Miracle-dz/UniFAR-FTUs huggingface dataset:
1 Creation and Exploration of Musical Information Spaces

With the creation of large audio collections, available on small portable devices or via Web portals, new ways for interacting with these collections need to be devised. Retrieving specific songs, or navigating through such audio repositories, relying on the way music sounds rather than on metadata tags, poses challenging problems. This paper presents the SOMeJB system, which builds on features extracted directly from sound signals such as CD recordings or MP3 files, to create a navigable information space of music according to perceived sound similarities of the individual titles.
Physiological considerations on Neuromuscular Electrical Stimulation (NMES) in muscular strength training Consideraţii fiziologice asupra utilizării electrostimulării neuro- musculare (ESNM) ca metodă de creştere a forţei musculare

Neuromuscular Electrical Stimulation (NMES) is a form of electrical stimulation that uses the application of electric current through electrodes, leading to the depolarization of the motoneuron, thus eliciting a muscular contraction (stimulation over the motor threshold). Although its beneficial effects on strength training are widely recognized, some controversial aspects concerning the underlying physiological mechanisms of this strength gain still persist. This paper reviews the main aspects of motor unit recruitment in NMES versus Voluntary Muscular Contraction (VMC) and of the involvement of the Central Nervous System - through spinal and supraspinal mechanisms - in the muscle strength gain during NMES.
Seroprevalence of Leptospira borgpetersenii serovar javanica infection among dairy cattle, rats and humans in the Cauvery river valley of southern India.

Leptospirosis is a major problem of dairy farms in Tamilnadu, India, resulting in abortions, stillbirths and infertility. Serologic and genetic analyses of samples from cattle, humans and rodents were performed in order to estimate infection prevalence and identify leptospiral species. Five hundred and fifteen sera and 76 urine samples were collected from dairy cattle on 25 farms including a farm that practiced rat control. Sera and kidney samples were also collected from field rats (Rattus norvegicus) in the vicinity of these farms. In addition, sera were collected from farm workers. Serum antibody was measured by the microscopic agglutination test. Leptospires isolated from blood, kidney, and urine were characterized as to serovar. Genomospecies were predicted using random amplified polymorphic DNA (RAPD) profiling. SecY gene sequencing was performed as a tool for tracing of source. Seroprevalence of 87. %, 51. % and 76.5% for cattle, rats and humans, respectively, was observed on endemic farms. Prevalences on a non-endemic farm were lower. Antibodies to Autumnalis, Javanica, Icterohaemorrhagiae and Pomona predominated in both cattle and rats. Thirteen isolates from rat kidneys were identified as serogroup Javanica, serovar Javanica. RAPD comparisons and secY gene sequencing identified these isolates as Leptospira borgpetersenii. These results altogether indicated that L. borgpetersenii was the dominant species in these areas with serovar Javanica apparently derived from rats which provided an important source of infection in cattle resulting a high incidence of infertility, abortion and.still-birth in the Cauvery river valley, Tiruchirappalli, Tamilnadu.
The IGWM Method for Tabriz Traffic Modeling: Data-Oriented Approach

Traffic models play an important role in traffic research and in many traffic applications such as traffic flow prediction, incident detection and traffic control. The traffic problem is one of the challenging issues in large cities nowadays. Intelligent Transportation System (ITS) is one of the suitable methods for solving this problem. ITS for Tabriz as a large city in Iran is very vital. Traffic modeling is the first step to implement the ITS. In this paper an Intelligent Green Wave Model (IGWM) based on data-oriented approach has been introduced for traffic modeling of this city. This model is suitable for green wave based controller systems.
Scanning the Technology Applications of Asynchronous Circuits

A comparison with synchronous circuits suggests four opportunities for the application of asynchronous circuits: high performance, low power, improved noise and electromagnetic compatibility (EMC) properties, and a natural match with heterogeneous system timing. In this overview article each opportunity is reviewed in some detail, illustrated by examples, compared with synchronous alternatives, and accompanied by numerous pointers to the literature. Conditions for applying asynchronous circuit technology, such as the existence and availability of computer-aided design (CAD) tools, circuit libraries, and effective test approaches, are discussed briefly. Asynchronous circuits do offer advantages for many applications, and their design methods and tools are now starting to become mature.
DC — 15 GHz CMOS SP8T switches using defected ground structure low pass filter

In this paper, we present a novel concept to design single-pole eight-throw (SP8T) switch using a defected ground structure low pass filter (DGS LPF). The DGS LPF produces an enhanced inductance to compensate the parasitic capacitances of the control transistors. As a result, the SP8T switch will consume much less silicon area. The total areas and active areas of the SP8T switches are less than 860 × 460 μm2 and 425 × 165 μm2 respectively. The concept is validated with post layout simulation results of three SP8T switches in a 65-nm CMOS.
Simulated Crowd: Towards a Synthetic Culture for Engaging a Learner in Culture-dependent Nonverbal Interaction

Difficulties in living in a different culture are caused by different patterns of thinking, feeling and potential actions. A good way to experience cultural immersion is to walk in a crowd. This paper proposes a simulated crowd as a novel tool for allowing people to practice culture-specific nonverbal communication behaviors. We present a conceptual framework of a simulated crowd using an immersive interactive environment. We discuss technical challenges concerning a simulated crowd, including realtime eye gaze recognition in a dynamic moving situation, sensing of nonverbal behaviors using multiple range sensors, and behavior generation based on novel temporal data mining algorithms.
Dynamic resource allocation using auto-negotiation in Haizea

Higher hardware utilization and SLA fulfillment are two main objectives of any infrastructure cloud, thus, making resource allocation to virtual machines as one of the most critical aspect. Haizea is a popular cloud lease manager which supports a variety of resource leases according to the application requirements. These leases are: Immediate, Best-Effort, Deadline Sensitive and Advance Reservation (AR). But all these leases are static in nature viz. once resources are allocated to a lease, these resources cannot be altered during the complete lifetime of the lease. This contradicts with the philosophy and implementation of a pure on-demand elastic cloud where resources of a lease are continuously monitored against the utilization and altered based on the requirements. Our work aims at the inclusion of three important features to mitigate this shortcoming in Haizea. First, it introduces a new class of lease: Dynamic lease to accommodate resource changes. Second, it examines virtual machine resource utilization to decide about the demand and need of allocation change and third, it accommodates the expected changes in resource allocation by introducing two new sub-leases which allow dynamic resource allocation in the schedule. Lease experiments are performed on Haizea to validate the introduced features.
Trade and Transboundary Pollution

This paper examines how national income and trading opportunities interact to determine the level and incidence of world pollution. The authors find that free trade raises world pollution if incomes differ substantially across countries; if trade equalizes factor prices, human-capital-abundant countries lose from trade, while human-capital-scarce countries gain; international trade in pollution permits can lower world pollution even when governments' supply of permits is unrestricted; international income transfers may not affect world pollution or welfare; and attempts to manipulate the terms of trade with pollution policy leave world pollution unaffected. Copyright 1995 by American Economic Association.
Stock and Bond Pricing in an Affine Economy

This article provides a stochastic valuation framework for bond and stock returns that builds on three different pricing traditions: affine models of the term structure, present-value pricing of equities, and consumption-based asset pricing. Our model provides a more general application of the affine framework in that both bonds and equities are priced in a consistent fashion. This pricing consistency implies that term structure variables help price stocks while stock price fundamentals help price the term structure. We illustrate our model by considering three examples that are similar in spirit to well-known pricing models that fall within our general framework: a Mehra and Prescott (1985) economy, a present value model similar to Campbell and Shiller (1988b), and a model with stochastic risk aversion similar to Campbell and Cochrane (1998). The empirical performance of our models is explored, with a particular emphasis on return predictability.
Sphingosine 1-Phosphate Receptor 2 Signals Through Leukemia-Associated RhoGEF (LARG), to Promote Smooth Muscle Cell Differentiation

Objective—The goals of this study were to identify the signaling pathway by which sphingosine 1-phosphate (S1P) activates RhoA in smooth muscle cells (SMC) and to evaluate the contribution of this pathway to the regulation of SMC phenotype. Methods and Results—Using a combination of receptor-specific agonists and antagonists we identified S1P receptor 2 (S1PR2) as the major S1P receptor subtype that regulates SMC differentiation marker gene expression. Based on the known coupling properties of S1PR2 and our demonstration that overexpression of G&agr;12 or G&agr;13 increased SMC-specific promoter activity, we next tested whether the effects of S1P in SMC were mediated by the regulator of G protein-signaling-Rho guanine exchange factors (RGS-RhoGEFs) (leukemia-associated RhoGEF [LARG], PDZ-RhoGEF [PRG], RhoGEF [p115]). Although each of the RGS-RhoGEFs enhanced actin polymerization, myocardin-related transcription factor-A nuclear localization, and SMC-specific promoter activity when overexpressed in 10T1/2 cells, LARG exhibited the most robust effect and was the only RGS-RhoGEF activated by S1P in SMC. Importantly, siRNA-mediated depletion of LARG significantly inhibited the activation of RhoA and SMC differentiation marker gene expression by S1P. Knockdown of LARG had no effect on SMC proliferation but promoted SMC migration as measured by scratch wound and transwell assays. Conclusion—These data indicate that S1PR2-dependent activation of RhoA in SMC is mediated by LARG and that this signaling mechanism promotes the differentiated SMC phenotype.
An ERD/ERS analysis of the relation between human arm and robot manipulator movements

This work aims to analyze the relation between the movement of an anthropomorphic robotic manipulator with the brain cortex response elicited in healthy subjects for three experimental conditions. The experiment was divided in three parts: in the first one, the subject only observes the movement of the robotic manipulator; in the second part, the subject follows the robot movement with his right arm; finally, in the third part, the subject imagines the execution of the corresponding movement synchronized with the movement of the robot. Event related (de)synchronization in each of the recorded electroencephalogram (EEG) channels was analyzed. Event related desyn-chronization was present in alpha and beta bands in various areas of the cortex, including occipital, parietal, central and prefrontal areas. The results provided some physiological insights into human-robot interaction for future developments in brain-machine interfaces.
A Weighted DV-Hop Localization Scheme for Wireless Sensor Networks

Localization is an important problem in wireless sensor networks (WSNs), since location information is widely requested in various location-dependent applications. As one of the range-free localization algorithm DV-Hop, a well known localization algorithm, can be simply implement in real WSNs. To improve the accuracy of localization, this paper proposes an improved DV-Hop algorithm. The proposed algorithm is derived from DV-Hop algorithm, and uses weight of anchors to improve localization accuracy without needing no additional hardware device. Simulation results show that the improved DV-Hop algorithm can provide more accurate location estimation than the DV-Hop algorithm.
Asymmetry and Leverage in Stochastic Volatility Models : An Exposition

The accurate specification and modelling of risk are integral to optimal portfolio and risk management. In this context, a wide variety of conditional and stochastic volatility models has been used to estimate latent volatility (or risk). In both the conditional and stochastic volatility literature, there has been some confusion between the definitions of asymmetry and leverage. This paper examines alternative univariate SV models that have recently been developed and estimated in to order to understand the differences and similarities between the definitions of asymmetry and leverage. Five univariate SV models, namely the basic SV model, SV model with leverage, and three different types of asymmetric SV models, are analysed in order to clarify the distinction between asymmetry and leverage. Alternative specifications of SV models are defined according to the use of standardized or unstandardized returns, with or without leverage, in order to evaluate the differential impacts of positive and negative returns on future volatility, namely symmetry, asymmetry, type I asymmetry (or leverage), type II asymmetry, and type III asymmetry.
Habitat Composition and Connectivity Predicts Bat Presence and Activity at Foraging Sites in a Large UK Conurbation

Background Urbanization is characterized by high levels of sealed land-cover, and small, geometrically complex, fragmented land-use patches. The extent and density of urbanized land-use is increasing, with implications for habitat quality, connectivity and city ecology. Little is known about densification thresholds for urban ecosystem function, and the response of mammals, nocturnal and cryptic taxa are poorly studied in this respect. Bats (Chiroptera) are sensitive to changing urban form at a species, guild and community level, so are ideal model organisms for analyses of this nature. Methodology/Principal Findings We surveyed bats around urban ponds in the West Midlands conurbation, United Kingdom (UK). Sites were stratified between five urban land classes, representing a gradient of built land-cover at the 1 km2 scale. Models for bat presence and activity were developed using land-cover and land-use data from multiple radii around each pond. Structural connectivity of tree networks was used as an indicator of the functional connectivity between habitats. All species were sensitive to measures of urban density. Some were also sensitive to landscape composition and structural connectivity at different spatial scales. These results represent new findings for an urban area. The activity of Pipistrellus pipistrellus (Schreber 1774) exhibited a non-linear relationship with the area of built land-cover, being much reduced beyond the threshold of ∼60% built surface. The presence of tree networks appears to mitigate the negative effects of urbanization for this species. Conclusions/Significance Our results suggest that increasing urban density negatively impacts the study species. This has implications for infill development policy, built density targets and the compact city debate. Bats were also sensitive to the composition and structure of the urban form at a range of spatial scales, with implications for land-use planning and management. Protecting and establishing tree networks may improve the resilience of some bat populations to urban densification.
Photometric Invariant Projective Registration Using ECC Maximization

The ability of an algorithm to accurately estimate the parameters of the geometric transformation which aligns two image profiles even in the presence of photometric distortions can be considered as a basic requirement in many computer vision applications. Projective transformations constitute a general class which includes as special cases the affine, as well as the metric subclasses of transformations. In this paper the applicability of a recently proposed iterative algorithm, which uses the Enhanced Correlation Coefficient as a performance criterion, in the projective image registration problem is investigated. The main theoretical results concerning the iterative algorithm and an efficient approximation that leads to an optimal closed form solution (per iteration) are presented. Furthermore, the performance of the iterative algorithm in the presence of nonlinear photometric distortions is compared against the leading Lucas-Kanade algorithm by performing numerous simulations. In all cases the proposed algorithm outperforms the Lucas-Kanade algorithm in convergence speed and robustness against photometric distortions under ideal and noisy conditions.
FAVC: Clustering Categorical Data Using the Frequency of Attribute Values Combinations

This paper proposes a new clustering algorithm for categorical data based on the frequency of attribute values combinations (FAVC). This algorithm finds all the combinations of attribute values in a record (which represent a subset of all the attribute values), and then groups the records using the frequency of these combinations. As the FAVC algorithm considers all the subsets of attribute values in a record, records in a cluster have not only similar attribute value sets but also strongly associated attribute values. The FAVC algorithm evaluated with real and synthetic data sets. The FAVC is shown better clustering results and superior running time in comparison with that of COOLCAT.
Exploring the Seasonality of Reported Treated Malaria Cases in Mpumalanga, South Africa

South Africa, having met the World Health Organisation's pre-elimination criteria, has set a goal to achieve malaria elimination by 2018. Mpumalanga, one of three provinces where malaria transmission still occurs, has a malaria season subject to unstable transmission that is prone to sporadic outbreaks. As South Africa prepares to intensify efforts towards malaria elimination, there is a need to understand patterns in malaria transmission so that efforts may be targeted appropriately. This paper describes the seasonality of transmission by exploring the relationship between malaria cases and three potential drivers: rainfall, geography (physical location) and the source of infection (local/imported). Seasonal decomposition of the time series by Locally estimated scatterplot smoothing is applied to the case data for the geographical and source of infection sub-groups. The relationship between cases and rainfall is assessed using a cross-correlation analysis. The malaria season was found to have a short period of no/low level of reported cases and a triple peak in reported cases between September and May; the three peaks occurring in October, January and May. The seasonal pattern of locally-sourced infection mimics the triple-peak characteristic of the total series while imported infections contribute mostly to the second and third peak of the season (Christmas and Easter respectively). Geographically, Bushbuckridge municipality, which exhibits a different pattern of cases, contributed mostly to the first and second peaks in cases while Maputo province (Mozambique) experienced a similar pattern in transmission to the imported cases. Though rainfall lagged at 4 weeks was significantly correlated with malaria cases, this effect was dampened due to the growing proportion of imported cases since 2006. These findings may be useful as they enhance the understanding of the current incidence pattern and may inform mathematical models that enable one to predict the impact changes in these drivers will have on malaria transmission.
FEM modeling of conductivity and electrical coupling in polymeric nanocomposite material

We propose an approach useful for the evaluation of electrical conductivity of nanocomposite materials. We consider the modeling of a polymeric matrix with gold nanoparticles by evaluating the electrical coupling of spherical gold nanoparticles embedded in chitosan polymer. The electrical coupling is generated by a voltage signal which provides a current distribution which is function of the gold nanonoparticles filling factor. We use a properly designed finite element method (FEM) tool.
Confidence, Pessimism and their Impact on Product Differentiation in a Hotelling Model with Demand Location Uncertainty

We analyze a Hotelling location-then-price duopoly game under demand uncertainty with uniformly distributed consumers in a standard quadratic costs scenario. The novelty of our approach consists of assuming that firms' beliefs are represented by non-extreme-outcome-additive (neo-additive) capacities. We derive firms' subgame-perfect product design decisions under ambiguity. Furthermore, we investigate the influence of ambiguity and ambiguity attitude on equilibrium product differentiation and contrast our results with an environment of risky firms. We find that the impact of the degree of confidence or ambiguity is particularly significant when it comes to delivering accurate explanations for a wide range of phenomena related to observed product design behavior.
Coalition Games in Fisheries Economics

We review the literature on coalition games applied in fisheries economics. We first indicate the importance and origin of the theory. Then we compare noncooperative and cooperative coalition game approaches. Our conclusion is that the non-cooperative and the cooperative approach should be linked together. To achieve this aim future research on stability of cooperative solutions and factors influencing stability is needed.
PrtT-Regulated Proteins Secreted by Aspergillus fumigatus Activate MAPK Signaling in Exposed A549 Lung Cells Leading to Necrotic Cell Death

Aspergillus fumigatus is the most commonly encountered mold pathogen of humans, predominantly infecting the respiratory system. Colonization and penetration of the lung alveolar epithelium is a key but poorly understood step in the infection process. This study focused on identifying the transcriptional and cell-signaling responses activated in A549 alveolar carcinoma cells incubated in the presence of A. fumigatus wild-type and ΔPrtT protease-deficient germinating conidia and culture filtrates (CF). Microarray analysis of exposed A549 cells identified distinct classes of genes whose expression is altered in the presence of germinating conidia and CF and suggested the involvement of both NFkB and MAPK signaling pathways in mediating the cellular response. Phosphoprotein analysis of A549 cells confirmed that JNK and ERK1/2 are phosphorylated in response to CF from wild-type A. fumigatus and not phosphorylated in response to CF from the ΔPrtT protease-deficient strain. Inhibition of JNK or ERK1/2 kinase activity substantially decreased CF-induced cell damage, including cell peeling, actin-cytoskeleton damage, and reduction in metabolic activity and necrotic death. These results suggest that inhibition of MAPK-mediated host responses to treatment with A. fumigatus CF decreases cellular damage, a finding with possible clinical implications.