Miracle-dz/UniFAR-FTUs huggingface dataset:
I speak fast when I move fast: the speed of illusory self-motion (vection) modulates the speed of utterances

Speed of utterance is an important factor in smooth and efficient conversation. We report a technique to increase utterance speed and that might improve a speaker's impression and information efficiency in conversation. We used a visual display consisting of optic flows in a large visual field that induced participants' illusory self-motion perception (vection). The speed of vection corresponded to the speed of the optic flows. Using this method, we investigated whether vection speed affects utterance speed. We presented fast- and slow-moving optic flow stimuli while dynamically swapping random dots presented to participants, during which time the participants were asked to talk for 2 min. Results revealed that the utterance speed was significantly faster in the fast optic flow condition. Our method could be a stepping stone for establishing a technique of modulating speech speed effectively.
Control Improvement of a C Sugar Cane Crystallization Using an Auto-Tuning PID Controller Based on Linearization of a Neural Network

The industrial process of the sugar cane crystallization produces a residual that still contains a lot of soluble sucrose and the objective of the factory is to improve its extraction. Therefore, there are substantial losses justifying the search for the optimization of the process. Crystallization process studied on the industrial site is based on the “three massecuites process”. The third step of this process constitutes the final stage of exhaustion of the sucrose dissolved in the mother liquor. During the process of the third step of crystallization (Ccrystallization), the phase that is studied and whose control is to be improved, is the growing phase (crystal growth phase). The study of this process on the industrial site is a problem in its own. A control scheme is proposed to improve the standard PID control law used in the factory. An auto-tuning PID controller based on instantaneous linearization of a neural network is then proposed. Keywords—Auto-tuning, PID, Instantaneous linearization, Neural network, Non linear process, C-crystallisation.
A novel patch-based image denoising algorithm using finite radon transform for good visual

—Patch-based denoising methods have recently emerged due to its good denoising performance. In this paper, based on analysis of the optimal over-complete patch aggregation, we highlight the importance of a local transform for good image features representation. A finite Radon transform (FRAT) based two-stage over-complete image denoising algorithm is then proposed for obtaining good visual quality of denoised images. Experimental results demonstrate good performance in that the denoised images obtained by the proposed method are less influenced by artifacts.
LEGO Pictorial Scales for Assessing Affective Responses

This article presents the design and evaluation of novel types of pictorial scales for assessing emotional response based on LEGO Minifigures. We describe the creation of two pictorial scales (LEGO Face Scale and Stylized LEGO Face Scale) through the use of a semi-automatic process. We report on the results of two evaluation studies conducted to assess the validity of the proposed pictorial scales. The first study evaluated the rating of emotions expressed by other humans; the second focused on rating one’s own emotional state when looking at expressive stimuli. We investigate the validity of the two pictorial scales by comparing them to ratings given on a conventional Likert Scale. Results show that assessing expressive faces using the proposed pictorial scales can differ from using a Likert scale; however, when rating one’s own emotional state there is no difference. Finally, we assembled a physical version of the LEGO Face scale and discuss future work.
Approach and Withdrawal Tendencies during Written Word Processing: Effects of Task, Emotional Valence, and Emotional Arousal

The affective dimensions of emotional valence and emotional arousal affect processing of verbal and pictorial stimuli. Traditional emotional theories assume a linear relationship between these dimensions, with valence determining the direction of a behavior (approach vs. withdrawal) and arousal its intensity or strength. In contrast, according to the valence-arousal conflict theory, both dimensions are interactively related: positive valence and low arousal (PL) are associated with an implicit tendency to approach a stimulus, whereas negative valence and high arousal (NH) are associated with withdrawal. Hence, positive, high-arousal (PH) and negative, low-arousal (NL) stimuli elicit conflicting action tendencies. By extending previous research that used several tasks and methods, the present study investigated whether and how emotional valence and arousal affect subjective approach vs. withdrawal tendencies toward emotional words during two novel tasks. In Study 1, participants had to decide whether they would approach or withdraw from concepts expressed by written words. In Studies 2 and 3 participants had to respond to each word by pressing one of two keys labeled with an arrow pointing upward or downward. Across experiments, positive and negative words, high or low in arousal, were presented. In Study 1 (explicit task), in line with the valence-arousal conflict theory, PH and NL words were responded to more slowly than PL and NH words. In addition, participants decided to approach positive words more often than negative words. In Studies 2 and 3, participants responded faster to positive than negative words, irrespective of their level of arousal. Furthermore, positive words were significantly more often associated with “up” responses than negative words, thus supporting the existence of implicit associations between stimulus valence and response coding (positive is up and negative is down). Hence, in contexts in which participants' spontaneous responses are based on implicit associations between stimulus valence and response, there is no influence of arousal. In line with the valence-arousal conflict theory, arousal seems to affect participants' approach-withdrawal tendencies only when such tendencies are made explicit by the task, and a minimal degree of processing depth is required.
Demography and Language Competition

Abstract Attempts to describe language competition and extinction in a mathematical way have enjoyed increased popularity recently. In this paper I review recent modeling approaches and, based on these findings, propose a model of reaction-diffusion type. I analyze the dynamics of interactions of a population with two monolingual groups and a group that is bilingual in these two languages. The results show that demographic factors, such as population growth or population dispersal, play an important role in the competition dynamic. Furthermore, I consider the impact of two strategies for language maintenance: adjusting the status of the endangered language and adjusting the availability of monolingual and bilingual educational resources.
1 , 2 , 3 , More : An Accumulator Architecture for Anchoring and Adjustment

We present a computational model of probabilistic reasoning in a synthetic task environment. The task is a solitaire game called TRACS in which a player must update odds as card are turned, like Blackjack. Initial experiments with this game showed that human subjects exhibit a “baseline bias” due to a heuristic strategy of “anchoring and adjustment”. Here we develop a computational model of this behavior using fuzzy functions and simple summing to simulate the cognitive processes of memory activation and evidence accumulation. We compare the simulation results to experimental data and highlight the practical value of our approach.
The Impact of R&D Spillovers on Export Value: Does the Transmission Channel matter?

There is overwhelming evidence in the literature that open economies benefit from spillover effects from foreign R&D efforts. These effects increase in particular total factor productivity. Several transmission channels have been detected and studied intensively. Most of them are related to foreign direct investments or international trade. These real economic phenomena are themselves affected by spillovers, either indirectly through their effect on total factor productivity or directly through, for example, increased business contacts between investors, traders and producers. Â In this empirical paper we study the effects of R&D spillovers on exports within the OECD. Previous evidence pointed to the crucial role of the transmission channel for such spillovers. Therefore we distinguish between trade-related and foreign-direct-investment related channels and indicators. By doing so we are able to determine the relevance and importance of each of the suggested channels and measures. We control for alternative determinants of export value by extending the well-accepted gravity model for international trade by incorporating R&D spillovers in the standard gravity specification. Our results indicate that – at least at the macro-level – the choice of the transmission channel matters. In particular we find clear evidence that imports are an important transmission channel for technological spillovers, whereas there is only weak evidence in favour of any role for foreign direct investments. Hence these findings simply that openness to trade is a better policy in order to benefit from foreign knowledge than openness to investments.
AGRIDEMA: un esfuerzo europeo para la introducción de herramientas de simulación en la toma de decisiones agrícolas : oportunidades para mejorar la eficiencia del uso del agua

The details of the Specific Support Action entitled “Introducing tools for agricultural decision-making under climate change conditions by connecting users and tool-providers” (AGRIDEMA), funded by the European Union in its Sixth Framework Program, are presented. AGRIDEMA is being coordinated by ITACYL, from Castilla y Leon, and comprises partners from the Agricultural University of Vienna (Austria) and the Bulgarian Institute of Meteorology. The AGRIDEMA central goal is to promote a network, connecting the European producers of simulating tools with their potential users. Only the potential users of such simulating tools, located mainly in Agricultural Research Services, are able to apply those tools to support effective local decisions. AGRIDEMA will focus on the impacts of extreme events, such as droughts and flooding, due to the significant risk that those extreme events mean for agricultural production. AGRIDEMA involves contacts between “providers” of the simulating tools and their “users”, as well as Courses on such simulating tools to be held at the end of 2005. Pilot applications or assessments to be carried out in different regions of Europe, particularly in Mediterranean and Eastern-European countries, are included in AGRIDEMA also. AGRIDEMA will finish in 2007, with an International Workshop to be held in Valladolid. The European-Network for Simulating-Tool Applications will be launched in the Valladolid Workshop. The Network will be aimed to facilitate the potential users’ access to the available tools. Probably, one of the main applications of simulating-tool is to support effective irrigation water-management designs. In that sense, this presentation finishes inviting to the specialists on soil-water movement to attend the AGRIDEMA activities.
Geometrically induced spectrum in curved leaky wires

We study measure perturbations of the Laplacian in L2(2) supported by an infinite curve ? in the plane which is asymptotically straight in a suitable sense. We show that if ? is not a straight line, such a `leaky quantum wire' has at least one bound state below the threshold of the essential spectrum.
TPpred3 detects and discriminates mitochondrial and chloroplastic targeting peptides in eukaryotic proteins

MOTIVATION Molecular recognition of N-terminal targeting peptides is the most common mechanism controlling the import of nuclear-encoded proteins into mitochondria and chloroplasts. When experimental information is lacking, computational methods can annotate targeting peptides, and determine their cleavage sites for characterizing protein localization, function, and mature protein sequences. The problem of discriminating mitochondrial from chloroplastic propeptides is particularly relevant when annotating proteomes of photosynthetic Eukaryotes, endowed with both types of sequences. RESULTS Here, we introduce TPpred3, a computational method that given any Eukaryotic protein sequence performs three different tasks: (i) the detection of targeting peptides; (ii) their classification as mitochondrial or chloroplastic and (iii) the precise localization of the cleavage sites in an organelle-specific framework. Our implementation is based on our TPpred previously introduced. Here, we integrate a new N-to-1 Extreme Learning Machine specifically designed for the classification task (ii). For the last task, we introduce an organelle-specific Support Vector Machine that exploits sequence motifs retrieved with an extensive motif-discovery analysis of a large set of mitochondrial and chloroplastic proteins. We show that TPpred3 outperforms the state-of-the-art methods in all the three tasks. AVAILABILITY AND IMPLEMENTATION The method server and datasets are available at http://tppred3.biocomp.unibo.it. CONTACT gigi@biocomp.unibo.it SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Selecting best attributes for software defect prediction

A software defect prediction model is used to help identifying the defects of software module. Software attributes play an important role to build the model. The performance and effectiveness of a software defection model depends on the characteristics of various software attributes which can be used to predict whether a software module is defected or non-defected. Based on software, one or more software metrics can become irrelevant as those do not contain significant information or contains redundant information. If appropriate attributes are not used for defect prediction model, the performance of the model may decrease. Therefore, in order to improve the effectiveness and performance of defect prediction model, it is important to select proper attributes which can be used to build a good predictor model. In this study, we propose an attribute selection process for software defect prediction model. Our experiment shows that our proposed approach provides comparatively better set of attributes which increases the performance of defect prediction model. We compared our approach with two existing approaches using eight NASA data set and our approach showed up to 54% improvement in software defect prediction.
Efficient time-bound hierarchical key assignment scheme

The access privileges in distributed systems can be effectively organized as a hierarchical tree that consists of distinct classes. A hierarchical time-bound key assignment scheme is to assign distinct cryptographic keys to distinct classes according to their privileges so that users from a higher class can use their class key to derive the keys of lower classes, and the keys are different for each time period; therefore, key derivation is constrained by both the class relation and the time period. We propose, based on a tamper-resistant device, a new time-bound key assignment scheme that greatly improves the computational performance and reduces the implementation cost.
Optical gain and green/red vertical cavity surface emitting lasing from cdse-based colloidal nanocrystal quantum dot thin films

We demonstrate robust excitonic gain from colloidal close-packed, CdSe-based nanocrystal quantum dot thin films at record low threshold excitation energy of 90 μJ/cm2 for amplified spontaneous emission. The optical gain is employed in pulsed optically pumped quantum dot vertical cavity surface emitting lasers in the green and the red, respectively.
An Unsupervised Algorithm for Person Name Disambiguation in the Web

In this paper we present an unsupervised approach for clustering the results of a search engine when the query is a person name shared by different individuals. We represent the web pages using n-grams, comparing different kind of information and different length of n-grams. Moreover, we propose a new clustering algorithm that calculates the number of clusters and establishes the groups of web pages according to the different individuals, without the need of any training data or predefined thresholds, as the successful state of the art systems do. Our approach is compared with three gold standard collections compiled by different evaluation campaigns for the task of Web People Search. We obtain really competitive results, comparable to those obtained by the best approaches that use annotated data.
Identifying Spectrum Usage by Unknown Systems using Experiments in Machine Learning

We adopt a machine learning approach towards the problem of identifying wireless systems present in a dynamic radio environment with heterogeneous usage. To classify the wireless systems, we utilize two features that typify spectrum use--center frequency and the frequency spread--and cluster the measurement data in this space. Since the systems are unknown prior to clustering, we use an unsupervised clustering method that uses the Chinese restaurant process implemented using Gibbs sampling. The system identification is divided into two parts: training and online classification. In the training phase, we assign wireless systems present in the surrounding to the clusters while the online classification uses this trained data to perform classification. By means of an extensive measurement campaign, we show that the proposed machine learning process achieves up to 90% correctness in classifying the wireless systems considered here.
Mobility Helps Energy Balancing in Wireless Networks

In this paper, we investigate the effects of mobility on the energy dissipation characteristics of wireless networks. We construct a Linear Programming (LP) framework that jointly captures data routing, mobility, and energy dissipation aspects and explore the design space by performing numerical analysis using the developed LP framework. Our results show that mobility has significant effects on the energy dissipation trends of wireless nodes. Mobility can improve the energy balancing up to a certain level, however extreme mobility may lead to a degradation in energy balancing, and thus energy efficiency of wireless networks.
Funding Individuals – Changing Organisations: The Impact of the ERC on Universities

Abstract University governance is constantly challenged by changing expectations and contexts. New, prestigious and well-endowed funding schemes are one possible source of pressure for change of university governance. This article analyses the impact of one such scheme, the grants of the European Research Council (ERC), on the governance of European universities. After outlining a model of how this impact on universities can be expected to occur, we present the results of an exploratory study at a very early stage of the ERC’s existence (2010–2011). The empirical analysis is based on an investigation of 11 universities in eight countries, which shows that different kinds of universities are affected in varied and often unexpected ways, with particular differences arising at different levels within the universities.
Comparative steady-state pharmacokinetic study of an extended-release formulation of itopride and its immediate-release reference formulation in healthy volunteers

Background This study was conducted to compare the oral bioavailability of an itopride extended-release (ER) formulation with that of the reference immediate-release (IR) formulation in the fasting state. The effect of food on the bioavailability of itopride ER was also assessed. Methods A single-center, open-label, randomized, multiple-dose, three-treatment, three-sequence, crossover study was performed in 24 healthy male subjects, aged 22–48 years, who randomly received one of the following treatments for 4 days in each period: itopride 150 mg ER once daily under fasting or fed conditions, or itopride 50 mg IR three times daily in the fasting state. Steady-state pharmacokinetic parameters of itopride, including peak plasma concentration (Cmax) and area under the plasma concentration versus time curve over 24 hours after dosing (AUC0–24h), were determined by noncompartmental analysis. The geometric mean ratio of the pharmacokinetic parameters was derived using an analysis of variance model. Results A total of 24 healthy Korean subjects participated, 23 of whom completed the study. The geometric mean ratio and its 90% confidence interval of once-daily ER itopride versus IR itopride three times a day for AUC0–24h were contained within the conventional bioequivalence range of 0.80–1.25 (0.94 [0.88–1.01]), although Cmax was reached more slowly and was lower for itopride ER than for the IR formulation. Food delayed the time taken to reach Cmax for itopride ER, but AUC0–24h was not affected. There were no serious adverse events and both formulations were generally well tolerated. Conclusion At steady state, once-daily itopride ER at 150 mg has a bioavailability comparable with that of itopride IR at 50 mg given three times a day under fasting conditions. Food delayed the absorption of itopride ER, with no marked change in its oral bioavailability.
A self-shadow algorithm for dynamic hair using density clustering

Self-shadowing is an important factor in the appearance of hair and fur. In this paper we present a new rendering algorithm to accurately compute shadowed hair at interactive rates using graphics hardware. No constraint is imposed on the hair style, and its geometry can be dynamic. Similar to previously presented methods, a 1D visibility function is constructed for each line of sight of the light source view. Our approach differs from other work by treating the hair geometry as a 3D density eld, which is sampled on the y using simple rasterization. The rasterized fragments are clustered, effectively estimating the density of hair along a ray. Based hereon, the visibility function is constructed. We show that realistic selfshadowing of thousands of individual dynamic hair strands can be rendered at interactive rates using consumer graphics hardware.