User Attribution Through Keystroke Dynamics-Based Author Age Estimation

Keystroke dynamics analysis has often been used in user authentication. In this work, it is used to classify users according to their age. The authors have extended their previous research in which they managed to identify the age group that a user belongs to with an accuracy of 66.1%. The main changes made were the use of a larger dataset, which resulted from a new volunteer recording phase, the exploitation of more keystroke dynamics features, and the use of a procedure for selecting those features that can best distinguish users according to their age. Five machine learning models were used for the classification, and their performance in relation to the number of features involved was tested. As a result of these changes in the research method, an improvement in the performance of the proposed system has been achieved. The accuracy of the improved system is 89.7%

Small molecule activators of SIRT1 replicate signaling pathways triggered by calorie restriction in vivo

<p>Abstract</p> <p>Background</p> <p>Calorie restriction (CR) produces a number of health benefits and ameliorates diseases of aging such as type 2 diabetes. The components of the pathways downstream of CR may provide intervention points for developing therapeutics for treating diseases of aging. The NAD⁺-dependent protein deacetylase SIRT1 has been implicated as one of the key downstream regulators of CR in yeast, rodents, and humans. Small molecule activators of SIRT1 have been identified that exhibit efficacy in animal models of diseases typically associated with aging including type 2 diabetes. To identify molecular processes induced in the liver of mice treated with two structurally distinct SIRT1 activators, SIRT501 (formulated resveratrol) and SRT1720, for three days, we utilized a systems biology approach and applied Causal Network Modeling (CNM) on gene expression data to elucidate downstream effects of SIRT1 activation.</p> <p>Results</p> <p>Here we demonstrate that SIRT1 activators recapitulate many of the molecular events downstream of CR <it>in vivo</it>, such as enhancing mitochondrial biogenesis, improving metabolic signaling pathways, and blunting pro-inflammatory pathways in mice fed a high fat, high calorie diet.</p> <p>Conclusion</p> <p>CNM of gene expression data from mice treated with SRT501 or SRT1720 in combination with supporting <it>in vitro </it>and <it>in vivo </it>data demonstrates that SRT501 and SRT1720 produce a signaling profile that mirrors CR, improves glucose and insulin homeostasis, and acts via SIRT1 activation <it>in vivo</it>. Taken together these results are encouraging regarding the use of small molecule activators of SIRT1 for therapeutic intervention into type 2 diabetes, a strategy which is currently being investigated in multiple clinical trials.</p

Experimental and numerical study of cemented bone-implant interface behavior

Although the total hip replacement (THR) is a long-proven method of surgical treatment of diseases and disorders of the human hip, the surgery brings some risk of long-term instability of the joint. The aim of the research was to investigate the cemented bone-implant interface behavior. The main problems (cement layer degradation and bone-cement interface debonding) during physiological loading conditions have been investigated using a custom hip simulator. The experimental setup was designed to allow cyclic loading of the sample of pelvic bone with implanted cemented acetabular component. The hip contact force of required direction and magnitude was applied to the implant using a spherical femoral component head. The most unfavorable activity (downstairs walking) was simulated. The process of damage accumulation in the fixation was monitored by repeated scanning using high resolution micro Computed Tomography (µCT). Use of micro-focus source and large high-resolution flat panel detector allows investigation of structural changes and crack propagation both in the cement layer and the trabecular bone

Functionally Compatible Local Characteristics for the Local Specification of Priors in Graphical Models

The local specification of priors in non-decomposable graphical models does not necessarily yield a proper joint prior for all the parameters of the model. Using results concerning general exponential families with cuts, we derive specific results for the multivariate Gamma distribution (conjugate prior for Poisson counts) and the Wishart distribution (conjugate prior for Gaussian models). These results link the existence of a locally specified joint prior to the solvability of a related marginal problem over the cliques of the graph. Copyright 2007 Board of the Foundation of the Scandinavian Journal of Statistics..