Atom-Aid: Detecting and Surviving Atomicity Violations

Hardware can play a significant role in improving reliability of multithreaded software. Recent architectural proposals arbitrarily group consecutive dynamic memory operations into atomic blocks to enforce coarse-grained memory ordering, providing implicit atomicity. The authors of this article observe that implicit atomicity probabilistically hides atomicity violations by reducing the number of interleaving opportunities between memory operations. They propose Atom-Aid, which creates implicit atomic blocks intelligently instead of arbitrarily, dramatically reducing the probability that atomicity violations will manifest themselves.     

A Kleene–Schützenberger theorem for weighted timed automata

During the last years, weighted timed automata have received much interest in the real-time community. Weighted timed automata form an extension of timed automata and allow us to assign weights (costs) to both locations and edges. This model, introduced by Alur et al. (2001) and Behrmann et al. (2001), permits the treatment of continuous consumption of resources and has led to much research on scheduling problems, optimal reachability and model checking. Also, several authors have derived Kleene-type characterizations of (unweighted) timed automata and their accepted timed languages. The goal of this paper is to provide a characterization of the behaviours of weighted timed automata by rational power series. We define weighted timed automata with weights taken in an arbitrary semiring, resulting in a model that subsumes several weighted timed automata concepts of the literature. For our main result, we combine the methods of Schützenberger, a recent approach for a Kleene-type theorem for unweighted timed automata by Bouyer and Petit as well as new techniques. Our main result also implies Kleene-type theorems for several subclasses of weighted timed automata investigated before, e.g., for timed automata and timed automata with stopwatch observers.     

Artificial Agent Action in Markets

We summarise our experiences of a number of demonstrators and simulation experiments designed to test the feasibility of using artificial decision making agents in real-time domains, and comment on the significance of our results to autonomous artificial agent action patterns in markets. Our main hypothesis is that the use of norms can extend the capability of artificial decision makers beyond what is obtained from implementing individual utility maximizers in keeping with rational choice theory.     

Proteomic studies in animal models of diabetes

The aim of this review is to provide an overview of proteomic studies in animal models of diabetes and to give some insight into the different methods available today in the rapidly developing field of proteomics. A summary of 31 papers published between 1997 and 2007 is presented. For instance, proteomics has been used to study the development of both type 1 and type 2 diabetes, diabetic complications in tissues like heart, kidney and retina and changes after treatment with anti-diabetic drugs like peroxisome proliferator-activated receptors agonists. Together, these studies give a good overview of a number of experimental approaches. Proteomics holds the promise of providing major contributions to the field of diabetes research. However, to achieve this, a number of issues need to be resolved. Appropriate data representation to facilitate data comparison, exchange, and verification is required, as well as improved statistical assessment of proteomic experiments. In addition, it is important to follow up the results with functional studies to be able to make biologically relevant conclusions. The potential of proteomics to dissect complex human disorders is now beginning to be realized. In the future, this will result in new important information concerning diabetes.     

Computer use in older adults: Determinants and the relationship with cognitive change over a 6 year episode

Cognitively challenging activities may support the mental abilities of older adults. The use of computers and the Internet provides divergent cognitive challenges to older persons, and in previous studies, positive effects of computer and Internet use on the quality of life have been demonstrated. The present study addresses two research aims regarding predictors of computer use and the relationship between computer use and changes in cognitive abilities over a 6-year period in both younger (24-49 years) and older adults (older than 50 years). Data were obtained from an ongoing study into cognitive aging: the Maastricht Aging Study, involving 1823 normal aging adults who were followed for 9 years. The results showed age-related differences in predictors of computer use: the only predictor in younger participants was level of education, while in older participants computer use was also predicted by age, sex and feelings of loneliness. Protective effects of computer use were found for measures of selective attention and memory, in both older and younger participants. Effect sizes were small, which suggests that promotion of computer activities in older adults to prevent cognitive decline may not be an efficient strategy.     

Reducing Playground Bullying and Supporting Beliefs: An Experimental Trial of the Steps to Respect Program.

Six schools were randomly assigned to a multilevel bullying intervention or a control condition. Children in Grades 3-6 (N=1,023) completed pre- and posttest surveys of behaviors and beliefs and were rated by teachers. Observers coded playground behavior of a random subsample (n=544). Hierarchical analyses of changes in playground behavior revealed declines in bullying and argumentative behavior among intervention-group children relative to control-group children, increases in agreeable interactions, and a trend toward reduced destructive bystander behavior. Those in the intervention group reported enhanced bystander responsibility, greater perceived adult responsiveness, and less acceptance of bullying/aggression than those in the control group. Self-reported aggression did not differ between the groups. Implications for future research on the development and prevention of bullying are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Extraction of Algal Lipids and Their Analysis by HPLC and Mass Spectrometry

Algae are a promising source of biofuel but claims about their lipid content can be ambiguous because extraction methods vary and lipid quantitation often does not distinguish between particular lipid classes. Here we compared methods for the extraction of algal lipids and showed that 2-ethoxyethanol (2-EE) provides superior lipid recovery (>150–200 %) compared to other common extraction solvents such as chloroform:methanol or hexane. Extractions of wet and dry algal biomass showed that 2-EE was more effective at extracting lipids from wet rather than dried algal pellets. To analyze lipid content we used normal-phase HPLC with parallel quantitation by an evaporative light scattering detector and a mass spectrometer. Analysis of crude lipid extracts showed that all major lipid classes could be identified and quantified and revealed a surprisingly large amount of saturated hydrocarbons (HC). This HC fraction was isolated from extracts of bioreactor-grown algae and further analyzed by HPLC/MS, NMR, and GC/MS. The results showed that the sample consisted of a mixture of saturated, straight- and branched-chain HC of different chain lengths. These algal HC could represent an alternative biofuel to triacylglycerols (TAG) that could feed directly into the current petroleum infrastructure.