Miracle-dz/UniFAR-FTUs huggingface dataset:
00 02 00 9 v 1 1 F eb 2 00 0 Stabilization of internal spaces in multidimensional cosmology

Effective 4-dimensional theories are investigated which were obtained under dimensional reduction of multidimensional cosmological models with a minimal coupled scalar field as a matter source. Conditions for the internal space stabilization are considered and the possibility for inflation in the external space is discussed. The electroweak as well as the Planck fundamental scale approaches are investigated and compared with each other. It is shown that there exists a rescaling for the effective cosmological constant as well as for gravitational exciton masses in the different approaches.
Inspirational Reality TV: The Prosocial Effects of Lifestyle Transforming Reality Programs on Elevation and Altruism

In light of recent theories of meaningful media that suggest a host of psychological benefits, the present study uniquely extends the boundaries of the effects of reality TV from simply offering pleasure, diversion, and amusement to its viewers to also providing deep insight and meaning. In particular, a between-subjects experiment (N = 143) examined differences in affective, cognitive, and motivational responses to lifestyle transforming versus game based reality programs. Findings indicate that lifestyle transforming reality TV produced stronger feelings of elevation and perceptions of the program as moving and thought-provoking than game reality TV, which in turn increased motivations for altruism. Avenues for future research and theoretical implications of meaningful and inspiring reality TV for positive psychology are discussed.
Digital processing in the optical communications

Digital processing role in the optical communications is analyzed together with its historical evolution and perspectives. If optical systems at their early stage included weak digital processing in the electrical domain, a fast evolution towards completely all-optical technologies arises due to the bottleneck caused by the electronics bandwidth limitation. With the return of coherent communications, digital processing migrated again back to the electronic domain. Nowadays, algorithm complexity capable of mitigating for linear and nonlinear fibre impairments is becoming unsustainable due to huge level of parallelization and power demand. For such a reason one possible evolution will include processing both in the electronic and optical domain.
Current established risk assessment methodologies and tools

The technology behind information systems evolves at an exponential rate, while at the same time becoming more and more ubiquitous. This brings with it an implicit rise in the average complexity of systems as well as the number of external interactions. In order to allow a proper assessment of the security of such (sub)systems, a whole arsenal of methodologies, methods and tools have been developed in recent years. However, most security auditors commonly use a very small subset of this collection, that best suits their needs. This thesis aims at uncovering the differences and limitations of the most common Risk Assessment frameworks, the conceptual models that support them, as well as the tools that implement them. This is done in order to gain a better understanding of the applicability of each method and/or tool and suggest guidelines to picking the most suitable one.
Use of Buchi automata and randomness for the description of biological processes

The main topic of this study is the modelling and verification of biological systems using ω -automata. This work focuses on the protein folding problem and the infinite behaviour it features in many cases. Specifically, stochastic computational models with infinite input are used in this paper’s approach and indicative aspects of a biological problem are presented using both ω -automata and probabilistic Buchi automata (PBAs), making a novel attempt to establish their use in reasoning about biological processes. Necessary preliminary definitions and background towards this direction are provided. Finally, the pros and cons of each model are shown through examples. Overall, this work contributes by combining for the very first time PBAs with real biological mechanisms, with indicative examples, both with PBAs and NBAs (non-deterministic Buchi automata).
Social IPTV: a Survey on Chances and User-Acceptance

Incorporating Social Networking and IPTV, the two arguably fastest growing and most accepted services on the Internet today, yields strong synergies. However, it opens a very complex design space of feature combinations. Selecting features, aiming at achieving the best user acceptance, hence, is a difficult, yet vital task for the development of an integrated service. This paper presents the results of an initial user study conducted to gain a better understanding of the complex design space. It identifies classes of demanded, promising features and indicates that social features in IPTV services in general will be well accepted, even if they are quite immersive to the TV experience. The study was conducted with user groups from central Europe as well as with a group from Korea.
A novel support vector machine algorithm for solving nonlinear regression problems based on symmetrical points

A novel support vector machine (SVM) algorithm for regression problems is proposed in this paper. Each pattern in the original training set is converted into a pair of patterns, which are labeled by 1 and −1, respectively. Therefore, the regression problem can be considered as a classification problem. By optimizing the obtained decision function, the model output of unknown samples can be estimated. Experimental results show the proposed method works well, and in many cases it produces less support vectors than the normal support vector regression (SVR) machine.
Optimization on time-varying networks

This thesis introduces two classes of discrete-time distributed online optimization algorithms, with a group of agents which communicate over a network. At each time, a private convex objective function is revealed to each agent. In the next time step, each agent updates its state using its own objective function and the information gathered from its immediate in-neighbors at that time. We design algorithms distributed over the network topologies, which guarantee that the individual regret, the difference between the network cost incurred by the agent’s states estimation and the cost incurred by the best fixed choice, grows only sublinearly. One algorithm is based on gradient-flow, which provably works for a sequence of time-varying uniformly strongly connected graphs. The other one is based on Alternating Direction Method of Multipliers, which works on fixed undirected graphs and gives an explicit regret bound in terms of the size of the network. We implement the proposed algorithms on a sensor network and the results demonstrate the good performance for both algorithms.
EXFI: a low-cost fault injection system for embedded microprocessor-based boards

Evaluating the faulty behavior of low-cost embedded microprocessor-based boards is an increasingly important issue, due to their adoption in many safety critical systems. The architecture of a complete Fault Injection environment is proposed, integrating a module for generating a collapsed list of faults, and another for performing their injection and gathering the results. To address this issue, the paper describes a software-implemented Fault Injection approach based on the Trace Exception Mode available in most microprocessors. The authors describe EXFI, a prototypical system implementing the approach, and provide data about some sample benchmark applications. The main advantages of EXFI are the low cost, the good portability, and the high efficiency
Communication and control co-design for networked control system in optimal control

Communication and control co-design for networked control system in optimal control in the paper. Under p - to - wσ communication sequence which sensors access communication medium and m - to - wρ communication sequence which actuators access communication medium, the plant of networked control system acts as a linear periodic time-varying system. Using lifting technology, a linear periodic time-varying system is transformed to a linear periodic time-invariant system, linear quadratic performance index of a linear periodic time-varying system is transformed to that of a linear periodic time-invariant system. An optimal state feedback control and an optimal output feedback control are given.
Enriching Documents in an Information Portal using Superimposed Schematics

Portals offer relevant information often with improved and customizable search. However, most portals concentrate on locating documents as opposed to enhancing their use. We present superimposed schematics which serve to enrich documents by adding a structured, conceptual guide for their contents. A schematic provides entity-relationship (E-R) style structures integrated with marks, where each mark holds an address to an excerpt in an underlying document. Schematics enable enhanced addressing of documents, conceptual navigation, and query all at "no additional cost," i.e., without modifying the base documents. We report on superimposed schematics and discuss their application to documents, such as the Appeal Decision of the USDA Forest Service, within the Adaptive Management Portal.
THE OPTIMAL SUPPLY OF PUBLIC GOODS AND THE DISTORTIONARY COST OF TAXATION

The conventional view of economists is that the optimal supply of public goods must directly take into account the cost of financing them with distortionary taxes, notably the income tax. However, this article demonstrates, under standard simplifying assumptions, that it is possible to finance a public good in a manner that results in no additional distortion, by using an adjustment to the income tax that offsets the benefits of the public good. In this case, it is optimal to supply the public good whenever the simple costbenefit test is satisfied. The article also shows that if a different tax adjustment is made, the difference in outcome will be purely redistributive; thus, any change in distortionary costs will be accompanied by an opposing change in redistributive benefits. In this case, the cost-benefit test should be modified to reflect both of these changes. Finally, it is explained that the present analysis is fully applicable to determining the optimal level of environmental taxes.
Access Control List Mediation System for Large-Scale Network

Large-Scale network such as the Internet consist of a large number of sub-networks. Since each subnetwork has management privileges and policies individually, it is difficult to respond to harmful traffic such as warm viruses that affect entire networks. In this paper, we propose a high-level policy language and a middle-level data structure. They were named Triton language and Common Access Management Form (CAMF). It enables the administrator to authorize a policy effectively and rapidly. Large-scale networks have a number of administrators so that policy collision can occur. Access control list mediation system selects or adapts the most important policy among colliding policies through a policy importance valuation.
Relative Contributions of the Candida albicans ABC Transporters Cdr1p and Cdr2p to Clinical Azole Resistance

ABSTRACT Candida albicans frequently develops resistance to treatment with azole drugs due to the acquisition of gain-of-function mutations in the transcription factor Tac1p. Tac1p hyperactivation in azole-resistant isolates results in the constitutive overexpression of several genes, including CDR1 and CDR2, which encode two homologous transporters of the ATP-binding cassette family. Functional studies of Cdr1p and Cdr2p have been carried out so far by heterologous expression in the budding yeast Saccharomyces cerevisiae and by gene deletion or overexpression in azole-sensitive C. albicans strains in which CDR1 expression is low and CDR2 expression is undetectable. Thus, the direct demonstration that CDR1 and CDR2 overexpression causes azole resistance in clinical strains is still lacking, as is our knowledge of the relative contribution of each transporter to clinical azole resistance. In the present study, we used the SAT1 flipper system to delete the CDR1 and CDR2 genes from clinical isolate 5674. This strain is resistant to several azole derivatives due to a strong hyperactive mutation in Tac1p and expresses high levels of Cdr1p and Cdr2p. We found that deleting CDR1 had a major effect, reducing resistance to fluconazole (FLC), ketoconazole (KTC), and itraconazole (ITC) by 6-, 4-, and 8-fold, respectively. Deleting CDR2 had a much weaker effect, reducing FLC or KTC resistance by 1.5-fold, and had no effect on ITC resistance. These results demonstrate that Cdr1p is a major determinant of azole resistance in strain 5674 and potentially in other clinical strains overexpressing Cdr1p and Cdr2p, while Cdr2p plays a more minor role.
The relationship between perceived pay equity, productivity, and organizational commitment for US professionals of color

Purpose The purpose of this paper is to examine: the direct effect of perceived pay equity, the interaction of perceived pay equity and productivity, and the relative effects of perceived internal and external pay equity on organizational commitment (OC) among US scholars of color. Design/methodology/approach The study surveyed 160 professionals. Correlation and hierarchical regression were employed to test the hypotheses. Findings Perceived pay equity directly influenced OC and interacted with scholarly productivity to affect commitment. Highly productive participants who perceived pay equity reported the highest commitment. When pay was seen as inequitable, the most productive scholars reported the lowest commitment. Perceived internal pay equity had an effect, over and above perceived external pay equity on commitment. Research limitations/implications The study was conducted in one industry in the USA, so the results should be generalized cautiously. While, the data were single-source and cross-sectional, the findings were consistent with previous research. Practical implications Findings may be useful for minority scholars’ supervisors since they have knowledge of the productivity and salaries in the department and can provide a detailed explanation for pay differences to enhance pay equity perceptions, particularly for the most productive scholars. Originality/value This study adds to the equity and relative deprivation theory research investigating the effect of perceived pay equity on employee outcomes by examining perceived internal and external pay equity perceptions and productivity on OC. Results suggest that highly productive minority professionals in higher education are particularly sensitive to pay equity.
A Novel Automatic Classification Method for Flash Based on BP Neural Network

With the rapid development of Internet, the network has penetrated into many areas of people's lives. It has become an indispensable communication tool, information access tool and entertainment tool for people. Flash as a new multimedia has become an important part on the Internet. Because the advantages of strong artistic expression, simplified manufacture, flexible interaction, small storage and easy communication, it has been widely used on the Internet. Faced with the growing number of Flash, how to retrieve Flash accurately and efficiently is becoming a noticeable problem. Based on the study of file structures, forming principles and content features, a novel automatic classification method for Flash is proposed in this paper. The algorithm of BP neural network algorithm is adopted in this method. It is called BPFAC which can realize the automatic classification of Flash, and can make retrieval system for Flash more efficient and accurate. On the basis of the optimizing the efficiency of algorithm, we have developed the prototype of BPFAC by C++. Based on two experimental parameters, the Accuracy Rate and the Time Consumption, several comparative experiments have been carried out respectively. Results show that BPFAC has higher accuracy in classification of Flash, and has relatively stable time consumption at the same time.
Gravitational Lensing by Power-Law Mass Distributions: A Fast and Exact Series Approach

We present an analytical formulation of gravitational lensing using familiar triaxial power-law mass distributions, where the three-dimensional mass density is given by ρ(X, Y, Z) = ρ0[1 + (X/a)2 + (Y/b)2 + (Z/c)2]-ν/2. The deflection angle and magnification factor are obtained analytically as Fourier series. We give the exact expressions for the deflection angle and magnification factor. The formulae for the deflection angle and magnification factor given in this paper will be useful for numerical studies of observed lens systems. An application of our results to the Einstein Cross can be found in Chae, Turnshek, & Khersonsky. Our series approach can be viewed as a user-friendly and efficient method to calculate lensing properties that is better than the more conventional approaches, e.g., numerical integrations and multipole expansions.
Security Exercises for the Online Classroom with DETER

Creating high-quality homework with an emphasis on creativity and open-ended learning is challenging. This is especially true for online classes, which must be both accessible via the Internet and comparable in quality and value to projects that could be used in a traditional classroom. UCLA recently began offering an online master's degree program in computer science, which includes a course in computer security. This motivated the design of online coursework intended to take the place of the traditional in-class homework and group projects. The resulting security labs use standard security tools and the DETER testbed, which can be organized into networks of physical machines running real software. In these environments, students perform open-ended exercises involving file permissions, firewalls, software vulnerabilities, eavesdropping and injection, man-in-the-middle attacks, computer forensics, and network intrusion detection systems. We also created an extensive online lab manual to accompany the exercises. With some important technical caveats, DETER proved to be an excellent platform for online education, and the labs themselves have been a great success since they were introduced in 2008.
USING CONCEPT HIERARCHIES TO ENHANCE USER QUERIES IN WEB-BASED INFORMATION RETRIEVAL

The effectiveness of Internet search engines is often hampered by the ambiguity of user queries and the reluctance or inability of users to build less ambiguous multi-word queries. Our system, ARCH, is a client-side Web agent, which incorporates domain-specific concept hierarchies together with interactive query formulation in order to automatically produce a richer and therefore less ambiguous query. Unlike traditional relevance feedback methods, ARCH assists users in query modification prior to the search task. ARCH uses the domain knowledge inherent in Web-based classification hierarchies such as Yahoo, combined with a user’s profile information, to add just those terms likely to improve the match with the user’s intent. The goal of the system is therefore to meet the user’s information needs by closing the gap between the user’s stated query and the actual intent of the search. We present a detailed evaluation of the query enhancement in ARCH, comparing enhanced and non-enhanced queries over a range of topics. Our results show that concept-based query enhancement in ARCH leads to significantly higher precision for ambiguous queries without sacrificing recall.
Incentives and Social Norms in Household Behavior

In a broad psychological perspective, both economic incentives and social norms may be be regarded as giving rise to purposesful, or “rational” behavior. By this I simply mean that individuals act in accordance with expected reward or punishment, even though the form these take differs substantially in the two cases. Whereas economic incentives imply “material rewards”, or favors that can be traded for such rewards including leisure, social norms imply “social rewards”. The latter basically take the form of approval or disapproval from others, and related feelings of pride or shame. Moreover, once a social norm has been internalized in an individual’s own value system, behavior in accordance with, or against, the norm will also result in feelings of self-respect or guilt. All this suggests that not only economic incentives but also social norms may be analyzed by means of utility theory, as will be illustrated below. Many social norms may not have much to do with economic incentives (Elster,1989). In some cases, it is, however, useful to study the interaction between them. Indeed, this is the basic message of the paper. My discussion will be limited to three norms of apparent importance for household behavior: (i) work norms; (ii) norms against wage underbidding; and (iii) saving and consumption norms. Thus, the paper deals with norms concerning willingness to work, ability to get a job and the use of income.
ASCLU : Alternative Subspace Clustering

Finding groups of similar objects in databases is one of the most important data mining tasks. Recently, traditional clustering approaches have been extended to generate alternative clustering solutions. The basic observation is that for each database object multiple meaningful groupings might exist: the data allows to be clustered through different perspectives. It is thus reasonable to search for deviating clusters compared to a given clustering result, that the user is not satisfied with. The existing methods focus on full space clustering. However, for today’s applications, where many attributes per object are recorded, traditional clustering is known to generate no meaningful results. Instead, the analysis of subspace projections of the data with subspace or projected clustering techniques is more suitable. In this paper, we develop the first method that detects alternative subspace clusters based on an already known subspace clustering. Considering subspace projections, we can identify alternative clusters also based on deviating dimension sets besides just deviating object sets. Thus, we realize different views on the data by using different attributes. Besides the challenge of detecting alternative subspace clusters our model avoids redundant clusters in the overall result, i.e. the generated clusters are dissimilar among each other. In experiments we analyze the effectiveness of our model and show that meaningful alternative subspace clustering solutions are generated.