Reducing aliasing in images: a PDE-based diffusion revisited

In this paper, we introduce a new diffusion algorithm that can be used for reducing aliasing on both step edges and lines. It derives from the diffusion model of Perona and Malik, and works as an adaptive level-curve method in which diffusion is carried out in the normal direction of the gradient for step edges, while the eigenvalues of the Hessian matrix are used for lines. To get sharp images, we use high-pass filters to preserve as much as possible the high frequency content while diffusing. Experimental tests using grayscale and colour images show that our algorithm efficiently reduces aliasing.     

Inferential Queueing and Speculative Push

Communication latencies within critical sections constitute a major bottleneck in some classes of emerging parallel workloads. In this paper, we argue for the use of two mechanisms to reduce these communication latencies: Inferentially Queued locks (IQLs) and Speculative Push (SP). With IQLs, the processor infers the existence, and limits, of a critical section from the use of synchronization instructions and joins a queue of lock requestors, reducing synchronization delay. The SP mechanism extracts information about program structure by observing IQLs. SP allows the cache controller, responding to a request for a cache line that likely includes a lock variable, to predict the data sets the requestor will modify within the associated critical section. The controller then pushes these lines from its own cache to the target cache, as well as writing them to memory. Overlapping the protected data transfer with that of the lock can substantially reduce the communication latencies within critical sections. By pushing data in exclusive state, the mechanism can collapse a read-modify-write sequences within a critical section into a single local cache access. The write-back to memory allows the receiving cache to ignore the push. Neither mechanism requires any programmer or compiler support nor any instruction set changes. Our experiments demonstrate that IQLs and SP can improve performance of applications employing frequent synchronization.     

Reliability and performance optimization of pipelined real-time systems

We consider pipelined real-time systems that consist of a chain of tasks executing on a distributed platform. The processing of the tasks is pipelined: each processor executes only one interval of consecutive tasks. We are interested in minimizing both the input–output latency and the period of application mapping. For dependability reasons, we are also interested in maximizing the reliability of the system. We therefore assign several processors to each interval of tasks, so as to increase the reliability of the system. Both processors and communication links are unreliable and subject to transient failures. We assume that the arrival of the failures follows a constant parameter Poisson law, and that the failures are statistically independent events. We study several variants of this multiprocessor mapping problem, with several hypotheses on the target platform (homogeneous/heterogeneous speeds and/or failure rates). We provide NP-hardness complexity results, and optimal mapping algorithms for polynomial problem instances. Efficient heuristics are presented to solve the general case, and experimental results are provided.     

Exploring networks with traceroute-like probes: Theory and simulations

Mapping the Internet generally consists in sampling the network from a limited set of sources by using traceroute-like probes. This methodology, akin to the merging of different spanning trees to a set of destination, has been argued to introduce uncontrolled sampling biases that might produce statistical properties of the sampled graph which sharply differ from the original ones. In this paper, we explore these biases and provide a statistical analysis of their origin. We derive an analytical approximation for the probability of edge and vertex detection that exploits the role of the number of sources and targets and allows us to relate the global topological properties of the underlying network with the statistical accuracy of the sampled graph. In particular, we find that the edge and vertex detection probability depends on the betweenness centrality of each element. This allows us to show that shortest path routed sampling provides a better characterization of underlying graphs with broad distributions of connectivity. We complement the analytical discussion with a throughout numerical investigation of simulated mapping strategies in network models with different topologies. We show that sampled graphs provide a fair qualitative characterization of the statistical properties of the original networks in a fair range of different strategies and exploration parameters. Moreover, we characterize the level of redundancy and completeness of the exploration process as a function of the topological properties of the network. Finally, we study numerically how the fraction of vertices and edges discovered in the sampled graph depends on the particular deployements of probing sources. The results might hint the steps toward more efficient mapping strategies.     

Characterization of a Cutibacterium acnes Camp Factor 1-Related Peptide as a New TLR-2 Modulator in In Vitro and Ex Vivo Models of Inflammation

Cutibacterium acnes (C. acnes) has been implicated in inflammatory acne where highly mutated Christie–Atkins–Munch–Petersen factor (CAMP)1 displays strong toll like receptor (TLR)-2 binding activity. Using specific antibodies, we showed that CAMP1 production was independent of C. acnes phylotype and involved in the induction of inflammation. We confirmed that TLR-2 bound both mutated and non-mutated recombinant CAMP1, and peptide array analysis showed that seven peptides (A14, A15, B1, B2, B3, C1 and C3) were involved in TLR-2 binding, located on the same side of the three-dimensional structure of CAMP1. Both mutated and non-mutated recombinant CAMP1 proteins induced the production of C-X-C motif chemokine ligand interleukin (CXCL)8/(IL)-8 in vitro in keratinocytes and that of granulocyte macrophage-colony stimulating factor (GM-CSF), tumor necrosis factor (TNF)-α, IL-1β and IL-10 in ex vivo human skin explants. Only A14, B1 and B2 inhibited the production of CXCL8/IL-8 by keratinocytes and that of (GM-CSF), TNF-α, IL-1β and IL-10 in human skin explants stimulated with rCAMP1 and C. acnes. Following pretreatment with B2, RNA sequencing on skin explants identified the 10 genes displaying the strongest differential expression as IL6, TNF, CXCL1, CXCL2, CXCL3, CXCL8, IL-1β, chemokine ligand (CCL)2, CCL4 and colony stimulating factor (CSF)2. We, thus, identified a new CAMP1-derived peptide as a TLR-2 modulator likely to be a good candidate for clinical evaluation.     

Portfolio Risk Measures: The Time’s Arrow Matters

The traditional ex post risk measure associated to a portfolio, a fund or a market performance, is the standard deviation of a series of past returns, called volatility. We propose an alternative risk measure, that turns out to better quantify the risk actually supported by an investor or asset manager with respect to a portfolio or a fund. This alternative measure is computed from the actual dispersion of successive cumulated returns relative to the corresponding successive cumulated returns produced by an accrued performance of null volatility, which better reflects the dynamics of the risk-return relationship over time. Hence, the proposed name of “accrued returns variability”, for such a risk measure that incorporates the passage of time. Applications are presented, to enlighten the advantage of this risk measure.     

Project scheduling under uncertainty using fuzzy modelling and solving techniques

In the real world, projects are subject to numerous uncertainties at different levels of planning. Fuzzy project scheduling is one of the approaches that deal with uncertainties in project scheduling problem. In this paper, we provide a new technique that keeps uncertainty at all steps of the modelling and solving procedure by considering a fuzzy modelling of the workload inspired from the fuzzy/possibilistic approach. Based on this modelling, two project scheduling techniques, Resource Constrained Scheduling and Resource Leveling, are considered and generalized to handle fuzzy parameters. We refer to these problems as the Fuzzy Resource Constrained Project Scheduling Problem (FRCPSP) and the Fuzzy Resource Leveling Problem (FRLP). A Greedy Algorithm and a Genetic Algorithm are provided to solve FRCPSP and FRLP respectively, and are applied to civil helicopter maintenance within the framework of a French industrial project called Helimaintenance.     

BSEM estimation of network effect and customer orientation empowerment on trust in social media and network environment

This paper presents a stochastic model that identifies network effect and customer orientation empowerment as strong antecedents of trustworthiness and trust in social media network environment. As Trust is emerging as a critical influencer of consumer behavior in organizations, social media has become the facilitator or the enabler of this influence. This paper aims to explore and examine the relationships amongst the antecedents of trust in the context of the social media network environment via Bayesian estimation and testing of the structural equation model. In facilitating the estimation of the stochastic model, a survey was conducted on 255 social media users. A series of statistical analyses were conducted prior to the estimation using Bayesian Markov Chain Monte Carlo (MCMC). Results showed that network effect and customer orientation empowerment were significant predictors of trustworthiness and trust. Bayesian MCMC results confirmed that the findings were consistent with the literature.     

A differential inclusion approach for modeling and analysis of dynamical systems under uncertainty

In this paper we deal with the application of differential inclusions to modeling nonlinear dynamical systems under uncertainty in parameters. In this case, differential inclusions seem to be better suited to modeling practical situations under uncertainty and imprecision than formulations by means of fuzzy differential equations. We develop a practical algorithm to approximate the reachable sets of a class of nonlinear differential inclusion, which eludes the computational problems of a previous set-valued version of the Heun’s method. Our algorithm is based on a complete discretization (time and state space) of the differential inclusion and it suits hardware features, handling the memory used by the method in a controlled fashion during all iterations. As a case of study, we formulate a differential inclusion to model an epidemic outbreak of dengue fever under Cuban conditions. The model takes into account interaction of human and mosquito populations as well as vertical transmission in the mosquito population. It is studied from the theoretical point of view to apply the Practical Algorithm. Also, we estimate the temporal evolution of the different human and mosquito populations given by the model in the Dengue 3 epidemic in Havana 2001, through the computation of the reachable sets using the Practical Algorithm.     

Review of Memory, war and trauma.

Reviews the book, Memory, war and trauma by Nigel C. Hunt (see record 2010-17048-000). Hunt’s book presents a very different perspective on how memory, war, and trauma interface, drawing upon a variety of sources not frequently accessed by psychologists. He promotes an interdisciplinary approach to studying memory and war; however, rather than drawing upon the usual fields, such as biology or sociology, Dr. Hunt suggests that a careful examination of history and literature are also integral to developing a complete understanding of memory and war. This book is not designed for individuals unfamiliar with the field of trauma and war. Memory, war and trauma highlights the limitations of current empirical approaches to studying war trauma and presents a narrative methodology that he argues will better capture the unique individual experience of trauma. Hunt rightly demonstrates weaknesses of current methods, and suggests that the narrative method may be the solution to some of the problems with current methods. Though his argument is likely that the narrative method should supplement rather than replace current experimental method, one is left feeling that he believes current methods are wholly inadequate and his method is better. Despite this central weakness, this book will be a benefit to psychologists who study and treat individuals touched by war because it will encourage them to think beyond traditional approaches to research and treatment. (PsycINFO Database Record (c) 2011 APA, all rights reserved)