Adaptive primal-dual genetic algorithms in dynamic environments

This article is placed here with permission of IEEE - Copyright @ 2010 IEEERecently, there has been an increasing interest in applying genetic algorithms (GAs) in dynamic environments. Inspired by the complementary and dominance mechanisms in nature, a primal-dual GA (PDGA) has been proposed for dynamic optimization problems (DOPs). In this paper, an important operator in PDGA, i.e., the primal-dual mapping (PDM) scheme, is further investigated to improve the robustness and adaptability of PDGA in dynamic environments. In the improved scheme, two different probability-based PDM operators, where the mapping probability of each allele in the chromosome string is calculated through the statistical information of the distribution of alleles in the corresponding gene locus over the population, are effectively combined according to an adaptive Lamarckian learning mechanism. In addition, an adaptive dominant replacement scheme, which can probabilistically accept inferior chromosomes, is also introduced into the proposed algorithm to enhance the diversity level of the population. Experimental results on a series of dynamic problems generated from several stationary benchmark problems show that the proposed algorithm is a good optimizer for DOPs.This work was supported in part by the National Nature Science Foundation of China (NSFC) under Grant 70431003 and Grant 70671020, by the National Innovation Research Community Science Foundation of China under Grant 60521003, by the National Support Plan of China under Grant 2006BAH02A09, by the Engineering and Physical Sciences Research Council (EPSRC) of U.K. under Grant EP/E060722/1, and by the Hong Kong Polytechnic University Research Grants under Grant G-YH60

AID-RL: Active information-directed reinforcement learning for autonomous source seeking and estimation

This paper proposes an active information-directed reinforcement learning (AID-RL) framework for autonomous source seeking and estimation problem. Source seeking requires the search agent to move towards the true source, and source estimation demands the agent to maintain and update its knowledge regarding the source properties such as release rate and source position. These two objectives give rise to the newly developed framework, namely, dual control for exploration and exploitation. In this paper, the greedy RL forms an exploitation search strategy that navigates the agent to the source position, while the information-directed search commands the agent to explore most informative positions to reduce belief uncertainty. Extensive results are presented using a high-fidelity dataset for autonomous search, which validates the effectiveness of the proposed AID-RL and highlights the importance of active exploration in improving sampling efficiency and search performance

Epistasis not needed to explain low dN/dS

An important question in molecular evolution is whether an amino acid that occurs at a given position makes an independent contribution to fitness, or whether its effect depends on the state of other loci in the organism's genome, a phenomenon known as epistasis. In a recent letter to Nature, Breen et al. (2012) argued that epistasis must be "pervasive throughout protein evolution" because the observed ratio between the per-site rates of non-synonymous and synonymous substitutions (dN/dS) is much lower than would be expected in the absence of epistasis. However, when calculating the expected dN/dS ratio in the absence of epistasis, Breen et al. assumed that all amino acids observed in a protein alignment at any particular position have equal fitness. Here, we relax this unrealistic assumption and show that any dN/dS value can in principle be achieved at a site, without epistasis. Furthermore, for all nuclear and chloroplast genes in the Breen et al. dataset, we show that the observed dN/dS values and the observed patterns of amino acid diversity at each site are jointly consistent with a non-epistatic model of protein evolution.Comment: This manuscript is in response to "Epistasis as the primary factor in molecular evolution" by Breen et al. Nature 490, 535-538 (2012

An Investigation on Integrating Eastern and Western Medicine with Informatics

Today, in many western countries, acceptance of alternate forms of healthcare such as Chinese medicine (CM) is increasing. In fact, countries such as Australia, Canada, and England are going so far as to set regulations, education, and standards regarding the practice of CM in these respective countries. Further, we can see the integration between western and Chinese medicine delivery of care and treatments in many instances. Information Systems and Information Technology (IS/IT) can be a key enabler in assisting this integration. The following study examines aspects of such integrations using IS/IT and identifies that CM IS/IT is more likely to succeed when there is synthesis between key aspects of the unique environment and user requirements. This perspective is supported theoretically by adapting Churchman’s Inquiring Systems to frame CM as a combination of Hegelian and Kantian inquiring systems with the support of Singerian, Lockean, and Leibnizian inquiring systems and Knowledge Management (KM) features. Based on this, the study then proposes a new design for a patient management system in clinics and hospitals

A small synthetic molecule functions as a chloride–bicarbonate dual-transporter and induces chloride secretion in cells

A C2 symmetric small molecule composed of L-phenylalanine and isophthalamide was found to function as a Cl−/HCO3− dual transporter and self-assemble into chloride channels. In Ussing-chamber based short-circuit current measurements, this molecule elicited chloride-dependent short-circuit current (Isc) increase in both Calu-3 cell and CFBE41o-cell (with F508del mutant CFTR) monolayers.postprin

Fabric defect detection using AI and machine learning for lean and automated manufacturing of acoustic panels

Fabric defects in the conventional manufacturing of acoustic panels are detected via manual visual inspections, which are prone to problems due to human errors. Implementing an automated fabric inspection system can improve productivity and increase product quality. In this work, advanced machine learning (ML) techniques for fabric defect detection are reviewed, and two deep learning (DL) models are developed using transfer learning based on pre-trained convolutional neural network (CNN) architectures. The dataset used for this work consists of 1800 images with six different classes, made up of one class of fabric in good condition and five classes of fabric defects. The model design process involves pre-processing of the images, modification of the neural network layers, as well as selection and optimisation of the network’s hyperparameters. The average accuracies of the two CNN models developed in this work, which used the GoogLeNet and the ResNet50 architectures, are 89.84% and 95.45%, respectively, showing statistically significant results. The interpretability of the models is discussed using the Grad-CAM technique. Relevant image acquisition hardware requirements are also put forward for integration with the detection software, which can enable successful deployment of the model for the automated fabric inspection.Partially supported by Innovate UK (KTP 12273)

Spatial, Temporal, and Human-Induced Variations in Suspended Sediment Concentration in the Surface Waters of the Yangtze Estuary and Adjacent Coastal Areas

To delineate temporal and spatial variations in suspended sediment concentration (SSC) in the Yangtze (Changjiang) Estuary and adjacent coastal waters, surface-water samples were taken twice daily from 10 stations over periods ranging from 2 to 12 years (total number of samples \u3e 28,000). Synoptic measurements in 2009 showed an increase in surface SSC from 0.058 g/l in the upper sections of the estuary to similar to 0.6 g/l at the Yangtze River turbidity maximum at the river mouth, decreasing seaward to 0.057 g/l. Annual periodicities reflect variations in the Yangtze discharge, which affect the horizontal distribution and transport of SSC, and seasonal winds, which result in vertical resuspension and mixing. Over the past 10-20 years, annual surface SSC in the lower Yangtze River and the upper estuary has decreased by 55%, due mainly to dam construction in the upper and middle reaches of the river. The 20-30% decrease in mean surface SSC in the lower estuary and adjacent coastal waters over the same period presumably reflects sediment resuspension, in part due to erosion of the subaqueous Yangtze Delta. SSCs in the estuary and adjacent coastal waters are expected to continue to decline as new dams are constructed in the Yangtze basin and as erosion of the subaqueous delta slows in coming decades

First two cases of living related liver transplantation with complicated anatomy of blood vessels in Beijing

Aim: Living related liver transplantation (LRLT) has been developed in response to the paediatric organ donor shortage. Though it has been succeeded in many centers worldwide, the safety of the donor is still a major concern, especially in donors with anatomy variation. We succeeded in performing the first two cases of living related liver transplantation with complicated anatomy of blood vessels as a way to overcome cadaveric organ shortage in Beijing. Methods: Two patients, with congenital liver fibrosis and congenital biliary atresia were performed with living donor liver transplantation in our hospital and then followed up from November 12 to December 13, 2001. The two living donors, mother and father, were healthy aged 34 and 35 years. One right lobe (segment V, VI, VII, VIII) and one left lateral lobe (segment II and III) were used. The grafts weighed 394 g and 300 g. The ratio of graff weight to the standard liver volume (SLV) of donors was 68% and 27%. The graft weight to recipient body weight ratio was 3.2% and 4.4%. The graft weight to recipient estimated standard liver mass (ESLM) ratio was 63% and 85%. The two donors had complicated blood vessel variation. Results: Two patients undergone living donor liver transplantation had good results. Abnormal liver function with high bilirubin level appeared in a few days after operation, bur liver function returned to normal one month after operation with bilirubin level almost decreased to near normal. No bleeding, thrombosis, infection and bile leakage occurred. One had an acure rejection and recovered. The two donors recovered in two weeks. One had slight fever because of a little collection in abdomen and recovered after paracentesis and drainage. Conclusion: Living donor liver transplantation has been proved to be a good way that offers a unique opportunity of getting a timely liver graft as a response to shortage of pediatric donors, though it could be a technically difficult operation if there is anatomical variation. Copyright © 2004 by The WJG Press.published_or_final_versio

Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion

Size-Dependent Materials Properties Toward a Universal Equation

Due to the lack of experimental values concerning some material properties at the nanoscale, it is interesting to evaluate this theoretically. Through a “top–down” approach, a universal equation is developed here which is particularly helpful when experiments are difficult to lead on a specific material property. It only requires the knowledge of the surface area to volume ratio of the nanomaterial, its size as well as the statistic (Fermi–Dirac or Bose–Einstein) followed by the particles involved in the considered material property. Comparison between different existing theoretical models and the proposed equation is done