Miracle-dz/UniFAR-FTUs huggingface dataset:
U(1) gauge theory over discrete space-time and phase transitions

We first apply Connes' noncommutative geometry to a finite point space. The explicit form of the action functional of U(1) gauge field on this n-point space is obtained. We then consider the case when the n-point space is replaced by {space-time}\times{n-point space}. This action is shown to relate the Hamiltonian of the continuous-spin formulation of the Potts model. We argue that U(1) gauge theory on the discrete space-time determines the geometric origin of a class of phase transitions.
Euclidean distance matrices, semidefinite programming and sensor network localization

The fundamental problem of distance geometry involves the characterization and study of sets of points based only on given values of some or all of the distances between pairs of points. This problem has a wide range of applications in various areas of mathe- matics, physics, chemistry, and engineering. Euclidean distance matrices play an important role in this context by providing elegant and powerful convex relaxations. They play an important role in problems such as graph realization and graph rigidity. Moreover, by relaxing the embedding dimension restriction, these matrices can be used to approximate the hard problems e‰ciently using semidefinite programming. Throughout this survey we emphasize the interplay between these concepts and problems. In addition, we illustrate this interplay in the context of the sensor network localization problem.
High-Functional-Avidity Cytotoxic T Lymphocyte Responses to HLA-B-Restricted Gag-Derived Epitopes Associated with Relative HIV Control

ABSTRACT Virus-specific cytotoxic T lymphocytes (CTL) with high levels of functional avidity have been associated with viral clearance in hepatitis C virus infection and with enhanced antiviral protective immunity in animal models. However, the role of functional avidity as a determinant of HIV-specific CTL efficacy remains to be assessed. Here we measured the functional avidities of HIV-specific CTL responses targeting 20 different, optimally defined CTL epitopes restricted by 13 different HLA class I alleles in a cohort comprising 44 HIV controllers and 68 HIV noncontrollers. Responses restricted by HLA-B alleles and responses targeting epitopes located in HIV Gag exhibited significantly higher functional avidities than responses restricted by HLA-A or HLA-C molecules (P = 0.0003) or responses targeting epitopes outside Gag (P < 0.0001). The functional avidities of Gag-specific and HLA-B-restricted responses were higher in HIV controllers than in noncontrollers (P = 0.014 and P = 0.018) and were not restored in HIV noncontrollers initiating antiretroviral therapy. T-cell receptor (TCR) analyses revealed narrower TCR repertoires in higher-avidity CTL populations, which were dominated by public TCR sequences in HIV controllers. Together, these data link the presence of high-avidity Gag-specific and HLA-B-restricted CTL responses with viral suppression in vivo and provide new insights into the immune parameters that mediate spontaneous control of HIV infection.
A Multiobjective Genetic Algorithm for Asymmetric FIR Filters

A genetic algorithm (GA) for the design of asymmetric FIR filters that would satisfy multiple requirements imposed on the amplitude response and group-delay characteristic is proposed. The GA implements a multiobjective optimization approach for obtaining so-called Pareto-optimal solutions of the problem at hand. Flexibility is introduced in the design by imposing phase linearity only in the passband instead of the entire baseband as in conventional designs. The proposed GA is a specially tailored elitist nondominated sorting genetic algorithm (ENSGA) and it involves a decimal encoding scheme and a multiobjective error formulation based on the amplitude response and passband group delay. Experimental results show that the ENSGA leads to improved amplitude response as well as delay characteristic relative to those achieved by using a state-of-the-art weighted least-squares approach.
A Memory-Efficient Architecture of Full HD Around View Monitor Systems

The around view monitor (AVM) is one of the representative features of smart vision systems adopted in various application areas, e.g., advanced driver assistance systems. The design of AVM systems with full high-definition (HD)-level resolution presents significant technical challenges. In particular, a high-memory performance is required to process full HD images obtained from multiple cameras. Specifically, a full HD AVM system requires a high-memory bandwidth (six times higher than D1 image-based systems) and is characterized by a significant amount of single writes, which degrades the effective performance of modern DRAM. To address these problems, two methods are proposed in this paper. The first method reduces the required memory bandwidth by storing in the memory only the input pixel data that will be used in the final processing step, and the second improves the single-write performance of a DRAM subsystem by DRAM-aware data mapping. The effectiveness of the proposed methods is proved by designing an AVM system incorporating field-programmable gate arrays and DDR2-200 SDRAMs. The proposed methods reduce the memory bandwidth requirement by 51%, allowing a full HD AVM system to run at over 24 frames per second.
An Improved Approach for Detecting Car in Video using Neural Network Model

The study represents a novel approach taken towards car detection, feature extraction and classification in a video. Though many methods have been proposed to deal with individual features of a vehicle, like edge, license plate, corners, no sy stem has been implemented to combine features. Combination of four unique features, namely, color, shape, number plate and logo gives the application a stronghold on various applications li ke surveillance recording to detect accident percentage(for every make of a company), authentication of a car in the Parliament(for high security), learning system(readily available knowledge for aut omobile tyro enthusiasts) with increased accuracy o f matching. Video surveillance is a security solution for government buildings, facilities and operation s. Installing this system can enhance existing securit y systems or help start a comprehensive security so lution that can keep the building, employees and records s afe. The system uses a Haar cascaded classifier to detect a car in a video and implements an efficient algori thm to extract the color of it along with the confi dence rating. An gadabouts trained classifier is used to detect the logo (Suzuki/Toyota/Hyunadai) of the car whose accuracy is enhanced by implementing SURF matching. A combination of blobs and contour tracing is applied for shape detection and model classificatio n while number plate detection is performed in a smart and efficient algorithm which uses morphological op erations and contour tracing. Finally, a trained, s ingle perceptron neural network model is integrated with the system for identifying the make of the car. A thorough work on the system has proved it to be eff icient and accurate, under different illumination conditions, when tested with a huge dataset which h as been collected over a period of six months.
A Novel Asymptotical Stability Criterion for Fuzzy Neutral Systems

In this paper, the asymptotical stability criterion for the fuzzy neutral systems is investigated. By means of the Lyapunov-Krasovskii functional, Barbalat lemma, Sala- Arino lemma, the descriptor model transformation and LMI approach, a novelty less conservative sufficient condition (in terms of LMIs) for asymptotical stability of the fuzzy neutral systems is deduced. Finally, an illustrative numerical example is provided to demonstrate the effectiveness of the proposed criterion.
The Applications of GIS in the Analysis of the Impacts of Human Activities on South Texas Watersheds

With water resource planning assuming greater importance in environmental protection efforts, analyzing the health of agricultural watersheds using Geographic Information Systems (GIS) becomes essential for decision-makers in Southern Texas. Within the area, there exist numerous threats from conflicting land uses. These include the conversion of land formerly designated for agricultural purposes to other uses. Despite current efforts, anthropogenic factors are greatly contributing to the degradation of watersheds. Additionally, the activities of waste water facilities located in some of the counties, rising populations, and other socioeconomic variables are negatively impacting the quality of water in the agricultural watersheds. To map the location of these stressors spatially and the extent of their impacts across time, the paper adopts a mix scale method of temporal spatial analysis consisting of simple descriptive statistics. In terms of objectives, this research provides geo-spatial analysis of the effects of human activities on agricultural watersheds in Southern Texas and the factors fuelling the concerns under the purview of watershed management. The results point to growing ecosystem decline across time and a geographic cluster of counties experiencing environmental stress. Accordingly, the emergence of stressors such as rising population, increased use of fertilizer treatments on farm land, discharges of atmospheric pollutants and the large presence of municipal and industrial waste treatment facilities emitting pathogens and pesticides directly into the agricultural watersheds pose a growing threat to the quality of the watershed ecosystem.
Achieving high availability and security of web services for SOA-based applications

Today, web services are being deployed increasingly in industries as a means of enabling Business-to-Business integration (B2Bi) and Enterprise Application Integration (EAI). With the success of such deployments, there are high demands from the industry for mechanisms that can enable highly secure and available web services, for handling complex business problems. This report discusses the results of the project that investigated and developed the mechanisms for building highly secure and available web service-enabled applications. The methodology used in developing the mechanism is also introduced. The key features and implementation consideration are described, with potential usage scenarios provided as examples.
Uniform asymptotics for orthogonal polynomials

We consider asymptotics of orthogonal polynomials with respect to a weight e ? Q(x) dx on R, where either Q(x) is a polynomial of even order with positive leading coeecient, or Q(x) = NV (x), where V (x) is real analytic on R and grows suuciently rapidly as jxj ! 1. We formulate the orthogonal polynomial problem as a Riemann-Hilbert problem following the work of Fokas, Its and Kitaev. We employ the steepest descent-type method for Riemann-Hilbert problems introduced by Deift and Zhou, and further developed by Deift, Venakides and Zhou, in order to obtain uniform Plancherel-Rotach-type asymptotics in the entire complex plane, as well as asymptotic formulae for the zeros, the leading coeecients and the recurrence coeecients of the orthogonal poly-nomials. These asymptotics are also used to prove various universality conjectures in the theory of random matrices. Let w(x)dx = e ? Q(x) dx be a measure on the real line. Denote by n (x; Q) = n (x) = x n + : : : the n-th monic orthogonal polynomial with respect to the measure , and by p n (x; Q) = p n (x) = n n (x), n > 0, the normalized n-th orthogonal polynomial, or simply the n-th orthogonal polynomial, i.e. Furthermore, denote by (a n) n2N , (b n) n2N the coeecients of the associated three term recurrence relation, namely, xp n (x) = b n p n+1 (x) + a n p n (x) + b n? 1 p n? 1 (x),
Judging a bot by its cover: An experiment on expectation setting for personal robots

Managing user expectations of personal robots becomes particularly challenging when the end-user just wants to know what the robot can do, and neither understands nor cares about its technical specifications. In describing what a robot can do to such an end-user, we explored the questions of (a) whether or not such users would respond to expectation setting about personal robots and, if so, (b) how such expectation setting would influence human-robot interactions and people's perceptions of the robots. Using a 2 (expectation setting: high vs. low) x 2 (robot type: Pleo vs. AIBO) between-participants experiment (N=24), we examined these questions. We found that people's initial beliefs about the robot's capabilities are indeed influenced by expectation setting tactics. Contrary to the hypotheses predicted by the Self-Fulfilling Prophecy and Confirmation Bias, we found that erring on the side of setting expectations lower rather than higher led to less disappointment and more positive appraisals of the robot's competence.
A Novel Method of Topology Modeling in Heterogeneous Wireless Network

In the future network research, network simulation and modeling is very important. If the topology model of network is not consistent with the actual network, the conclusion is not correct. Heterogeneous wireless network has characteristic of Hierarchy, Power law distribution, Self-similarity, Rich-club property and others. Based on the actual network topology model analysis and using complex network theory, we put forward a topology modeling method suitable for heterogeneous wireless network. Simulation result shows that the proposed method works well, and has more realistic characteristics of the heterogeneous wireless network.
Security challenges for wearable computing - a case study

This paper discusses IT- and information security challenges for wearable computing encountered during the WearIT@work project. The following novel ideas are introduced in this paper: authorization by proximity using dynamic context information to enable transfer of authorization from one party to another, a wearable pairing mechanism to use devices on other wearables, and a more intelligent management of dynamic IT-security policies to reduce computational overhead on wearable devices having limited capabilities. The last idea includes the importance of having a dynamic security baseline adapted to wearables to maintain the integrity and confidentiality of the body network as well as the privacy of the wearers' personal and biometric information.
Query Processing Along with Query Clustering Analysis in Information Retrieval

Query being the essential in an Information Retrieval (IR) system and user looking to fulfil information need has to formulate a query usually consisting of a small set of keywords summarizing the information need. It reiterates the significance of the query processing in an information retrieval system. The main objective of query processing is to translate a user level query into a low level machine understandable query. The main purpose of this paper is to analyse query clustering along with the query processing and semantic web. Query clustering being one of the emerging techniques and query processing being one of widely used in database systems makes an interesting combination to be analysed. In this paper an attempt is made to evaluate the performance of query clustering along with query processing algorithms in each of the category. The evaluation was based on dataset as specified by Forum for Information Retrieval [FIRE11].
Double Helix Relationships in Use and Design of Informing Systems: Lessons to Learn from Phenomenology and Hermeneutics

The theme of this monograph of Informing Science is a dialectic we perceive to exist between meaningful use and reflection upon use. This dialectic between use and reflection on use (or thinking, and thinking about thinking) may be considered in the following way. Each of these elements is subject to change. As reflection triggers change in use, and such change triggers further reflection, a spiral comes about. Lived human experience, and reflection upon that experience, seems to shape a double helix. The monograph contains contributions exploring particular ways in which studies of use could benefit from a relationship to philosophical frameworks such as hermeneutics and phenomenology. (Less)
Armonía de pareja en población de personas mayores: diferencias entre sexos

El ajuste diadico no solamente es un factor esencial en la perdurabilidad y calidad de toda relacion de pareja, sino que ademas, puede afectar a la vida personal y a la salud de sus miembros. El presente estudio explora el ajuste percibido por las personas mayores en Espana en su relacion de pareja presente o pasada, analizando las posibles diferencias entre hombres y mujeres. Se administro la Escala de Ajuste Diadico a 80 personas entre los 51 y los 81 anos. El 55% eran mujeres. El 66,3% estaban casados, el 21,3% separados o divorciados y un 12,5% habia enviudado. Se tomo el valor 107 propuesto en la literatura como punto de corte para establecer un ajuste diadico positivo. La puntuacion global media en el total de poblacion fue 101,47 (DT = 21,75). Los hombres presentan una mayor puntuacion que las mujeres en la escala global y en cada una de sus dimensiones, pero unicamente se hallo diferencias significativas en la escala Consenso (hombres: 48,87 vs mujeres: 41,17; p=0,042). Los resultados muestran la influencia de los roles de genero tradicionales en la valoracion percibida de la relacion de pareja y la necesidad de establecer estrategias clinicas y sociales para favorecer el disfrute y la armonia en las parejas de personas mayores.
A QoS-Driven Channel Allocation Strategy for Multiuser Cooperative Networks

In cooperation uplink user systems, most exiting works on resource allocation focused on maximizing system throughput without considering of services and demand. We focus, in this paper, on leveraging cooperation for channel allocation. The aim is to improve the system throughput besides meeting the QoS requirements. By introducing QoS price which calculates the difference of the maximum system throughput and the practical throughput, we proposed a suboptimal heuristic algorithm utilizing virtual nodes to solve the joint channel allocation and cooperation problem. This algorithm simplifies the joint problem by allowing the consideration of only direct transmissions. Simulation results indicate that our proposed algorithm significantly outperforms the previous works in terms of both system throughput and QoS satisfaction.
Phenotypic evolution with a mutation based on symmetric α-stable distributions

<2 and the fact that the most probable distance of mutated points is not in a close neighborhood of the origin, but at a certain distance from it. It is the so-called surrounding effect (Obuchowicz, 2001b; 2003b). For = 2, the SS mutation reduces to the Gaussian one, and in the case of = 1, the Cauchy mutation is obtained. The exploration and exploitation abilities of evolutionary algorithms, using SS mutations for different , are analyzed by a set of simulation experiments. The obtained results prove the important influence of the surrounding effect of symmetric -stable mutations on both the abilities considered.
Identification of Neutral Members in Social Networks using a Distance and Fuzzy based Model

Understanding community structure helps to interpret the role of actors in a social network. Actor has close ties to actors within a community than actors outside of its community. Community structure reveals important information such as central members in communities and bridges members who connect communities. Clustering algorithms like hierarchical clustering, affinity propagation, modularity and spectral graph clustering had been applied in social network clustering to identify community structures in it. This study proposes a novel method for distance measurement between nodes and centroids. Distance is measured based on the shortest path length and number of common nearest neighbors with one path length. This measure, "Proportional closeness" is used to assign nodes to the closest centroid. A fuzzy system is also applied to find the closest centroid to a node when similar proportional closeness values are present for multiple centroids. The method has been applied to two artificial networks and one real world network data to test its accuracy on membership identification. The results revealed that the method successfully assigns members to its nearest centroid and leave neutral members aside without assigning to any centroid. General Terms Membership identification, Closeness
Applying Demand Response Programs for Electric Vehicle Fleets

In this study, we demonstrate the contribution of ISsupported demand response (DR) programs to the development of a sustainable transport sector. Based on the energy informatics framework, we develop an IS artifact that can be used to apply DR programs for electric vehicle (EV) fleets. Furthermore, we quantify one DR program in economic terms by analyzing data gathered in an electric mobility project with a carsharing provider that uses EVs. The find ings indicate that fleet operators can expect significant cost savings when applying DR programs; energy procurement costs can be reduced significantly by adjusting the time of energy use. Applying DR programs therefore has the potential to make EV fleets economically sensible because the already existing operational cost advantage can be further increased. Consequently, DR for EVs can foster sustainable development, as higher profitability could promote the market penetration of ecofriendly vehicles.
Identification of microRNA profiles in salivary adenoid cystic carcinoma cells during metastatic progression

Salivary adenoid cystic carcinoma (SACC) is a common type of salivary gland cancer. The poor long-term prognosis of patients with SACC is primarily due to local recurrence, distant metastasis and perineural invasion. MicroRNAs (miRNAs) have been identified as important post-transcriptional regulators, which are involved in various biological processes. The aim of the present study was to identify the miRNA expression profiles that are involved in the metastatic progression of SACC. Therefore, microarray technology was employed to identify miRNA expression profiles in an SACC cell line, ACC-2, and a highly metastatic SACC cell line, ACC-M, which was screened from ACC-2 by a combination of in vivo selection and cloning in vitro. Differences in miRNA expression were assessed by quantitative polymerase chain reaction (qPCR) assay. In addition, the potential target genes that are regulated by selected miRNAs were analyzed by various target prediction tools. The microarray data revealed that the levels of 38 miRNAs significantly differed between the ACC-M cells and the control ACC-2 cells. Six miRNAs (miR-4487, -4430, -486-3p, -5191, -3131 and -211-3p) were selected to validate the microarray data via qPCR. The expression of two miRNAs (miR-4487 and -4430) was significantly upregulated in the ACC-M cells, while the expression of two other miRNAs (miR-5191 and -3131) was significantly downregulated in the ACC-M cells. The potential target genes that were identified to be controlled by the six selected miRNAs were divided into four groups according to function, as follows: Apoptosis and proliferation (46 genes), cell cycle (30 genes), DNA damage and repair (24 genes) and signaling pathway (30 genes). The identification of microRNA expression profiles in highly metastatic SACC cells may provide an improved understanding of the mechanisms involved in metastatic progression, which would aid in the development of novel strategies for the treatment of SACC.