Miracle-dz/UniFAR-FTUs huggingface dataset:
Page Proof Instructions and Queries

Estuaries are sensitive to changes in global to regional sea level to climate-driven variation in rainfall and to fluvial discharge. In this study, we use source and environmentally sensitive proxies together with radiocarbon dating to examine a 7-m-thick sedimentary record from the Sado estuary accumulated throughout the last 3.6 kyr. The lithofacies, geochemistry and diatom assemblages in the sediments accumulated between 3570 and 3240 cal. BP indicate a mixture between terrestrial and marine sources. The relative contribution of each source varied through time as sedimentation progressed in a low intertidal to high subtidal and low-energy accreting tidal flat. The sedimentation proceeded under a general pattern of drier and higher aridity conditions, punctuated by century-long changes of the rainfall regime that mirror an increase in storminess that affected SW Portugal and Europe. The sediment sequence contains evidence of two periods characterized by downstream displacement of the estuarine/freshwater transitional boundary, dated to 3570–3400 cal. BP and 3300–3240 cal. BP. These are intercalated by one episode where marine influence shifted upstream. All sedimentation episodes developed under high terrestrial sediment delivery to this transitional region, leading to exceptionally high sedimentation rates, independently of the relative expression of terrestrial/marine influences in sediment facies. Our data show that these disturbances are mainly climate-driven and related to variations in rainfall and only secondarily with regional sea-level oscillations. From 3240 cal. BP onwards, an abrupt change in sediment facies is noted, in which the silting estuarine bottom reaches mean sea level and continued accreting until present under prevailing freshwater conditions, the tidal flat changing to an alluvial plain. The environmental modification is accompanied by a pronounced change in sedimentation rate that decreased by two orders of magnitude, reflecting the loss of accommodation space rather than the influence of climate or regional sea-level drivers.
of benthic macrofauna in a protected area of the northern Adriatic Sea: a three-year study

The macrozoobenthic community at a sublittoral station located in the Marine Protected Area of Miramare, Gulf of Trieste (Italy) was investigated monthly from June 2002 to July 2005. Community variables were studied and related to food sources (particulate, total and biopolymeric carbon contents, benthic microalgae and meiofauna). In addition, macrofaunal response to a heatwave that occurred in summer 2003 in the area was also explored. Univariate and multivariate analyses highlighted that the macrozoobenthic community structure shifted towards the end of the study. Diversity remained fairly stable throughout the study, despite the high turnover values. From a dominance of short-lived invertebrates related to irregular fresh organic matter inputs, the community shifted toward long-lived taxa, principally related to an increase of biopolymeric C and microalgal biomass. Semelpa- rous invertebrates seem to be less resistant to high temperatures compared to iteroparous ones. The latter proved to be capable competitors since they prevailed over the semelparous species towards the end of the study. The community exhibited a certain degree of resistance to high temperature, due to the adaptation of the macrofaunal invertebrates to this particular stress, induced by the wide natural fluctuations in temperature that occur on a seasonal basis in the Gulf of Tri- este. This study highlights the importance of long datasets to assess the state and ecological processes of macrofaunal communities.
Acoustic rendering with wave field synthesis

Wave Field Synthesis is a method of sound reproduction, based on the precise construction of the desired wave field by secondary sources, implemented as arrays of loudspeakers. The method is derived from acoustic wave field theory, and implemented in a practical approach based on physical as well as perceptual laws. An overview is given of the theory, the implementation as a Laboratory Demonstration System and some interesting applications of the method. Presently, the method is further developed in an ISTproject of the European Commission, called CARROUSO.
WallPlan

Floorplan generation has drawn widespread interest in the community. Recent learning-based methods for generating realistic floorplans have made significant progress while a complex heuristic post-processing is still necessary to obtain desired results. In this paper, we propose a novel wall-oriented method, called WallPlan, for automatically and efficiently generating plausible floorplans from various design constraints. We pioneer the representation of the floorplan as a wall graph with room labels and consider the floorplan generation as a graph generation. Given the boundary as input, we first initialize the boundary with windows predicted by WinNet. Then a graph generation network GraphNet and semantics prediction network LabelNet are coupled to generate the wall graph progressively by imitating graph traversal. WallPlan can be applied for practical architectural designs, especially the wall-based constraints. We conduct ablation experiments, qualitative evaluations, quantitative comparisons, and perceptual studies to evaluate our method's feasibility, efficacy, and versatility. Intensive experiments demonstrate our method requires no post-processing, producing higher quality floorplans than state-of-the-art techniques.
Efficient estimation of boundary integrals for path-space differentiable rendering

Boundary integrals are unique to physics-based differentiable rendering and crucial for differentiating with respect to object geometry. Under the differential path integral framework---which has enabled the development of sophisticated differentiable rendering algorithms---the boundary components are themselves path integrals. Previously, although the mathematical formulation of boundary path integrals have been established, efficient estimation of these integrals remains challenging. In this paper, we introduce a new technique to efficiently estimate boundary path integrals. A key component of our technique is a primary-sample-space guiding step for importance sampling of boundary segments. Additionally, we show multiple importance sampling can be used to combine multiple guided samplings. Lastly, we introduce an optional edge sorting step to further improve the runtime performance. We evaluate the effectiveness of our method using several differentiable-rendering and inverse-rendering examples and provide comparisons with existing methods for reconstruction as well as gradient quality.
True seams

Seams play a fundamental role in the way a garment looks, fits, feels and behaves. Seams can have very different shapes and mechanical properties depending on how fabric is overlapped, folded and stitched together, with garment designers often choosing specific seam and stitch type combinations depending on the appearance and behavior they want for the garment. Yet, virtually all 3D CAD tools for fashion and visual effects ignore most of the visual and mechanical complexity of seams, and just treat them as joint edges, their simplest possible form, drastically limiting the fidelity of digital garments. In this paper, we present a method that models seams following their true, real-life construction. Each seam brings together and overlaps the fabric pieces to be sewn, folds the fabric according to the type of seam, and stitches the resulting assembly following the type of stitch. To avoid dealing with the complexities of folding in 3D space, we cast the problem into a sequence of simpler 2D problems where we can easily shape the seam and produce a result free of self-intersections, before lifting the folded geometry back to 3D space. We run a series of constrained optimizations to enforce spatial properties in these 2D settings, allowing us to treat asymmetric seams, gatherings and overlapping construction orders. Using a variety of common seams and stitches, we show how our approach substantially improves the visual appearance of full garments, for a better and more predictive digital replica.
Efficient kinetic simulation of two-phase flows

Real-life multiphase flows exhibit a number of complex and visually appealing behaviors, involving bubbling, wetting, splashing, and glugging. However, most state-of-the-art simulation techniques in graphics can only demonstrate a limited range of multiphase flow phenomena, due to their inability to handle the real water-air density ratio and to the large amount of numerical viscosity introduced in the flow simulation and its coupling with the interface. Recently, kinetic-based methods have achieved success in simulating large density ratios and high Reynolds numbers efficiently; but their memory overhead, limited stability, and numerically-intensive treatment of coupling with immersed solids remain enduring obstacles to their adoption in movie productions. In this paper, we propose a new kinetic solver to couple the incompressible Navier-Stokes equations with a conservative phase-field equation which remedies these major practical hurdles. The resulting two-phase immiscible fluid solver is shown to be efficient due to its massively-parallel nature and GPU implementation, as well as very versatile and reliable because of its enhanced stability to large density ratios, high Reynolds numbers, and complex solid boundaries. We highlight the advantages of our solver through various challenging simulation results that capture intricate and turbulent air-water interaction, including comparisons to previous work and real footage.
Shape dithering for 3D printing

We present an efficient, purely geometric, algorithmic, and parameter free approach to improve surface quality and accuracy in voxel-controlled 3D printing by counteracting quantization artifacts. Such artifacts arise due to the discrete voxel sampling of the continuous shape used to control the 3D printer, and are characterized by low-frequency geometric patterns on surfaces of any orientation. They are visually disturbing, particularly on small prints or smooth surfaces, and adversely affect the fatigue behavior of printed parts. We use implicit shape dithering, displacing the part's signed distance field with a high-frequent signal whose amplitude is adapted to the (anisotropic) print resolution. We expand the reverse generalized Fourier slice theorem by shear transforms, which we leverage to optimize a 3D blue-noise mask to generate the anisotropic dither signal. As a point process it is efficient and does not adversely affect 3D halftoning. We evaluate our approach for efficiency, geometric accuracy and show its advantages over the state of the art.
Physics-based character controllers using conditional VAEs

High-quality motion capture datasets are now publicly available, and researchers have used them to create kinematics-based controllers that can generate plausible and diverse human motions without conditioning on specific goals (i.e., a task-agnostic generative model). In this paper, we present an algorithm to build such controllers for physically simulated characters having many degrees of freedom. Our physics-based controllers are learned by using conditional VAEs, which can perform a variety of behaviors that are similar to motions in the training dataset. The controllers are robust enough to generate more than a few minutes of motion without conditioning on specific goals and to allow many complex downstream tasks to be solved efficiently. To show the effectiveness of our method, we demonstrate controllers learned from several different motion capture databases and use them to solve a number of downstream tasks that are challenging to learn controllers that generate natural-looking motions from scratch. We also perform ablation studies to demonstrate the importance of the elements of the algorithm. Code and data for this paper are available at: https://github.com/facebookresearch/PhysicsVAE
Affine body dynamics

Simulating stiff materials in applications where deformations are either not significant or else can safely be ignored is a fundamental task across fields. Rigid body modeling has thus long remained a critical tool and is, by far, the most popular simulation strategy currently employed for modeling stiff solids. At the same time, rigid body methods continue to pose a number of well known challenges and trade-offs including intersections, instabilities, inaccuracies, and/or slow performances that grow with contact-problem complexity. In this paper we revisit the stiff body problem and present ABD, a simple and highly effective affine body dynamics framework, which significantly improves state-of-the-art for simulating stiff-body dynamics. We trace the challenges in rigid-body methods to the necessity of linearizing piecewise-rigid trajectories and subsequent constraints. ABD instead relaxes the unnecessary (and unrealistic) constraint that each body's motion be exactly rigid with a stiff orthogonality potential, while preserving the rigid body model's key feature of a small coordinate representation. In doing so ABD replaces piecewise linearization with piecewise linear trajectories. This, in turn, combines the best of both worlds: compact coordinates ensure small, sparse system solves, while piecewise-linear trajectories enable efficient and accurate constraint (contact and joint) evaluations. Beginning with this simple foundation, ABD preserves all guarantees of the underlying IPC model we build it upon, e.g., solution convergence, guaranteed non-intersection, and accurate frictional contact. Over a wide range and scale of simulation problems we demonstrate that ABD brings orders of magnitude performance gains (two- to three-orders on the CPU and an order more when utilizing the GPU, obtaining 10, 000× speedups) over prior IPC-based methods, while maintaining simulation quality and nonintersection of trajectories. At the same time ABD has comparable or faster timings when compared to state-of-the-art rigid body libraries optimized for performance without guarantees, and successfully and efficiently solves challenging simulation problems where both classes of prior rigid body simulation methods fail altogether.
Dynamic optimal space partitioning for redirected walking in multi-user environment

In multi-user Redirected Walking (RDW), the space subdivision method divides a shared physical space into sub-spaces and allocates a sub-space to each user. While this approach has the advantage of precluding any collisions between users, the conventional space subdivision method suffers from frequent boundary resets due to the reduction of available space per user. To address this challenge, in this study, we propose a space subdivision method called Optimal Space Partitioning (OSP) that dynamically divides the shared physical space in real-time. By exploiting spatial information of the physical and virtual environment, OSP predicts the movement of users and divides the shared physical space into optimal sub-spaces separated with shutters. Our OSP framework is trained using deep reinforcement learning to allocate optimal sub-space to each user and provide optimal steering. Our experiments demonstrate that OSP provides higher sense of immersion to users by minimizing the total number of reset counts, while preserving the advantage of the existing space subdivision strategy: ensuring better safety to users by completely eliminating the possibility of any collisions between users beforehand. Our project is available at https://github.com/AppleParfait/OSP-Archive.
A unified newton barrier method for multibody dynamics

We present a simulation framework for multibody dynamics via a universal variational integration. Our method naturally supports mixed rigid-deformables and mixed codimensional geometries, while providing guaranteed numerical convergence and accurate resolution of contact, friction, and a wide range of articulation constraints. We unify (1) the treatment of simulation degrees of freedom for rigid and soft bodies by formulating them both in terms of Lagrangian nodal displacements, (2) the handling of general linear equality joint constraints through an efficient change-of-variable strategy, (3) the enforcement of nonlinear articulation constraints based on novel distance potential energies, (4) the resolution of frictional contact between mixed dimensions and bodies with a variational Incremental Potential Contact formulation, and (5) the modeling of generalized restitution through semi-implicit Rayleigh damping. We conduct extensive unit tests and benchmark studies to demonstrate the efficacy of our method.
Moving level-of-detail surfaces

We present a simple, fast, and smooth scheme to approximate Algebraic Point Set Surfaces using non-compact kernels, which is particularly suited for filtering and reconstructing point sets presenting large missing parts. Our key idea is to consider a moving level-of-detail of the input point set which is adaptive w.r. t. to the evaluation location, just such as the samples weights are output sensitive in the traditional moving least squares scheme. We also introduce an adaptive progressive octree refinement scheme, driven by the resulting implicit surface, to properly capture the modeled geometry even far away from the input samples. Similarly to typical compactly-supported approximations, our operator runs in logarithmic time while defining high quality surfaces even on challenging inputs for which only global optimizations achieve reasonable results. We demonstrate our technique on a variety of point sets featuring geometric noise as well as large holes.
Procedural texturing of solid wood with knots

We present a procedural framework for modeling the annual ring pattern of solid wood with knots. Although wood texturing is a well-studied topic, there have been few previous attempts at modeling knots inside the wood texture. Our method takes the skeletal structure of a tree log as input and produces a three-dimensional scalar field representing the time of added growth, which defines the volumetric annual ring pattern. First, separate fields are computed around each strand of the skeleton, i.e., the stem and each knot. The strands are then merged into a single field using smooth minimums. We further suggest techniques for controlling the smooth minimum to adjust the balance of smoothness and reproduce the distortion effects observed around dead knots. Our method is implemented as a shader program running on a GPU with computation times of approximately 0.5 s per image and an input data size of 600 KB. We present rendered images of solid wood from pine and spruce as well as plywood and cross-laminated timber (CLT). Our results were evaluated by wood experts, who confirmed the plausibility of the rendered annual ring patterns. Link to code: https://github.com/marialarsson/procedural_knots.
Developability-driven piecewise approximations for triangular meshes

We propose a novel method to compute a piecewise mesh with a few developable patches and a small approximation error for an input triangular mesh. Our key observation is that a deformed mesh after enforcing discrete developability is easily partitioned into nearly developable patches. To obtain the nearly developable mesh, we present a new edge-oriented notion of discrete developability to define a developability-encouraged deformation energy, which is further optimized by the block nonlinear Gauss-Seidel method. The key to successfully applying this optimizer is three types of auxiliary variables. Then, a coarse-to-fine segmentation technique is developed to partition the deformed mesh into a small set of nearly discrete developable patches. Finally, we refine the segmented mesh to reduce the discrete Gaussian curvature while keeping the patches smooth and the approximation error small. In practice, our algorithm achieves a favorable tradeoff between the number of developable patches and the approximation error. We demonstrate the feasibility and practicability of our method over various examples, including seventeen physical manufacturing models with paper.
Preparation, Characterization and Properties of Ti3C2TX MXene Aerogel

Abstract As a new kind of carbon nanomaterial, MXene not only has the characteristics of high specific surface area and high conductivity, but also has the advantages of flexible composition and controllable minimum nanometer thickness. The large specific surface and large number of functional groups provide rich active sites for it, which is an ideal adsorbent for the removal of heavy metal ions and dyes [1,2]. The unique structure of aerogel can not only give full play to the inherent physical and chemical properties of monolayer MXene, solve the problem of easy agglomeration of MXene lamella, but also give it uniform and dense porosity, which can greatly improve the adsorption effect, and the macro structure is easy to recycle when used in water phase, reducing the secondary pollution it may bring to the environment. In this project, Ti3C2Tx aerogels with excellent mechanical properties and stability were prepared, and Ti3C2Tx MXene/CNTs aerogels were compounded with carbon nanotubes, and the adsorption performance of Pb2+ in water was investigated at different temperatures and pH values, It can purify water source polluted by heavy metals discharged by industry greatly [3–5]. The following topics are discussed in this paper：（1）MXene aerogel and Ti3C2Tx/MWCNTs aerogel were prepared by self-assembly method. （2）Study on the adsorption performance of MXene aerogel and Ti3C2Tx/MWCNTs aerogel for Pb2+.
Improved Analytical Modeling of an Axial Flux Double-Sided Eddy-Current Brake With Slotted Conductor Disk

Due to the enhanced air gap flux density and eddy currents in the favorable path, eddy current brakes with slotted conductors have attracted more attention in recent years. However, due to the increased difficulty in analytical modeling, there is currently no suitable analytical model available for the optimization design of eddy current brakes with slotted conductor. To solve this problem, an improved analytical model is provided based on the subdomain model and the least squares method in this article. The proposed analytical model considers slotted conductor disk, magnetic saturation of primary core and actual path of eddy currents in the conductor disk. The accuracy of the proposed analytical model is verified by finite-element method (FEM) and experimental measurement. The results show that the improved analytical model has good accuracy in the entire speed range. As the analytical model takes less computational time than three-dimensional FEM, it can be used as an effective tool for the optimization design.
A Literature Review on Pedagogical Conversational Agent Adaptation

Conversational agents (CAs) — software systems emulating conversations with humans through natural language — have been widely used to communicate and collaborate with humans in various settings. A rising application domain is education since so-called Pedagogical Conversational Agents (PCAs) hold the potential for individualized learning and thus the long-term improvement of learning success. However, existing research on CA adaptation is scattered across different application domains and user groups, so researchers face difficulty in understanding the current state of the art on the adaptation design of PCAs as an independent field of interest. To address this gap, we systematically analyze existing scientific literature and discuss identified adaptation aspects of PCAs in scientific publications. Our literature review contributes to IS research by providing an overview of existing adaptive and adaptable PCA designs, identified gaps, and future research streams with the rising potential thereupon.