Estimating and reducing the memory requirements of signal processing codes for embedded systems

Most embedded systems have limited amount of memory. In contrast, the memory requirements of the digital signal processing (DSP) and video processing codes (in nested loops, in particular) running on embedded systems is significant. This paper addresses the problem of estimating and reducing the amount of memory needed for transfers of data in embedded systems. First, the problem of estimating the region associated with a statement or the set of elements referenced by a statement during the execution of nested loops is analyzed. For a fixed execution ordering, a quantitative analysis of the number of elements referenced is presented; exact expressions for uniformly generated references and a close upper and lower bound for nonuniformly generated references are derived. Second, in addition to presenting an algorithm that computes the total memory required, this paper also discusses the effect of transformations (that change the execution ordering) on the lifetimes of array variables, i.e., the time between the first and last accesses to a given array location. The term maximum window size is introduced, and quantitative expressions are derived to compute the maximum window size. A detailed analysis of the effect of unimodular transformations on data locality, including the calculation of the maximum window size, is presented.     

Reliability models for computer systems: An overview including dataflow graphs

The reliability of a system is the probability that the system will perform its intended mission under given conditions. This paper provides an overview of the approaches to reliability modelling and identifies their strengths and weaknesses. The models discussed include structure models, simple stochastic models and decomposable stochastic models. Ignoring time-dependence, structure models give reliability as a function of the topological structure of the system. Simple stochastic models make direct use of the properties of underlying stochastic processes, while decomposable models consider more complex systems and analyse them through subsystems. Petri nets and dataflow graphs facilitate the analysis of complex systems by providing a convenient framework for reliability analysis.     

Neural correlates of sexual arousal in homosexual and heterosexual men.

Men exhibit much higher levels of genital and subjective arousal to sexual stimuli containing their preferred sex than they do to stimuli containing only the nonpreferred sex. This study used event-related functional magnetic resonance imaging to investigate how this category-specific pattern would be reflected in the brains of homosexual (n = 11) and heterosexual (n = 11) men. Comparisons of activation to preferred sexual stimuli, nonpreferred sexual stimuli, and sports stimuli revealed large networks correlated with sexual arousal, spanning multiple cortical and subcortical areas. Both homosexual and heterosexual men exhibited category-specific arousal in brain activity. Within the amygdala, greater preference-related activity was observed in homosexual men, but it is unclear whether this is a cause or a consequence of their sexuality. In a subsequent analysis of regions hypothesized to support arousal, both participant groups demonstrated widespread increases in evoked activity for preferred stimuli. Aggregate data from these regions produced significant differences between stimulus types in 16 out of 22 participants. Significant activational differences matched reported sexual orientation in 15 of these 16 participants, representing an advance in psychophysiological measures of arousal. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Automating the identification and analysis of protein {beta}-barrels

ßBarrels are widespread and well-studied featuresof a great many protein structures. In this paper an unsuper-visedmethod for the detection of P-barrels is developed based ontechniques from graph theory. The hydrogen bonded connectivityof ß-sheets is derived using standard pattern recognitiontechniques and expressed as a graph. Barrels correspond to topologicalrings in these connectivity graphs and can thus be identifiedusing ring perception algorithms. Following from this, the characteristictopological structure of a barrel can be expressed using a novelform of reduced nomenclature that counts sequence separationsbetween successive members of the ring set These techniquesare tested by applying them to the detection of barrels in anon-redundant subset of the Brookhaven database. Results indicatethat topological rings do seem to correspond uniquely to ß-barrelsand that the technique, as implemented, finds the majority ofbarrels present in the dataset.     

External-Memory Algorithms for Processing Line Segments in Geographic Information Systems

In the design of algorithms for large-scale applications it is essential to consider the problem of minimizing I/O communication. Geographical information systems (GIS) are good examples of such large-scale applications as they frequently handle huge amounts of spatial data. In this paper we develop efficient external-memory algorithms for a number of important problems involving line segments in the plane, including trapezoid decomposition, batched planar point location, triangulation, red--blue line segment intersection reporting, and general line segment intersection reporting. In GIS systems the first three problems are useful for rendering and modeling, and the latter two are frequently used for overlaying maps and extracting information from them.     

Adenosine A1 receptor stimulation antagonizes the negative inotropic effects of the PKC activator dioctanoylglycerol

It has been suggested that adenosine cardioprotection occurs via adenosine A1 receptor-mediated activation of protein kinase C (PKC). However, adenosine has well-known vasodilatory effects in the myocardium, whereas PKC is a vasoconstrictor. This study examined whether adenosine A1 receptor activation alters the effects of the PKC activator. 1,2-dioctanoyl-s,n-glycerol (DOG) in isolated perfused rat hearts (left-ventricular developed pressure) and rat ventricular myocytes ([Ca2+]i and cell shortening). Exposure to DOG decreased left-ventricular developed pressure by 30%, an effect that was completely reversible. Pretreatment of isolated hearts with either the PKC inhibitor chelerythrine or the adenosine A1 agonist 2-chloro-N6-cyclo-cyclo-isolated pentlyadenosine (CCPA) attenuated the negative inotropic effects of DOG. In the isolated myocytes, DOG decreased [Ca2+]i and cell shortening by 25 and 28%, respectively, effects that were attenuated by both chelerythrine and CCPA. The CCPA attenuation of the DOG-induced decrease in [Ca2+]i and cell shortening was blocked by pretreating the myocytes with the adenosine A1 antagonist, 8-cyclopentyl-1,3-dipropylxanthine (DPCPX). These results indicate that in rat ventricular myocardium, adenosine A1 receptor activation attenuates the apparent PKC-dependent negative inotropic effects of DOG via preservation of [Ca2+]i levels.     

The effects of stress on memory and the hippocampus throughout the life cycle: implications for childhood development and aging

Studies in animals showing hippocampal atrophy and associated memory deficits in stress and aging have implications for stress and aging in humans. Clinical studies in traumatized human populations with posttraumatic stress disorder (PTSD) have replicated studies in animals, showing reduction in volume of the hippocampus measured with magnetic resonance imaging and associated memory deficits. Trauma at different stages of development (early childhood abuse versus trauma in later life due to combat) may influence the nature of memory deficits and hippocampal atrophy. Studies in aging human subjects are consistent with animal studies, although future research is needed in this area. The similarities between biological findings related to cortisol and the hippocampus in stress and aging in both animal and human studies raises the question of whether PTSD can be seen as a form of accelerated aging. Evidence that stress affects the hippocampus and the capacity for learning has broad implications for public health policy, underlying the need for additional resources in this important area and a reexamination of our understanding of factors influencing academic achievement.