Miracle-dz/UniFAR-FTUs huggingface dataset:
Cursive:: controlling expressive avatar gesture using pen gesture

We describe an interaction technique for expressive nonverbal communication through an avatar. The input consists of letters written with expressive modulation, by hand, using a pen tablet input device. This technique, which we call Cursive, translates an alphabetic letter into a body gesture. Our design is inspired by the observation that handwriting, like some kinds of human gesture, informs through the symbols it depicts, and through the manner in which the symbols are produced. The technique is especially suited for desktop and portable virtual reality applications--appli¿cations that do not use special rooms or equipment but only two-dimensional displays and simple pointing devices for interaction with the virtual environment. Our system solves the difficult prob¿lem of controlling the movements of a highly articulated, 3D ava¿tar using a common input device within the context of an office or other real world environment.
Haploinsufficiency of Akt1 Prolongs the Lifespan of Mice

There is increasing evidence that nutrient-sensing machinery is critically involved in the regulation of aging. The insulin/insulin-like growth factor-1 signaling pathway is the best-characterized pathway with an influence on longevity in a variety of organisms, ranging from yeast to rodents. Reduced expression of the receptor for this pathway has been reported to prolong the lifespan; however, the underlying mechanisms are largely unknown. Here we show that haploinsufficiency of Akt1 leads to an increase of the lifespan in mice. Akt1 +/– mice had a lower body weight than their littermates with less fat mass and normal glucose metabolism. Ribosomal biogenesis and the mitochondrial DNA content were significantly reduced in these mice, along with a decrease of oxidative stress. Consistent with the results obtained in mice, inhibition of Akt-1 promoted longevity in nematodes (Caenorhabditis elegans), whereas activation of Akt-1 shortened the lifespan. Inhibition of Akt-1 led to a decrease of ribosomal gene expression and the mitochondrial DNA content in both human cells and nematodes. Moreover, deletion of ribosomal gene expression resulted in a decrease of the mitochondrial DNA content and normalized the lifespan shortened by Akt-1 activation in nematodes. These results suggest that an increase of mitochondrial amount and energy expenditure associated with enhanced protein synthesis accelerates both aging and the onset of age-associated diseases.
Report of the National Heart, Lung, and Blood Institute Working Group on Outcomes Research in Cardiovascular Disease

The National Heart, Lung, and Blood Institute convened a working group on outcomes research in cardiovascular disease (CVD). The working group sought to provide guidance on research priorities in outcomes research related to CVD. For the purposes of this document, “outcomes research” is defined as investigative endeavors that generate knowledge to improve clinical decision making and healthcare delivery to optimize patient outcomes. The working group identified the following priority areas: (1) national surveillance projects for high-prevalence CV conditions; (2) patient-centered care; (3) translation of the best science into clinical practice; and (4) studies that place the cost of interventions in the context of their real-world effectiveness. Within each of these topics, the working group described examples of initiatives that could serve the Institute and the public. In addition, the group identified the following areas that are important to the field: (1) promotion of the use of existing data; (2) facilitation of collaborations with other federal agencies; (3) investigations into the basic science of outcomes research, with an emphasis on methodological advances; (4) strengthening of appropriate study sections with individuals who have expertise in outcomes research; and (5) expansion of opportunities to train new outcomes research investigators. The working group concluded that a dedicated investment in CV outcomes research could directly improve the care delivered in the United States.
Pilin Processing Follows a Different Temporal Route than That of Archaellins in Methanococcus maripaludis

Methanococcus maripaludis has two different surface appendages: type IV-like pili and archaella. Both structures are believed to be assembled using a bacterial type IV pilus mechanism. Each structure is composed of multiple subunits, either pilins or archaellins. Both pilins and archaellins are made initially as preproteins with type IV pilin-like signal peptides, which must be removed by a prepilin peptidase-like enzyme. This enzyme is FlaK for archaellins and EppA for pilins. In addition, both pilins and archaellins are modified with N-linked glycans. The archaellins possess an N-linked tetrasaccharide while the pilins have a pentasaccharide which consists of the archaellin tetrasaccharide but with an additional sugar, an unidentified hexose, attached to the linking sugar. In this report, we show that archaellins can be processed by FlaK in the absence of N-glycosylation and N-glycosylation can occur on archaellins that still retain their signal peptides. In contrast, pilins are not glycosylated unless they have been acted on by EppA to have the signal peptide removed. However, EppA can still remove signal peptides from non-glycosylated pilins. These findings indicate that there is a difference in the order of the posttranslational modifications of pilins and archaellins even though both are type IV pilin-like proteins.
High level high performance computing for multitask learning of time-varying models

We propose an approach suitable to learn multiple time-varying models jointly and discuss an application in data-driven weather forecasting. The methodology relies on spectral regularization and encodes the typical multi-task learning assumption that models lie near a common low dimensional subspace. The arising optimization problem amounts to estimating a matrix from noisy linear measurements within a trace norm ball. Depending on the problem, the matrix dimensions as well as the number of measurements can be large. We discuss an algorithm that can handle large-scale problems and is amenable to parallelization. We then compare high level high performance implementation strategies that rely on Just-in-Time (JIT) decorators. The approach enables, in particular, to offload computations to a GPU without hard-coding computationally intensive operations via a low-level language. As such, it allows for fast prototyping and therefore it is of general interest for developing and testing novel computational models.
Homeostatic control of the excitation–inhibition balance in cortical layer 5 pyramidal neurons

Homeostatic regulation in the brain is thought to be achieved through a control of the synaptic strength by close interactions between excitation and inhibition in cortical circuits. We recorded in a layer 5 pyramidal neuron of rat cortex the composite response to an electrical stimulation of various layers (2–3, 4 or 6). Decomposition of the global conductance change in its excitatory and inhibitory components permits a direct measurement of excitation–inhibition (E‐I) balance. Whatever the stimulated layer was, afferent inputs led to a conductance change consisting of 20% excitation and 80% inhibition. Changing synaptic strengths in cortical networks by using a high‐frequency of stimulation (HFS) protocol or a low‐frequency of stimulation (LFS) protocol (classically used to induce long‐term potentiation or long‐term depression at the synaptic level) were checked in order to disrupt this balance. Application of HFS protocols in layers 2–3, 4 or 6, or of LFS protocols in layer 4 induced, respectively, long‐term paralleled increases or long‐term paralleled decreases in E and I which did not change the E‐I balance. LFS protocols in layers 2–3 or 6 decreased E but not I and disrupted the balance. It is proposed that regulatory mechanisms might be mainly sustained by recurrent connectivity between excitatory and inhibitory neuronal circuits and by modulation of shunting GABAA inhibition in the layer 5 pyramidal neuron.
Model Selection and Feature Ranking for Financial Distress Classification

In this paper we apply several learning machine techniques to the problem of financial distress classification of medium-sized private companies. Financial data was obtained from Diana, a large database containing financial statements of French companies. Classification accuracy is evaluated with Artificial Neural Networks, Classification and Regression Tress (CART), TreeNet, Random Forests and Liner Genetic Programs (LGPs). We analyze both type I (bankrupted companies misclassified as healthy) and type II (healthy companies misclassified as bankrupted) errors on two datasets containing balanced and unbalanced class distribution. LGPs have the best performance accuracy in both balanced data and unbalanced dataset. Our results demonstrate the potential of using learning machines, with respect to discriminant analysis, in solving important economics problems such as bankruptcy detection. We also address the related issue of ranking the importance of input features, which is itself a problem of great interest. Elimination of the insignificant inputs leads to a simplified problem and possibly faster and more accurate classification of financial distress. Experiments on Diana dataset have been carried out to assess the effectiveness of this criterion. Results show that using significant features gives the most remarkable performance and performs consistently well over financial datasets we used.
A PLL based analog core tester

A novel architecture for testing the analog cores of a mixed signal system-on-chip (SoC) has been proposed. A phase locked loop (PLL) has been modified to enable an accurate analog built-in self-test (BIST) capability. The specified phase and amplitude response of the circuit-under-test (CUT) are represented as a test control voltage that determines the lock condition for the PLL based tester. The test control voltage locks the PLL depending on the frequency response of the CUT. Faults are detected either by the PLL not locking or by determining that the locking frequency is not the nominal value for a fault free CUT. The proposed tester has capabilities to test high frequency analog circuits. Experimental results demonstrate the effectiveness of the proposed method
1 2 2 A ug 2 00 4 Molecular Hydrogen Kinematics in Cepheus A 1

We present the radial velocity structure of the molecular hydrogen outflows associated to the star forming region Cepheus A. This structure is derived from the doppler shift of the H2 v=1–0 S(1) emission line obtained by Fabry–Pérot spectroscopy. The East and West regions of emission, called Cep A (E) and Cep A (W), show radial velocities in the range of -20 to 0 km s with respect to the molecular cloud. Cep A (W) shows an increasing velocity with position offset from the core indicating the existence of a possible accelerating mechanism. Cep A (E) has an almost constant mean radial velocity of -18 km s along the region although with a large dispersion in velocity, indicating the possibility of a turbulent outflow. A detailed analysis of the Cep A (E) region shows evidence for the presence of a Mach disk on that outflow. Also, we argue that the presence of a velocity gradient in Cep A (W) is indicative of a C-shock in this region. Following Riera et al. (2003), we analyzed the data using wavelet analysis to study the line width and central radial velocity distributions. We found that both outflows have complex spatial and velocity structure characteristic of a turbulent flow. Subject headings: ISM: individual (Cepheus A) – ISM: jets and outflows – ISM: kinematics and dynamics – ISM: molecules – ISM: Turbulence – infrared: ISM
K-Multipath Routing Mechanism with Load Balancing in Wireless Sensor Networks

It is desirable to allow packets with the same source and destination to take more than one possible path. This facility can be used to ease congestion and overcome node failures. In this paper, we design and implement a k-multipath routing algorithm that allows a given source node send samples of data to a given sink node in a large scale sensor networks. Multipath routing can increase endto-end throughput and provide load balancing. However, its advantage is not obvious in wireless sensor networks because the traffic along the multiple paths will interfere with each other. Our multipath routing algorithm tries to keep multipath as node disjoint routes. In order to achieve a minimum mean delay for the whole network, we study the two different policies with which we distribute traffic over different paths. The simulation results reveal that our multipath routing approach does not surprisingly perform better than the shortest path routing (single path routing SPR) in terms of load balancing and quality of data (QoD).
Methodology and Experience of Simulation-Based Verification of Microprocessor Units Based on Cycle-Accurate Contract Specifications

In this paper we describe a methodology and experience of simulation-based verification of microprocessor units based on cycle-accurate contract specifications. Such specifications describe behavior of a unit in the form of preconditions and postconditions of microoperations. We have successfully applied the methodology to several units of the industrial microprocessor. The experience shows that cycle-accurate contract specifications are very suitable for simulation-based verification, since, first, they represent functional requirements on a unit in comprehensible declarative form, and second, they make it possible to automatically construct test oracles which verify unit correctness.
Real Time Gray Level Corner Detector

In this paper, we will introduce a new corner detector and compare its performance with other three popular corner detectors. The new detector assumes a welldefined corner of a gray level image should have a good corner structure that is similar with the ideal corner structure. Experiments have shown that the new corner detector is accurate and efficient. What’s more, the corner detector estimates the corner attributes, such as corner angles and corner orientations, without additional computational cost.
Mathematics of Probabilistic Uncertainty Modeling

This chapter presents the uncertainty modeling using probabilistic methods. Probabilistic method of uncertainty analysis is due to randomness of the parameters of a model. Randomness of parameters is characterized by specified probability distribution such as normal, log normal, exponential etc., and the corresponding samples are generated by various methods. Monte Carlo simulation is applied to explore the probabilistic uncertainty modeling. Monte Carlo simulation being a statistical process is based on the random number generation from the specified distribution of the uncertain random parameters. Sample size is generally very large in Monte Carlo simulation which is required to have small errors in the computation. Latin hypercube sampling and importance sampling are explored in brief. This chapter also presents Polynomial Chaos theory based probabilistic uncertainty modeling. Polynomial Chaos theory is an efficient Monte Carlo simulation in the sense that sample size here is very small and dictated by the number of the uncertain parameters and by choice of the order of the polynomial selected to represent the uncertain parameter.
Job Security Perceptions and the Saving Behavior of German Households

This paper investigates the co-movements of job security perceptions and household saving rates using data from the 1992 to 2010 waves of the German Socio-Economic Panel. The empirical analysis reveals that higher job insecurity is generally accompanied by slightly lower saving which suggests that employment and financial insecurity typically go hand-in-hand. When confounding changes in the perception of financial security are controlled for, slight evidence for precautionary saving behavior is found. This behavior is of rather small economic importance and limited to households that are somewhat worried about their financial situation who increase their saving by about 0.3%-points or EUR 100 annually in the light of increased job insecurity. In contrast, no significant change in saving is observed for households that are either very concerned or not at all concerned about their financial situation, i.e., either financially constrained or in possession of a buffer-stock of wealth.
XCS based hidden firmware modification on embedded devices

Most contemporary embedded devices, such as wireless routers, digital cameras, and digital photo frames, have Web based management interfaces that allow an administrator to perform management tasks on the device from a Web browser connecting to the device's Web server. It has been shown earlier that many of these devices are vulnerable to Cross Site Scripting type attacks whereby some malicious JavaScript code can be injected in the Web pages stored on the device. When such infected pages are opened by the administrator, the malicious script is executed with admin privileges, and it can potentially fully compromise the embedded device. In this paper, we demonstrate that such full compromise of embedded devices is indeed possible in practice by showing how the injected malicious script can install an arbitrarily modified firmware on the device. We present the general framework of this kind of hidden firmware modification attacks, and report on our proof-of-concept implementation that targets Planex MZK-W04NU wireless routers. In addition, we also show how this vulnerability can be exploited to install botnet clients on embedded devices, and by doing so, to create embedded botnets. Our work proves that the risk of this type of attacks on embedded systems is considerable, and it will further increase in the future.
Predicting distributions with Linearizing Belief Networks

Conditional belief networks introduce stochastic binary variables in neural networks. Contrary to a classical neural network, a belief network can predict more than the expected value of the output $Y$ given the input $X$. It can predict a distribution of outputs $Y$ which is useful when an input can admit multiple outputs whose average is not necessarily a valid answer. Such networks are particularly relevant to inverse problems such as image prediction for denoising, or text to speech. However, traditional sigmoid belief networks are hard to train and are not suited to continuous problems. This work introduces a new family of networks called linearizing belief nets or LBNs. A LBN decomposes into a deep linear network where each linear unit can be turned on or off by non-deterministic binary latent units. It is a universal approximator of real-valued conditional distributions and can be trained using gradient descent. Moreover, the linear pathways efficiently propagate continuous information and they act as multiplicative skip-connections that help optimization by removing gradient diffusion. This yields a model which trains efficiently and improves the state-of-the-art on image denoising and facial expression generation with the Toronto faces dataset.
Incomplete data: what went wrong, and how to fix it

Incomplete data is ubiquitous: the more data we accumulate and the more widespread tools for integrating and exchanging data become, the more instances of incompleteness we have. And yet the subject is poorly handled by both practice and theory. Many queries for which students get full marks in their undergraduate courses will not work correctly in the presence of incomplete data, but these ways of evaluating queries are cast in stone -- SQL standard. We have many theoretical results on handling incomplete data but they are, by and large, about showing high complexity bounds, and thus are often dismissed by practitioners. Even worse, we have a basic theoretical notion of what it means to answer queries over incomplete data, and yet this is not at all what practical systems do. Is there a way out of this predicament? Can we have a theory of incompleteness that will appeal to theoreticians and practitioners alike, by explaining incompleteness and being at the same time implementable and useful for applications? After giving a critique of both the practice and the theory of handling incompleteness in databases, the paper outlines a possible way out of this crisis. The key idea is to combine three hitherto used approaches to incompleteness: one based on certain answers and representation systems, one based on viewing incomplete databases as logical theories, and one based on orderings expressing relative value of information.
Typically-correct derandomization

A fundamental question in complexity theory is whether every randomized polynomial time algorithm can be simulated by a deterministic polynomial time algorithm (that is, whether BPP=P). A beautiful theory of derandomization was developed in recent years in attempt to solve this problem. In this article we survey some recent work on relaxed notions of derandomization that allow the deterministic simulation to err on some inputs. We use this opportunity to also provide a brief overview to some results and research directions in "classical derandomization".
Has Globalization Gone Far Enough?: The Costs of Fragmented Markets

The authors use the underlying data from purchasing power parity surveys to estimate the potential benefits from fully integrating goods markets among major OECD countries. These data are particularly useful because they are comprehensive, and every effort has been made to ensure that they are comparable. Input-output tables are used to eliminate distribution margins from final goods prices and thereby provide estimates of ex-factory prices. Price differentials have been taken as measures of barriers, and the welfare effects of eliminating these barriers have been estimated in a general equilibrium model. The study also provides insights into the relative openness of individual OECD countries to the world economy and the degree to which Europe has become a single market.
Introductory Chapter: Discourse and Discourse Analysis. A Retrospective Approach

The aim of this chapter is to highlight the theoretical frame of reference for the works included in this book. We intend to delimit the field of study for discourse analysis by highlighting the main theories and concepts that ensure its specificity. Interdisciplinary, which is the distinctive feature of discourse analysis, marks the evolution of research in this field that we are trying to capture in our proposed retrospective approach. The review of research that configures the domain of discourse analysis illustrates the latter relevance in deciphering the meaning of communication as an important qualitative research method in the field of communication sciences. This is, in fact, the orientation we propose to the Discourse Analysis book, since the studies that it contains reflect the usefulness of discourse analysis in determining the meaning in real-life communication situations.