Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel force-velocity field for object manipulation with a model-free cooperative controller

When robots grasp a rigid object, homogeneous holonomic constraints give rise to stiff nonlinear constrained dynamics. As a result, a smooth motion is preferred when grasping an object in a tight but gentle manner, making it a difficult control problem that increases when uncertainties and unmodelled dynamics exist. In this paper, a fuzzy design is proposed by exploiting a physics-based orthogonalization of contact mechanics to produce desired velocity and force fields. The proposed scheme enables the regulation of the velocity component in order to navigate smoothly, while the force field enforces grasp at contact in the normal direction of the cooperative joint-velocity field. Then, the robust model-free controller is designed to track such orthogonal fields while enforcing cooperation among all robots, even under uncertainties and unknown dynamics. A representative simulation study is discussed to show the feasibility of the proposal.
On the relationship of online and offline social cognition

Social neuroscience studies the neurobiological underpinnings of people making sense of people. Due to both conceptual and methodological constraints, the majority of studies in this field of research, however, has employed experimental paradigms that focus on social cognition from an observer’s rather than from an interactor’s point of view (offline vs. online social cognition). This calls for an increased effort to systematically investigate the neural bases of participation in real-time social interaction. In light of the ontogenetic primacy of social interaction over observation and the idea that neural networks established during social interaction may be “re-used” during observation, other important objectives of the field will be to relate new findings into the neural bases of social interaction to previous work investigating the neural bases of social observation as well as to find ways to directly compare the two.
Nonmarket Household Time and the Cost of Children

Raising children demands a considerable amount of parental time, obliging working parents either to reduce their leisure time further or to buy childcare services in the market. Parents may face additional opportunity costs upon deciding to participate in the labor market, but these are difficult to measure. Using a survey instrument in Belgium and Germany, we estimate the income compensation needed to maintain family well-being when adults work versus when they do not enter the labor market. In both countries we find that full-time working parents face extra child costs and require higher labor market participation compensation compared with childless adults.
Does Learning Lead to Coordination in Market Clearing Institutions ?

This paper analyzes the question whether traders learn to coordinate on a trading institution that guarantees market clearing, or whether other market institutions can survive in the long run. While we . nd that the market clearing institution is indeed always stable under a general class of learning dynamics, it turns out that also other, non-market clearing institutions are stable. Hence, in the long run traders may fail to coordinate exclusively in market clearing institutions.
Experimental Data and SNL-EFDC Simulations Flow Sensitivity to MHK Energy Generation from Currents Using the SNL-EFDC Model

Conclusions, Implications and Future Work  Marine hydrokinetic (MHK) projects will generate power from ocean and river currents and tides, thereby altering water velocities and currents in the site’s waterway. These hydrodynamic changes can potentially affect the ecosystem, both near the MHK installation and in surrounding (i.e., far field) regions.  For the MHK industry to succeed, it is imperative that project build-out maximize energy capture and minimize potential detrimental effects to the ecosystem.  In response to this need, SNL has developed and implemented modifications to an existing flow, sediment dynamics, and water-quality code (SNL-EFDC) to qualify, quantify, and visualize the interaction and influence of MHK-device momentum sinks at a representative site.
Status of the JWST sunshield and spacecraft

This paper reports on the development, manufacture and integration of the James Webb Space Telescope’s sunshield and spacecraft. Both of these JWST elements have completed design and development testing. This paper will review basic architecture and roles of these systems. Also to be presented is the current state of manufacture, assembly integration and test. This paper will conclude with a look at the road ahead for each subsystem prior to integration with the integrated telescope and instrument elements at Northrop Grumman’s Space Park facility in late 2017.
Deep Gaussian Embedding of Attributed Graphs: Unsupervised Inductive Learning via Ranking

Methods that learn representations of graph nodes play a critical role in network analysis since they enable many downstream learning tasks. We propose Graph2Gauss – an approach that can efficiently learn versatile node embeddings on large scale (attributed) graphs that show strong performance on tasks such as link prediction and node classification. Unlike most approaches that represent nodes as (point) vectors in a lower-dimensional continuous space, we embed each node as a Gaussian distribution, allowing us to capture uncertainty about the representation. Furthermore, in contrast to previous approaches we propose a completely unsupervised method that is also able to handle inductive learning scenarios and is applicable to different types of graphs (plain, attributed, directed, undirected). By leveraging both the topological network structure and the associated node attributes, we are able to generalize to unseen nodes without additional training. To learn the embeddings we adopt a personalized ranking formulation w.r. t. the node distances that exploits the natural ordering between the nodes imposed by the network structure. Experiments on real world networks demonstrate the high performance of our approach, outperforming state-of-the-art network embedding methods on several different tasks.
FiWi access networks: Future research challenges and moonshot perspectives

Global cellular networks are currently undergoing a major paradigm shift to cope with the unprecedented growth of mobile data traffic driven by the popularity of smart phones and mobile-connected tablets running diverse data-centric applications. In fiber-wireless (FiWi) enhanced LTE-Advanced heterogeneous networks (HetNets), the traditional barriers between coverage-centric mobile networks and capacity-centric FiWi broadband access networks may be removed in order to benefit from fiber backhaul sharing and WiFi offloading. In this paper, we elaborate on emerging trends, identify open key research challenges to unleash the full potential of FiWi enhanced LTE-Advanced HetNets, including their future convergence with other technologies and economic sectors, and attempt to make an educated guess about possible moonshot perspectives for future non-incremental FiWi research.
Advances and Challenges with Data Broadcasting in Wireless Mesh Networks

Wireless mesh networks have become a promising means to provide low-cost broadband access. Many WMN applications require broadcasting data (IPTV etc.) over the WMN. This article studies how efficient data broadcast, measured in terms of broadcast latency, can be realized by exploiting two features of WMNs: the use of multiple transmission rates at the link layer and the use of multiple radio interfaces on each node. We demonstrate that by exploiting these features, broadcast latency can be reduced severalfold compared to the current default practice in wireless LANs of using the lowest transmission rate for broadcast traffic. We also discuss two important insights we have gained from our investigation. First, we find that when multiple radio interfaces are used, a channel assignment algorithm designed for unicast traffic may often perform poorly for broadcast flows. Second, we find that the efficiency of a transmission rate for reducing broadcast latency can be reasonably predicted by the product of the transmission rate and its coverage area.
Opportunities and challenges to mass customise low-income housing in Brazil

Mass Customization (MC) stands for the ability to develop high value-added products within short time frames and at relatively low costs. Although this strategy has been successfully applied in several industries, in construction it has been mostly limited to a few companies that produce factory-built and manufactured homes. In Brazil, where traditional construction techniques are majorly adopted in low-income housing programs, there have been many critics regarding the excessive standardization and thus, non-consideration of the increasing diversity of households and their specific needs. Such standardization is mainly due to the use of mass production core ideas as a way to achieve low costs. The aim of this paper was then to explore the possibilities of adopting mass customization in this context. Two existing low-income housing programs in Brazil were investigated. The discussion on the opportunities and challenges to introduce mass customization ideas in these programs are based on the analysis of the product development process, as well as an analysis of household profiles and needs. The results indicated that the household profile is very diverse in low-income housing. Thus, demand for customization is high, as well as attributed to different products’ characteristics. However, the product development process in this context was found to be very different from a process of mass customized products. Despite the need to modify such process, it was identified that mass customization can be achieved in a variety of ways, and does not necessarily imply on the modernization of construction techniques. However, a major challenge for achieving higher customization in this context seems to be related to the programs’ rules and how it restraints innovation and diversity. Keywords: product development process, low-income housing, mass customization, value management
On the acceleration of the expansion of a cosmological medium

In this letter, we propose a theory of expansion of a cosmological medium in a 3+1-dimensional space-time. After deriving the modified Friedmann equations, we show that the density of dark energy is the product of the bulk modulus $K$ and the time-dependent deformation rate $\epsilon(t)$ of the cosmological medium, and we examine the effect of these parameters on the luminosity curves of celestial bodies. We demonstrate that a cosmological inflation scenario occurs for $K=1.64 \times 10^{109}\text{N}\cdot\text{m}^{-2}$ and show that the dark energy density is decreased by a factor of $\sim 10^{122}$, while the scaling factor expands from $\sim 10^{-60}$ to $\sim 10^{-32}$ during a time of the order of $10^{-42}\text{s}$. At the end of this paper, we discuss a microscopic interpretation of the inflation mechanism and propose future investigations on this matter.
Computational continua for linear elastic heterogeneous solids on unstructured finite element meshes

The computational continua framework, which is a variant of higher‐order computational homogenization theories that is free of scale separation, does not require higher‐order finite element continuity, and is free of higher‐order boundary conditions, has been generalized to unstructured meshes. The salient features of the proposed generalization are (i) a nonlocal quadrature scheme for distorted elements that accounts for unit cell distortion in the parent element domain and (ii) an approximate variant of the nonlocal quadrature that eliminates the cost of computing positions of the quadrature points in the preprocessing stage. The performance of the computational continua framework on unstructured meshes has been compared to the first‐order homogenization theory and the direct numerical simulation.
Affine Stochastic Mortality

We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing models. We test the model fit using data on Dutch mortality rates. Furthermore, we discuss the specification of a market price of mortality risk and apply the model to the pricing of a guaranteed annuity option and the calculation of required economic capital for mortality risk.
Large Scale-ratio Asymptotics for Nonparametric Estimation

We provide large scale-ratio asymptotics for nonparametric estimation to avoid a large risk for a fixed noise variance. Focusing on the scale ratio of the parameter and noise, we investigate the asymptotic risk when the ratio is large. The asymptotics as the ratio becomes large includes the asymptotics as the noise variance becomes small. We propose a prior distribution of which the Bayes estimator is minimax up to a logarithmic factor when the ratio is large and satisfies a weak form of admissibility.
Deterrence and

Tax compliance has been dealt with in the literature almost exclusively by studying the behavior of taxpay ­ ers. But important insights on tax compliance can be gained by looking at how the tax authority deals with taxpayers. Taxpayers ’ willingness to pay their taxes, or tax morale, is supported, or even raised, when the tax officials treat them with respect. In contrast, when the tax officials consider taxpayers purely as ‘ sub ­ jects ’ who have to be forced to pay their dues, the taxpayers tend to respond by actively trying to avoid taxation. Using data for Swiss cantons and five different years from the period 1970 to 1995, we establish a systematic relationship between external intervention (in this case, how the tax officials deal with taxpay ­ ers) and intrinsic motivation (in this case, individuals ’ tax morale). We are grateful to Hannelore Weck-Hannemann for providing, us with data on Swiss tax evasion and Reto Casserini for valuable research assistance. The paper also gained from discussions with Gebhard Kirchgassner and Jean-Robert Tyran. We are also grateful to Rosemary Brown for improving the English Preliminary versions of the paper were presented at the 2 nd International Conference on Taxation, organ ­ ized by the Centre for Tax System Integrity of the Australian N ational University in Canberra, December 10 and 11, 2001.
A Method of Computing Many Functions Simultaneously by Using Many Parallel Quantum Systems

We suggest a method of computing many functions in the same time by using many parallel quantum systems. We use the Bernstein-Vazirani algorithm. Given the set of real values $\{a_1,a_2,a_3,\ldots,a_N\}$, and the function $g:{\bf R}\rightarrow \{0,1\}$, we shall determine the following values $\{g(a_1),g(a_2),g(a_3),\ldots, g(a_N)\}$ simultaneously. By using $M$ parallel quantum systems, we can compute $M$ functions $g^1,g^2,. ,g^M$ simultaneously. The speed of determining the $N\times M$ values will be shown to outperform the classical case by a factor of $N$.
Existence, stability and dynamics of solitary waves in nonlinear Schrodinger models with periodic potentials

EXISTENCE, STABILITY, AND DYNAMICS OF SOLITARY WAVES IN NONLINEAR SCHRÖDINGER MODELS WITH PERIODIC POTENTIALS FEBRUARY 2010 KODY J. H. LAW, B.S., UNIVERSITY OF MASSACHUSETTS AMHERST M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Panayotis G. Kevrekidis The focus of this dissertation is the existence, stability, and resulting dynamical evolution of localized stationary solutions to Nonlinear Schrödinger (NLS) equations with periodic confining potentials in 2(+1) dimensions. I will make predictions about these properties based on a discrete lattice model of coupled ordinary differential equations with the appropriate symmetry. The latter has been justified by Wannier function expansions in a so-called tight-binding approximation in the appropriate parametric regime. Numerical results for the full 2(+1)-D continuum
Physical Laws and a New Discrete Space Concept

In this article some problems in modern physics and cosmology was discussed. The inconsistencies between experimental astrophysical data and basic physical laws are revealed. A new concept of the quantum - discrete space, the defiance in the law of conservation of energy and limited radius of gravitational forces spread are discussed. The alternate sight on a nature of cosmic microwave background (CMB) is offered. The conclusions about a local range of the classical physical laws are made and the reasons for the benefit of is quasi-steady state model of our Universe are represented.
Améliorer l’isolation des utilisateurs sur les IaaS: Placement de Machine Virtuelle avec contrainte de sécurité

: Nowadays virtualization is used as the sole mechanism to isolate diﬀerent users on Cloud platforms. We will show that due to improper virtualization of micro-architectural components, data leak and modiﬁcation can occur on public Clouds. Furthermore, using the same vector, it is possible to induce performance interferences, i.e. noisy neighbors. Using this approach, a VM can slow down and steal resources from concurrent VMs. We propose placement heuristics that take into account isolation requirements. We modify three classical heuristics to take into account these requirements. Furthermore, we propose four new heuristics that take into account the hierarchy of the Cloud platforms and the isolation requirements. Finally, we evaluate these heuristics and compare them with the modiﬁed classical ones. We show that our heuristics are performing at least as good as classical ones but are scaling better and are faster by a few order of magnitude than the classical ones.
3D modeling and registration under wide baseline conditions

During the 90s important progess has been made in the area of structure-from-motion. From a series of closely spaced images a 3D model of the observed scene can now be reconstructed, without knowledge about the subsequent camera positions or settings. From nothing but a video, the camera trajectory and scene shape are extracted. Progress has also been important in the area of structured light techniques. Rather than having to use slow and/or bulky laser scanners, compact one-shot systems have been developed. Upon projection of a pattern onto the scene, its 3D shape and texture can be extracted from a single image. This paper presents recent extensions on both strands, that have a common theme: how to cope with large baseline conditions. In the case of shape-from-video we discuss ways to ﬁnd correspondences and, hence, extract 3D shapes even when the images are taken far apart. In the case of structured light, the problem solved is how to combine partial 3D patches into complete models, without a good initialisation of their relative poses.
Novel Virtual Network Function Service Chain Deployment Algorithm based on Q-learning

—As a new cloud service mode, mobile edge computing distributes the traditional centralized deployment and management of cloud resources to the wireless access network. Mobile services can be processed for the sake of obtaining a good service experience and reduce the network load of the backtrip network. In order to effectively improve the end-to-end service delay of the ﬂow in multi-clusters coexisting mobile edge computing (MEC) network, an improved virtual network function (VNF) service chain deployment algorithm based on Q-learning was proposed. Based on the planning model, a spatial-temporal optimization model of VNF service chain deployment was established by markov decision process, and an improved BPQ-learning algorithm was designed to solve the model. The method considered both the virtual deployment of MEC service chain in space dimension and the life cycle management of VNF in time dimension. The optimization of VNF deployment is realized. The possible network congestion is avoided by deployment service nodes in advance. Experimental results show that the proposed strategy can provide end-to-end services with lower latency and better experience for delay-sensitive mobile services under different VNF service chain scale, service node scale, cluster number and logical connection relationship among the virtual network functions.
Temperature-drift-immune wavelength meter based on an integrated micro-ring resonator

We present an integrated optical wavelength meter based on a Si3N4/SiO2 micro ring resonator (operating over a free spectral range of ≈ 2.6 nm) whose output response is immune to temperature changes. The wavelength meter readout is performed by a neural network and a non-linear optimization algorithm. This novel approach ensures a high wavelength estimation precision (≈ 50 pm). We observe a long-term reproducibility of the wavelength meter response over a time interval of one week. We investigate the influence of the ambient temperature on the estimated wavelength. We observe an immunity of the displayed output wavelength to temperature changes of up to several degrees. The temperature-drift immunity appears to be caused by deviations from the theoretically expected (perfect) transmission function of a ring resonator, i.e., caused by deviations that are usually undesired in spectroscopic devices.
Safety and efficacy of elbasvir/grazoprevir for the treatment of chronic hepatitis C: current evidence

: Treatments for hepatitis C virus (HCV) have advanced greatly, becoming more efficacious with fewer adverse events, due to the availability of direct-acting antiviral agents, which target specific steps in the HCV life cycle. Recently, a combination regimen consisting of the HCV nonstructural protein 5A inhibitor elbasvir (EBR) and the HCV NS3/4A protease inhibitor grazoprevir (GZR) was approved for the treatment of patients with chronic HCV and genotypes (Gts) 1 and 4 in various countries. In Phase III trials, the combination of EBR/GZR (fixed-dose combination table or single agent) for 12 or 16 weeks of treatment with or without ribavirin resulted in a high sustained virological response at 12 weeks in treatment-naïve and treatment-experienced patients with HCV Gt 1a, 1b, 4, or 6, including special populations, such as individuals with advanced chronic kidney disease, HCV-HIV coinfection, and compensated cirrhosis. In this review, we focus on the mode of action, pharmacokinetics, clinical applica-tions, efficacy, and safety profile of EBR/GZR, including special populations who have been considered refractory from the extensive evidence of clinical trials.
The Lower Bound Error for polynomial NARMAX using an Arbitrary Number of Natural Interval Extensions

The polynomial NARMAX (Nonlinear AutoRegressive Moving Average model with eXogenous input) is a model that represents the dynamics of physical systems. This polynomial contains information from the past of the inputs and outputs of the process, that is, it is a recursive model. In digital computers this generates the propagation of the rounding error. Our procedure is based on the estimation of the maximum value of the lower bound error considering an arbitrary number of pseudo-orbits produced from different natural interval extensions, and a posterior Lyapunov exponent calculation. We applied successfully our technique for two identified models of the systems: sine map and Duffing-Ueda oscillator