dataesr/scientific-paragraphs-categorization huggingface dataset:
We thus set ν = ν l = 5, µ = 10 -3 , ρ 1 = 10 -2 , ρ 2 = 10 -2 , γ1 = 0. 9, γ2 = 2, α = β = 0. 1, ξ = 3/4, γ min = 10 -16 , and γ 0 = 1. For the sequence {a k }, we used a 0 = min 0. 1 max(1, C j ), W j (g j ) + C j and a k = a 0 (k + 1) -1/2 ∀k ≥ 1. In all our variants, the Lagrange multipliers y j are computed as the solution of min y g j -J c j y 2 2. We implemented Algorithm 2. 2 in an exact and an inexact variant, respectively using direct and iterative linear algebra. For the exact variant, named LM-EC-EXACT, the subproblems (2. 1) and (2. 5) are solved with the backslash Matlab operator (which uses the UMFPACK Fortran library). Direct elimination based on Matlab's LU-factorization routine was used to compute W j = Γ j (Γ ⊤ j Γ j ) -1 Γ ⊤ j where Γ j = P ⊤ j -L -⊤ j N ⊤ j I n-p , where N j ∈ R (n-p)×p , L j ∈ R p×p (a lower triangular matrix), and P j (permutation matrix) are computed from a factorization of the Jacobian matrix J c j of the form L j N j R j = P j J c j.
6) with the same tolerance. Finally, the vector t j and the projection operator W j are computed using minres with the tolerance min{1e-4, max{1e-15,min{ n j , 1/γ 2 j }}}. For comparison, we implemented a Gauss-Newton solver that does not rely on regularization: the underlying iteration is x j+1 = x j + n j + t j , where n j and t j are respectively solutions of (2. 1) and (2. 5) with γ j = 0. As for our proposed solver, we implemented two variants of the Gauss-Newton method; an exact version, termed GN-EC-EXACT, where the two steps n j and t j are computed using the backslash Matlab operator; and a matrix-free implementation, named GN-EC-MATRIXFREE, where the steps are computed using the same procedure as our matrix-free implementation of Algorithm 2. 2. Our tests also include an implementation of the nonmonotone SQP trust-region method  [28] : this trust-region solver will be referred to as TR-EC-EXACT.
4. 4. A PDE-constrained optimization problem. We now study a leastsquares problem with a hyperbolic forward PDE as equality constraints  [10]. Given a time interval [0, T ], a time dependent density field y(x, t), and a time velocity field u(x, t), one wishes to solve the constrained nonlinear least-squares problem (4. 2) min (y,u) f ([y, u]) := 1 2 Qy -z 2 + 1 2 Ω (u -u r ) 2 + |∇(u -u r )| 2 s. t. y + ∇ • (yu) = 0 y(0, x) = y 0. where u r is a chosen reference model. Given the forward problem on y, the operator Q represents the projection of y onto the space of the data z. Since problem (4. 2) is infinite-dimensional, we considered a discretization grid such that d = 4096. To this end, we adapted the existing Matlab implementation of this problem available online 1. To initialize the variables in each optimization procedure, we used the reference model for u and zero for y.
Due to the nature of the PDE problem, only matrix-free optimization solvers can be used, hence only LM-EC-MATRIXFREE and GN-EC-MATRIXFREE were tested on this problem. Figure  4. 3 shows the first 200 iterations of the two methods. Within 200 iterations, our proposed approach is able to reduce both the norm of the gradient and the norm of the constraints below 10 -5. The Gauss-Newton method converges to a feasible point but does not reach a first-order optimal solution as the norm of the projected gradient remains large. where {θ m , θ im , V m , α, D m } are parameters, c m and c im are the functions to determine, ĥ is the infinite-dimensional observation vector, and Ω × T = (0, 80) × (0, 2. 55] is the domain. The initial conditions are that c im (x, 0) = 0 and c m (x, 0) = 0. In order to generate the measurements, we took the values of the parameters corresponding to the lowest residual in the reported results in  [24] , and simulated the PDE using a spatial discretization with n x = 16 using the ode15s MATLAB function, which generated a time discretization of n t = 197.
More specifically, the sensitivity of the model to these determinants and the way OLYMPUS can help explore the main levers of air quality will be discussed, putting into perspective the potential of the model with regard to the needs of decision support. The next paragraph is devoted to presenting the general approach underlying the development of the model. The structure of the code and the methodological and numerical choices are also presented and commented on, in view of the ambitions of the model. Then, in the last part, the data generated during the implementation of OLYMPUS in two French regions are presented as a basis for reflection on the key parameters of pollutant emissions in the model.
Model structure and operation OLYMPUS is a numerical modeling platform whose code is entirely written in Python. OLYMPUS is a numerical modeling platform whose code is entirely written in Python and based on the simulation of the practices of a population of agents. To do this, it integrates meta-models -and notably activity-based models, gravity models and utility models that restitute the agents' decisions linked with mobility and energy consumption. In accordance with the aims and goals described above, OLYMPUS is structured around three main calculation blocks, as shown in Fig. 2  This figure presents the central concepts of the current implementation of the model (blue lozenges), the sequential organization of the calculations performed by mathematical models (green squares) and the main components (indicators and meta-parameters) produced during the simulation (pink squares).
Emissions The pollutant and GHG emissions calculated by OLYMPUS result from the total energy demand of the buildings, and from the integration and spatialization of all agents' trips described above. In OLYMPUS, the modelling of combustion emissions in buildings is based on combustion activities for residential, institutional and commercial heating, but also for hot water production and cooking. To determine household energy demand, the key data is the unit consumption of households, in kWh/m², and is derived from surveys. It is then cross-referenced with data on average housing areas by type of dwelling, type of household and housing area (based on the work carried out in Block 1). To model the institutional and commercial sector, the module is based on annual consumption data per employee and locates these emissions in the employment centers, according to their respective capacities.
The OLYMPUS emission maps for this sector is thus fully determined by the parameterization of the link between UDI / housing / energy mix per housing. In OLYMPUS, energy distribution is a parameter based on survey data, and therefore easily adaptable to the site under consideration, but the data does not always exist with the desired refinement. Moreover, the data are rapidly evolving (especially with the recent transition to closed fireplaces and more environmentally friendly stoves). In any case, it is an important air quality lever, the role of which in winter episodes of particulate pollution can and should be investigated. Quantitatively speaking, an interesting result is the ability of OLYMPUS to understand the utility of modal supply and to capture the modal share of private vehicle trips, using the random utility equations of the transport module.
Acknowledgements The work presented here received support from the  French department Val-de-Marne , the  French Ecological transition agency (ADEME) , the  PRIMEQUAL program  ( POLL-EPXO/Convention 1862C0012 ), the  French National Agency for Research  ( VITE!/ANR-14-CE22-0013 ) and the  Île-de-France region  ( DIM R2DS  and  DIM QI2 ). It was initiated in the frame of the LABEX Urban Futures and performed using HPC resources from  GENCI-CCRT  (grant no. 2017-t2015017232 ). We specially acknowledge AIRPARIF for providing data.
QUANTIFICATION AND ANALYSIS The principal problem which our project encountered in the aisles at Tewkesbury was how to quantify such curvatures and the stonelaying practices which produced them. Before this point, the digital techniques which we had developed were exclusively focused on analysing rib geometries, following the principle established by the 19th-century scholar Robert Willis (1842) that ribs were the defining elements of a vault's three-dimensional form. Surveys were conducted using digital laser scans taken at strategic points in each of our case study sites, creating detailed point cloud models made up from hundreds of thousands of individual measurements. These were then converted into mesh models which could be imported into Rhinoceros, an advanced 3D modelling program. The software was then used to trace the intrados lines of each rib in three-dimensions, producing a wireframe model of best fit curves.
An alternative method which we attempted was height mapping. This is a method of indicating the differences in height across the surface of the vault using a graduated change in colour. This was accomplished using a script written using Grasshopper, a plug-in for Rhinoceros which uses an advanced visual programming language as a parametric design tool. Mesh models are a polygonal surface consisting of tens of thousands of triangular facets, forming a mesh of lines connecting individual points or vertices. Our script deconstructed the mesh into these vertices and extracted the z component of their coordinates within Rhinoceros, giving a numerical value for the height  of each vertex. Each point was then mapped automatically onto a colour gradient extending from black (top) to white (bottom), producing a new texture which was then overlaid onto the surface of the model (Figure  7 ).
The level floor (facing upwards) would possess a value of (0, 0, 1) and the walls (facing inwards) a z component of 0, with the north wall represented by (0, -1, 0), the south wall (0, 1, 0), the west wall (1, 0, 0) and east wall (-1, 0, 0). Alternatively, if the room had a ceiling sloping upwards from east to west at an angle of 45 • , then its surface would possess a y component of 0, an x component of -√ 0. 5 and a z component of -√ 0. 5, resulting in a value of (-0. 707, 0. 000, -0. 707) to three significant figures. As in the case of height mapping, we were able to use a Grasshopper script to extract the individual components of the normal vectors automatically and position them on a colour gradient that could be overlaid directly onto the mesh model (Figure  8 ). If the z component is isolated, the resulting texture relates the changing slope of the vault surface from block to block, the shade assigned to each face indicating how close its gradient is to that of a flat ceiling (-1, black), wall (0, grey) or floor (1, white).
Estimates for the shape and structure of the stones beneath the surface of the webbing will be provided by comparative study of ruined or partially deconstructed vaults at other sites, as well as reference data relating the material properties of the stone and mortar. This numerical model will then be validated using small scale construction experiments of parts of the vault, allowing us to test whether our theoretical modelling could work in practice. Even if such a modelling process is ultimately inconclusive, the form of the masonry at Tewkesbury has far wider implications for the study of medieval design and construction processes. The cambered surfaces of the webbing indicate that their form was not solely defined by the geometry of the surrounding ribs. Instead, the stonelaying process itself was integral to the conception of the vault's three-dimensional form, constituting as much a process of active design as passive realization.
ACKNOWLEDGEMENTS The research contained in this paper would not have been possible without the efforts of  J. R. Peterson  and  Sarah Duffy  ( University of Liverpool, Liverpool, UK ), who helped to gather and process the data. We would also like to acknowledge the invaluable contributions of  Jenny Alexander  ( University of Warwick, Coventry, UK ),  Han-Mei Chen  ( University of Liverpool ),  Stuart Harrison  ( University of York, York, UK ) and  Richard Plant  ( Christie's Education, London, UK ), who advised us during the research process.
Fragmentation is also likely to change the mechanical properties of the ice, but the evolution of dynamical and mechanical properties of sea ice cover with floe size remains poorly understood. Intuitively, we expect that broken ice is more mobile than continuous ice (e. g. McPhee, 1980) , having lower internal stress. This seems to be consistent with the deformation observations of  Oikkonen et al. (2017)  collected by ship radar during the N-ICE-2015 expedition. In their observations, deformation in fragmented sea ice was an order of magnitude higher than in the pack. However, in the absence of routinely available datasets providing synoptic information on sea ice drift, wave height and floe size in the MIZ, observations do not allow us to arrive at any explicit relationship between the level of fragmentation and the ability of sea ice cover to be deformed.
(2018). We also used the same sea ice concentration data as  Ardhuin et al. (2018)  to force the uncoupled wave model. They were obtained from a re-analysis of the 3 km resolution sea ice concentration dataset derived from the AMRS2 radiometer using the ASI algorithm  (Kaleschke et al. , 2001; Spreen et al. , 2008)   1. This re-analysis produced 12-hourly maps that gathered all the AMSR2 passes acquired between 00:00 and 13:59 UTC and 10:00 and 23:59 UTC for the morning (AM) and evening (PM) fields, respectively. Similarly to  Ardhuin et al. (2018) , sea ice thickness was set constant to 15 cm. Sea ice concentration was also kept constant to make the comparison with a coupled simulation easier. Sea ice concentration for this 3 d run corresponded to the conditions on the evening of 12 October provided by the AMSR-2 sea ice concentration re-analysis at the same time as illustrated in  Ardhuin et al.
Acknowledgements. This work was carried out as part of the  Copernicus Marine Environment Monitoring Service (CMEMS) WIzARd  project. CMEMS is implemented by Mercator Ocean in the framework of a delegation agreement with the  European Union. It was also funded by institutional support from the  Nansen Center. We thank the editor, the two anonymous reviewers and  Christopher Horvat  for their suggestions and their support for the publication of the manuscript. Finally, we thank  Fabrice Ardhuin  for providing the wave height data from SAR. Financial support. This research was supported by the  CMEMS (WIzARd)  and the  NERSC  (internal funding). Review statement. This paper was edited by  Daniel Feltham  and reviewed by  Christopher Horvat  and two anonymous referees.
For instance, turning, a cutting tool has to make several revolutions around the part. It is obvious that the tool relaxes part of the residual stress state induced during the previous revolutions, and at the same time, it induces its own residual stresses. This phenomenon has been revealed by  [23]. As a consequence, a steady state can be reached only after several revolutions. Some authors, such as  [24] , proposed to couple two Lagrangian plane models: simulation containing the cutting direction (orthogonal cutting) and another simulation considering an indentation-like configuration of a corner radius into the machined surface. Recently  [25]  proposed to use a 3D Lagrangian formulation (DEFORM software) to predict residual stresses induced in longitudinal turning. The main limitation of this work comes from the explicit and Lagrangian formulations previously discussed.
Recently  [25]  proposed to use a 3D Lagrangian formulation (DEFORM software) to predict residual stresses induced in longitudinal turning. The main limitation of this work comes from the explicit and Lagrangian formulations previously discussed. Moreover, the computational time is very long that makes it difficult for an industrial use. An alternative approach, proposed by  [23] , consists of modelling the residual stress generation by removing the chip formation and replacing it with equivalent thermomechanical loadings (Figure  1 ). The thermal and mechanical loadings have various shapes depending on the active area, such as the primary shear zone (PSZ), in front of the cutting tool, or the third shear zone (TSZ), below the flank face. The magnitude of the thermomechanical loading is calibrated by means of preliminary experimental tests: friction tests and orthogonal cutting tests, as described by  [23].
The combination of simple thermo-mechanical distributions of loadings with experimental parameters (force, chip thickness, contact length, etc. ) is the origin of its name: the 3D hybrid model (hybrid means experimental data and numerical calculation). These equivalent loadings are moved onto the machined surface with a velocity equal to the cutting speed. After several revolutions (enabling a 3D steady state), this model makes the prediction of 3D residual stress fields possible (Figure  2 ). This hybrid model for residual stress prediction, based on an implicit formulation in the SYS-WELD software, presents advantages like the absence of highly distorted mesh, the possibility of 3D multi-revolution simulations and accurate mechanical equilibrium computation after the cooling phase. A good agreement is obtained between the predicted and analyzed residual stress profiles (X-Ray diffraction method) for a finished, longitudinal turning operation on 15-5PH martensitic stainless steel  [23].
After several revolutions (enabling a 3D steady state), this model makes the prediction of 3D residual stress fields possible (Figure  2 ). This hybrid model for residual stress prediction, based on an implicit formulation in the SYSWELD software, presents advantages like the absence of highly distorted mesh, the possibility of 3D multi-revolution simulations and accurate mechanical equilibrium computation after the cooling phase. A good agreement is obtained between the predicted and analyzed residual stress profiles (X-ray diffraction method) for a finished, longitudinal turning operation on 15-5PH martensitic stainless steel  [23]. However, this work has only been validated for a single case study and for 3 feed rates. This paper relates to longitudinal turning operations. The objective consists of investigating the reliability of this 3D multi-revolution numerical model, by proposing a sensitivity study of cutting speed, feed rate, cutting tool geometry and cutting tool flank wear.
Experimental Database and Residual Stresses Measurements Initially, the sensitivity study was performed experimentally. The longitudinal turning operations were performed on a 15-5PH (i. e. , X5CrNiCu15-5) martensitic stainlesssteel cylinder, as shown in Figure  3. This material is used in the aircraft industry for safety components that should stand high mechanical cyclic loadings such as transmission shafts. In this work, the material was in its H1025 state. As this material has not been widely investigated in the scientific literature, the mechanical properties have been characterized by tensile stresses. All the results are available in  [26]  (yield strength ~1000 MPa -ultimate tensile strength ~1100 MPa-hardness ~331 HB). This paper relates to longitudinal turning operations. The objective consists of investigating the reliability of this 3D multi-revolution numerical model, by proposing a sensitivity study of cutting speed, feed rate, cutting tool geometry and cutting tool flank wear.
Experimental Database and Residual Stresses Measurements Initially, the sensitivity study was performed experimentally. The longitudinal turning operations were performed on a 15-5PH (i. e. , X5CrNiCu15-5) martensitic stainless-steel cylinder, as shown in Figure  3. This material is used in the aircraft industry for safety components that should stand high mechanical cyclic loadings such as transmission shafts. In this work, the material was in its H1025 state. As this material has not been widely investigated in the scientific literature, the mechanical properties have been characterized by tensile stresses. All the results are available in  [26]  (yield strength ~1000 MPa -ultimate tensile strength ~1100 MPa-hardness ~331 HB). This paper relates to longitudinal turning operations. The objective consists of investigating the reliability of this 3D multi-revolution numerical model, by proposing a sensitivity study of cutting speed, feed rate, cutting tool geometry and cutting tool flank wear.
Experimental Database and Residual Stresses Measurements Initially, the sensitivity study was performed experimentally. The longitudinal turning operations were performed on a 15-5PH (i. e. , X5CrNiCu15-5) martensitic stainlesssteel cylinder, as shown in Figure  3. This material is used in the aircraft industry for safety components that should stand high mechanical cyclic loadings such as transmission shafts. In this work, the material was in its H1025 state. As this material has not been widely investigated in the scientific literature, the mechanical properties have been characterized by tensile stresses. All the results are available in  [26]  (yield strength ~1000 MPa -ultimate tensile strength ~1100 MPa-hardness ~331 HB). As the objective of the paper is to investigate the sensitivity to cutting speed, feed rate, cutting tool geometry and cutting tool flank wear, a reference case study corresponding to the investigated industrial case study (test n 2 in Table  1 ) has been considered.
This paper presents an overview of emerging memory technologies. It begins with the presentation of stand-alone and embedded memory technology evolution, since the appearance of Flash memory in the 1980s. Then, the progress of emerging memory technologies (based on filamentary, phase change, magnetic, and ferroelectric mechanisms) is presented with a review of the major demonstrations in the literature. The potential of these technologies for storage applications addressing various markets and products is discussed. Finally, we discuss how the rise of artificial intelligence and bio-inspired circuits offers an opportunity for emerging memory technology and shifts the application from pure data storage to storage and computing tasks, and also enlarges the range of required specifications at the device level due to the exponential number of new systems and architectures.
Then, critical limits led to the appearance of 3D memory  [16]  that entered the market in ~2015 and changed the conservative memory world. In 2020, vertical NAND stacked up to 96 layers, used QLC (quad level cells, four bits per cells) and reached a density of about 10 Gb/mm 2 , with typical memory capacities of one terabyte  [17]. In 21 years, multilevel cell flash memory density has increased 10,000 times. Flash NAND has been adopted in solid state drives (SSD) over the past 10 years and now shares the data storage market with hard disk drives (HDD) thanks to its constant decreasing bit cost. Three-dimensional NAND continues to improve and is expected to continue as a leading technology for data storage  [1]. In the case of 3D NAND, scaling is mainly achieved by stacking, making it possible to retain the same cell dimensions in some successive nodes to maintain cell characteristics.
The technology is used as a storage class memory to fill the latency gap between DRAM and NAND in the memory hierarchy. Two types were initially envisaged with two different locations in the system  [1] : "Storage mapped" is part of the memory hierarchy with typical 128 Gb memory capacities. The memory is faster than NAND, has higher endurance, and is 10X more dense than conventional memories. "Memory mapped" is a shadow of DRAM; data in DRAM are copied to the 3D XPoint in order to expand the size of the main memory. Intel has proposed Optane. Intel Optane DC Persistent and SSD/Caches memories can achieve 100s ns and 1s µs, respectively, allowing significant improvement of computer architecture  [79]. Micron also offered the X100 NVMe™ SSD cache memory based on 3D XPoint™ Technology. STMicroelectronics also provides PCRAM technology for automotive embedded applications for 28 nm node and beyond  [80, 81].