979 resultados para IS Function
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Many RFID protocols use cryptographic hash functions for their security. The resource constrained nature of RFID systems forces the use of light weight cryptographic algorithms. Tav-128 is one such 128-bit light weight hash function proposed by Peris-Lopez et al. for a low-cost RFID tag authentication protocol. Apart from some statistical tests for randomness by the designers themselves, Tav-128 has not undergone any other thorough security analysis. Based on these tests, the designers claimed that Tav-128 does not posses any trivial weaknesses. In this article, we carry out the first third party security analysis of Tav-128 and show that this hash function is neither collision resistant nor second preimage resistant. Firstly, we show a practical collision attack on Tav-128 having a complexity of 237 calls to the compression function and produce message pairs of arbitrary length which produce the same hash value under this hash function. We then show a second preimage attack on Tav-128 which succeeds with a complexity of 262 calls to the compression function. Finally, we study the constituent functions of Tav-128 and show that the concatenation of nonlinear functions A and B produces a 64-bit permutation from 32-bit messages. This could be a useful light weight primitive for future RFID protocols.
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It’s commonly assumed that psychiatric violence is motivated by delusions, but here the concept of a reversed impetus is explored, to understand whether delusions are formed as ad-hoc or post-hoc rationalizations of behaviour or in advance of the actus reus. The reflexive violence model proposes that perceptual stimuli has motivational power and this may trigger unwanted actions and hallucinations. The model is based on the theory of ecological perception, where opportunities enabled by an object are cues to act. As an apple triggers a desire to eat, a gun triggers a desire to shoot. These affordances (as they are called) are part of the perceptual apparatus, they allow the direct recognition of objects – and in emergencies they enable the fastest possible reactions. Even under normal circumstances, the presence of a weapon will trigger inhibited violent impulses. The presence of a victim will also, but under normal circumstances, these affordances don’t become violent because negative action impulses are totally inhibited, whereas in psychotic illness, negative action impulses are treated as emergencies and bypass frontal inhibitory circuits. What would have been object recognition becomes a blind automatic action. A range of mental illnesses can cause inhibition to be bypassed. At its most innocuous, this causes both simple hallucinations (where the motivational power of an object is misattributed). But ecological perception may have the power to trigger serious violence also –a kind that’s devoid of motives or planning and is often shrouded in amnesia or post-rational delusions.
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Wrong-Doing, Truth-Telling: The Function of Avowal in Justice is a collection of seven lectures delivered by French philosopher and historian Michel Foucault at the Catholic University of Louvain in 1981. Compiled from audiovisual recordings and Foucault’s original manuscripts, these lectures explore the notion of avowal and its place within criminal justice processes. Accompanied by three contemporaneous interviews given by Foucault (only one of which has previously been available in English), and a preface and concluding essay by the editors contextualizing these lectures in Foucault’s oeuvre, this volume contributes much to Foucaultian scholarship, particularly when considered alongside the recently published volumes of Foucault’s lecture courses at the Collège de France. However, while the book promises to offer some insights of relevance to criminology, it is important to remember that this is not its key purpose, and criminologists should read it with this caveat in mind...
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The laz gene of Neisseria meningitidis is predicted to encode a lipid-modified azurin (Laz). Laz is very similar to azurin, a periplasmic protein, which belongs to the copper-containing proteins in the cupredoxin superfamily. In other bacteria, azurin is an electron donor to nitrite reductase, an important enzyme in the denitrifying process. It is not known whether Laz could function as an electron transfer protein in this important pathogen. Laz protein was heterologously expressed in Escherichia coli and purified. Electrospray mass spectrometry indicated that the Laz protein contains one copper ion. Laz was shown to be redox-active in the presence of its redox center copper ion. When oxidized, Laz exhibits an intense blue colour and absorbs visible light around 626 nm. The absorption is lost when exposed to diethyldithiocarbamate, a copper chelating agent. Polyclonal antibodies were raised against purified Laz for detecting expression of Laz under different growth conditions and to determine the orientation of Laz on the outer membrane. The expression of Laz under microaerobic and microaerobic denitrifying conditions was slightly higher than that under aerobic conditions. However, the expression of Laz was similar between the wild type strain and an fnr mutant, suggesting that Fumarate/Nitrate reduction regulator (FNR) does not regulate the expression of Laz despite the presence of a partial FNR box upstream of the laz gene. We propose that some Laz protein is exposed on the outer membrane surface of N. meningitidis as the αLaz antibodies can increase killing by complement in a capsule deficient N. meningitidis strain, in a dose-dependent fashion.
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Clinical studies have demonstrated an impairment of glucocorticoid receptor (GR)-mediated negative feedback on the hypothalamic-pituitary-adrenal (HPA) axis in patients with major depression (GR resistance), and its resolution by antidepressant treatment. Recently, we showed that this impairment is indeed due to a dysfunction of GR in depressed patients (Carvalho et al., 2009), and that the ability of the antidepressant clomipramine to decrease GR function in peripheral blood cells is impaired in patients with major depression who are clinically resistant to treatment (Carvalho et al. 2008). To further investigate the effect of antidepressants on GR function in humans, we have compared the effect of the antidepressants clomipramine, amytriptiline, sertraline, paroxetine and venlafaxine, and of the antipsychotics, haloperidol and risperidone, on GR function in peripheral blood cells from healthy volunteers (n=33). GR function was measured by glucocorticoid inhibition of lypopolysaccharide (LPS)-stimulated interleukin-6 (IL-6) levels. Compared to vehicle-treated cells, all antidepressants inhibited dexamethasone (DEX, 10-100nM) inhibition of LPS-stimulated IL-6 levels (p values ranging from 0.007 to 0.1). This effect was specific to antidepressants, as antipsychotics had no effect on DEX-inhibition of LPS-stimulated IL-6 levels. The phosphodiesterase (PDE) type 4 inhibitor, rolipram, potentiated the effect of antidepressants on GR function, while the GR antagonist, RU-486, inhibited the effect of antidepressants on GR function. These findings indicate that the effect of antidepressants on GR function are specific for this class of psychotropic drugs, and involve second messenger pathways relevant to GR function and inflammation. Furthermore, it also points towards a possible mechanism by which one maybe able to overcome treatment-resistant depression. Research in this field will lead to new insights into the pathophysiology and treatment of affective disorders.
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The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.
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Background The purpose of this study was to adapt and validate the Foot Function Index to the Spanish (FFI-Sp) following the guidelines of the American Academy of Orthopaedic Surgeons. Methods A cross-sectional study 80 participants with some foot pathology. A statistical analysis was made, including a correlation study with other questionnaires (the Foot Health Status Questionnaire, EuroQol 5-D, Visual Analogue Pain Scale, and the Short Form SF-12 Health Survey). Data analysis included reliability, construct and criterion-related validity and factor analyses. Results The principal components analysis with varimax rotation produced 3 principal factors that explained 80% of the variance. The confirmatory factor analysis showed an acceptable fit with a comparative fit index of 0.78. The FFI-Sp demonstrated excellent internal consistency on the three subscales: pain 0.95; disability 0.96; and activity limitation 0.69, the subscale that scored lowest. The correlation between the FFI-Sp and the other questionnaires was high to moderate. Conclusions The Spanish version of the Foot Function Index (FFI-Sp) is a tool that is a valid and reliable tool with a very good internal consistency for use in the assessment of pain, disability and limitation of the function of the foot, for use both in clinic and research.
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Background The evaluation of the hand function is an essential element within the clinical practice. The usual assessments are focus on the ability to perform activities of daily life. The inclusion of instruments to measure kinematic variables provides a new approach to the assessment. Inertial sensors adapted to the hand could be used as a complementary instrument to the traditional assessment. Material: clinimetric assessment (Upper Limb Functional Index, Quick Dash), antrophometric variables (eight and weight), dynamometry (palm preasure) was taken. Functional analysis was made with Acceleglove system for the right hand and computer system. The glove has six acceleration sensor, one on each finger and another one on the reverse palm. Method Analytic, transversal approach. Ten healthy subject made six task on evaluation table (tripod pinch, lateral pinch and tip pinch, extension grip, spherical grip and power grip). Each task was made and measure three times, the second one was analyze for the results section. A Matlab script was created for the analysis of each movement and detection phase based on module vector. Results The module acceleration vector offers useful information of the hand function. The data analysis obtained during the performance of functional gestures allows to identify five different phases within the movement, three static phase and tow dynamic, each module vector was allied to one task. Conclusion Module vector variables could be used for the analysis of the different task made by the hand. Inertial sensor could be use as a complement for the traditional assessment system.
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Control of iron homeostasis is essential for healthy central nervous system function: iron deficiency is associated with cognitive impairment, yet iron overload is thought to promote neurodegenerative diseases. Specific genetic markers have been previously identified that influence levels of transferrin, the protein that transports iron throughout the body, in the blood and brain. Here, we discovered that transferrin levels are related to detectable differences in the macro- and microstructure of the living brain. We collected brain MRI scans from 615 healthy young adult twins and siblings, of whom 574 were also scanned with diffusion tensor imaging at 4 Tesla. Fiber integrity was assessed by using the diffusion tensor imaging-based measure of fractional anisotropy. In bivariate genetic models based on monozygotic and dizygotic twins, we discovered that partially overlapping additive genetic factors influenced transferrin levels and brain microstructure. We also examined common variants in genes associated with transferrin levels, TF and HFE, and found that a commonly carried polymorphism (H63D at rs1799945) in the hemochromatotic HFE gene was associated with white matter fiber integrity. This gene has a well documented association with iron overload. Our statistical maps reveal previously unknown influences of the same gene on brain microstructure and transferrin levels. This discovery may shed light on the neural mechanisms by which iron affects cognition, neurodevelopment, and neurodegeneration.
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Diffusion weighted magnetic resonance (MR) imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of 6 directions, second-order tensors can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve crossing fiber tracts. Recently, a number of high-angular resolution schemes with greater than 6 gradient directions have been employed to address this issue. In this paper, we introduce the Tensor Distribution Function (TDF), a probability function defined on the space of symmetric positive definite matrices. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the diffusion orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function.
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Fractional anisotropy (FA), a very widely used measure of fiber integrity based on diffusion tensor imaging (DTI), is a problematic concept as it is influenced by several quantities including the number of dominant fiber directions within each voxel, each fiber's anisotropy, and partial volume effects from neighboring gray matter. With High-angular resolution diffusion imaging (HARDI) and the tensor distribution function (TDF), one can reconstruct multiple underlying fibers per voxel and their individual anisotropy measures by representing the diffusion profile as a probabilistic mixture of tensors. We found that FA, when compared with TDF-derived anisotropy measures, correlates poorly with individual fiber anisotropy, and may sub-optimally detect disease processes that affect myelination. By contrast, mean diffusivity (MD) as defined in standard DTI appears to be more accurate. Overall, we argue that novel measures derived from the TDF approach may yield more sensitive and accurate information than DTI-derived measures.
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We demonstrate a geometrically inspired technique for computing Evans functions for the linearised operators about travelling waves. Using the examples of the F-KPP equation and a Keller–Segel model of bacterial chemotaxis, we produce an Evans function which is computable through several orders of magnitude in the spectral parameter and show how such a function can naturally be extended into the continuous spectrum. In both examples, we use this function to numerically verify the absence of eigenvalues in a large region of the right half of the spectral plane. We also include a new proof of spectral stability in the appropriate weighted space of travelling waves of speed c≥sqrt(2δ) in the F-KPP equation.
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Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.
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The total entropy utility function is considered for the dual purpose of Bayesian design for model discrimination and parameter estimation. A sequential design setting is proposed where it is shown how to efficiently estimate the total entropy utility for a wide variety of data types. Utility estimation relies on forming particle approximations to a number of intractable integrals which is afforded by the use of the sequential Monte Carlo algorithm for Bayesian inference. A number of motivating examples are considered for demonstrating the performance of total entropy in comparison to utilities for model discrimination and parameter estimation. The results suggest that the total entropy utility selects designs which are efficient under both experimental goals with little compromise in achieving either goal. As such, the total entropy utility is advocated as a general utility for Bayesian design in the presence of model uncertainty.
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Interleukin-10 (IL-10) is an important immunoregulatory cytokine produced by various types of cells. Researchers describe here the isolation and characterization of olive flounder IL-10 (ofIL-10) cDNA and genomic organization. The ofIL-10 gene encodes a 187 amino acid protein and is composed of a five exon/four intron structure, similar to other known IL-10 genes. The ofIL-10 promoter sequence analysis shows a high level of homology in putative binding sites for transcription factors which are sufficient for transcriptional regulation ofIL-10. Important structural residues are maintained in the ofIL-10 protein including the four cysteines responsible for the two intra-chain disulfide bridges reported for human IL-10 and two extra cysteine residues that exist only in fish species. The phylogenetic analysis clustered ofIL-10 with other fish IL-10s and apart from mammalian IL-10 molecules. Quantitative real-time Polymerase Chain Reaction (PCR) analysis demonstrated ubiquitous ofIL-10 gene expression in the 13 tissues examined. Additionally, the induction of ofIL-10 gene expression was observed in the kidney tissue from olive flounder infected with bacteria (Edawardsiella tarda) or virus (Viral Hemorrhagic Septicemia Virus; VHSV). These data indicate that IL-10 is an important immune regulator that is conserved strictly genomic organization and function during the evolution of vertebrate immunity.