Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameter matching using adaptive synchronization of two Chua's oscillators

In this paper, we develop an adaptive synchronization technique for parameter matching with chaotic persistent excitation (PE). Two Chua's oscillators, identical in every parameter except for one, are set up in a master/slave configuration where the slave's mismatched parameter is adaptable. Using Lyapunov functions and incorporating the presence of PE, adaptive control laws are designed to ensure exact parameter matching. One of the derived adaptive controllers is experimentally validated by using an adaptive inductor-gyrator composed of current feedback op-amps (CFOAs).
Enhancement in Motor Learning through Genetic Manipulation of the Lynx1 Gene

The cholinergic system is a neuromodulatory neurotransmitter system involved in a variety of brain processes, including learning and memory, attention, and motor processes, among others. The influence of nicotinic acetylcholine receptors of the cholinergic system are moderated by lynx proteins, which are GPI-anchored membrane proteins forming tight associations with nicotinic receptors. Previous studies indicate lynx1 inhibits nicotinic receptor function and limits neuronal plasticity. We sought to investigate the mechanism of action of lynx1 on nicotinic receptor function, through the generation of lynx mouse models, expressing a soluble version of lynx and comparing results to the full length overexpression. Using rotarod as a test for motor learning, we found that expressing a secreted variant of lynx leads to motor learning enhancements whereas overexpression of full-length lynx had no effect. Further, adult lynx1KO mice demonstrated comparable motor learning enhancements as the soluble transgenic lines, whereas previously, aged lynx1KO mice showed performance augmentation only with nicotine treatment. From this we conclude the motor learning is more sensitive to loss of lynx function, and that the GPI anchor plays a role in the normal function of the lynx protein. In addition, our data suggests that the lynx gene plays a modulatory role in the brain during aging, and that a soluble version of lynx has potential as a tool for adjusting cholinergic-dependent plasticity and learning mechanisms in the brain.
Humanoid motion representation by sensory state transitions

Given the complexity and the high number of degrees of freedom humanoid robot motions often are generated off-line, stored in the robot memory and then reproduced. In the simplest cases motor commands are just replayed in open-loop (i.e. feed-forward), in more advanced implementations few parameters are changed on fly to adapt the motion to the external conditions. Indeed, several authors proposed a large variety of techniques to exploit the input from sensory feedback to modify a reference trajectory, in order to cope with environment changes and disturbances. In this paper, we propose a motion representation for humanoid robots that includes the sensory feedback information in the motion representation itself. This motion description allows stabilization against disturbances and environmental changes, but does not require any design or tuning of the relationships between sensory inputs and movement modification. We present experimental results on a simulated small humanoid robot equipped with motor encoders and touch sensors covering the whole body.
Discovery of three nearby L dwarfs in the Southern Sky

We report the discovery of three L dwarfs in the solar vicinity within 30 parsecs. These objects were originally found as proper motion objects from a combination of R and I photographic plates measured as part of the SuperCOSMOS Sky Surveys. We subsequently identified these objects as bona fide brown dwarf candidates on the basis of their R - I colour, as first criterion, and subsequently their J - K colours when the infrared data were available from the 2MASS database. Spectroscopic observations in the optical with the ESO 3.6 m/EFOSC2 and in the near-infrared with the NTT/SOFI led to the classification of their spectral types as early L dwarfs.
Using Spanning Sets for Coverage Testing

A test coverage criterion defines a set E/sub r/ of entities of the program flowgraph and requires that every entity in this set is covered under some test Case. Coverage criteria are also used to measure the adequacy of the executed test cases. In this paper, we introduce the notion of spanning sets of entities for coverage testing. A spanning set is a minimum subset of E/sub r/, such that a test suite covering the entities in this subset is guaranteed to cover every entity in E/sub r/. When the coverage of an entity always guarantees the coverage of another entity, the former is said to subsume the latter. Based on the subsumption relation between entities, we provide a generic algorithm to find spanning sets for control flow and data flow-based test coverage criteria. We suggest several useful applications of spanning sets: They help reduce and estimate the number of test cases needed to satisfy coverage criteria. We also empirically investigate how the use of spanning sets affects the fault detection effectiveness.
Motivation and Education: The Self-Determination Perspective

Self-determination theory (Deci & Ryan, 1985, 1991), when applied to the realm of education, is concerned primarily with promoting in students an interest in learning, a valuing of education, and a confidence in their own capacities and attributes. These outcomes are manifestations of being intrinsically motivated and internalizing values and regulatory processes. Research suggests that these processes result in high-quality learning and conceptual understanding, as well as enhanced personal growth and adjustment. In this article we also describe social-contextual factors that nurture intrinsic motivation and pralmote internalization, leading to the desired educational outcomes.
A Growth Model with Corruption in Public Procurement: Equilibria and Policy Implications

We study the relationship between corruption in public procurement and economic growth, within the Solow framework in discrete time, while assuming that the public good is an input in the productive process and that the State fixes a monitoring level on corruption depending on the tax revenues. The resulting model is a two-dimensional, continuous and piecewise smooth map describing the evolution of the capital per capita and that of the corruption level. We study model from the analytical point of view: we determine its fixed points, we study their local stability and, finally, we find conditions on parameters such that multiple equilibria co-exist. We also present numerical simulations useful to explain the role of parameters in the long{run path of the model and to analyze the structure of the basins of attraction when multiple equilibria emerge. Our study aims at demonstrating that stable equilibria with positive corruption may exist (according to empirical evidence), even though the State may reduce corruption by increasing the wage of the bureaucrat or by increasing the amount of tax revenues used to monitor corruption.
A Precision-Recall Criterion Based Consensus Model For Fusing Multiple Segmentations

This paper presents a general framework for seamlessly combining multiple low cost and inaccurate estimated segmentation maps (with an arbitrary number of regions) of the same scene to achieve a final improved segmentation. The proposed fusion model is derived from the well-known precision-recall criterion, specially dedicated to the specific clustering problem of any spatially indexed data and which is also efficient and widely used in the vision community for evaluating both a region-based segmentation and the quality of contours produced by this segmentation map compared to one or multiple ground-truth segmentations of the same image. The proposed combination framework is here specifically designed to be robust with respect to outlier segmentations (that appear to be inconsistent with the remainder of the segmentation ensemble) and includes an explicit internal regularization factor reflecting the inherent ill-posed nature of the segmentation problem. We propose also a hierarchical and efficient way to optimize the consensus energy function related to this fusion model that exploits a simple and deterministic iterative relaxation strategy combining the different segments or individual regions belonging to the segmentation ensemble in the final solution. The experimental results on the Berkeley database with manual ground truth segmentations show the effectiveness of our combination model.
Consumption and Real Exchange Rates With Incomplete Markets and Non-Traded Goods

This paper addresses the consumption-real exchange rate anomaly. International real business cycle models based on complete financial markets predict a unitary correlation between the real exchange rate and the ratio of home to foreign consumption when subjected to supply side shocks. In the data, this correlation is usually small and often negative. This paper shows that this anomaly can be successfully addressed by models that have an incomplete financial market structure and a non-traded as well as traded goods production sector.
Executive control and felt concentrative engagement following intensive meditation training

Various forms of mental training have been shown to improve performance on cognitively demanding tasks. Individuals trained in meditative practices, for example, show generalized improvements on a variety of tasks assessing attentional performance. A central claim of this training, derived from contemplative traditions, posits that improved attentional performance is accompanied by subjective increases in the stability and clarity of concentrative engagement with one's object of focus, as well as reductions in felt cognitive effort as expertise develops. However, despite frequent claims of mental stability following training, the phenomenological correlates of meditation-related attentional improvements have yet to be characterized. In a longitudinal study, we assessed changes in executive control (performance on a 32-min response inhibition task) and retrospective reports of task engagement (concentration, motivation, and effort) following one month of intensive, daily Vipassana meditation training. Compared to matched controls, training participants exhibited improvements in response inhibition accuracy and reductions in reaction time variability. The training group also reported increases in concentration, but not effort or motivation, during task performance. Critically, increases in concentration predicted improvements in reaction time variability, suggesting a link between the experience of concentrative engagement and ongoing fluctuations in attentional stability. By incorporating experiential measures of task performance, the present study corroborates phenomenological accounts of stable, clear attentional engagement with the object of meditative focus following extensive training. These results provide initial evidence that meditation-related changes in felt experience accompany improvements in adaptive, goal-directed behavior, and that such shifts may reflect accurate awareness of measurable changes in performance.
Gest-O: Performer gestures used to expand the sounds of the saxophone

This paper describes the conceptualization and development of an open source tool for controlling the sound of a saxophone via the gestures of its performer. The motivation behind this work is the need for easy access tools to explore, compose and perform electroacoustic music in Colombian music schools and conservatories. This work led to the adaptation of common hardware to be used as a sensor attached to an acoustic instrument and the development of software applications to record, visualize and map performers gesture data into signal processing parameters. The scope of this work suggested that focus was to be made on a specific instrument so the saxophone was chosen. Gestures were selected in an iterative process with the performer, although a more ambitious strategy to figure out main gestures of an instruments performance was first defined. Detailed gesture-to-sound processing mappings are exposed in the text. An electroacoustic musical piece was successfully rehearsed and recorded using the Gest-O system.
S-SUM: A System for Summarizing the Summaries

Query-specific summarization of multiple documents is a useful task in the current day context of the WWW, that is containing huge amount of information. When different summarizers have access to different sets of documents for a query, generating a summary of the summaries produced by the multiple summarizers becomes an interesting and useful task. In this paper, we propose an efficient solution for this problem. Sentences from the individual summaries are used to construct an Integrated Linear Structure (ILS) and are given unique position numbers. All the sentences in the ILS are then assigned weights that reflect the importance of the sentences to the given query. Sentences are selected according to these weights using the Maximal Marginal Relevance (MMR) approach for inclusion into the final summary of summaries. Finally, the sentences in the final summary are sorted based on their position numbers given using ILS. Experimental results show that S-SUM is efficient.
ARQ-BLAST system with adaptive error control

It is well known that multiple-input multiple-output (MIMO) wireless communication systems that employ multiple transmit and receive antennas can provide very high-rate data transmissions. We study an ARQ-BLAST scheme and use turbo codes as FEC. Based on the research, an ARQ-BLAST system with adaptive error control is presented in this paper. It provides the best tradeoff between throughput, delay time, and decoding complexity.
Empirical Analysis of Metering Price Discrimination: Evidence from Concession Sales at Movie Theaters

Prices for goods such as blades for razors, ink for printers, and concessions at movies are often set well above cost. Theory has shown that this could yield a profitable price discrimination strategy often termed “metering. ” The idea is that a customer's intensity of demand for aftermarket goods (e.g., the concessions) provides a meter of how much the customer is willing to pay for the primary good (e.g., admission). If this correlation in tastes for the two goods is positive, a high price on the aftermarket good allows firms to extract a greater total price (admissions plus concessions) from higher-type customers. This paper develops a simple aggregate model of discrete-continuous demand to motivate how this correlation can be tested using simple regression techniques and readily available firm data. Model simulations illustrate that the regressions can be used to predict whether aftermarket prices should be above, below, or equal to their marginal cost. We then apply the approach to box office and concession data from a chain of Spanish theaters and find that high-priced concessions do extract more surplus from customers with a greater willingness to pay for the admission ticket.
Ameliorative Effects of Curcumin on Artesunate-Induced Subchronic Toxicity in Testis of Swiss Albino Male Mice

India is one of the endemic areas where control of malaria has become a formidable task. Artesunate is the current antimalarial drug used to treat malaria, especially chloroquine resistant. The objective of the present study was to investigate the dose-dependent effect of oral administration of artesunate on the oxidative parameters in testes of adult male Swiss albino mice and ameliorative efficacy of curcumin, a widely used antioxidant. An oral dose of 150 mg/kg body weight (bwt; low dose) and 300 mg/kg bwt (high dose) of artesunate was administered for a period of 45 days to male mice, and ameliorative efficacy of curcumin was also assessed. The results revealed that artesunate caused significant alteration in oxidative parameters in dose-dependent manner. Administration of artesunate brought about significant decrease in activities of superoxide dismutase, glutathione, glutathione peroxidase, and glutathione reductase, whereas lipid peroxidation and glutathione-S-transferase activity were found to be significantly increased. The results obtained show that oxidative insult is incurred upon the intracellular antioxidant system of testis tissue by artesunate treatment. Further, administration of curcumin at the dose level of 80 mg/kg bwt along with both doses of artesunate attenuated adverse effects in male mice.
An accelerated pshchoacoustic model chip design for MPEG 2/4 AAC audio

This paper presents a new architecture design for MDCT-based PAM co-processor which is used in MPEG2/4 audio encoder. PAM is important tool. It determines quality of a given audio encoder. This work is based on the dedicated hardware design which is different from traditional programmable approaches. Moreover, to reduce the complexity, we replace the calculations of spreading function with reduced fixed coefficients, and decrease the transform kernels from three to one units. We also convert the calculation into the log number system (LNS). The multiplication and division in LNS is just add and sub respectively.
Inferring a Distributed Application Behavior Model for Anomaly Based Intrusion Detection

As distributed computations become more and more common in highly distributed environments like the cloud, intrusion detection systems have to follow these paradigms. Anomaly based intrusion detection systems in distributed systems usually rely on a total order of the observed events. However, such hypothesis is often too strong, as in a highly distributed environment the order of the observed events is partially unknown. This paper demonstrates it is possible to infer a distributed application behavior model for intrusion detection, relying only on a partial ordering of events. The originality of the proposed approach is to tackle the problem by combining two types of models that are usually used separately: an automaton modeling the distributed computation, and a list of temporal properties that the computation must comply with. Finally, we apply the approach on two examples, and assess the method on a real distributed application.
Prediction of chaotic time series with NARX recurrent dynamic neural networks

The problem of chaotic time series prediction is studied in various disciplines now including engineering, medical and econometric applications. Chaotic time series are the output of a deterministic system with positive Liapunov exponent. A time series prediction is a suitable application for a neuronal network predictor. The NN approach to time series prediction is non-parametric, in the sense that it is not necessary to know any information regarding the process that generates the signal. It is shown that the recurrent NN (RNN) with a sufficiently large number of neurons is a realization of the nonlinear ARMA (NARMA) process. In this paper we present the nonlinear autoregressive network with exogenous inputs (NARX), the architecture, the training method, the input data to network, the simulation results.
20 kW 18-pulse diode converter - results of laboratory tests

The article presents the principle of operation of a coupled three-phase reactor (CTRλ) used applied in 18-pulse diode converter. Using sets of coupled three-phase power network reactors, the presented converter makes it possible to considerably reduce, at low cost, undesired higher harmonics in the power network current. Selected results of laboratory tests done on a 20kVA 18-pulse diode converter are included.
Infusing social data analytics into Future Internet applications for manufacturing

Today, a new age of engagement and collaboration has emerged with the proliferation of usergenerated content in social networks and generally the Web 2.0, rendering it particularly difficult for enterprises to monitor and act upon all content following conventional data mining methodologies. In this paper, we present our approach for a Future Internet enabler (FITMAN Anlzer) that provides automated, social data analytics and aims at assisting enterprises in becoming more tuned to their customer needs and gaining insights into current and future trends to early embed them into product design. The FITMAN Anlzer implementation is domainindependent and allows any manufacturer to effectively train it based on his needs and create personalized reports to timely capture the right information. Our methodology includes trend analytics, polarity detection through machine learning, data querying through flexible reports and finally informative charts to visualize the results in order to help companies in their decision making procedures.
Industry-Inspired Guidelines to Improve Students’ Pair Programming Communication

Novice pair programmers find communication within their pairs to be one of the greatest difficulties they face when starting to pair program. However, developers cannot pair program without a certain amount of communication. This research describes the development of an analytic coding scheme derived from observation of the communication of expert pairs working in industry. Communication patterns identified from these expert pairs are being used by lecturers to help novices learn to be more effective in their pair communication.
Elastic time slice scheduler in virtualized system

Virtualization is a key technology in the modern data centers as well as in the cloud computing industry. Modern virtual machine monitors (VMM) like KVM and Xen play a key role in the management and maintenance of virtual machines (VM). However, as a software middle layer, VMM brings in a negative impact in terms of VM's performance, among which the I/O events latency problem is one of the biggest issue.
CEO Pulchronomics and Appearance Discrimination

PurposePulchronomics studies the economics of beauty. The purpose of this paper is to research CEO pulchronomics by examining whether a beauty premium exists in CEO compensation and whether this beauty premium is justified by differences in CEO performance.Design/methodology/approachThe authors calculate a facial attractiveness scores (FAS) based on facial symmetry, facial structure and the golden ratio. The authors then perform OLS regressions to examine the effect of CEO beauty on CEO compensation and firm performances.FindingsThe authors find that base salaries for attractive CEOs are higher than those for unattractive CEOs, but incentive pays for attractive CEOs are not different from those for unattractive CEOs. The latter is likely due to the fact that attractive CEOs do not outperform unattractive CEOs in operations, innovation, corporate social responsibility and financial reporting quality.Originality/valueSince the CEO beauty premium is not supported by the superior performance of attractive CEOs, this paper provides new evidence of appearance discrimination in CEO compensation.