Miracle-dz/UniFAR-FTUs huggingface dataset:
STATISTICAL PRINCIPLES OF SOURCE

Blind signal separation (BSS) is an emerging signal processing technique, aiming at recovering unobserved signals or`sources' from observed mixtures (typically, the output of an array of sensors), exploiting only the assumption of mutual independence between the signals. The weakness of the assumptions makes it a powerful approach but requires to venture beyond familiar second order statistics. The objective of this paper is to review some of the approaches that have been recently developed to address this exciting problem, to show how they stem from basic principles and how they relate together.
Forecasting the Main Tax Revenues in the Czech Economy

This article deals with the forecasting of the main tax revenues in the Czech economy. The authors analyze the relationship between taxes (value added, excise, corporate income, personal income, and social-security contributions) and selected macroeconomic variables (especially, GDP and wage growth). Several linear regression models are presented. They tend to be viable and suitable for the short-term estimation of tax revenues conditional to no structural changes in the fiscal framework. The authors, in emphasizing the difficulties associated with the predictability of budget resources, shed light upon the fiscal processes in the Czech economy.
Language Emergence and Grounding in Sensorimotor Agents and Robots

The grounding of linguistic symbols in the organism’ cognitive system, and indirectly in the physical and social environment in which individuals live, is one of the most important issues in recent experimental and computational approaches to language. This is normally referred as the Symbol Grounding Problem (Harnad 1990). In cognitive science, psychological experiments have focused on the relationship between language and perception (Barsalou 1999; Coventry & Garrod 2004) and language and action (Glenberg & Kaschak 2002). These empirical investigations show a strong interdependence between language development and perceptual and embodiment factors. In robotics and artificial intelligence, various models have been proposed to ground language in neural networks (Joyce et al. 2003; Cangelosi et al. 2000; Dyer 1994) and in interactive robots (Steels 2002; Vogt 2002; Roy & Pentland 2002). Moreover, computational approaches to the evolution of language (Cangelosi & Parisi 2002) commonly deal with the issue of symbol grounding. In this paper we present a computational modeling approach to language based on an integrative view of the agent’s cognitive system. This work has mainly been developed at the “Adaptive Behaviour & Cognition” research group 1 of the University of Plymouth. All models reviewed here are characterized by the fact that the emergence of linguistic abilities (both evolutionarily and developmentally) is strictly dependent on, and grounded in, other behaviors and abilities. These include sensorimotor skills (e.g. action categories), cognitive abilities (e.g. categorical perception), neural mechanisms, and social and evolutionary factors. Agents are able to build an intrinsic link between the linguistic symbols (words) they use to communicate and their own sensorimotor and cognitive representations (meanings) of the perceptual and sensorimotor interaction with the external world (referents). This approach is called “grounded adaptive agent modeling” for the emergence of language (Cangelosi in press). Linguistic simulations with such agents imply the use of groups of autonomous agents that interact via language games to exchange information about the environment. It also entails the fact that their coordinated communication system is not externally imposed by the researcher, but emerges from the interaction between agents. The paper will present a series of past and current studies on grounded adaptive agent models. Some will be based on simulated sensorimotor agents, others on evolutionary and epigenetic robots.
Empirical Study of Multi-objective Ant Colony Optimization to Software Project Scheduling Problems

The Software Project Scheduling Problem (SPSP) focuses on the management of software engineers and tasks in a software project so as to complete the tasks with a minimal cost and duration. It's becoming more and more important and challenging with the rapid development of software industry. In this paper, we employ a Multi-objective Evolutionary Algorithm using Decomposition and Ant Colony (MOEA/D-ACO) to solve the SPSP. To the best of our knowledge, it is the first application of Multi-objective Ant Colony Optimization (MOACO) to SPSP. Two heuristics capable of guiding the algorithm to search better in the SPSP model are examined. Experiments are conducted on a set of 36 publicly available instances. The results are compared with the implementation of another multi-objective evolutionary algorithm called NSGA-II for SPSP. MOEA/D-ACO does not outperform NSGA-II for most of complex instances in terms of Pareto Front. But MOEA/D-ACO can obtain solutions with much less time for all instances in our experiments and it outperforms NSGA-II with less duration for most of test instances. The performance may be improved with tuning of the algorithm such as incorporating more heuristic information or using other MOACO algorithms, which deserve further investigation.
Hand based biometr

A biometric scheme based on the silhouettes and/or textures of the hands is developed. The crucial part of the algorithm is the accurate registration of the deformable shape of the hands since subjects are not constrained in pose or posture during acquisition. A host of shape and texture features are comparatively evaluated, such as Independent component features (ICA features), Principal Component Analysis (PCA features), Angular Radial Transform (ART features) and the distance transform (DT) based features. Even with a limited number of training data it is shown that this biometric scheme can perform reliably for populations up to several hundreds.
Excitatory synaptic potentials in kainic acid-denervated rat CA1 pyramidal neurons

Intracellular recordings were performed in the CA1 region of the rat hippocampus following an ipsilateral intraventricular injection of kainic acid. Seven days postlesion, graded bursts of up to four action potentials could be evoked by stimulation of the stratum radiatum. The evoked EPSPs underlying these bursts showed a prolonged 10–90% rise time and half-width compared to control EPSPs, an absence of a significant inhibitory phase, and an increase in magnitude and duration at depolarized resting levels. The evoked EPSPs also exhibited a significant decrease in amplitude and time course in response to D-APV (D-2-amino-5-phosphonovaleric acid; 1–20 microM), though this effect was variable from cell to cell. The prolonged time course, voltage sensitivity, and response to a selective NMDA antagonist confirmed that the major component of the EPSP in neurons from lesioned slices was mediated by NMDA receptors. The partial denervation of the CA1 area induced by the kainic acid led to both an enhanced NMDA-mediated excitatory phase and a decrease in postsynaptic inhibition, resulting in the pronounced hyperexcitability noted in the lesioned slices.
Controlling carbon emissions and measuring the carbon footprint across a supply chain is a challenge for organizations

Supply chain network design attempts to define the best supply chain configuration that enables an organization to maximize its long-term economic performance. Typically, the decisions cover three planning levels (Anthony, 1965; Bertrand, 2003; Fleischmann et al., 2002; Manzini et al., 2008): • Long-term planning (three to five years): Decisions of this level are called strategic decisions and should address how much capacity is needed in each entity, where each part of finished product should be made and in what quantities, how many safety stocks should be formed, how many resources should be bought, and so on. • Mid-term (or tactical) planning (six to twenty-four months): Tactical planning determines an outline of the regular operations, in particular rough quantities and times for the flows and resources enabling the consideration of seasonal trends of demand. Tactical problem types attempt to adopt the most optimal use of the various resources, including manufacturing plants, warehouses, transports, and so on. Using the available flexibility to realize the required performance is the realm of the tactical decision-making process. • Short-term planning (from one to four months): The lowest planning or operational level has to specify all activities in a detailed schedule for immediate execution and Supply chain scheduling strategies historically have emphasized lead time; in almost all cases, energy and environmental factors have not been considered in scheduling. This article presents a new mathematical programming model of the supply chain scheduling problem that considers CO2 emissions and their associated carbon footprint in addition to lead time. To model the problem we chose the job shop theoretical model in which each machine represents a supply chain member and jobs represent the product batches. The new model is demonstrated using a simple case study: a supply chain in which two plants are employed to produce a variety of parts. We illustrate how carbon emissions concerns can be integrated into operational decision making with regards to production and financial flows. The results show that carbon emissions across stages in a supply chain can constitute a significant threat that merits careful attention in the operational planning of supply chains.
Some Remarks on Reconstructing the Prehistoric Linguistic Relationships of the Tai-Kadai Language Family and Its Putative Linguistic Affiliations with Other Language Families : A Review Article

From the outset the researcher has approached the t opic of this review article with great trepidation. Obviously, the paper does not purport t provide final answers or solutions to problems associated with the reconstruction of the linguistic prehistory of the Tai-Kadai language family or even less definitive conclusions concerning the ethnolingustic affiliations or affinities with other language families. Even so, the researcher has the temerity to review research investigations impinging on this topic in the work of archaeologists, geneticists, historians and linguists. Special attention is dir ected to recent advances in genetic investigations of the peopling of Asia. It is in t he context that the researcher discusses what can be inferred from these investigations concernin g the prehistoric linguistic relationships between the Tai-Kadai the Austronesian, and the Aus tro-Tai language families, on the one hand, and the languages of the Baiyue (Chinese: 百越; Bǎiyuè) peoples on the other. As such, this review article offers suggestions for re classifying the Tai-Kadai language family and related language families with which it was ass ociated or had affinities so as to include the Bǎiyuè (or Hundred Yue) languages and some of its sub divisions, including proto-Yaht and proto-Vietnamese (Vi ệt) in the prehistory of these language groups.
Simulation of RF Noise in MOSFETs Using Different Transport Models

SUMMARY RF noise in quarter-micron nMOSFETs is analysed on the device level based on Shockley’s impedance field method. The impact of different transport models and physical parameters is discussed in detail. Well-calibrated drift-diffusion and energy-balance models give very similar results for noise current spectral densities and noise figures. We show by numerical simulations with the general-purpose device simulator DESSIS−ISE that the hot-electron effect on RF noise is unimportant under normal operating conditions and that thermal substrate noise is dominant below 0.5 GHz. The contribution of energy-current fluctuations to the terminal noise is found to be negligible. Application of noise sources generated in bulk fullband Monte Carlo simulations changes the noise figures considerably, which underlines the importance of proper noise source models for far-from-equilibrium conditions.
Cross-talk and regulation between glutamate and GABAB receptors

Brain function depends on co-ordinated transmission of signals from both excitatory and inhibitory neurotransmitters acting upon target neurons. NMDA, AMPA and mGluR receptors are the major subclasses of glutamate receptors that are involved in excitatory transmission at synapses, mechanisms of activity dependent synaptic plasticity, brain development and many neurological diseases. In addition to canonical role of regulating presynaptic release and activating postsynaptic potassium channels, GABAB receptors also regulate glutamate receptors. There is increasing evidence that metabotropic GABAB receptors are now known to play an important role in modulating the excitability of circuits throughout the brain by directly influencing different types of postsynaptic glutamate receptors. Specifically, GABAB receptors affect the expression, activity and signaling of glutamate receptors under physiological and pathological conditions. Conversely, NMDA receptor activity differentially regulates GABAB receptor subunit expression, signaling and function. In this review I will describe how GABAB receptor activity influence glutamate receptor function and vice versa. Such a modulation has widespread implications for the control of neurotransmission, calcium-dependent neuronal function, pain pathways and in various psychiatric and neurodegenerative diseases.
Impacts of environment, nervous system and movements of preterms on body map development: Fetus simulation with spiking neural network

Recent developmental studies have shown the importance of interaction with the environment resulting from fetal spontaneous movements for the formation of body maps in the spinal cord and primary somatosensory area. However, the underlying mechanism as well as the factors which contribute to the development of body maps is largely unknown. Here, we simulated the development of the body map using a human fetus simulation, and investigated the contribution of three factors which often differ in normal fetuses and preterms: (i) developmental environment, (ii) nervous system and (iii) movement patterns. The fetus model has a musculoskeletal body as well as sensory organs for tactile and proprioception, which allows us to simulate sensory feedbacks resulting from interaction with the uterine environment. We simulated the development of body maps by using these sensory feedbacks as inputs to the spinal and somatosensory cortex models, which are spiking neural networks with leaky integrate-and-fire neurons and spike-timing-dependent synaptic plasticity. We showed that the networks under normal fetus conditions can learn body part-specific modular architectures and responses, and have neurons encoding specific postures and double-touch events. In contrast, we found that (i) a change in environment from inside to outside the uterus, (ii) an imbalance between excitation and inhibition of the nervous system and (iii) decrease in variation and complexity of movement patterns each lead to the development of abnormal body maps in terms of function and structure of learned networks. These results suggest that these factors influence or disrupt body map development in preterms and their subsequent cognitive development.
Evolutionary algorithmic approaches for solving three objectives task scheduling problem on heterogeneous systems

The task scheduling problem in a heterogeneous system (TSPHS) is a NP-complete problem. It is a multiobjective optimization problem (MOP). The objectives such as makespan, average flow time, robustness and reliability of the schedule are considered for solving task scheduling problem. This paper considers three objectives of minimizing the makespan (schedule length), minimizing the average flow-time and maximizing the reliability in the multiobjective task scheduling problem. Multiobjective Evolutionary Computation algorithms (MOEAs) are well suited for Multiobjective task scheduling for heterogeneous environment. The two Multi-Objective Evolutionary Algorithms such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Evolutionary Programming (MOEP) with non-dominated sorting are developed and compared for the various random task graphs and also for a real-time numerical application graph. This paper also demonstrates the capabilities of MOEAs to generate well-distributed pareto optimal fronts in a single run.
Cost incentives in European football.

We examine the effects of financial incentives on effort supplied by football clubs in European domestic leagues. Tournament theory predicts that the amount of effort supplied varies with returns to effort. We analyze variation in 31,746 domestic league match outcomes in ten European leagues over eleven seasons, exploiting the actual standings on the league table to generate variables reflecting incentives to provide effort in each match. Results from ordered logit regressions indicate that the effort implied by observed match outcomes support the predictions of tournament theory in this setting; clubs supply more or less effort in response to changes in incentives.
Towards an e-Publishing library service in Humanities and Social Sciences: a feasibility study

The paper describes a methodology used to analyze the editorial production of CNR Institutes belonging to the Department of Humanities and Social Sciences HSS. This analysis is considered a pre-requisite to design a feasibility study to develop an e-Publishing service tailored to HSS. To reach this aim the paper describes in particular the characteristics of currently published products defining a set of quality indicators that can help designing a future e-Publishing service.
Torification and factorization of birational maps

Building on the work of the fourth author in math.AG/9904074, we prove the weak factorization conjecture for birational maps in characteristic zero: a birational map between complete nonsingular varieties over an algebraically closed field K of characteristic zero is a composite of blowings up and blowings down with smooth centers. Such a factorization exists which is functorial with respect to absolute isomorphisms, and compatible with a normal crossings divisor. The same holds for algebraic and analytic spaces. Another proof of the main theorem by the fourth author appeared in math.AG/9904076.
Growing Beyond the Low-Cost Advantage: How the People's Republic of China Can Avoid the Middle-Income Trap

Growing beyond the low-cost advantage: how the People's Republic of China can avoid the middle-income trap. The views expressed in this book are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. By making any designation of or reference to a particular territory or geographic area, or by using the term " country " in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area. ADB encourages printing or copying information exclusively for personal and noncommercial use with proper acknowledgment of ADB. Users are restricted from reselling, redistributing, or creating derivative works for commercial purposes without express, written consent of ADB. Contents iii Boxes, Figures, and Tables iv Foreword vii Preface viii Acknowledgments ix Abbreviations and Acronyms x Symbols and Measures x Executive Summary xi 1. Introduction 1
Separating Words from Continuous Bangla Speech T

In this paper we present a new word separation algorithm for Real Time Speech i.e., Continuous Bangla Speech Recognition (CBSR). Prosody has great impact on Bangla speech and the algorithm is developed by considering prosodic feature with energy. Task of this algorithm is to separate Bangla speech into words. At first continuous Bangla speech are fed into the system and the word separation algorithm separate speech into isolate words. Performance of the proposed algorithm is compared to the existing algorithms and result shows that 98% word boundaries are correctly
The Construction of Movement with Behavior-Specific and Behavior-Independent Modules

Growing evidence suggests that different forms of complex motor acts are constructed through flexible combinations of a small number of modules in interneuronal networks. It remains to be established, however, whether a module simply controls groups of muscles and functions as a computational unit for use in multiple behaviors (behavior independent) or whether a module controls multiple salient features that define one behavior and is used primarily for that behavior (behavior specific). We used the Aplysia feeding motor network to examine the two proposals by studying the functions of identifiable interneurons. We identified three types of motor programs that resemble three types of behaviors that Aplysia produce: biting, swallowing, and rejection. Two ingestive programs (biting, swallowing) are defined by two movement parameters of the feeding apparatus (the radula): one is the same in both programs (phasing of radula closure motoneurons relative to radula protraction-retraction), whereas the other parameter (protraction duration) is different in the two programs. In each program, these two parameters were specified together by an individual neuron, but the neurons in each were different (B40 for biting, B30 for swallowing). These findings support the existence of behavior-specific modules. Furthermore, neuron B51 was found to mediate a phase that can be flexibly added on to both ingestive and egestive-rejection programs, suggesting that B51 may be a behavior-independent module. The functional interpretation of the role played by these modules is supported by the patterns of synaptic connectivity that they make. Thus, both behavior-specific and behavior-independent modules are used to construct complex behaviors.
Optimal Portfolio of the Low Liquid Asset with the Log-utility Function Optimal Portfolio of the Low Liquid Asset with the Log-utility Function

When the asset is not completely liquid, we cannot trade the asset continuously. To represent this we assume that the risky asset can be traded at the random times that are exponentially distributed. We solve the optimal portfolio problem of this asset. And the asymptotic character of the optimal strategy is discussed. Further we show the convergence of the value function when the liquidity becomes increasing.
Nitric oxide as a mediator of ABA signalling in stomatal guard cells

Water shortage is likely to be one of the major global environmental stresses of the 21st century. A key plant response to declining soil water potential is increased biosynthesis and subsequent action of abscisic acid (ABA). ABA is an endogenous anti-transpirant that induces stomatal closure, thereby leading to water conservation. The signal transduction processes commencing with guard cell ABA recognition and culminating in transport of ions and water across the vacuolar and plasma membranes, resulting in guard cell shrinkage and stomatal closure, have not yet been completely resolved. Nitric oxide (NO) has recently been identified as a mediator of guard cell ABA signalling (Neill et al., 2002. Plant Physiol. 128, 13-16). ABA induces the synthesis of NO in guard cells, NO induces stomatal closure and either scavenging of NO or inhibition of NO synthesis reduces ABA-induced stomatal closure. These data indicate that NO synthesis is a critical component of ABA-induced stomatal closure. Aspects of NO synthesis and action are discussed.