134 resultados para Hardware Transactional Memory


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Human memory is a complex neurocognitive process. By combining psychological and molecular genetics expertise, we examined the APOE ε4 allele, a known risk factor for Alzheimer's disease, and the COMT Val 158 polymorphism, previously implicated in schizophrenia, for association with lowered memory functioning in healthy adults. To assess memory type we used a range of memory tests of both retrospective and prospective memory. Genotypes were determined using RFLP analysis and compared with mean memory scores using univariate ANOVAs. Despite a modest sample size (n=197), our study found a significant effect of the APOE ε4 polymorphism in prospective memory. Supporting our hypothesis, a significant difference was demonstrated between genotype groups for means of the Comprehensive Assessment of Prospective Memory total score (p=0.036; ε4 alleles=1.99; all other alleles=1.86). In addition, we demonstrate a significant interactive effect between the APOE ε4 and COMT polymorphisms in semantic memory. This is the first study to investigate both APOE and COMT genotypes in relation to memory in non-pathological adults and provides important information regarding the effect of genetic determinants on human memory.

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A key question in neuroscience is how memory is selectively allocated to neural networks in the brain. This question remains a significant research challenge, in both rodent models and humans alike, because of the inherent difficulty in tracking and deciphering large, highly dimensional neuronal ensembles that support memory (i.e., the engram). In a previous study we showed that consolidation of a new fear memory is allocated to a common topography of amygdala neurons. When a consolidated memory is retrieved, it may enter a labile state, requiring reconsolidation for it to persist. What is not known is whether the original spatial allocation of a consolidated memory changes during reconsolidation. Knowledge about the spatial allocation of a memory, during consolidation and reconsolidation, provides fundamental insight into its core physical structure (i.e., the engram). Using design-based stereology, we operationally define reconsolidation by showing a nearly identical quantity of neurons in the dorsolateral amygdala (LAd) that expressed a plasticity-related protein, phosphorylated mitogen-activated protein kinase, following both memory acquisition and retrieval. Next, we confirm that Pavlovian fear conditioning recruits a stable, topographically organized population of activated neurons in the LAd. When the stored fear memory was briefly reactivated in the presence of the relevant conditioned stimulus, a similar topography of activated neurons was uncovered. In addition, we found evidence for activated neurons allocated to new regions of the LAd. These findings provide the first insight into the spatial allocation of a fear engram in the LAd, during its consolidation and reconsolidation phase.

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Pavlovian fear conditioning is a robust technique for examining behavioral and cellular components of fear learning and memory. In fear conditioning, the subject learns to associate a previously neutral stimulus with an inherently noxious co-stimulus. The learned association is reflected in the subjects' behavior upon subsequent re-exposure to the previously neutral stimulus or the training environment. Using fear conditioning, investigators can obtain a large amount of data that describe multiple aspects of learning and memory. In a single test, researchers can evaluate functional integrity in fear circuitry, which is both well characterized and highly conserved across species. Additionally, the availability of sensitive and reliable automated scoring software makes fear conditioning amenable to high-throughput experimentation in the rodent model; thus, this model of learning and memory is particularly useful for pharmacological and toxicological screening. Due to the conserved nature of fear circuitry across species, data from Pavlovian fear conditioning are highly translatable to human models. We describe equipment and techniques needed to perform and analyze conditioned fear data. We provide two examples of fear conditioning experiments, one in rats and one in mice, and the types of data that can be collected in a single experiment. © 2012 Springer Science+Business Media, LLC.

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Pavlovian fear conditioning, also known as classical fear conditioning is an important model in the study of the neurobiology of normal and pathological fear. Progress in the neurobiology of Pavlovian fear also enhances our understanding of disorders such as posttraumatic stress disorder (PTSD) and with developing effective treatment strategies. Here we describe how Pavlovian fear conditioning is a key tool for understanding both the neurobiology of fear and the mechanisms underlying variations in fear memory strength observed across different phenotypes. First we discuss how Pavlovian fear models aspects of PTSD. Second, we describe the neural circuits of Pavlovian fear and the molecular mechanisms within these circuits that regulate fear memory. Finally, we show how fear memory strength is heritable; and describe genes which are specifically linked to both changes in Pavlovian fear behavior and to its underlying neural circuitry. These emerging data begin to define the essential genes, cells and circuits that contribute to normal and pathological fear.

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This thesis is a study of how the contents of volatile memory on the Windows operating system can be better understood and utilised for the purposes of digital forensic investigations. It proposes several techniques to improve the analysis of memory, with a focus on improving the detection of unknown code such as malware. These contributions allow the creation of a more complete reconstruction of the state of a computer at acquisition time, including whether or not the computer has been infected by malicious code.

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This paper presents a new framework for distributed intrusion detection based on taint marking. Our system tracks information flows between applications of multiple hosts gathered in groups (i.e., sets of hosts sharing the same distributed information flow policy) by attaching taint labels to system objects such as files, sockets, Inter Process Communication (IPC) abstractions, and memory mappings. Labels are carried over the network by tainting network packets. A distributed information flow policy is defined for each group at the host level by labeling information and defining how users and applications can legally access, alter or transfer information towards other trusted or untrusted hosts. As opposed to existing approaches, where information is most often represented by two security levels (low/high, public/private, etc.), our model identifies each piece of information within a distributed system, and defines their legal interaction in a fine-grained manner. Hosts store and exchange security labels in a peer to peer fashion, and there is no central monitor. Our IDS is implemented in the Linux kernel as a Linux Security Module (LSM) and runs standard software on commodity hardware with no required modification. The only trusted code is our modified operating system kernel. We finally present a scenario of intrusion in a web service running on multiple hosts, and show how our distributed IDS is able to report security violations at each host level.

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Reconfigurable computing devices can increase the performance of compute intensive algorithms by implementing application specific co-processor architectures. The power cost for this performance gain is often an order of magnitude less than that of modern CPUs and GPUs. Exploiting the potential of reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) is typically a complex and tedious hardware engineering task. Re- cently the major FPGA vendors (Altera, and Xilinx) have released their own high-level design tools, which have great potential for rapid development of FPGA based custom accelerators. In this paper, we will evaluate Altera’s OpenCL Software Development Kit, and Xilinx’s Vivado High Level Sythesis tool. These tools will be compared for their per- formance, logic utilisation, and ease of development for the test case of a Tri-diagonal linear system solver.

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The study of memory in most behavioral paradigms, including emotional memory paradigms, has focused on the feed forward components that underlie Hebb’s first postulate, associative synaptic plasticity. Hebb’s second postulate argues that activated ensembles of neurons reverberate in order to provide temporal coordination of different neural signals, and thereby facilitate coincidence detection. Recent evidence from our groups has suggested that the lateral amygdala (LA) contains recurrent microcircuits and that these may reverberate. Additionally this reverberant activity is precisely timed with latencies that would facilitate coincidence detection between cortical and sub cortical afferents to the LA.Thus, recent data at the microcircuit level in the amygdala provide some physiological evidence in support of the second Hebbian postulate.

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Physical design objects such as sketches, drawings, collages, storyboards and models play an important role in supporting communication and coordination in design studios. CAM (Cooperative Artefact Memory) is a mobile-tagging based messaging system that allows designers to collaboratively store relevant information onto their design objects in the form of messages, annotations and external web links. We studied the use of CAM in a Product Design studio over three weeks, involving three different design teams. In this paper, we briefly describe CAM and show how it serves as 'object memory'.

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Here, we investigate the genetic basis of human memory in healthy individuals and the potential role of two polymorphisms, previously implicated in memory function. We have explored aspects of retrospective and prospective memory including semantic, short term, working and long-term memory in conjunction with brain derived neurotrophic factor (BDNF) and tumor necrosis factor-alpha (TNF-alpha). The memory scores for healthy individuals in the population were obtained for each memory type and the population was genotyped via restriction fragment length polymorphism for the BDNF rs6265 (Val66Met) SNP and via pyrosequencing for the TNF-alpha rs113325588 SNP. Using univariate ANOVA, a significant association of the BDNF polymorphism with visual and spatial memory retention and a significant association of the TNF-alpha polymorphism was observed with spatial memory retention. In addition, a significant interactive effect between BDNF and TNF-alpha polymorphisms was observed in spatial memory retention. In practice visual memory involves spatial information and the two memory systems work together, however our data demonstrate that individuals with the Val/Val BDNF genotype have poorer visual memory but higher spatial memory retention, indicating a level of interaction between TNF-alpha and BDNF in spatial memory retention. This is the first study to use genetic analysis to determine the interaction between BDNF and TNF-alpha in relation to memory in normal adults and provides important information regarding the effect of genetic determinants and gene interactions on human memory.

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The increasing growth in the use of Hardware Security Modules (HSMs) towards identification and authentication of a security endpoint have raised numerous privacy and security concerns. HSMs have the ability to tie a system or an object, along with its users to the physical world. However, this enables tracking of the user and/or an object associated with the HSM. Current systems do not adequately address the privacy needs and as such are susceptible to various attacks. In this work, we analyse various security and privacy concerns that arise when deploying such hardware security modules and propose a system that allow users to create pseudonyms from a trusted master public-secret key pair. The proposed system is based on the intractability of factoring and finding square roots of a quadratic residue modulo a composite number, where the composite number is a product of two large primes. Along with the standard notion of protecting privacy of an user, the proposed system offers colligation between seemingly independent pseudonyms. This new property when combined with HSMs that store the master secret key is extremely beneficial to a user, as it offers a convenient way to generate a large number of pseudonyms using relatively small storage requirements.

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The motion response of marine structures in waves can be studied using finite-dimensional linear-time-invariant approximating models. These models, obtained using system identification with data computed by hydrodynamic codes, find application in offshore training simulators, hardware-in-the-loop simulators for positioning control testing, and also in initial designs of wave-energy conversion devices. Different proposals have appeared in the literature to address the identification problem in both time and frequency domains, and recent work has highlighted the superiority of the frequency-domain methods. This paper summarises practical frequency-domain estimation algorithms that use constraints on model structure and parameters to refine the search of approximating parametric models. Practical issues associated with the identification are discussed, including the influence of radiation model accuracy in force-to-motion models, which are usually the ultimate modelling objective. The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.

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This paper addresses the problem of joint identification of infinite-frequency added mass and fluid memory models of marine structures from finite frequency data. This problem is relevant for cases where the code used to compute the hydrodynamic coefficients of the marine structure does not give the infinite-frequency added mass. This case is typical of codes based on 2D-potential theory since most 3D-potential-theory codes solve the boundary value associated with the infinite frequency. The method proposed in this paper presents a simpler alternative approach to other methods previously presented in the literature. The advantage of the proposed method is that the same identification procedure can be used to identify the fluid-memory models with or without having access to the infinite-frequency added mass coefficient. Therefore, it provides an extension that puts the two identification problems into the same framework. The method also exploits the constraints related to relative degree and low-frequency asymptotic values of the hydrodynamic coefficients derived from the physics of the problem, which are used as prior information to refine the obtained models.

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Urban space has the potential to shape people's experience and understanding of the city and of the culture of a place. In some respects, murals and allied forms of wall art occupy the intersection of street art and public art; engaging, and sometimes, transforming the urban space in which they exist and those who use it. While murals are often conceived as a more ‘permanent’ form of painted art there has been a trend in recent years towards more deliberately transient forms of wall art such as washed-wall murals and reverse graffiti. These varying forms of public wall art are embedded within the fabric of the urban space and history. This paper will explore the intersection of public space, public art and public memory in a mural project in the Irish city of Cork. Focussing on the washed-wall murals of Cork's historic Shandon district, we explore the sympathetic and synergetic relationship of this wall art with the heritage architecture of the built environment and of the murals as an expression of and for the local community, past and present. Through the Shandon Big Wash Up murals we reflect on the function of participatory public art as an explicit act of urban citizenship which works to support community-led re-enchantment in the city through a reconnection with its past.