Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological Mechanisms Underlying the Ultraviolet Radiation-Induced Formation of Skin Wrinkling and Sagging II: Over-Expression of Neprilysin Plays an Essential Role

Our previous studies strongly indicated that the up-regulated activity of skin fibroblast-derived elastase plays a pivotal role in wrinkling and/or sagging of the skin via the impairment of elastic fiber configuration and the subsequent loss of skin elasticity. Fortunately, we succeeded in identifying human skin fibroblast-derived elastase as a previously known enzyme, neprilysin or neutral endopeptidase (NEP). We have also characterized epithelial-mesenchymal paracrine cytokine interactions between UVB-exposed-keratinocytes and dermal fibroblasts and found that interleukin-1α and granulocyte macrophage colony stimulatory factor (GM-CSF) are intrinsic cytokines secreted by UVB-exposed keratinocytes that stimulate the expression of neprilysin by fibroblasts. On the other hand, direct UVA exposure of human fibroblasts significantly stimulates the secretion of IL-6 and also elicits a significant increase in the gene expression of matrix metallo-protease(MMP)-1 as well as neprilysin (to a lesser extent), which is followed by distinct increases in their protein and enzymatic activity levels. Direct UVA exposure of human keratinocytes also stimulates the secretion of IL-6, IL-8 and GM-CSF but not of IL-1 and endothelin-1. These findings suggest that GM-CSF secreted by UVA-exposed keratinocytes as well as IL-6 secreted by UVA-exposed dermal fibroblasts play important and additional roles in UVA-induced sagging and wrinkling by up-regulation of neprilysin and MMP-1, respectively, in dermal fibroblasts.
Online convex optimization in the bandit setting: gradient descent without a gradient

We study a general online convex optimization problem. We have a convex set <i>S</i> and an unknown sequence of cost functions <i>c</i><inf>1</inf>, <i>c</i><inf>2</inf>,. , and in each period, we choose a feasible point <i>x<inf>t</inf></i> in <i>S</i>, and learn the cost <i>c<inf>t</inf></i>(<i>x<inf>t</inf></i>). If the function <i>c<inf>t</inf></i> is also revealed after each period then, as Zinkevich shows in [25], gradient descent can be used on these functions to get regret bounds of <i>O</i>(√<i>n</i>). That is, after <i>n</i> rounds, the total cost incurred will be <i>O</i>(√<i>n</i>) more than the cost of the best single feasible decision chosen with the benefit of hindsight, min<inf><i>x</i></inf> Σ <i>ct</i>(<i>x</i>). We extend this to the "bandit" setting, where, in each period, only the cost <i>c<inf>t</inf></i>(<i>x<inf>t</inf></i>) is revealed, and bound the expected regret as <i>O</i>(<i>n</i><sup>3/4</sup>). Our approach uses a simple approximation of the gradient that is computed from evaluating <i>c<inf>t</inf></i> at a single (random) point. We show that this biased estimate is sufficient to approximate gradient descent on the sequence of functions. In other words, it is possible to use gradient descent without seeing anything more than the value of the functions at a single point. The guarantees hold even in the most general case: online against an adaptive adversary.For the online linear optimization problem [15], algorithms with low regrets in the bandit setting have recently been given against oblivious [1] and adaptive adversaries [19]. In contrast to these algorithms, which distinguish between explicit <i>explore</i> and <i>exploit</i> periods, our algorithm can be interpreted as doing a small amount of exploration in each period.
Intelligent search of correlated alarms from database containing noise data

Alarm correlation plays an important role in improving the service and reliability in modern telecommunication networks. Most previous research of alarm correlation did not consider the effects of noise data in the database. This paper focuses on the method of discovering alarm correlation rules from a database containing noise data. We firstly define two parameters, win-freq and win-add, as the measures of noise data and then present a robust search algorithm to solve the problem. At different size of win-freq and win-add, the experiments on the alarm database containing noise data show that the robust search algorithm can discover more rules with the bigger size of win-add. We also compare, by experiments, two different interestingness measures of confidence and correlation.
Implementing a Unification Algorithm for Protocol Analysis with XOR

In this paper, we propose a unification algorithm for the theory $E$ which combines unification algorithms for $E_{\std}$ and $E_{\ACUN}$ (ACUN properties, like XOR) but compared to the more general combination methods uses specific properties of the equational theories for further optimizations. Our optimizations drastically reduce the number of non-deterministic choices, in particular those for variable identification and linear orderings. This is important for reducing both the runtime of the unification algorithm and the number of unifiers in the complete set of unifiers. We emphasize that obtaining a ``small'' set of unifiers is essential for the efficiency of the constraint solving procedure within which the unification algorithm is used. The method is implemented in the CL-Atse tool for security protocol analysis.
Decomposing finite Abelian groups

This paper describes a quantum algorithm for efficiently decomposing finite Abelian groups into a product of cyclic groups. Such a decomposition is needed in order to apply the Abelian hidden subgroup algorithm. Such a decomposition (assuming the Generalized Riemann Hypothesis) also leads to an efficient algorithm for computing class numbers (known to be at least as difficult as factoring).
Semantical characterizations and complexity of equivalences in answer set programming

In recent research on nonmonotonic logic programming, repeatedly strong equivalence of logic programs P and Q has been considered, which holds if the programs P∪R and Q∪R have the same answer sets for any other program R. This property strengthens the equivalence of P and Q with respect to answer sets (which is the particular case for R=∅), and has its applications in program optimization, verification, and modular logic programming. In this article, we consider more liberal notions of strong equivalence, in which the actual form of R may be syntactically restricted. On the one hand, we consider uniform equivalence where R is a set of facts, rather than a set of rules. This notion, which is well-known in the area of deductive databases, is particularly useful for assessing whether programs P and Q are equivalent as components of a logic program which is modularly structured. On the other hand, we consider relativized notions of equivalence where R ranges over rules over a fixed alphabet, and thus generalize our results to relativized notions of strong and uniform equivalence. For all these notions, we consider disjunctive logic programs in the propositional (ground) case as well as some restricted classes, providing semantical characterizations and analyzing the computational complexity. Our results, which naturally extend to answer set semantics for programs with strong negation, complement the results on strong equivalence of logic programs and pave the way for optimizations in answer set solvers as a tool for input-based problem solving.
Nonuniform sampling theorems for random signals in the offset linear canonical transform domain

With the rapid development of the offset linear canonical transform (OLCT) in the fields of optics and signal processing, it is necessary to consider the nonuniform sampling associated with the OLCT. Nowadays, the analysis and applications of the nonuniform sampling for deterministic signals in the OLCT domain have been well published and studied. However, none of the results about the reconstruction of nonuniform sampling for random signals in the OLCT domain have been proposed until now. In this paper, the nonuniform sampling and reconstruction of random signals in the OLCT domain are investigated. Firstly, a brief introduction to the fundamental knowledge of the OLCT and some special nonuniform sampling models are given. Then, the reconstruction theorems for random signals from nonuniform samples in the OLCT domain have been derived for different nonuniform sampling models. Finally, the simulation results are given to verify the accuracy of theoretical results.
Performance of a DECnet based disk block server

This report describes an experimental disk block server implemented for the RSX-11M Operating System using DECnet. The block server allows user programs on one system to access files on a disk physically located on a different system. The actual interface is at the level of physical blocks and IO transfers. Results of basic performance measurements are given, and explained in terms of major components. Performance predictions are made for servers of this type supporting more complex workloads.
Algebraic Structures and Algorithms for Matching and Matroid Problems

We present new algebraic approaches for several well-known combinatorial problems, including non-bipartite matching, matroid intersection, and some of their generalizations. Our work yields new randomized algorithms that are the most efficient known. For non-bipartite matching, we obtain a simple, purely algebraic algorithm with running time O(nw) where n is the number of vertices and w is the matrix multiplication exponent. This resolves the central open problem of Mucha and Sankowski (2004). For matroid intersection, our algorithm has running time O(nrw - 1)for matroids with n elements and rank r that satisfy some natural conditions. This algorithm is based on new algebraic results characterizing the size of a maximum intersection in contracted matroids. Furthermore, the running time of this algorithm is essentially optimal
Error Rate Analysis for Coded Multicarrier Systems Over Quasi-Static Fading Channels

Several standards such as IEEE 802.11a/g, IEEE 802.16, and the European Computer Manufacturers Association (ECMA) multiband orthogonal frequency division multiplexing (MB-OFDM) for high data-rate ultra-wideband employ bit-interleaved convolutionally coded multicarrier modulation over quasi-static fading channels. Motivated by the lack of appropriate error rate analysis techniques for this popular type of system and channel model, we present two novel analytical methods for bit error rate (BER) estimation of coded multicarrier systems operating over frequency-selective quasi-static channels with nonideal interleaving. In the first method, the approximate performance of the system is calculated for each realization of the channel, which is suitable for obtaining the outage BER performance (a common performance measure for, e.g., MB-OFDM systems). The second method assumes Rayleigh distributed frequency-domain subcarrier channel gains and knowledge of their correlation matrix, and can be used to directly obtain the average BER performance. Both methods are applicable to convolutionally coded interleaved multicarrier systems employing quadrature amplitude modulation, and are also able to account for narrowband interference (modeled as a sum of tone interferers). To illustrate the application of the proposed analysis, both methods are used to study the performance of a tone-interference-impaired MB-OFDM system.
NodeTrix: Hybrid Representation for Analyzing Social Networks

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily answer the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections from either a node-link or a matrix, flexibly manipulate the NodeTrix representation to explore the dataset, and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results.
Spatial Relations in Text-to-Scene Conversion

Spatial relations play an important role in our understanding of language. In particular, they are a crucial component in descriptions of scenes in the world. WordsEye (www.wordseye.com) is a system for automatically converting natural language text into 3D scenes representing the meaning of that text. Natural language offers an interface to scene generation that is intuitive and immediately approachable by anyone, without any special skill or training. WordsEye has been used by several thousand users on the web to create approximately 15,000 fully rendered scenes. We describe how the system incorporates geometric and semantic knowledge about objects and their parts and the spatial relations that hold among these in order to depict spatial relations in 3D scenes.
Application Software, Domain-Specific Languages, and Language Design Assistants

While application software does the real work, domain-specific languages (DSLs) are tools to help produce it efficiently, and language design assistants in turn are meta-tools to help produce DSLs quickly. DSLs are already in wide use (HTML for web pages, Excel macros for spreadsheet applications, VHDL for hardware design, .), but many more will be needed for both new as well as existing application domains. Language design assistants to help develop them currently exist only in the basic form of language development systems. After a quick look at domain-specific languages, and especially their relationship to application libraries, we survey existing language development systems and give an outline of future language design assistants.
GUARDS: A Generic Upgradable Architecture for Real-Time Dependable Systems

The development and validation of fault-tolerant computers for critical real-time applications are currently both costly and time consuming. Often, the underlying technology is out-of-date by the time the computers are ready for deployment. Obsolescence can become a chronic problem when the systems in which they are embedded have lifetimes of several decades. This paper gives an overview of the work carried out in a project that is tackling the issues of cost and rapid obsolescence by defining a generic fault-tolerant computer architecture based essentially on commercial off-the-shelf (COTS) components (both processor hardware boards and real-time operating systems). The architecture uses a limited number of specific, but generic, hardware and software components to implement an architecture that can be configured along three dimensions: redundant channels, redundant lanes, and integrity levels. The two dimensions of physical redundancy allow the definition of a wide variety of instances with different fault tolerance strategies. The integrity level dimension allows application components of different levels of criticality to coexist in the same instance. The paper describes the main concepts of the architecture, the supporting environments for development and validation, and the prototypes currently being implemented.
A Multiplexer-Based Arbiter PUF Composition with Enhanced Reliability and Security

Arbiter Physically Unclonable Functions (APUFs), while being relatively lightweight, are extremely vulnerable to modeling attacks. Hence, various compositions of APUFs such as XOR APUF and Lightweight Secure PUF have been proposed to be secure alternatives. Previous research has demonstrated that PUF compositions have two major challenges to overcome: vulnerability against modeling and statistical attacks, and lack of reliability. In this paper, we introduce a multiplexer-based composition of APUFs, denoted as MPUF, to simultaneously overcome these challenges. In addition to the basic MPUF design, we propose two MPUF variants namely cMPUF and rMPUF to improve the robustness against cryptanalysis and reliability-based modeling attack, respectively. An rMPUF demonstrates enhanced robustness against the reliability-based modeling attack, while even the well-known XOR APUF, otherwise robust to machine learning based modeling attacks, has been modeled using the same technique with linear data and time complexities. The rMPUF can provide a good trade-off between security and hardware overhead while maintaining a significantly higher reliability level than any practical XOR APUF instance. Moreover, MPUF variants are the first APUF compositions, to the best of our knowledge, that can achieve Strict Avalanche Criterion without using any additional input network (or hardware) for challenge transformation. Finally, we validate our theoretical findings using Matlab-based simulations of MPUFs.
Going Stupid with EcoLab

The very simple model known as Stupid Model was proposed in 2005. Stupid Model could be implemented within a couple of hours, and was later extended to demonstrate the use of common ABM platform functionality. Implementations of the model in several agent-based modeling platforms were provided, and platforms were compared for ease of implementation and performance. In this paper, Stupid Model is implemented in the EcoLab simulation platform (a C++ based modeling platform), demonstrating that it is a feasible platform for these sorts of models. The performance of the implementation is compared with the Repast, Mason and Swarm versions.
Developing Enterprise Applications with Support to Dynamic Unanticipated Evolution

This paper presents a component based framework for developing enterprise applications with support to dynamic unanticipated evolution. The framework is based on the COMPOR Component Model Specification, which provides mechanisms to manage unpredicted evolution even at runtime. We describe the framework design that is based on design patterns and aspect-oriented concepts. Finally, we present a example application of the framework in the context of electronic commerce.
Unified Large-System Analysis of MMSE and Adaptive Least Squares Receivers for a Class of Random Matrix Channels

We present a unified large-system analysis of linear receivers for a class of random matrix channels. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random independent, identically distributed (i.i.d.) and random orthogonal precoding. We derive expressions for the asymptotic signal-to-interference-plus-noise ratio (SINR) of the MMSE receiver, and both the transient and steady-state SINR of the ALS receiver, trained using either i.i. d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i. d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission
Clustering under Perturbation Resilience

Motivated by the fact that distances between data points in many real-world clustering instances are often based on heuristic measures, Bilu and Linial [6] proposed analyzing objective based clustering problems under the assumption that the optimum clustering to the objective is preserved under small multiplicative perturbations to distances between points. In this paper, we provide several results within this framework. For separable center-based objectives, we present an algorithm that can optimally cluster instances resilient to $(1 + \sqrt{2})$-factor perturbations, solving an open problem of Awasthi et al. [2]. For the k-median objective, we additionally give algorithms for a weaker, relaxed, and more realistic assumption in which we allow the optimal solution to change in a small fraction of the points after perturbation. We also provide positive results for min-sum clustering which is a generally much harder objective than k-median (and also non-center-based). Our algorithms are based on new linkage criteria that may be of independent interest.
Models and Tools for Collaborative Annotation

The Annotation Graph Toolkit (AGTK) is a collection of software which facilitates development of linguistic annotatio n tools. AGTK provides a database interface which allows applications to use a database server for persistent storage. This paper dis cusses various modes of collaborative annotation and how they can be supported with tools built using AGTK and its database interface. We describe the relational database schema and API, and describe a version of the TableTrans tool which supports collaborative annotation. The remainder of the paper discusses a high-level query language for annotation graphs, along with optimizations, in support of expressive and efficient access to the annotations held on a large centra l server. The paper demonstrates that it is straightforward to support a variety of different levels of collaborative annotation with exist ing AGTK-based tools, with a minimum of additional programming effort.
The Quadratic Gaussian Rate-Distortion Function for Source Uncorrelated Distortions

We characterize the rate-distortion function for zero-mean stationary Gaussian sources under the MSE fidelity criterion and subject to the additional constraint that the distortion is uncorrelated to the input. The solution is given by two equations coupled through a single scalar parameter. This has a structure similar to the well known water-filling solution obtained without the uncorrelated distortion restriction. Our results fully characterize the unique statistics of the optimal distortion. We also show that, for all positive distortions, the minimum achievable rate subject to the uncorrelation constraint is strictly larger than that given by the un-constrained rate-distortion function. This gap increases with the distortion and tends to infinity and zero, respectively, as the distortion tends to zero and infinity.