Miracle-dz/UniFAR-FTUs huggingface dataset:
Practical course on computing derivatives in code

Derivatives occur frequently in computer graphics and arise in many different contexts. Gradients and often Hessians of objective functions are required for efficient optimization. Gradients of potential energy are used to compute forces. Constitutive models are frequently formulated from an energy density, which must be differentiated to compute stress. Hessians of potential energy or energy density are needed for implicit integration. As the methods used in computer graphics become more accurate and sophisticated, the complexity of the functions that must be differentiated also increases. The purpose of this course is to show that it is practical to compute derivatives even for functions that may seem impossibly complex. This course provides practical strategies and techniques for planning, computing, testing, debugging, and optimizing routines for computing first and second derivatives of real-world routines. This course will also introduce and explore auto differentiation, which encompasses a variety of techniques for obtaining derivatives automatically. Applications to machine learning and differentiable simulation are also considered. The goal of this course is not to introduce the concept of derivatives, how to use them, or even how to calculate them per se. This is not intended to be a calculus course; we will assume that our audience is familiar with multivariable calculus. Instead, the emphasis is on implementing derivatives of complicated computational procedures in computer programs and actually getting them to work.
Contact and friction simulation for computer graphics

Efficient simulation of contact is of interest for numerous physics-based animation applications. For instance, virtual reality training, video games, rapid digital prototyping, and robotics simulation are all examples of applications that involve contact modeling and simulation. However, despite its extensive use in modern computer graphics, contact simulation remains one of the most challenging problems in physics-based animation. This course covers fundamental topics on the nature of contact modeling and simulation for computer graphics. Specifically, we provide mathematical details about formulating contact as a complementarity problem in rigid body and soft body animations. We briefly cover several approaches for contact generation using discrete collision detection. Then, we present a range of numerical techniques for solving the associated LCPs and NCPs. The advantages and disadvantages of each technique are further discussed in a practical manner, and best practices for implementation are discussed. Finally, we conclude the course with several advanced topics such as methods for soft body contact problems, barrier functions, and anisotropic friction modeling. Programming examples are provided in our appendix as well as on the course website to accompany the course notes.
Phase stability and Nucleation effect upon Iron addition to SmCo5 bulk magnets

Change in structure and magnetic properties of SmCo5-xFex permanent magnets for different values of x ranging from 0 to 2 have been studied. Structural investigation from X-ray diffraction (XRD) patterns confirms the hexagonal CaCu5-type structure of the SmCo5-xFex ribbons for 0 2 and has been confirmed by both XRD studies and magnetic measurements. Nucleation effect induced by the additive Fe enhances the coercivity (Hc)up to 27 kOe which is much larger than 4.5 kOe obtained for pure SmCo5.
A single‐phase q‐source AC‐AC converter with continuous input current, safe commutation feature, and reduced bidirectional switch counts

This paper proposes a single‐phase q‐source AC‐AC converter with a wide and flexible voltage gain. The converter only incorporates two bidirectional power switches. This new topology has many bold features like continuous input current, non‐inverting boost, and inverting buck modes. The high voltage gain is achieved by utilizing a coupled inductor in the converter. The converter gain is increased by the turns ratio of the coupled inductor proportionately. The proposed q‐source comprises one input inductor, one coupled inductor, and one capacitor, which are less than other competitors. In order to reduce the voltage and current stresses on power semiconductors, a safe commutation strategy for the converter is also introduced that eliminates snubber circuits. The input and output filters are no longer required due to the proposed converter specifications. So the volume and cost of the converter are decreased significantly. The achieved efficiency equals 94.5% due to utilizing the proposed optimized topology and switching strategy. In this paper, the operating principle of the converter is presented in detail. An experimental prototype has been designed to examine the performance of the suggested converter. Results confirm the theory and operation of the proposed topology.
General method for constructing multi‐input high‐boost DC‐DC converters with low spike current

Switched‐capacitor (SC) technique is widely used in high step‐up DC‐DC converters. Yet the unwanted high spike current in the SC‐based loop deteriorates the converters performances. To find a solution to this issue, this paper devises a general method of constructing topologies that can prevent high spike current and obtain additional voltage pumping as well. By inserting a VSL unit, which consists of an inductor, an active switch, and a voltage source, into a typical SC‐based converter, a series of improved topologies can be obtained systematically. Based on the proposed rule of inserting VSL units, the operating modes and sequence of the SC‐VSL‐based loop are first discussed to explain the principle of preventing current spike. Then, performances are analyzed in detail, and experiments are carried out for further verification of the proposed rules and the converters derived from these rules. Results from theoretical analysis and experiments show that the proposed converters can produce an additional voltage pumping capability while suppressing the spike current in the SC loop and thus have a higher efficiency.
Memes, trolls and the manosphere: mapping the manifold expressions of antifeminism and misogyny online

ABSTRACT Through a number of case studies, this article will conduct an analysis of the sometimes seemingly ubiquitous antifeminism, and even misogyny, in certain anglophone online spaces, and of their roots in older historical antifeminist discourses. It will also discuss how this patriarchal backlash is strategically presented by its proponents as an indicator of a crisis in contemporary masculinity, and to what extent it is part of a wider phenomenon of reaction against progressive advances, in both online and offline spaces.
Long-Distance Caregivers’ Use Of Supportive Services

ABSTRACT While long-distance caregiving has received increased attention as a unique care experience, prior research has not explored the supportive services used by long-distance caregivers (LDCs) and the factors that predict their supportive service utilization. Using the Andersen Model of Health Care Utilization, the current study sought to: 1) describe the types of supportive services LDCs used and the frequency of usage and 2) identify predisposing, enabling, and need-related factors associated with supportive service use in a sample of LDCs. Participants were recruited from aging services organizations, a national participant registry, professional networks, participant referrals, and an existing pool of research participants. The sample included 304 LDCs who reported on the use of nine supportive services and completed measures assessing depression, caregiver burden, self-rated health, sociodemographic characteristics, and the condition of the care recipient (CR). Fifty percent of LDCs reported no service use. Multiple hierarchical regression analyses demonstrated that younger age, higher caregiver burden, greater depressive symptoms, more time spent helping the CR, and worse CR functional status were significantly related to greater total supportive service use by LDCs. The current study contributes to our understanding of the factors associated with LDCs’ supportive service utilization, highlighting the importance of need-related factors.
Mobility distributions of Sub 5 nm singly self-charged water soluble and non-soluble particles from a heated NiCr wire in clean dry air

Abstract Sub 5 nm particles are more and more detected, measured and monitored since few years. They appear in many fields including combustion, atmosphere, automotive industry, filtration, … They are studied because of the development during the last decades, of their different instrumentation in terms of generation, classification, detection and counting (CPCs, PSMs, DMAs, and mass spectrometers). These instruments need to be calibrated with stable sources of particles down to 1 nm. Electrospray source plays a major role in the generation of singly charged ions, soluble in water or alcohols from 1 to 1.8 nm. Unfortunately, clusters larger than 1.8 nm produced with electrospray atomization are multi charged. Charge reduction with a neutralizer or bipolar electrospray source are then required to bring their electrical charge to unity. Heated wires have shown their ability to produce non-soluble hydrophobic singly self-charged particles from 1.3 nm to 20 nm without any external device to bring their electrical charge to unity. The heated wire method have been widely used with noble and inert gases (N2, He, Ar) to produce clean and pure nanoparticles. The present work focuses on the generation in air of hydrophobic nickel chrome oxides and hydrophilic and water-soluble chlorides particles. The study focuses on the generation of sub 5 nm. A high flow and high resolution DMA is used for this purpose. The method produces concentrations up to 5 104 p/cc after classification with a DMA. The generation presents a long-term high stability in terms of concentration. The losses and rate of agglomeration inside the chamber and in the DMA are not taken into account. The results given in the article are the distributions available after classification and ready to be used. Copyright © 2022 University Paris Est Creteil
Investigation of surface treatment effects on the environmentally-assisted cracking behaviour of Alloy 182 in boiling water reactor environment

Surface treatments of primary circuit components in light water reactors are regarded as possible ways to mitigate environmentally-assisted cracking (EAC). To date, it is not fully conclusive which surface condition is suitable to reduce the EAC initiation susceptibility. Constant extension rate tensile (CERT) tests were performed by several labs using flat tapered tensile specimens with different surface conditions (ground, industrial face milled, advanced face milled and shot peened), exposed to a boiling water reactor normal water chemistry environment at 288°C. Despite some scatter in the results, the CERT tests revealed that the EAC initiation susceptibility seems lowest for the advanced face milled surface and highest for the shot peened surface. However, it must be emphasised that the differences were moderate and that the surprising behaviour of the shot peened surface can be explained. The mechanical grinding of the surface did not significantly retard EAC initiation compared to industrial face milling.
Using CoST on self-assessment domain expertise in complex search tasks

While great progress is made in the area of information access, there are still open issues that involve designing intelligent systems supporting task-based search. Despite the importance of task-based search, the information retrieval and information science communities still feel the lack of open-ended and annotated datasets that enable the evaluation of a number of related facets of search tasks in downstream applications. Existing datasets are either sampled from large-scale logs but provide poor annotations, or sampled from lower-scale user studies but focus on ranked list evaluation. In this work, we briefly present CoST 1 : a novel richly annotated dataset for evaluating complex search tasks, collaboratively designed by researchers from the computer science and cognitive psychology domains, and intended to answer a wide range of research questions dealing with task-based search. CoST collection has been entirely detailed in a previous paper [1]. We report here its main design methodology, characteristics of the data provided and illustrative evaluations showing its importance to the IR community, among which a new evaluation (in comparison to [1]) related to the impact of user’s domain expertise on his self-assessment about task complexity.
3D Models Classification with Use of Convolution Neural Network

Nowadays the most urgent challenge behind computer image recognition has become a problem of three dimensional reconstruction of the world or environment from the two dimensional representation like 2D images. Such a tendency is especially obvious in the example of architecture companies' requirements. In common one has no access to the ready-to-use 3D model. Therefore one has to somehow recognize and reconstruct a three dimensional model or object based on its two dimensional representation from different viewports. Novelty can be an approach that allows one not only to use 2D images for feature extraction and classification but also ready 3D models or objects of the same type. In such circumstances one can train neural network recognition models to utilize 3D models, especially their distinguishing features as voxel occupancy or surface curvature. It became obvious that most of the scientists and researchers that are researching the processes in this area commonly develop algorithms of 2D image recognition and extraction features of the same 2D images for further usage in image recognition systems with the aim to classify them and reconstruct the 3D model. Therefore one can build a classifier of three dimensional shapes using not only two dimensional images but also 3D models. Therefore in this paper we propose a new multi presentational 3D model classification framework. Precisely, in this work for the cross presentational information multiple two dimensional images of a three dimensional model as input was used, as well as the extraction of the high level cross presentational information using multiple 2D CNN in separated mode.
Secure, Confidential Blockchains Providing High Throughput and Low Latency

One of the core promises of blockchain technology is that of enabling trustworthy data dissemination in a trustless environment. What current blockchain systems deliver, however, is slow dissemination of public data, rendering blockchain technology unusable in settings where latency, transaction capacity or data confidentiality is important. In this thesis, we focus on providing solutions on two of the most pressing problems blockchain technology currently faces: scalability and data confidentiality. To address the scalability issue, we present OMNILEDGER, a novel scale-out distributed ledger that preserves long-term security under permissionless operation. It ensures security and correctness by using a bias-resistant public-randomness protocol for choosing large, statistically representative shards that process transactions, and by introducing an efficient cross-shard commit protocol that atomically handles transactions affecting multiple shards. To enable the secure sharing of confidential data we present CALYPSO, the first fully decentralized auditable access-control framework for secure blockchain-based data sharing which builds upon two abstractions. First, on-chain secrets enable collective management of (verifiably shared) secrets under a Byzantine adversary where an access-control blockchain enforces user-specific access rules and a secret-management cothority administers encrypted data. Second, skipchain-based identity and access management enables efficient administration of dynamic, sovereign identities and access policies and, in particular, permits clients to maintain long-term relationships with respect to the evolving user identities thanks to the trust-delegating forward links of skipchains. In order to build OMNILEDGER and CALYPSO, we first build a set of tools for efficient decentralization, which are presented in Part II of this dissertation. These tools can be used in decentralized and distributed systems to achieve (1) scalable consensus (BYZCOIN), (2) biasresistant distributed randomness creations (RANDHOUND), and (3) relationship-keeping between independently updating communication endpoints (SKIPPER). Although we use these tools in the scope of this thesis, they can be (and already have been) used in a far wider scope.
An Argument-based Search Framework: Implementation on a Spanish Corpus in the E-Participation Domain

There are many domains and applications where generated textual content is rich with argumentative information, such as product reviews, online forum discussions, court orders, and parliamentary debates. In all of them, the automatic extraction and search of arguments can be very valuable for decision and policy making purposes, and represent challenging problems. Aiming to address these problems, we propose a general and flexible information retrieval framework which, in addition to text documents relevant for a given query, returns categorized and linked argumentative structures existing in or related to such documents within a collection. The framework is composed of a pipeline of modules targeting several tasks: text processing, argument-based annotation, argument mining, information retrieval, reranking and evaluation. As a proof of concept, we have implemented and tested the framework on a Spanish corpus with citizen proposals and comment threads from an e-participation platform.
Control of legged locomotion using dynamical systems - design methods and adaptive frequency oscillators

Legged robots have gained an increased attention these past decades since they offer a promising technology for many applications in unstructured environments where the use of wheeled robots is clearly limited. Such applications include exploration and rescue tasks where human intervention is difficult (e.g. after a natural disaster) or impossible (e.g. on radioactive sites) and the emerging domain of assistive robotics where robots should be able to meaningfully and efficiently interact with humans in their environment (e.g. climbing stairs). Moreover the technology developed for walking machines can help designing new rehabilitation devices for disabled persons such as active prostheses. However the control of agile legged locomotion is a challenging problem that is not yet solved in a satisfactory manner. By taking inspiration from the neural control of locomotion in animals, we develop in this thesis controllers for legged locomotion. These controllers are based on the concept of Central Pattern Generators (CPGs), which are neural networks located in the spine of vertebrates that generate the rhythmic patterns that control locomotion. The use of a strong mathematical framework, namely dynamical systems theory, allows one to build general design methodologies for such controllers. The original contributions of this thesis are organized along three main axes. The first one is a work on biological locomotion and more specifically on crawling human infants. Comparisons of the detailed kinematics and gait pattern of crawling infants with those of other quadruped mammals show many similarities. This is quite surprising since infant morphology is not well suited for quadruped locomotion. In a second part, we use some of these findings as an inspiration for the design of our locomotion controllers. We try to provide a systematic design methodology for CPGs. Specifically we design an oscillator to independently control the swing and stance durations during locomotion, then using insights from dynamical systems theory we construct generic networks supporting different gaits and finally we integrate sensory feedback in the system. Experiments on three different simulated quadruped robots show the effectiveness of the approach. The third axis of research focus on dynamical systems theory and more specifically on the development of an adaptive mechanism for oscillators such that they can learn the frequency of any periodic signal. Interestingly this mechanism is generic enough to work with a large class of oscillators. Extensive mathematical analysis are provided in order to understand the fundamental properties of this mechanism. Then an extension to pools of adaptive frequency oscillators with a negative feedback loop is used to build programmable CPGs (i.e. CPGs that can encode any periodic pattern as a structurally stable limit cycle). We use the system to control the locomotion of a humanoid robot. We also show applications of this system to signal processing.
Fusion strategies to combine topical and temporal information for publication venue recommendation

We study the publication venue recommendation problem, where a recommender system must help a researcher to decide where to submit a given target article for possible publication. We focus on content-based recommendation approaches, where we explicitly look for a good match between the topics discussed in the article and the recommended venue. But, in addition to this topical dimension, we also want to include a temporal dimension, in such a way that we prefer those venues where the articles which are more related with the target article have been published more recently. We use an information retrieval system to obtain separate topical and temporal recommendations and then combine them by means of different fusion strategies. The experimental results obtained on a collection of biomedical journal articles confirm the effectiveness of our proposals.
The Method of Fractal Structuring as on Evolutionary Method of Global Optimization

Decision making processes in the modern world are based on the solutions of optimization problems. The variety of such problems, the corresponding objective functions and areas for finding optimal solutions is the reason for the development of new and improvement of the known optimization methods. This paper proposes a new method of fractal structuring, which is an evolutionary method from the category of soft computing methods. A feature of this method is a quick and in-depth study of the area in which the local extremum is located and the global optimum can also be found. A fractal structuring method has been developed for finding the optimum for one-dimensional, two-dimensional and n-dimensional objective functions. The first experiments were carried out, which prove the prospects and effectiveness of this method, and also indicate the possibility of its improvement.
Relevance Model Augmented with Inter-Collection Co-occurrence Statistics for Ad-hoc Retrieval in Precision Medicine

The ubiquitous growth of the volume of medical literature has necessitated the use of search systems to retrieve the relevant literature from a large collection of medical documents. Such a retrieval based approach has been shown to be useful in the precision medicine task, where instead of keyword-based queries of ad-hoc IR, the queries comprise of a disease name and the personal context associated with the disease, e.g., the gene sequence of the person or their demographics. The two fundamental sources of information useful for the precision medicine task are the medical literature (e.g. PubMed articles) and randomized control trials (RCTs). In this paper, we propose a symbiotic relevance feedback model that is able to utilize the information not only individually from each collection, but is also able to operate across collections improving the retrieval effectiveness of each collection by leveraging information from the top-retrieved documents of the other. Our experiments on the TREC 2019 and 2020 precision medicine track show that our proposed symbiotic relevance feedback model outperforms post-hoc combinations of standard relevance feedback models operating independently on respective collections.