Complexity reduction of influence nets using arc removal

© 2015 - IOS Press and the authors. The model building of Influence Nets, a special instance of Bayesian belief networks, is a time-consuming and labor-intensive task. No formal process exists that decision makers/system analyst, who are typically not familiar with the underlying theory and assumptions of belief networks, can use to build concise and easy-to-interpret models. In many cases, the developed model is extremely dense, that is, it has a very high link-to-node ratio. The complexity of a network makes the already intractable task of belief updating more difficult. The problem is further intensified in dynamic domains where the structure of the built model is repeated for multiple time-slices. It is, therefore, desirable to do a post-processing of the developed models and to remove arcs having a negligible influence on the variable(s) of interests. The paper applies sensitivity of arc analysis to identify arcs that can be removed from an Influence Net without having a significant impact on its inferencing capability. A metric is suggested to gauge changes in the joint distribution of variables before and after the arc removal process. The results are benchmarked against the KL divergence metric. An empirical study based on several real Influence Nets is conducted to test the performance of the sensitivity of arc analysis in reducing the model complexity of an Influence Net without causing a significant change in its joint probability distribution

The preliminary study of urbanization, fossil fuels consumptions and CO2 emission in Karachi

According to population, Karachi is the first largest city of Pakistan and 9th largest in the world. During last three decades, it has faced mass urbanization, huge population growth, many fold increase in vehicles and industrial development. As a result the demand of more energy in form of fossil fuels increased for domestic, industrial and transportation purpose. In this research the maximum available data of Karachi about urbanization, population and vehicles growth, industrialization, energy consumption and CO2 emissions are analyzed. Time periods considered for this work are according to the availability of the data. The results show that during 1947 to 2008, both urban population and urban area increased to 1500%. During 1990 to 2008, the percentage growth in vehicles is double than that of population growth during this time period. During 1980 to 2007 the consumption of oil and petrol, natural gas and coal increased to 219%, 365% and 287%, respectively. The emission of CO2 jumped from 39 million metric tons in 1980 to 151 million metric tons in 2007

Integrating personality and mood with agent emotions

© 2019 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). All rights reserved. An intelligent agent should be able to show different emotional behaviours in different interaction situations to become believable and establish close relationships with human counterparts. It is widely accepted that personality and mood play an important role in modulating emotions. However, current computational accounts of emotion for intelligent agents do not effectively integrate the notions of personality and mood in the process of emotion generation. Previous attempts that have been made are mostly based on the assumptions of the researcher, rather than on empirical data and scientific validation. In this paper, we present the results of a novel supervised machine learning approach used to train a network of emotions that integrates the factors of personality and mood, which provides a high emotion intensity prediction accuracy

Broadening of Plasmonic Resonance Due to Electron Collisions with Nanoparticle Boundary: а Quantum Mechanical Consideration

We present a quantum mechanical approach to calculate broadening of plasmonic resonances in metallic nanostructures due to collisions of electrons with the surface of the structure. The approach is applicable if the characteristic size of the structure is much larger than the de Broglie electron wavelength in the metal. The approach can be used in studies of plasmonic properties of both single nanoparticles and arrays of nanoparticles.Comment: 9 page

A Novel 24-GHz Miniaturized Flexible Rectifier for Wireless Energy Harvesting

In this research article, the design and fabrication of a miniaturized flexible rectifier at 24 GHz for wireless power transfer to wearables is presented. The proposed circuit consists of a shunt topology rectifier including a single stub impedance matching network. Conventional PCB fabrication technique is used for the prototyping of the proposed flexible rectifier. It has a total footprint of 5.29 cm². The proposed rectifier exhibits a good trade-off between compactness and RF-to-DC conversion efficiency. The implementation on a very thin substrate (130 µm) makes it durable for wearables applications. Experimental results of the proposed rectifier show an output DC voltage of 2.0 V across an optimal load resistance of 250 Ω and measured RF-DC conversion efficiency of 23% for an input power of 17 dBm at 24 GHz

Modulations of cell cycle checkpoints during HCV associated disease

Background Impaired proliferation of hepatocytes has been reported in chronic Hepatitis C virus infection. Considering the fundamental role played by cell cycle proteins in controlling cell proliferation, altered regulation of these proteins could significantly contribute to HCV disease progression and subsequent hepatocellular carcinoma (HCC). This study aimed to identify the alterations in cell cycle genes expression with respect to early and advanced disease of chronic HCV infection. Methods Using freshly frozen liver biopsies, mRNA levels of 84 cell cycle genes in pooled RNA samples from patients with early or advanced fibrosis of chronic HCV infection were studied. To associate mRNA levels with respective protein levels, four genes (p27, p15, KNTC1 and MAD2L1) with significant changes in mRNA levels (\u3e 2-fold, p-value \u3c 0.05) were selected, and their protein expressions were examined in the liver biopsies of 38 chronic hepatitis C patients. Results In the early fibrosis group, increased mRNA levels of cell proliferation genes as well as cell cycle inhibitor genes were observed. In the advanced fibrosis group, DNA damage response genes were up-regulated while those associated with chromosomal stability were down-regulated. Increased expression of CDK inhibitor protein p27 was consistent with its mRNA level detected in early group while the same was found to be negatively associated with liver fibrosis. CDK inhibitor protein p15 was highly expressed in both early and advanced group, but showed no correlation with fibrosis. Among the mitotic checkpoint regulators, expression of KNTC1 was significantly reduced in advanced group while MAD2L1 showed a non-significant decrease. Conclusion Collectively these results are suggestive of a disrupted cell cycle regulation in HCV-infected liver. The information presented here highlights the potential of identified proteins as predictive factors to identify patients with high risk of cell transformation and HCC development

Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement

Purpose: To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types. Methods: Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (Ktrans) and rate constant (kep). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model. Results: For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (kep) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter kepfrom the hot spot only achieved an AUC of 0.59, with a low added diagnostic value. Conclusion: The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement. © The Author(s) 2009

The HIV-1 Nef protein binds argonaute-2 and functions as a viral suppressor of RNA interference

The HIV-1 accessory protein Nef is an important virulence factor. It associates with cellular membranes and modulates the endocytic machinery and signaling pathways. Nef also increases the proliferation of multivesicular bodies (MVBs), which are sites for virus assembly and budding in macrophages. The RNA interference (RNAi) pathway proteins Ago2 and GW182 localize to MVBs, suggesting these to be sites for assembly and turnover of the miRNA-induced silencing complex (miRISC). While RNAi affects HIV replication, it is not clear if the virus encodes a suppressor activity to overcome this innate host response. Here we show that Nef colocalizes with MVBs and binds Ago2 through two highly conserved Glycine-Tryptophan (GW) motifs, mutations in which abolish Nef binding to Ago2 and reduce virus yield and infectivity. Nef also inhibits the slicing activity of Ago2 and disturbs the sorting of GW182 into exosomes resulting in the suppression of miRNA-induced silencing. Thus, besides its other activities, the HIV-1 Nef protein is also proposed to function as a viral suppressor of RNAi (VSR)