanchez ,  H. Valdivieso ,  T. Toda ,  T. Nakamura  ( YGRC/NBRP Japan ) and  J. Q. Wu , for sharing material. We acknowledge the  ImagoSeine facility , a member of  France BioImaging  ( ANR-10-INSB-04 ). Our laboratory is supported by the  CNRS  and grants from the  FP7 CIG program ,  ITN ''FungiBrain'' , and the  European Research Council  ( CoG Forcaster  no. 647073 ).
Rangogni  [26]  deals with the generalized Laplace equation by coupling the boundary element method with the perturbation method. The method requires an internal network but the unknowns are only on the boundary. Based on the VOF method, Meier et al. [27]  devises a new method, which uses empirical formulas obtained from databases that has been generated and stored in a data bank to determine the interface curvatures. Raessi et al. [28]  presents a new method for calculating interface normal vectors and curvatures, where the interface unit normal is advected along with whatever function represents the interface, and curvatures are calculated directly from these advected normal.
Numerical investigation and discussion In order to study the effect of surface tension in injection moulding process, the evaluation of surface tension force in filling viscous flow is realized by simulation. The development is made on the explicit algorithm with fully vectorial operations  [3] , previously developed in research team. Based on the finite element software developed on Matlab platform, this section focuses on realization and validation of the new developed function for surface tension. elements is shown in Fig. 3. The width of mould inlet W = 10 mm and the mould length L = 5 × W = 50 mm. 316 L stainless steel feedstock density, corresponding to 316 L stainless steel powders and thermoplastic binder based on paraffin wax, is set to be 711 kg. m -3. Feedstock shear viscosity is 20 Pa.
To develop such transport systems and include them on a global urban food policy, it is important to provide relevant decision support tools. Although such tools start to be used for non-food transport, they need to be adapted to the specificity (in demand characterization, distribution schemes, etc. ) to the field of food distribution, and more precisely to that of canteen distribution, for which very few works have been done and remain preliminary. For that reason, this paper proposes a framework to simulate various delivery scenarios, based on the localization of food hubs and capacity of the trucks that are used. The economic and environmental impacts of these scenarios are then assessed. We applied the proposed methodology to the assessment of possible Food hub-based distribution systems using public data from the Great Lyon region.
Waste reduction strategies were proposed. Gebresenbet et al. [27]  evaluated the performance of an integrated food distribution network in a Sweden catering industry by using Geographic Information System (GIS) tools and location analysis techniques. Nevertheless,  [25]  is mainly related to supply chain optimization and  [27]  proposes vehicle routing and location optimization in a computational way (so for theoretical and conceptual). Another characteristic of those works is that food demand is not quantified via a model or empirical procedure, but random-based generations are proposed to illustrate the optimization methods. Moreover, the need of suitable decision support methods for public and private planning in terms of urban distribution has led to the development of decision support systems, some of them being operational nowadays  [28] , like the CLASS platform  [29]  (for urban consolidation and retailing land-use issues), PLUME software  [30]  (for parcel delivery platform location), and some transport flow generation software tools  [31, 32] , mainly based on demand models.
Therefore, the choice of the data that is used and the adaptation of data aggregation and is motivated by the use that is envisioned for the models  [40]. Since we aim to propose a transferable methodology able to be used to any French city, it is important that the different modules of the proposed framework use standard databases able to be produced for any city of France. Moreover, the results of the assessment should be presented in a visual way, so a spatial approach is necessary. To deal with those needs, geographic and demographic data is needed. Since January 2017, different  3 We use mainly the economic activity registry (SIRENE file) and the open address database to geo-localize them. For spatial processing of data (and the calculation of distances and travel times), the most suitable is to use data from existing mapping platforms: Google Maps, Bing, Open Street Maps, etc.
In the proposed framework, we used mainly Open Street Maps, to follow an open data policy. To characterize demand, but also transport supply, data from carrier organization is necessary. It has been obtained from the carriers that will be considered in the scenario assessment, by a combination of quantitative and qualitative data collected from those carriers. To that issue, several semi-directive interviews to shippers, receivers and transport carriers of the considered food distribution system were carried out between September 2016 and May 2017. The information of how carriers are organized will be completed by assumptions to define the different scenarios to assess. Currently, a scenario is defined by a food distribution system, composed by various elements (analogously to other distribution systems,  [41]  as for example): Its network structure: a distribution system can be single echelon (i.
Estimation of the food portion (weight per meal). First, we classify the school canteen type (Primary, Middle or High School). Itis represented by the amount of food consumed (in g/meal) according to the age of the students and the nutritional requirements established by the national government. Then, the average composition per meal G c meal is estimated, where c is the category of school (p: primary school; m: middle school; h: high school). 2. Calculation of the daily demand of the central kitchen, from the overall needs of cooked food and conversion tables (to take into account the eventual losses related to the cooking processes and/or food waste at canteens). The loss coefficient α (which allows to consider the food loses) has been established via primary and secondary data on an average basis, without entering in detail on the management of canteens and the type of cooking preparation and distribution (hot or cold distribution).
Those algorithms are considered standard  [57, 58]  and have been used in many TMS  [52]. Moreover, the VRPH library allows to make the algorithm adaptable to different variants of VRP and then to represent different constraints and characteristics of real transport systems  [55]. In the present work, we used a time optimization since it is the most suitable in urban logistics according to practical issues  [51]. The particularity of the proposed approach is that the route construction procedure is interfaced to the data production modules in order to ensure the correct transferability from one context to another. Therefore, it was necessary to estimate a suitable path between two points to convert the real network into a VRP graph. To do that, the shortest path (in terms of travel time) from two points is pre-calculated using a Dijkstra's algorithm  [59] , using OpenStreetMap to estimate the possible paths between two points.
Finally, the obtained results in terms of travelled distances and times are extracted and used as input data for the estimation of impacts (see next subsection). The optimization problem solved with the VRP algorithm will vary in relation to the constraints and characteristics of the food transport system to assess. For the proposed application field (school canteens), the route construction method was configured according to the following requirements: A fleet of vehicles serves a set of delivery points; The demand of each customer per visit must be satisfied by a vehicle assigned on the route; Each vehicle leaves and returns to the depot; The vehicle capacity should not be exceeded; The delivery stages are single stages and; The working time constraints for the driver and vehicle on each route should not be violated.
To estimate those emissions, we need first to define the vehicles used. As shown by the interviews responses, main vehicles for canteen distribution are Light Commercial Vehicles (3. 5 t), and Heavy-Duty Trucks (14 t). However, a database including trucks from 3. 5 to 44 tons (in five categories) has been built. To each category, the emission functions (which relate each of the considered emissions per kilometre and average speeds) are defined: The emission factors and vehicle kilometres are in most cases split into certain classes of road types (as the use of the average speed for its calculation implies) and vehicle categories. The function f i emission is extracted from the emission database of COPERT V (Computer Programme to calculate Emissions from Road Transport -Methodology and emission factors)  [64].
The database used for function definition is from 2017 and includes the different euro norms (from 3 to 5). For the considered application, we concentrate on Light Commercial Vehicles (3. 5 t) of Euro 4-98/69/EC norm and Heavy-Duty Trucks (14 t) of HD Euro V -EGR. As the trucks make their rounds quasi continuously during the day (with only small waiting times for the delivery of the packages), the cold emissions were considered negligible. Therefore, the estimated emissions are slightly underestimated.
Economic evaluation The estimation of the transportation costs is estimated according to the secondary and primary information obtained. The main economic indicators are presented in the Table  6. The diesel cost was consulted on an official French web site supported by the Ministry of economy and finance, where the French government provides the data of fuel price on France. The vehicle fuel consumption was directly retrieved from the technical data given by the vehicles manufacturer. That information was then discussed and established with the key stakeholders of school canteen distribution during the interviews. Taking into account that each year the distribution operation is developed in 145 days, the daily transportation cost is estimated and detailed in the Table  7. The diesel consumption cost for vehicle 3.
Environmental evaluation The data based extracted is from 2010 regarding the Light Commercial Vehicles (3. 5 t) the Euro 4-98/69/EC and for Heavy Duty Trucks (14 t) the HD Euro V -EGR. The environmental evaluation from the VRP results were estimated for each scenario based on the total distance (km) and the average speed of routes in each scenario. The average speed calculated by the VRP Spreadsheet Solver (VRP-SS) using Bing maps and by ANNONA for each scenario is showed in Table  10. To compare the three scenarios, Tables  11  and 12  show the results of the yearly environmental assessment of the three scenarios. Taking into account the results of all the environmental indicators, the global warming potential (100 years) that is directly linked with fuel consumption, Particulate matter emissions at exhaust (PM), NOX emissions, Volatile Organic compounds that contribute to Photochemical oxidant emissions, the scenario 2 shows less impacts than the others two scenarios.
Conclusions and perspectives This paper proposed a methodology to assess the economic and environmental impacts of city food logistics systems, and applied it to different distribution schemes for the school canteens supply in Lyon (France) to address its application issues. The proposed methodology is divided in two main phases: scenario construction where data are prepared, logistics demand estimated and the resulting delivery routes constructed via a VRP procedure, to estimate travelled distances and total times), and scenario assessment of economic and environmental impacts. To illustrate it, we assessed three scenarios of school food supply in Lyon's conurbation, France. The first is a current distribution system, the second proposed a tion of the central distribution platform, and the third proposed two distribution facilities (one for fresh fruits and vegetables and the second for the other family products).
A further direction of the research would be that of establishing average travel profiles or defining a typology of roads and behaviours to have a higher detail of the different parts of a route (and the resulting speeds for each part). However, the proposed methodology presents other limits. Nowadays, there are not unified and standard databases to quantify food transport flows (only some general surveys on goods transport are available, but they are based on non-perishable goods transport mainly packaged in parcels and pallets). Moreover, canteen distribution data are issued in France mainly from private companies, which imply confidentiality issues and the need of reconstructing part of those data. For those reasons, it is currently difficult to define very specific demand models (for example by type of product, with a fine disaggregation for food supply frequencies, etc.
Since its first inception, aerial photography has been used for topographic mapping. Large-scale aerial photography contributed to the creation of many of the topographic maps around the world. In Indonesia, a 2013 government directive on spatial management has re-stressed the need for topographic maps, with aerial photogrammetry providing the main method of acquisition. However, the large need to generate such maps is often limited by budgetary reasons. Today, SfM (Structure-from-Motion) offers quicker and less expensive solutions to this problem. However, considering the required precision for topographic missions, these solutions need to be assessed to see if they provide enough level of accuracy. In this paper, a popular SfM-based software Agisoft PhotoScan is used to perform bundle adjustment on a set of large-scale aerial images.
The aim of the paper is to compare its bundle adjustment results with those generated by more classical photogrammetric software, namely Trimble Inpho and ERDAS IMAGINE. Furthermore, in order to provide more bundle adjustment statistics to be compared, the Damped Bundle Adjustment Toolbox (DBAT) was also used to reprocess the PhotoScan project. Results show that PhotoScan results are less stable than those generated by the two photogrammetric software programmes. This translates to lower accuracy, which may impact the final photogrammetric product.
, 2015). However, this advantage is also a double-edged sword precisely due to its simplicity. The black-box nature of some of the SfM (Structure from Motion) based commercial software has hindered a proper statistical analysis of its results  (Jaud et al. , 2016). The Indonesian Geospatial Information Agency (BIG, formerly BAKOSURTANAL) specifically uses aerial photogrammetry for mapping purposes; especially large scale mapping. Since 2013, the government policy on spatial planning requires the production of large-scale maps for effective spatial management. Consequently, as the only institution responsible for base geospatial information in the country, BIG is required to be able to provide large-scale maps in large quantities. Budgetary limitations mean that SfM software has become interesting solutions for this purpose.
However, due to the black-box nature of most commercial SfM software, there is a need to test their quality in order to fulfil the required national standard. The objective of this paper is to determine the feasibility of Agisoft PhotoScan, a commercial SfM software programme, to be used in mapping works compared to the results of classical photogrammetric solutions. This will be done by comparing the bundle adjustment results on the same dataset processed in Trimble Inpho and ERDAS IMAGINE Photogrammetry, two photogrammetric programmes which have been used extensively for mapping purposes. Similar assessments to PhotoScan's quality can be found in the literature, for example in the case of close-range photogrammetry  (Murtiyoso et al. , 2018)  or aerial UAV photogrammetry  (James et al. , 2017; Ouédraogo et al.
These improvements to the photogrammetric workflow have given rise to various software solutions providing relatively accurate results with increasingly less and less user involvement. The growing trend of the use of SfMbased software in topographic mapping is also aided by the democratisation of UAVs  (Murtiyoso and Grussenmeyer, 2017). That being said, in terms of topographic survey, mapping agencies such as BIG still prefers to employ photogrammetryfocused software (e. g. Trimble Inpho, ERDAS IMAGINE, etc. ) over SfM-based ones (e. g. Agisoft PhotoScan, Pix4D, etc. ). The main objective of this paper is to determine if one of those software solutions, namely PhotoScan, can be used for largescale topographic mapping. Comparisons between PhotoScan and other solutions has been much addressed in the literature, due to the popularity of the software  (Bedford, 2017).
For example, comparisons has been done in terms of dense point cloud  (Murtiyoso and Grussenmeyer, 2017; Sapirstein, 2016) , Digital Surface Models (DSM)  (Remondino et al. , 2013; Runkel et al. , 2017) , bundle adjustment results  (Murtiyoso et al. , 2018) , or orthophoto generation  (Chiabrando et al. , 2015). This paper will focus on bundle adjustment or aerotriangulation assessment, being one of the most important factors influencing the final precision of topographic mapping. Due to the absence of some bundle adjustment statistics in PhotoScan's results, DBAT (Damped Bundle Adjustment Toolbox)  (Börlin and Grussenmeyer, 2013)  will be used to reprocess the PhotoScan projects. Results were compared to those generated by two photogrammetry-based software programmes, namely Trimble Inpho (Inpho) and ERDAS IMAGINE Photogrammetry (ERDAS).
Agisoft PhotoScan (PhotoScan) is a commercial software which has seen a lot of use in the market  (Burns and Delparte, 2017; Verhoeven, 2011). Inpho on the contrary is a standard aerial photogrammetry software solution which has been employed by BIG for metric mapping projects. It is capable of performing a complete photogrammetric data processing, including bundle adjustment. Tie points extraction and matching are run automatically using two algorithms, feature based matching (FBM) for creating new points and least squares matching (LSM) for refining existing points  (Cramer, 2013). ERDAS has a similar algorithm with Inpho to process the data. Meanwhile, the bundle adjustment process in PhotoScan is hidden so the quality control is difficult to perform due to the scarcity of project diagnostic.