53 resultados para Exponential and trigonometrical octoniônic functions


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Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher’s equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations.

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Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.

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Biomolecules are chemical compounds found in living organisms which are the building blocks of life and perform important functions. Fluctuation from the normal concentration of these biomolecules in living system leads to several disorders. Thus the exact determination of them in human fluids is essential in the clinical point of view. High performance liquid chromatography, flow injection analysis, capillary electrophoresis, fluorimetry, spectrophotometry, electrochemical and chemiluminescence techniques were usually used for the determination of biologically important molecules. Among these techniques, electrochemical determination of biomolecules has several advantages over other methods viz., simplicity, selectivity and sensitivity. In the past two decades, electrodes modified with polymer films, self-assembled monolayers containing different functional groups and carbon paste have been used as electrochemical sensors. But in recent years, nanomaterials based electrochemical sensors play an important role in the improvement of public health because of its rapid detection, high sensitivity and specificity in clinical diagnostics. To date gold nanoparticles (AuNPs) have received arousing attention mainly due to their fascinating electronic and optical properties as a consequence of their reduced dimensions. These unique properties of AuNPs make them as an ideal candidate for the immobilization of enzymes for biosensing. Further, the electrochemical properties of AuNPs reveal that they exhibit interesting properties by enhancing the electrode conductivity, facilitating electron transfer and improving the detection limit of biomolecules. In this chapter, we summarized the different strategies used for the attachment of AuNPs on electrode surfaces and highlighted the electrochemical determination of glucose, ascorbic acid (AA), uric acid (UA) and dopamine derivatives using the AuNPs modified electrodes.

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We propose and mathematically examine a theory of calcium profile formation in unwounded mammalian epidermis based on: changes in keratinocyte proliferation, fluid and calcium exchange with the extracellular fluid during these cells' passage through the epidermal sublayers, and the barrier functions of both the stratum corneum and tight junctions localised in the stratum granulosum. Using this theory, we develop a mathematical model that predicts epidermal sublayer transit times, partitioning of the epidermal calcium gradient between intracellular and extracellular domains, and the permeability of the tight junction barrier to calcium ions. Comparison of our model's predictions of epidermal transit times with experimental data indicates that keratinocytes lose at least 87% of their volume during their disintegration to become corneocytes. Intracellular calcium is suggested as the main contributor to the epidermal calcium gradient, with its distribution actively regulated by a phenotypic switch in calcium exchange between keratinocytes and extracellular fluid present at the boundary between the stratum spinosum and the stratum granulosum. Formation of the extracellular calcium distribution, which rises in concentration through the stratum granulosum towards the skin surface, is attributed to a tight junction barrier in this sublayer possessing permeability to calcium ions that is less than 15 nm/s in human epidermis and less than 37 nm/s in murine epidermis. Future experimental work may refine the presented theory and reduce the mathematical uncertainty present in the model predictions.

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The forthcoming NIST’s Advanced Hash Standard (AHS) competition to select SHA-3 hash function requires that each candidate hash function submission must have at least one construction to support FIPS 198 HMAC application. As part of its evaluation, NIST is aiming to select either a candidate hash function which is more resistant to known side channel attacks (SCA) when plugged into HMAC, or that has an alternative MAC mode which is more resistant to known SCA than the other submitted alternatives. In response to this, we perform differential power analysis (DPA) on the possible smart card implementations of some of the recently proposed MAC alternatives to NMAC (a fully analyzed variant of HMAC) and HMAC algorithms and NMAC/HMAC versions of some recently proposed hash and compression function modes. We show that the recently proposed BNMAC and KMDP MAC schemes are even weaker than NMAC/HMAC against the DPA attacks, whereas multi-lane NMAC, EMD MAC and the keyed wide-pipe hash have similar security to NMAC against the DPA attacks. Our DPA attacks do not work on the NMAC setting of MDC-2, Grindahl and MAME compression functions.

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We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

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Human genetic and animal studies have implicated the costimulatory molecule CD40 in the development of multiple sclerosis (MS). We investigated the cell specific gene and protein expression variation controlled by the CD40 genetic variant(s) associated with MS, i.e. the T-allele at rs1883832. Previously we had shown that the risk allele is expressed at a lower level in whole blood, especially in people with MS. Here, we have defined the immune cell subsets responsible for genotype and disease effects on CD40 expression at the mRNA and protein level. In cell subsets in which CD40 is most highly expressed, B lymphocytes and dendritic cells, the MS-associated risk variant is associated with reduced CD40 cell-surface protein expression. In monocytes and dendritic cells, the risk allele additionally reduces the ratio of expression of full-length versus truncated CD40 mRNA, the latter encoding secreted CD40. We additionally show that MS patients, regardless of genotype, express significantly lower levels of CD40 cell-surface protein compared to unaffected controls in B lymphocytes. Thus, both genotype-dependent and independent down-regulation of cell-surface CD40 is a feature of MS. Lower expression of a co-stimulator of T cell activation, CD40, is therefore associated with increased MS risk despite the same CD40 variant being associated with reduced risk of other inflammatory autoimmune diseases. Our results highlight the complexity and likely individuality of autoimmune pathogenesis, and could be consistent with antiviral and/or immunoregulatory functions of CD40 playing an important role in protection from MS. © 2015 Field et al.

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OBJECTIVE: The study of ethnically homogeneous populations may help to identify schizophrenia risk loci. The authors conducted a genomewide linkage scan for schizophrenia in an Indian population. METHOD: Participants were 441 individuals (262 affected probands and siblings) who were recruited primarily from one ethnically homogeneous group, the Tamil Brahmin caste, although individuals from other geographically proximal castes also participated. Genotyping of 124 affected sibling pair pedigrees was performed with 402 short tandem repeat polymorphisms. Linkage analyses were conducted using nonparametric exponential LOD (logarithm of the odds ratio for linkage) scores and parametric heterogeneity LOD scores. Parametric heterogeneity scores were calculated using simple dominant and recessive models, correcting for multiple statistics. The data were examined for evidence of consanguinity. Genomewide significance levels were determined using 10,000 gene dropping simulations. RESULTS: These findings revealed genomewide significant linkage to chromosome 1p31.1, through the use of both exponential and heterogeneity LOD scores, incorporating correction for multiple statistics and mild consanguinity. The estimated sibling recurrence risk associated with this putative locus was 1.95. Analysis for heterogeneity LOD scores also detected suggestive linkage to chromosomes 13q22.1 and 16q12.2. Using 117 tag single nucleotide polymorphisms (SNPs), family-based association analyses of phosphodiesterase 4B (PDE4B), the closest schizophrenia candidate gene, detected no convincing evidence of association, suggesting that the chromosome 1 peak represents a novel risk locus. CONCLUSIONS: This is the first study-to the authors' knowledge-to report significant linkage of schizophrenia to chromosome 1p31.1. Further investigation of this chromosome region in diverse populations is warranted to identify underlying sequence variants.