Virtualization for cost-effective teaching of assembly language programming

A virtual system that emulates an ARM-based processor machine has been created to replace a traditional hardware-based system for teaching assembly language. The proposed virtual system integrates, in a single environment, all the development tools necessary to deliver introductory or advanced courses on modern assembly language programming. The virtual system runs a Linux operating system in either a graphical or console mode on a Windows or Linux host machine. No software licenses or extra hardware are required to use the virtual system, thus students are free to carry their own ARM emulator with them on a USB memory stick. Institutions adopting this, or a similar virtual system, can also benefit by reducing capital investment in hardware-based development kits and enable distance learning courses.

A scalable expressive ensemble learning using Random Prism: a MapReduce approach

The induction of classification rules from previously unseen examples is one of the most important data mining tasks in science as well as commercial applications. In order to reduce the influence of noise in the data, ensemble learners are often applied. However, most ensemble learners are based on decision tree classifiers which are affected by noise. The Random Prism classifier has recently been proposed as an alternative to the popular Random Forests classifier, which is based on decision trees. Random Prism is based on the Prism family of algorithms, which is more robust to noise. However, like most ensemble classification approaches, Random Prism also does not scale well on large training data. This paper presents a thorough discussion of Random Prism and a recently proposed parallel version of it called Parallel Random Prism. Parallel Random Prism is based on the MapReduce programming paradigm. The paper provides, for the first time, novel theoretical analysis of the proposed technique and in-depth experimental study that show that Parallel Random Prism scales well on a large number of training examples, a large number of data features and a large number of processors. Expressiveness of decision rules that our technique produces makes it a natural choice for Big Data applications where informed decision making increases the user’s trust in the system.

A parallel formulation for the simulation of a generic branch predictor

A parallel formulation for the simulation of a branch prediction algorithm is presented. This parallel formulation identifies independent tasks in the algorithm which can be executed concurrently. The parallel implementation is based on the multithreading model and two parallel programming platforms: pthreads and Cilk++. Improvement in execution performance by up to 7 times is observed for a generic 2-bit predictor in a 12-core multiprocessor system.

Want to block earworms from conscious awareness?B(u)y gum!

Three experiments examine the role of articulatory motor planning in experiencing an involuntary musical recollection (an “earworm”). Experiment 1 shows that interfering with articulatory motor programming by chewing gum reduces both the number of voluntary and the number of involuntary—unwanted—musical thoughts. This is consistent with other findings that chewing gum interferes with voluntary processes such as recollections from verbal memory, the interpretation of ambiguous auditory images, and the scanning of familiar melodies, but is not predicted by theories of thought suppression, which assume that suppression is made more difficult by concurrent tasks or cognitive loads. Experiment 2 shows that chewing the gum affects the experience of “hearing” the music and cannot be ascribed to a general effect on thinking about a tune only in abstract terms. Experiment 3 confirms that the reduction of musical recollections by chewing gum is not the consequence of a general attentional or dual-task demand. The data support a link between articulatory motor programming and the appearance in consciousness of both voluntary and unwanted musical recollections.

Sex differences in the programming effects of prenatal stress on psychopathology and stress responses: an evolutionary perspective

There is strong evidence from animal studies that prenatal stress has different effects on male and female offspring. In general, although not always, prenatal stress increases anxiety, depression and stress responses, both hypothalamic–pituitary–adrenal and cardiovascular, in female offspring rather than in male. Males are more likely to show learning and memory deficits. There have been few studies so far in humans which differentiate effects of prenatal stress on male and female psychopathology. Some studies support the animal models, but the evidence is inconsistent. The mediating mechanisms for any sex specific effects are little understood, but there is evidence that placental function can differ depending on the sex of the fetus. We suggest that there may be an evolutionary reason for any sex differences in the long term effects of prenatal stress. In a stressful environment it may be adaptive for females, who are more likely to stay in one place and look after children, to be more vigilant, alert to danger and thus show more stress responsiveness. This can give rise to a more anxious or depressed phenotype. With males it may be more adaptive to go out and explore new environments, compete with other males, and be more aggressive. For this it may help to be less responsive to external stressors. More research is needed into sex differences in the effects of prenatal stress in humans, to test these ideas.

Evidence for sex differences in fetal programming of physiological stress reactivity in infancy

Associations between low birth weight and prenatal anxiety and later psychopathology may arise from programming effects likely to be adaptive under some, but not other, environmental exposures and modified by sex differences. If physiological reactivity, which also confers vulnerability or resilience in an environment-dependent manner, is associated with birth weight and prenatal anxiety, it will be a candidate to mediate the links with psychopathology. From a general population sample of 1,233 first-time mothers recruited at 20 weeks gestation, a sample of 316 stratified by adversity was assessed at 32 weeks and when their infants were aged 29 weeks (N = 271). Prenatal anxiety was assessed by self-report, birth weight from medical records, and vagal reactivity from respiratory sinus arrhythmia during four nonstressful and one stressful (still-face) procedure. Lower birth weight for gestational age predicted higher vagal reactivity only in girls (interaction term, p = .016), and prenatal maternal anxiety predicted lower vagal reactivity only in boys (interaction term, p = .014). These findings are consistent with sex differences in fetal programming, whereby prenatal risks are associated with increased stress reactivity in females but decreased reactivity in males, with distinctive advantages and penalties for each sex.

Maternal antenatal anxiety, postnatal stroking and emotional problems in children: outcomes predicted from pre and postnatal programming hypotheses

Background Mothers' self-reported stroking of their infants over the first weeks of life modifies the association between prenatal depression and physiological and emotional reactivity at 7 months, consistent with animal studies of the effects of tactile stimulation. We now investigate whether the effects of maternal stroking persist to 2.5 years. Given animal and human evidence for sex differences in the effects of prenatal stress we compare associations in boys and girls. Method From a general population sample of 1233 first-time mothers recruited at 20 weeks gestation we drew a random sample of 316 for assessment at 32 weeks, stratified by reported inter-partner psychological abuse, a risk indicator for child development. Of these mothers, 243 reported at 5 and 9 weeks how often they stroked their infants, and completed the Child Behavior Checklist (CBCL) at 2.5 years post-delivery. Results There was a significant interaction between prenatal anxiety and maternal stroking in the prediction of CBCL internalizing (p = 0.001) and anxious/depressed scores (p < 0.001). The effects were stronger in females than males, and the three-way interaction prenatal anxiety × maternal stroking × sex of infant was significant for internalizing symptoms (p = 0.003). The interactions arose from an association between prenatal anxiety and internalizing symptoms only in the presence of low maternal stroking. Conclusions The findings are consistent with stable epigenetic effects, many sex specific, reported in animal studies. While epigenetic mechanisms may be underlying the associations, it remains to be established whether stroking affects gene expression in humans.

Fetal programming of adipose tissue function: an evolutionary perspective

Obesity is an escalating threat of pandemic proportions and has risen to such unrivaled prominence in such a short period of time that it has come to define a whole generation in many countries around the globe. The burden of obesity, however, is not equally shared among the population, with certain ethnicities being more prone to obesity than others, while some appear to be resistant to obesity altogether. The reasons behind this ethnic basis for obesity resistance and susceptibility, however, have remained largely elusive. In recent years, much evidence has shown that the level of brown adipose tissue thermogenesis, which augments energy expenditure and is negatively associated with obesity in both rodents and humans, varies greatly between ethnicities. Interestingly, the incidence of low birth weight, which is associated with an increased propensity for obesity and cardiovascular disease in later life, has also been shown to vary by ethnic background. This review serves to reconcile ethnic variations in BAT development and function with ethnic differences in birth weight outcomes to argue that the variation in obesity susceptibility between ethnic groups may have its origins in the in utero programming of BAT development and function as a result of evolutionary adaptation to cold environments.

Young Children's Ability to Engage in Cognitive Therapy Tasks: Associations With Age and Educational Experience

Abstract. In two linked studies we examined children’s performance on tasks required for participation in cognitive therapy. In Study 1 we piloted some new tasks with children aged 5 to 11 years. In study 2 the effects of IQ, age and educational experience were examined in children aged 5 to 7 years. In study 1, 14 children aged 5 to 11 completed three tasks related to cognitive therapy; generating post-event attributions, naming emotions, and linking thoughts and feelings. Study 2 used a between-subjects design in which 72 children aged 5, 6, or 7 years from two primary schools completed the three tasks and the Block Design and Vocabulary sub-tests from the WISC III or WPPSI-R. Children were tested individually during the school day. All measures were administered on the same occasion. In study 2 administration order of the cognitive therapy task and the WISC III/WPPSI-R were randomized. The majority of children demonstrated some ability on each of the three tasks. In study 2, performance was associated with school and with IQ but not with age. There were no gender differences. Children attending a school with an integrated thinking skills programme and those with a higher 1Q were more successful on the cognitive therapy tasks. These results suggest that many young children could engage in cognitive therapy given age-appropriate materials. The effects of training in relevant meta-cognitive skills on children’s ability to use concepts in CBT may warrant further research. Keywords: Cognitive behaviour therapy, young children, cognitive development

Enzymatically-triggered, isothermally responsive polymers: re-programming poly(oligoethylene glycols) to respond to phosphatase

Polymers which can respond to externally applied stimuli have found much application in the biomedical field due to their (reversible) coil–globule transitions. Polymers displaying a lower critical solution temperature are the most commonly used, but for blood-borne (i.e., soluble) biomedical applications the application of heat is not always possible, nor practical. Here we report the design and synthesis of poly(oligoethylene glycol methacrylate)-based polymers whose cloud points are easily varied by alkaline phosphatase-mediated dephosphorylation. By fine-tuning the density of phosphate groups on the backbone, it was possible to induce an isothermal transition: A change in solubility triggered by removal of a small number of phosphate esters from the side chains activating the LCST-type response. As there was no temperature change involved, this serves as a model of a cell-instructed polymer response. Finally, it was found that both polymers were non cytotoxic against MCF-7 cells (at 1 mg·mL–1), which confirms promise for biomedical applications.

Using computers to teach people with intellectual disabilities to perform some of the tasks used within cognitive behavioural therapy: a randomised experiment

Aims Training has been shown to improve the ability of people with intellectual disabilities (IDs) to perform some cognitive behavioural therapy (CBT) tasks. This study used a computerised training paradigm with the aim of improving the ability of people with IDs to: a) discriminate between behaviours, thoughts and feelings, and b) link situations, thoughts and feelings. Methods Fifty-five people with mild-to-moderate IDs were randomly assigned to a training or attention-control condition in a single-blind mixed experimental design. Computerised tasks assessed the participants’ skills in: (a) discriminating between behaviours, thoughts and feelings (separately and pooled together), and (b) cognitive mediation by selecting appropriate emotions as consequences to given thoughts, and appropriate thoughts as mediators of given emotions. Results Training significantly improved ability to discriminate between behaviours, thoughts and feelings pooled together, compared to the attention-control condition, even when controlling for baseline scores and IQ. Large within-group improvements in the ability to identify behaviours and feelings were observed for the training condition, but not the attention-control group. There were no significant between-group differences in ability to identify thoughts, or on cognitive mediation skills. Conclusions A single session of computerised training can improve the ability of people with IDs to understand and practise CBT tasks relating to behaviours and feelings. There is potential for computerised training to be used as a “primer” for CBT with people with IDs to improve engagement and outcomes, but further development on a specific computerised cognitive mediation task is needed.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.