Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex structure moduli stability in toroidal compactifications

In this paper we present a classification of possible dynamics of closed string moduli within specific toroidal compactifications of type-II string theories due to the NS-NS tadpole terms in the reduced action. They appear as potential terms for the moduli when supersymmetry is broken due to the presence of D-branes. We particularise to specific constructions with two, four and six-dimensional tori, and study the stabilisation of the complex structure moduli at the disk level. We find that, depending on the cycle on the compact space where the brane is wrapped, there are three possible cases: i) there is a solution inside the complex structure moduli space, and the configuration is stable at the critical point, ii) the moduli fields are driven towards the boundary of the moduli space, iii) there is no stable solution at the minimum of the potential and the system decays into a set of branes.
A 128 /spl times/ 128 pixel 120 dB dynamic range vision sensor chip for image contrast and orientation extraction

This vision sensor outputs luminance, contrast magnitude and contrast orientation of image features for surveillance and automotive applications. The sensor produces a contrast representation with a dynamic range of 120 dB and a sensitivity of 2%. The chip is fabricated in a 0.5 /spl mu/m 3M 2P process and dissipates 300 mW at 3.3 V.
Optimum band selection in hyperspectral imagery using swarm intelligence optimization algorithms

Despite rich and fine spectral information of hyperspectral imagery, curse of dimensionality and Hughes phenomenon affect the land use/cover classification accuracy of such images. In this situation, optimal feature/band selection based on optimization procedures has high potential to improve the accuracy of hyperspectral image pattern recognition and classification. Among other optimization techniques, Meta heuristic optimization algorithms such as Swarm intelligence-based methods are so capable in solving feature/band selection problems. This paper evaluates the potential of Firefly algorithm (FA) and Particle Swarm Optimization (PSO) as representatives of swarm intelligence-based methodologies in optimal band selection and dimensionality reduction of hyperspectral imagery. Implementation results of Firefly algorithm and PSO in the case of AVIRIS hyperspectral image classification is compared with Genetic algorithm as another well known Meta heuristic optimization method. The preliminarily results confirm the high capabilities of Firefly algorithm and PSO for solving optimal feature/band subset selection.
Alcohol Risk Environments, Vulnerability, and Social Inequalities in Alcohol Consumption

Alcohol and alcohol-related harm are key public health challenges. Research has shown that individual-level factors, such as age and sex, are important predictors of alcohol consumption, but such factors provide only a partial account of the drivers of consumption. In this article, we argue that individual-level factors interact with features of the risk environment to increase the vulnerability of individuals to such environments. Features of the alcohol risk environment include the density of alcohol premises in a neighborhood. Previous research has shown that neighborhoods with a higher density of alcohol outlets have higher levels of both alcohol consumption and alcohol-related harm. There has, however, been a distinct lack of attention paid to the differential ways in which particular sociodemographic groups might be more vulnerable to such risk environments. In this article, we address the risk environment through a primary focus on the local supply and availability of alcohol products (captured using a measure of outlet density) and the relationship with the harmful use of alcohol. Using responses to the Scottish Health Survey (2008–2011), we explore vulnerability through the interaction between individual-level socioeconomic position, measured using household income, and environmental risk to assess differential social vulnerability to such environments. We report findings showing that those in the lowest income groups might be disproportionately affected by outlet density. This evidence suggests that risk environments might not affect us all equally and that there could be socially differentiated vulnerability to such environments.
Meshing the hyperbolic octagon

This short report describes a preliminary study of a method computing meshes of the standard hyperbolic octagon that respects its symmetries. A prototype software was written, using the 2D meshing package of the CGAL library and a software computing hyperbolic triangulations, currently under development (see INRIA RR No 8146).
Congestion Control Algorithm for Data Center

With the problem of congestion becoming more and more serious in data centers, a great deal of attention has been paid to the congestion control technology. In this paper, we first analyze and summarize the reasons that cause congestion in data center. Second, from the point of the network congestion control algorithm, the improvement of packet loss detection, the modification for transmission completion time, adjustment of transmission speed and fairness are discussed, respectively. Finally, we discuss the future work based on the current status of congestion control algorithms.
Rate Smoothness and TCP-Friendliness through Two-step AIMD (TAIMD)

With the proliferation of Internet and the increasing amount of multimedia traffic delivered over it, there has been a pressing need for new transmission controls that facilitate high smoothness and fast convergence to fairness. Achieving these objectives in end-to-end scenario is promising but challenging. In this paper, we present a novel end-to-end TCP-Friendly algorithm that uses two-step additive increase and multiplicative decrease (TAIMD) to control the congestion window using a history-based fair-share estimation. TAIMD smoothes the rate variations by using a two-step increase function and adopting a timer-based packet scheduling mechanism. Convergence performance is improved by using a second fair-share estimation based on packet loss, yet keeping the control less sensitive to the inherent short term fluctuations in the loss-based fair-share estimation. Analytically, we derive parametric relationships for TCP-Friendliness and for fairness convergence of TAIMD. Through simulations conducted using the NS-2 network simulator, performance of TAIMD is observed and compared with the performance of TFRC
Optimal Investment in Knowledge within a Firm Using a Market Mechanism

There has been an extensive research literature on auctions, but recent developments in technology have resulted in new interest in auction mechanisms as a practical way of allocating resources. This paper presents a new double-auction mechanism to handle resource allocation for public goods when complementarity exists.The mechanism is placed in the context of an organization's internal knowledge investment. Knowledge goods have two distinct characteristics. First, knowledge within an organization can be considered apublic good, so it is subject to the free-rider problem. Second, knowledge is interrelated and interdependent; that is, there is complementarity among knowledge components. The value of knowledge often derives from abundle of knowledge components, rather than from its individual pieces. These two characteristics present a serious challenge to allocating organizational resources for knowledge goods.We introduce an internal market in which knowledge providers offer knowledge projects and knowledge consumers place bids to acquire them. The mechanism is a Groves-Clarke-type double auction that allows bundled knowledge goods to be traded so as to recognize complementarities between knowledge projects. The market mechanism we propose isincentive compatible; i.e., it induces people to reveal their true valuation. In addition, it allows trades of knowledge bundles to determine which knowledge components are most valuable from the organization's viewpoint. Under mild assumptions, the mechanism is a computationally tractable solution to operating a market of bundled public goods. We further show how "imputed prices" can be calculated for subsets of knowledge components and prove that a market mechanism that does not allow bundle orders or does not address the free-rider problem yields a systematicunderinvestment in knowledge.
A Visual Attention Model for Video Based on Non-Negative Matrix Factorization Sparseness on Parts

Visual attention is one of the most important mechanism of HVS (human visual system) and has been applied into many fields. Research on visual attention model is hot and difficult. This paper presents a novel visual attention model for video based on NMFSCP (non-negative matrix factorization sparseness on parts). Saliency map of this model is generated by utilizing four types of visual attention features such as intensity, color, orientation and motion. Motion feature of video key frame is extracted by the NMFCP (Non-negative matrix factorization sparseness on parts) algorithm. Intensity, color and orientation features were obtained by the Itti visual attention model. Four features are combined with unequal linear coefficients according to the ratio of motion block in video frame. Simulation result shows the efficiency of proposed model.
Basic study on aggregation of objective functions in Many-objective optimization problems

Recently, it has been reported that Genetic Algorithms (GAs) are applied to Multi-objective Optimization Problems (MOPs) in a lot of studies, which are called MOGA. It is generally important to search a set of Pareto solutions in MOPs which have plural fitness functions, and then GA is effective to apply because of the multi-point search. The performance of MOGA, however, decreases with increasing the number of objective functions because the solution space exponentially spreads. Therefore, effective search of MOGA is the important issue in many objective optimization problems. It is one effective approach to aggregate some objective functions and to reduce the number of them. However, it has not been studied appropriate ways to aggregate or the number of objective functions to be aggregated. The purpose of this study is to grasp the effects of aggregation of objective functions. This paper studies the effects of aggregation when MOGA is applied to a simplified Nurse Scheduling Problem (sNSP) in two aggregating ways based on the meaning of each objective function, and their correlation coefficients. This paper compares the difference of searching area and superiorities of solutions between two cases, i.e., whether objective functions of sNSP are aggregated or not, by the visualization. According to the experimental result, it is found that correlation coefficients are significantly useful to aggregate objective functions.
Assessing and Exploring the Oral Proficiency of Young Mandarin Immersion Learners

ABSTRACT This article presents original empirical research carried out in the early total Mandarin language immersion context. The study involves K–5 learners from three early total Mandarin immersion programs whose home language is English. We examined students’ second language (L2) oral proficiency in Mandarin in two ways: (a) a statistical comparative analysis of cross-sectional assessment data for kindergarten, Grade 2, and Grade 5 students and (b) a detailed linguistic complexity analysis comparing immersion students’ speech samples (one per grade level) produced during the assessment interview. Results indicate significant differences in median scores between kindergarten and Grade 2 in all domains; however, no median score differences were found between Grades 2 and 5. An exploratory complexity analysis of three speech samples revealed increasingly higher levels of grammatical complexity across grades. Measures of lexical complexity for the Grade 5 sample, while higher than those in kindergarten, were lower than those of Grade 2. Study findings question the efficacy of existing proficiency assessments at capturing the multidimensionality of oral proficiency in the intermediate and pre-advanced range. They also highlight the important role finely grained complexity measures can play in informing curriculum, instruction, and assessment practices.
Envelope Targeting: Hemagglutinin Attachment Specificity Rather than Fusion Protein Cleavage-Activation Restricts Tupaia Paramyxovirus Tropism

ABSTRACT To engineer a targeting envelope for gene and oncolytic vector delivery, we characterized and modified the envelope proteins of Tupaia paramyxovirus (TPMV), a relative of the morbilli- and henipaviruses that neither infects humans nor has cross-reactive relatives that infect humans. We completed the TPMV genomic sequence and noted that the predicted fusion (F) protein cleavage-activation site is not preceded by a canonical furin cleavage sequence. Coexpression of the TPMV F and hemagglutinin (H) proteins induced fusion of Tupaia baby fibroblasts but not of human cells, a finding consistent with the restricted TPMV host range. To identify the factors restricting fusion of non-Tupaia cells, we initially analyzed F protein cleavage. Even without an oligo- or monobasic protease cleavage sequence, TPMV F was cleaved in F1 and F2 subunits in human cells. Edman degradation of the F1 subunit yielded the sequence IFWGAIIA, placing the conserved phenylalanine in position 2, a novelty for paramyxoviruses but not the cause of fusion restriction. We then verified whether the lack of a TPMV H receptor limits fusion. Toward this end, we displayed a single-chain antibody (scFv) specific for the designated receptor human carcinoembryonic antigen on the TPMV H ectodomain. The H-scFv hybrid protein coexpressed with TPMV F mediated fusion of cells expressing the designated receptor, proving that the lack of a receptor limits fusion and that TPMV H can be retargeted. Targeting competence and the absence of antibodies in humans define the TPMV envelope as a module to be adapted for ferrying ribonucleocapsids of oncolytic viruses and gene delivery vectors.
An Interactive Visual Analytics System for Bridge Management

Bridges deteriorate over their life cycles and require continuous maintenance to ensure their structural integrity, and in turn, the safety of the public. Maintaining bridges is a multi‐faceted operation that requires both domain knowledge and analytics techniques over large data sources. Although most existing bridge management systems (BMS) are very efficient at data storage, they are not as effective at providing analytical capabilities or as flexible at supporting different inspection technologies. In this paper, we present a visual analytics system that extends the capability of current BMSs. Based on a nation‐wide survey and our interviews with bridge managers, we designed our system to be customizable so that it can provide interactive exploration, information correlation, and domain‐oriented data analysis. When tested by bridge managers of the U.S. Department of Transportation, we validated that our system provides bridge managers with the necessary features for performing in‐depth analysis of bridges from a variety of perspectives that are in accordance to their typical workflow.
Study of MLP and RBFN performance for signal detection

This paper deals with the application of Neural Networks to binary hypothesis tests based on multiple observations. The problem of detecting a desired signal in Additive-White-Gaussian-Noise is considered, assuming that the desired signal observations are also gaussian, independent and identically distributed random variables. The test statistic is then the squared magnitude of the observation vector and the optimum boundary is a hyper-sphere in the input space. The dependence of the neural network detector on the Training-Signal-to-Noise-Ratio and the number of hidden units is studied. Results show that Radial Basis Function Networks not only are more robust when varying the TrainingSignal-to-Noise-Ratio and the number of hidden units, but the best approximation to the Neyman-Pearson detector is achieved with them.
A MULTI-WAVELENGTH STUDY OF THE JET, LOBES, AND CORE OF THE QUASAR PKS 2101−490

We present a detailed study of the x-ray, optical, and radio emission from the jet, lobes, and core of the quasar PKS 2101−490 as revealed by new Chandra, Hubble Space Telescope (HST), and ATCA images. We extract the radio to x-ray spectral energy distributions from seven regions of the 13″ jet, and model the jet x-ray emission in terms of Doppler beamed inverse Compton scattering of the cosmic microwave background (IC/CMB) for a jet in a state of equipartition between particle and magnetic field energy densities. This model implies that the jet remains highly relativistic hundreds of kiloparsecs from the nucleus, with a bulk Lorentz factor Γ ∼ 6 and magnetic field of the order of 30 μG. We detect an apparent radiative cooling break in the synchrotron spectrum of one of the jet knots, and are able to interpret this in terms of a standard one-zone continuous injection model, based on jet parameters derived from the IC/CMB model. However, we note apparent substructure in the bright optical knot in one of the HST bands. We confront the IC/CMB model with independent estimates of the jet power, and find that the IC/CMB model jet power is consistent with the independent estimates, provided that the minimum electron Lorentz factor γmin ≳ 50, and the knots are significantly longer than the jet width, as implied by de-projection of the observed knot lengths.
Associative Learning Elicits the Formation of Multiple-Synapse Boutons

The formation of new synapses has been suggested to underlie learning and memory. However, previous work from this laboratory has demonstrated that hippocampus-dependent associative learning does not induce a net gain in the total number of hippocampal synapses and, hence, a net synaptogenesis. The aim of the present work was to determine whether associative learning involves a specific synaptogenesis confined to the formation of multiple-synapse boutons (MSBs) that synapse with more than one dendritic spine. We used the behavioral paradigm of trace eyeblink conditioning, which is a hippocampus-dependent form of associative learning. Conditioned rabbits were given daily 80-trial sessions to a criterion of 80% conditioned responses in a session. During each trial, the conditioned stimulus (tone) and the unconditioned stimulus (corneal airpuff) were presented with an intervening trace interval of 500 msec. Brain tissue was taken for morphological analyses 24 hr after the last session. Unbiased stereological methods were used for obtaining estimates of the total number of MSBs in the stratum radiatum of hippocampal subfield CA1. The results showed that the total number of MSBs was significantly increased in conditioned rabbits as compared with pseudoconditioned or unstimulated controls. This conditioning-induced change, which occurs without a net synaptogenesis, reflects a specific synaptogenesis resulting in MSB formation. Models of the latter process are proposed. The models postulate that it requires spine motility and may involve the relocation of existing spines from nonactivated boutons or the outgrowth of newly formed spines for specific synaptogenesis with single-synapse boutons activated by the conditioning stimulation.
Design space exploration and prototyping for on-chip multimedia applications

Traditionally, design space exploration for systems-on-chip (SoCs) has focused on the computational aspects of the problem at hand. However, as the number of components on a single chip and their performance continue to increase, a shift from computation-bound to communication-bound design becomes mandatory. Towards this end, this paper presents a comprehensive evaluation of two communication architectures targeting multimedia applications. Specifically, we compare and contrast the network-on-chip (NoC) and point-to-point (P2P) communication architectures in terms of power, performance, and area. As the main contribution, we present complete P2P and NoC-based implementations of a real multimedia application (MPEG-2 encoder), and provide direct measurements using a FPGA prototype and actual video clips, rather than simulation and synthetic workload. From an experimental standpoint, we show that the NoC architecture scales very well in terms of area, performance, power and design effort, while the P2P architecture scales poorly on all accounts except performance
Explosive force in football association: effects of competition and field location

Explosive force was assessed through squat jump (SJ), counter movement jump (CMJ), and elastic index (IE) in 21 South American football players at the beginning and the end of a six-month competitive period. Jumps were accomplished on a force platform and the data obtained were grouped according to: time, beginning and end of competitive period, and field location of the players (defenders, midfielders and attackers). T-test and Kruskal-Wallis analysis for the differences between positions were used to analyse its influence, as well as that of the competition, on the variables considered. The association between the CMJ and SJ was analysed by Pearson product- moment. The values found for SJ, CMJ and IE were below international standards. The IE showed that explosive force is significantly affected by the competitive period for those field positions implying high intensity activities during the match. The correlations suggest that differences exist on the factors that determine the significant changes for midfielders and forwards. It is concluded that the application of exercises that imply an action of the type stretch-shortening cycle (SSC) during the highly intensive competitive period could contribute to optimize the performance of the players.
Connecting Contiki enabled Versatile Sensor Nodes via CC 1101 radio

In this demo, we show message exchange between Versatile Sensor Nodes (VSN), which run the Contiki operating system and use the Texas Instruments CC1101 radio. We explain our port of the Contiki on VSN with the emphasis on the wireless communication. VSN is a modular sensor node platform featuring several communication interfaces. In the demo we use the CC1101 radio to connect VSNs and RS232 to connect VSNs to PCs. The application used to illustrate the functioning of the system sends messages from a computer and displays them on the screen of all other computers attached to VSNs that received that message.