Miracle-dz/UniFAR-FTUs huggingface dataset:
Model predictive sensor scheduling

The sensor scheduling is to select a sensor (or a group of sensors) from multiple sensors at each time step so as to perform optimally a task based on the sensed data. In this paper, we pose a model predictive type deterministic/stochastic sensor scheduling problem for discrete-time linear Gaussian time-varying systems, and develop an approach to solve these problems based on the dynamic programming recursion. We show first that, in a special case of deterministic scheduling where the Riccati recursion of error covariance satisfies a specific structural condition, the online optimization using the dynamic programming is reduced to a static optimization, so that the model predictive sensor scheduling can be easily implemented online. Next, we discuss the stochastic scheduling problem, and show an alternative condition of optimization reduction, which lead to a stochastic sensor scheduling easily implemented online. Finally, we propose two practical sensor schedulings for deterministic and stochastic case, and discuss an example to illustrate the two sensor schedulings.
The effect of realised volatility on stock returns risk estimates

In this paper, we estimate minimum capital risk requirements for short, long positions and three investment horizons, using the traditional GARCH model and two other GARCH-type models that incorporate the possibility of asymmetric responses of volatility to price changes; and, most importantly, we analyse the models performance when realised volatility is included as an explanatory variable into the models' variance equations. The results suggest that the inclusion of realised volatility improves the models forecastability and their capacity to calculate accurate measures of minimum capital risk requirements.
Computation of Compound Growth Rates in Agriculture: Revisited*

Growth rates are widely employed in the field of agriculture as these have important policy implications. The usual parametric approach for growth rate analysis is to assume multiplicative error in the underlying nonlinear geometric model and then fit the linearized model by ‘method of least squares’. The deficiencies of this approach have been highlighted. It has been argued that nonlinear estimation procedures should be employed for fitting the model and then only the growth rates should be computed. A methodology has been discussed to compute the compound growth rate by using growth models, viz. monomolecular, logistic and Gompertz. Further, as an illustration, the total foodgrain production of our country during the period 1980 to 2001 has been considered and its growth rate has been computed.
Radical Left Parties in Europe

1. Introduction 2. From Communist Crisis to Post-Communist Mutation 3. The West European Communists: Perpetual Crisis? 4. The Fall and (Partial) Rise of the Eastern European Communists 5. Modern Democratic Socialists or Old-Style Social Democrats? 6. Left-Wing Populism: Populist Socialists and Social Populists 7. Transnational Party Organizations: Towards a New International? 8. Parties and the Wider Movement 9. Explaining Electoral Success and Failure with Charlotte Rommerskirchen 10. Conclusion
Developing the Own-Race Advantage in 4-, 6-, and 9-Month-Old Taiwanese Infants: A Perceptual Learning Perspective

Previous infant studies on the other-race effect have favored the perceptual narrowing view, or declined sensitivities to rarely exposed other-race faces. Here we wish to provide an alternative possibility, perceptual learning, manifested by improved sensitivity for frequently exposed own-race faces in the first year of life. Using the familiarization/visual-paired comparison paradigm, we presented 4-, 6-, and 9-month-old Taiwanese infants with oval-cropped Taiwanese, Caucasian, Filipino faces, and each with three different manipulations of increasing task difficulty (i.e., change identity, change eyes, and widen eye spacing). An adult experiment was first conducted to verify the task difficulty. Our results showed that, with oval-cropped faces, the 4 month-old infants could only discriminate Taiwanese “change identity” condition and not any others, suggesting an early own-race advantage at 4 months. The 6 month-old infants demonstrated novelty preferences in both Taiwanese and Caucasian “change identity” conditions, and proceeded to the Taiwanese “change eyes” condition. The 9-month-old infants demonstrated novelty preferences in the “change identity” condition of all three ethnic faces. They also passed the Taiwanese “change eyes” condition but could not extend this refined ability of detecting a change in the eyes for the Caucasian or Philippine faces. Taken together, we interpret the pattern of results as evidence supporting perceptual learning during the first year: the ability to discriminate own-race faces emerges at 4 months and continues to refine, while the ability to discriminate other-race faces emerges between 6 and 9 months and retains at 9 months. Additionally, the discrepancies in the face stimuli and methods between studies advocating the narrowing view and those supporting the learning view were discussed.
Electrochemical Hydrogen Storage in a Highly Ordered Mesoporous Carbon

A highly order mesoporous carbon has been synthesized through a strongly acidic, aqueous cooperative assembly route. The structure and morphology of the carbon material were investigated using TEM, SEM and nitrogen adsorption-desorption isotherms. The carbon was proven to be meso-structural and consisted of graphitic micro-domain with larger interlayer space. AC impedance and electrochemical measurements reveal that the synthesized highly ordered mesoporous carbon exhibits a promoted electrochemical hydrogen insertion process and improved capacitance and hydrogen storage stability. The meso-structure and enlarged interlayer distance within the highly ordered mesoporous carbon are suggested as possible causes for the enhancement in hydrogen storage. Both hydrogen capacity in the carbon and mass diffusion within the matrix were improved.
A supervised approach for tag hierarchy construction in open source communities

The massive amounts of open source software provide sufficient reusable resources for software development. Most of the OSS communities adopt a kind of categorization or tagging mechanism to organize the software. However, the categorization often too coarse, while the tags are flat and fail to capture the inter-relation among them. In this paper, we propose a novel approach to reveal the latent relations between tags and build a tag hierarchy to help locate resources. We firstly build a co-occurrence network, based on which we compare the connotations of tags and construct a preliminary hierarchy. Then we leverage the domain knowledge of category in SourceForge to optimize and improve the relations between tags. At the end, we demonstrate the effectiveness of the constructed tag hierarchy with quantitative evaluation, which suggest the validation of our approach.
Architectural synthesis of digital signal processing applications dedicated to submicron technologies

Architectural synthesis is an efficient design process that reduces the gap between algorithms and architectures by raising the abstraction level. However, this process currently does not take the VLSI circuit interconnection cost into account whereas this cost becomes predominant using submicron technologies. In this paper, an interconnection cost analysis at the behavioural level is performed in order to provide rapid prototyping results and to direct the synthesis process with additional path constraints. Results are presented showing the interest of this approach.
Anthropomorphic Robot Hand : Gifu Hand III

This paper presents an anthropomorphic robot hand called Gifu Hand III, which is a modified version of Gifu Hand II. The Gifu Hand is aimed to be used as a platform of robot hands for robotics research. The Gifu Hand III is improved on the points of backlash of transmission, opposability of the thumb, and mobility space of fingertips. The opposability of the thumb is evaluated by a cubature of opposable space. An explicit kinematical relation between the fourth joint and the third one is shown, where the fourth joint is engaged with the third joint by a planar four-bars linkage mechanism. The distributed tactile sensor, which has grid pattern electrodes and uses conductive ink, is mounted on the hand surface. The sensor presents 235 points expansion relatively to that of the Gifu Hand II. To reduce insensitive area, the electrodes width and pitch are expanded and narrowed, respectively. In consequence, the insensitive area is reduced to 49.1%. Experiments of grasping several objects are shown. With these improvements and experiments, the Gifu hand III has a higher potential to perform dexterous object manipulations like the human hand.
Alcohol Regulates Gene Expression in Neurons via Activation of Heat Shock Factor 1

Drinking alcohol causes widespread alterations in gene expression that can result in long-term physiological changes. Although many alcohol-responsive genes (ARGs) have been identified, the mechanisms by which alcohol alters transcription are not well understood. To elucidate these mechanisms, we investigated Gabra4, a neuron-specific gene that is rapidly and robustly activated by alcohol (10–60 mm), both in vitro and in vivo. Here we show that alcohol can activate elements of the heat shock pathway in mouse cortical neurons to enhance the expression of Gabra4 and other ARGs. The activation of Gabra4 by alcohol or high temperature is dependent on the binding of heat shock factor 1 (HSF1) to a short downstream DNA sequence, the alcohol response element (ARE). Alcohol and heat stimulate the translocation of HSF1 from the cytoplasm to the nucleus and the induction of HSF1-dependent genes, Hsp70 and Hsp90, in cultured neurons and in the mouse cerebral cortex in vivo. The reduction of HSF1 levels using small interfering RNA prevented the stimulation of Gabra4 and Hsp70 by alcohol and heat shock. Microarray analysis showed that many ARGs contain ARE-like sequences and that some of these genes are also activated by heat shock. We suggest that alcohol activates phylogenetically conserved pathways that involve intermediates in the heat shock cascade and that sequence elements similar to the ARE may mediate some of the changes in gene expression triggered by alcohol intake, which could be important in a variety of pathophysiological responses to alcohol.
Effect of home-based training using a slant board with dorsiflexed ankles on walking function in post-stroke hemiparetic patients

[Purpose] To investigate the effects of a 30-day rehabilitation program using a slant board on walking function in post-stroke hemiparetic patients. [Subjects and Methods] Six hemiparetic patients with gait disturbance were studied. The patients were instructed to perform a home-based rehabilitation program using a slant board, thrice daily for 30 days, the exercise included standing on the slant board for 3 minutes, with both ankles dorsiflexed without backrest. For all patients, the Brunnstrom Recovery Stage, Barthel Index, range of motion of the ankle joint, modified Ashworth scale scole for calf muscle, sensory impairments with Numeral Rating Scale, maximum walking speed, number of steps, and Timed “Up and Go” test were serially evaluated at the beginning and end of the 30-day program. [Results] The program significantly increased walking velocity, decreased the number of steps in the 10-m walking test, and decreased Timed “Up and Go” test performance time. [Conclusion] This rehabilitation program using the slant board was safe and improved walking function in patients. The improvement in walking function could be due to a forward shift of the center of gravity, which can be an important part of motor learning for gait improvement.
Supervised Information Retrieval for Text and Images

Motivation: In recent years, with the continuing increase in available storage space, image repositories have grown to such sizes that it is becoming ever more difficult to keep track of this large amount of data. These images are usually ”unlabeled. ” If these images were categorized and ”labeled,” it would allow for the simple retrieval of a specific image upon request. It is important therefore, to find methods which enable us to automatically categorize and label these images. Say for example, we were requesting an image (photo) of the president of the U.S.A. from a large database of images. If all the images had already been placed into categories and labeled, then it would be trivial to just return all the images which fall into the category of U.S. President. The motivation for this work is the fact that several learning-machine algorithms have already been developed. Our goal is to combine several such algorithms and to use boosting techniques to improve our results.
Identification of Novel Genes Coding for Small Expressed RNAs

In Caenorhabditis elegans, lin-4and let-7 encode 22- and 21-nucleotide (nt) RNAs, respectively, which function as key regulators of developmental timing. Because the appearance of these short RNAs is regulated during development, they are also referred to as small temporal RNAs (stRNAs). We show that many 21- and 22-nt expressed RNAs, termed microRNAs, exist in invertebrates and vertebrates and that some of these novel RNAs, similar to let-7 stRNA, are highly conserved. This suggests that sequence-specific, posttranscriptional regulatory mechanisms mediated by small RNAs are more general than previously appreciated.
Moving object detection from moving platforms using Lagrange multiplier

Moving object detection is the first key step for many automated vision analysis applications. One of the major challenges to achieve accurate moving object detection is detecting moving objects in videos captured by moving camera platforms, also called active cameras, where both interest objects and background elements are moving. This paper presents a novel algorithm for moving objects detection from active cameras. The proposed method decomposes a video from an active camera into three components: background, moving objects, and transformation matrix between consecutive frames. The proposed method formulates the problem as a robust principle component analysis (PCA) problem (low rank matrix optimization problem) and solves it using inexact augmented Lagrange multiplier (IALM). In the proposed method, the background represents the low rank matrix, and the moving objects and transformation matrix are treated as added corruption. The robustness of the proposed method is demonstrated using a challenging dataset captured by camera mounted on unmanned air vehicle. The obtained results show that the proposed method achieves best results compared to other current state-of-the-art relevant methods.
Hole filling using dynamic programming for archaeological data completion

We develop a 3D mesh completion system for archaeological data. Topology inconsistency (such as local self-intersections) and holes on triangle meshes are detected and repaired via a dynamic programming paradigm. We demonstrate the effectiveness of our methodology on several datasets. The developed system is used for archaeological and forensic data completion. It serves as an important preprocessing step for many subsequent data analysis/processing tasks of forensic anthropologists.
Financial Markets and Economic Growth in Poland: Simulations with an Econometric Model

In this paper we present simulations of economic performance of the Polish economy based on a quarterly econometric model. The model consists of 22 stochastic equations, which link the financial market with the real economy. The purpose of the research is to present effects of changes to domestic and foreign interest rates and the EUR/USD exchange rate on economic growth in Poland over the period Q2, 1993 – Q2, 2003.
Analysis of Optical Code Division Multiple Access Passive Networks for Different Encoder Delay Elements

One of the most important core technologies in the development of optical code division multiple access (OCDMA) local area networks is the optical encoder/decoder embodiment technology which codes information to fixed patterns at the transmitting side and decodes information at the receiving side. The selection of optimized encoding method for network composition is necessary to accommodate a maximum number of subscribers that have simultaneous access over the local area network and the bandwidth of subscriber services available on it. When composing this encoder/decoder optically, passive elements are exclusively used, if possible, so as to make the composition method simple and economical. In this paper we present an analysis of OCDMA passive communication networks focusing on the modeling of optical encoder/decoder blocks for different types of delay elements. The main objective of the paper is to study the performance of these networks including the effect of the passive encoder/decoder parameters such as splitter and optical delay line losses. Different types of delay lines are proposed including optical fibers and fiber Bragg gratings (FBG) as delay elements for the selection of the optical delay line which achieves a better performance. A statistical model of an OCDMA network has been developed and used for this study, including the effect of different passive encoder/decoder parameters, multiple access interference and noise
More short signatures without random oracles

We construct three new signatures and prove their securities without random oracles. They are motivated, respectively, by Boneh and Boyen [9]’s, Zhang, et al. [45]’s, and Camenisch and Lysyanskaya [14]’s signatures without random oracles. The first two of our signatures are as short as [9, 45]’s state-of-the-art short signatures, and are 17% shorter if the pairings in use admits a Verheul homomorphism or an algebraic tori attack. Our third signature is reducible to a modified LRSW Assumption [31] but without the LRSW Assumption’s hypothesized external signing oracle. New and interesting variants of the q-SDH Assumption, the q-SR (Square Root) Assumption are also presented. New and independently interesting proof techniques extending the two-mode technique of [9] are used, including a combined three-mode simulation and rewinding in the standard model.
A case study of behavior-driven conjoint analysis on Yahoo!: front page today module

Conjoint analysis is one of the most popular market research methodologies for assessing how customers with heterogeneous preferences appraise various objective characteristics in products or services, which provides critical inputs for many marketing decisions, e.g. optimal design of new products and target market selection. Nowadays it becomes practical in e-commercial applications to collect millions of samples quickly. However, the large-scale data sets make traditional conjoint analysis coupled with sophisticated Monte Carlo simulation for parameter estimation computationally prohibitive. In this paper, we report a successful large-scale case study of conjoint analysis on click through stream in a real-world application at Yahoo! We consider identifying users' heterogenous preferences from millions of click/view events and building predictive models to classify new users into segments of distinct behavior pattern. A scalable conjoint analysis technique, known as tensor segmentation, is developed by utilizing logistic tensor regression in standard partworth framework for solutions. In offline analysis on the samples collected from a random bucket of Yahoo! Front Page Today Module, we compare tensor segmentation against other segmentation schemes using demographic information, and study user preferences on article content within tensor segments. Our knowledge acquired in the segmentation results also provides assistance to editors in content management and user targeting. The usefulness of our approach is further verified by the observations in a bucket test launched in Dec. 2008.
0 50 70 44 v 1 1 8 Ju l 2 00 5 Remarks on the K 41 scaling law in turbulent fluids

A definition of K41 scaling law for suitable families of measu res is given and investigated. First, a number of necessary conditions are p roved. They imply the absence of scaling laws for 2D stochastic Navier-Stokes equations and for the stochastic Stokes (linear) problem in any dimension, while they imply a lower bound on the mean vortex stretching in 3D. Second, for 3D stoc hastic NavierStokes equations necessary and sufficient conditions for K4 1 are proved, translating the problem into bounds for energy and enstrophy of high a nd low modes respectively. The validity of such conditions in 3D remains open. Finally, a stochastic vortex model with such properties is presented.
Title : Emerging feed-forward inhibition allows the robust formation of direction 1 selectivity in the developing ferret visual cortex 2 3 Abbreviated title : Feed-forward methods for learning direction selectivity

Title: Emerging feed-forward inhibition allows the robust formation of direction 1 selectivity in the developing ferret visual cortex 2 3 Abbreviated title: Feed-forward methods for learning direction selectivity 4 5 Authors: Stephen D. Van Hooser, Gina M. Escobar, Arianna Maffei, Paul 6 Miller 7 1: Department of Biology 8 2: Sloan-Swartz Center for Theoretical Neurobiology 9 3: Volen Center for Complex Systems 10 Brandeis University, Waltham, MA 02454 USA 11 4: Department of Neurobiology and Behavior 12 5: SUNY Eye Institute 13 State University of New York–Stony Brook, Stony Brook, NY 11794 14 15 16 Corresponding author: 17 Stephen D. Van Hooser, vanhooser@brandeis.edu 18 Brandeis University, 415 South St. MS008, Waltham, MA 02454 USA 19 20 Number of Pages: 33 21 Number of Figures and Tables: 10 Figures, 1 Table 22 Number of words: Abstract: 248 (250 max), Intro: 500 (500 max), Discussion: 1498 23 (1500 max) 24 25 Conflicts of interest: The authors declare no competing financial interests. 26 27 Acknowledgements: This work was funded by the Swartz Foundation (GE), NSF IOS 28 1120938 (SDV), NIH EY022122 (PM and SDV), the Charles H. Hood Foundation 29 (SDV), and the John Merck Foundation. We thank Neil Ritter, Jason Osik, Marjena 30 Popović, Arani Roy, Jennifer Wolff, J. Hayim Dar, and Ralf Haefner for comments on 31 the model and the manuscript. 32 33 Contributions: SDV, GME, PM designed the model, AM contributed the extension of 34 the model design to include feed-forward inhibition, SDV performed model simulations 35 and wrote the paper with input from all authors. 36 37