Explicit memory schemes for evolutionary algorithms in dynamic environments

Copyright @ 2007 Springer-VerlagProblem optimization in dynamic environments has atrracted a growing interest from the evolutionary computation community in reccent years due to its importance in real world optimization problems. Several approaches have been developed to enhance the performance of evolutionary algorithms for dynamic optimization problems, of which the memory scheme is a major one. This chapter investigates the application of explicit memory schemes for evolutionary algorithms in dynamic environments. Two kinds of explicit memory schemes: direct memory and associative memory, are studied within two classes of evolutionary algorithms: genetic algorithms and univariate marginal distribution algorithms for dynamic optimization problems. Based on a series of systematically constructed dynamic test environments, experiments are carried out to investigate these explicit memory schemes and the performance of direct and associative memory schemes are campared and analysed. The experimental results show the efficiency of the memory schemes for evolutionary algorithms in dynamic environments, especially when the environment changes cyclically. The experimental results also indicate that the effect of the memory schemes depends not only on the dynamic problems and dynamic environments but also on the evolutionary algorithm used

Water intoxication presenting as maternal and neonatal seizures: a case report.

Introduction We present an unusual case of fitting in the mother and newborn child, and the challenges faced in the management of their hyponatraemia due to water intoxication. Case presentation A previously well 37-year-old, primigravid Caucasian woman presented with features mimicking eclampsia during labour. These included confusion, reduced consciousness and seizures but without a significant history of hypertension, proteinuria or other features of pre-eclampsia. Her serum sodium was noted to be low at 111 mmol/litre as was that of her newborn baby. She needed anti-convulsants with subsequent intubation to stop the fitting and was commenced on a hypertonic saline infusion with frequent monitoring of serum sodium. There is a risk of long-term neurological damage from central pontine myelinolysis if the hyponatraemia is corrected too rapidly. Mother and baby went on to make a full recovery without any long-term neurological complications. Conclusion There is little consensus on the treatment of life-threatening hyponatraemia. Previous articles have outlined several possible management strategies as well as their risks. After literature review, an increase in serum sodium concentration of no more than 8–10 mmol/litre in 24 hours is felt to be safe but can be exceeded with extreme caution if life-threatening symptoms do not resolve. Formulae exist to calculate the amount of sodium needed and how much hypertonic intravenous fluid will be required to allow safer correction. We hypothesise the possible causes of hyponatraemia in this patient and underline its similarity in symptom presentation to eclampsia

On the role of different Skyrme forces and surface corrections in exotic cluster-decay

We present cluster decay studies of $^{56}$Ni$^*$ formed in heavy-ion collisions using different Skyrme forces. Our study reveals that different Skyrme forces do not alter the transfer structure of fractional yields significantly. The cluster decay half-lives of different clusters lies within \pm 10% for PCM and \pm 15% for UFM.Comment: 13 pages,6 figures and 1 table; in press Pramana Journal of Physics (2010

Relationship between temporary emotion of students and performance in learning through comparing facial expression analytics

This paper presents a study on temporary emotion of students and their performance related to learning activities. This paper elucidates different kinds of facial expressions elicited during the activities: quiz and a movie trailer with the help of existing facial expression analyzing applications. The user’s expressions are recorded as video while watching the movie trailer and doing the quiz. The video is processed by different applications which gives the score for different emotions. The results obtained are studied to find which emotion is mostly prevalent among the user in different situations. From this study, it is shown that students experience seemingly different emotions during the activity. The emotions they portrayed were confusion, sadness, anger and neutral. This study explores the use of affective computing for further comprehension of students’ emotion in learning environment

Maternal obesity increases the risk of metabolic disease and impacts renal health in offspring

© 2018 The Author(s). Obesity, together with insulin resistance, promotes multiple metabolic abnormalities and is strongly associated with an increased risk of chronic disease including type 2 diabetes (T2D), hypertension, cardiovascular disease, non-alcoholic fatty liver disease (NAFLD) and chronic kidney disease (CKD). The incidence of obesity continues to rise in astronomical proportions throughout the world and affects all the different stages of the lifespan. Importantly, the proportion of women of reproductive age who are overweight or obese is increasing at an alarming rate and has potential ramifications for offspring health and disease risk. Evidence suggests a strong link between the intrauterine environment and disease programming. The current review will describe the importance of the intrauterine environment in the development of metabolic disease, including kidney disease. It will detail the known mechanisms of fetal programming, including the role of epigenetic modulation. The evidence for the role of maternal obesity in the developmental programming of CKD is derived mostly from our rodent models which will be described. The clinical implication of such findings will also be discussed

Modelling the impact of calorie‐reduction interventions on population prevalence and inequalities in childhood obesity in the Southampton Women’s Survey

Background: In the United Kingdom, rates of childhood obesity are high and inequalities in obesity have widened in recent years. Children with obesity face heightened risks of living with obesity as adults and suffering from associated morbidities. Addressing population prevalence and inequalities in childhood obesity is a key priority for public health policymakers in the United Kingdom and elsewhere. Where randomized controlled trials are not possible, potential policy actions can be simulated using causal modeling techniques. Objectives: Using data from the Southampton Women's Survey (SWS), a cohort with high quality dietary and lifestyle data, the potential impact of policy-relevant calorie-reduction interventions on population prevalence and inequalities of childhood obesity was investigated. Methods: Predicted probabilities of obesity (using UK90 cut-offs) at age 6–7 years were estimated from logistic marginal structural models adjusting for observed calorie consumption at age 3 years (using food diaries) and confounding. A series of policy-relevant intervention scenarios were modeled to simulate reductions in energy intake (differing in effectiveness, the targeting mechanisms, and level of uptake). Results: At age 6–7 years, 8.3% of children were living with obesity, after accounting for observed energy intake and confounding. A universal intervention to lower median energy intake to the estimated average requirement (a 13% decrease), with an uptake of 75%, reduced obesity prevalence by 1% but relative and absolute inequalities remained broadly unchanged. Conclusions: Simulated interventions substantially reduced population prevalence of obesity, which may be useful in informing policymakers

Outcome of renal grafts after simultaneous kidney/ pancreas transplantation

Nineteen patients with endstage renal failure due to Type 1 (insulin-dependent) diabetes mellitus received simultaneous pancreas/kidney transplants using bladder drainage technique. Another group of 25 Type 1 diabetic patients received pancreas/kidney transplants by the duct occlusion technique. We observed a higher incidence of rejection episodes in the patients of the bladder drainage group than those in the duct occlusion group, 14 of 19 patients (74%) vs 7 of 25 (28%) respectively. Anti CD3 antibodies (Orthoclone, OKT3) as a part of induction treatment was used more often in the bladder drainage group (58%) than in the control group (20%)

Eudaimonistic Argumentation

Virtue theories have lately enjoyed a modest vogue in the study of argumentation, echoing the success of more far-reaching programmes in ethics and epistemology. Virtue theories of argumentation (VTA) comprise several conceptually distinct projects, including the provision of normative foundations for argument evaluation and a renewed focus on the character of good arguers. Perhaps the boldest of these is the pursuit of the fully satisfying argument, the argument that contributes to human flourishing. This project has an independently developed epistemic analogue: eudaimonistic virtue epistemology. Both projects stress the importance of widening the range of cognitive goals beyond, respectively, cogency and knowledge; both projects emphasize social factors, the right sort of community being indispensable for the cultivation of the intellectual virtues necessary to each project. This paper proposes a unification of the two projects by arguing that the intellectual good life sought by eudaimonistic virtue epistemologists is best realized through the articulation of an account of argumentation that contributes to human flourishing

Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off

Bundling of graph edges (node-to-node connections) is a common technique to enhance visibility of overall trends in the edge structure of a large graph layout, and a large variety of bundling algorithms have been proposed. However, with strong bundling, it becomes hard to identify origins and destinations of individual edges. We propose a solution: we optimize edge coloring to differentiate bundled edges. We quantify strength of bundling in a flexible pairwise fashion between edges, and among bundled edges, we quantify how dissimilar their colors should be by dissimilarity of their origins and destinations. We solve the resulting nonlinear optimization, which is also interpretable as a novel dimensionality reduction task. In large graphs the necessary compromise is whether to differentiate colors sharply between locally occurring strongly bundled edges ("local bundles"), or also between the weakly bundled edges occurring globally over the graph ("global bundles"); we allow a user-set global-local tradeoff. We call the technique "peacock bundles". Experiments show the coloring clearly enhances comprehensibility of graph layouts with edge bundling.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016