Diffusion Estimation Over Cooperative Multi-Agent Networks With Missing Data

In many fields, and especially in the medical and social sciences and in recommender systems, data are gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they may lack information to respond adequately to some questions. The data collected from these studies tend to lead to linear regression models where the regression vectors are only known partially: some of their entries are either missing completely or replaced randomly by noisy values. In this work, assuming missing positions are replaced by noisy values, we examine how a connected network of agents, with each one of them subjected to a stream of data with incomplete regression information, can cooperate with each other through local interactions to estimate the underlying model parameters in the presence of missing data. We explain how to adjust the distributed diffusion strategy through (de)regularization in order to eliminate the bias introduced by the incomplete model. We also propose a technique to recursively estimate the (de)regularization parameter and examine the performance of the resulting strategy. We illustrate the results by considering two applications: one dealing with a mental health survey and the other dealing with a household consumption survey

Effects of ultraviolet A on the activity of two metabolic enzymes, DNA damage and lipid peroxidation during early developmental stages of the African catfish, Clarias gariepinus (Burchell, 1822)

Many ultraviolet-A (UVA)-induced biochemical and physiological changes are valid as biomarkers using aquatic species for detection of the degree of stress. Changes in the concentration and activities of enzymes, such as glucose-6-phosphate dehyderogenase (G6PDH), lactate dehyderogenase (LDH), DNA damage and lipid peroxidation (LPO), can be used as biomarkers to identify possible environmental contamination in fish. This study aimed to investigate the impact of UVA on the activity of the selected enzymes, DNA damage and LPO during early developmental stages of the African catfish Clarias gariepinus. Embryo hemogenates were used for measurements of G6PDH, LDH, DNA damage and LPO concentrations and activities spectrophotometrically at 37°C. The normal ontogenetic variations in enzyme activities, DNA damage and LPO of the early developmental stages (24–168 h-PFS; hours-post fertilization stage) were studied. There was a significant decrease in the activity of G6PDH till 120 h-PFS. Then after 120 h-PFS, the activity of such enzymes insignificantly increased toward higher stages. The LDH activity was recorded with a pattern of decrease till 96 h-PFS, followed by a significant increase toward 168 h-PFS. The polynomial pattern of variations in DNA damage and LPO was also evident. The patterns of the enzyme activities, corresponding DNA damage and LPO of the early ontogenetic stages under the influence of three different UVA doses (15, 30 and 60 min), were recorded. The pattern of variations in G6PDH activity in UVA-induced groups was similar to that of the control group with variation in the magnitude of such activity. In all treated groups, LDH activity decreased till 96 h-PFS, then increased till 168 h-PFS. Within each of the embryonic stages, the increase in UVA led to a significant increase in DNA damage. A significant increase in lipid peroxidation under UVA doses was recorded. The variability in number and molecular weight of proteins under exposure to UVA was evident, reflecting some of the genetic and transcriptional changes during exposure and development

Motion artifacts in kidney stone imaging using single-source and dual-source dual-energy CT scanners: a phantom study

PURPOSE: Dual-energy computed tomography (DECT) has shown the capability of differentiating uric acid (UA) from non-UA stones with 90-100% accuracy. With the invention of dual-source (DS) scanners, both low- and high-energy images are acquired simultaneously. However, DECT can also be performed by sequential acquisition of both images on single-source (SS) scanners. The objective of this study is to investigate the effects of motion artifacts on stone classification using both SS-DECT and DS-DECT. METHODS: 114 kidney stones of different types and sizes were imaged on both DS-DECT and SS-DECT scanners with tube voltages of 80 and 140 kVp with and without induced motion. Postprocessing was conducted to create material-specific images from corresponding low- and high-energy images. The dual-energy ratio (DER) and stone material were determined and compared among different scans. RESULTS: For the motionless scans, all stones were correctly classified with SS-DECT, while two cystine stones were misclassified with DS-DECT. When motion was induced, 94% of the stones were misclassified with SS-DECT versus 11% with DS-DECT (P < 0.0001). Stone size was not a factor in stone misclassification under motion. Stone type was not a factor in stone misclassification under motion with SS-DECT, although with DS-DECT, cystine showed higher number of stone misclassification. CONCLUSIONS: Motion artifacts could result in stone misclassification in DECT. This effect is more pronounced in SS-DECT versus DS-DECT, especially if stones of different types lie in close proximity to each other. Further, possible misinterpretation of the number of stones (i.e., missing one, or thinking that there are two) in DS-DECT could be a potentially significant problem

Integrable and continuous solutions of a nonlinear quadratic integral equation

This addendum concerns the paper of the above title found in EJQTDE No. 25 (2008). There are some misprints in that paper: (i) Page 3, line 5 should be $k:[0,1] \times[0,1]\rightarrow R_+$ satisfies Carath\'{e}odory condition (i.e. measurable in $t$ for all $s \in [0,1]$ and continuous in $s$ for all $t\in [0,1]$) such that $\int_0^1 k(t,s) m_2(s)ds$ is bounded $\forall t\in[0,1].$ (ii) Page 6, line 6 should be $k:[0,1] \times [0,1]\rightarrow R_+$ satisfies Carath\'{e}odory condition (i.e. measurable in $s$ for all $t \in~[0,1]$ and continuous in $t$ for all $s \in [0,1]$) such that $k(t,s)m_2(s)\in L_1 \forall t\in[0,1].

Monotonic solutions of functional integral and differential equations of fractional order

The existence of positive monotonic solutions, in the class of continuous functions, for some nonlinear quadratic integral equations have been studied by J. Banas. Here we are concerned with a singular quadratic functional integral equations. The existence of positive monotonic solutions $x \in L_1[0,1]$ will be proved. The fractional order nonlinear functional differential equation will be given as a special case

Parameter Estimation in the Presence of Bounded Data Uncertainties

We formulate and solve a new parameter estimation problem in the presence of data uncertainties. The new method is suitable when a priori bounds on the uncertain data are available, and its solution leads to more meaningful results, especially when compared with other methods such as total least-squares and robust estimation. Its superior performance is due to the fact that the new method guarantees that the effect of the uncertainties will never be unnecessarily over-estimated, beyond what is reasonably assumed by the a priori bounds. A geometric interpretation of the solution is provided, along with a closed form expression for it. We also consider the case in which only selected columns of the coefficient matrix are subject to perturbations

GRIDKIT: Pluggable overlay networks for Grid computing

A `second generation' approach to the provision of Grid middleware is now emerging which is built on service-oriented architecture and web services standards and technologies. However, advanced Grid applications have significant demands that are not addressed by present-day web services platforms. As one prime example, current platforms do not support the rich diversity of communication `interaction types' that are demanded by advanced applications (e.g. publish-subscribe, media streaming, peer-to-peer interaction). In the paper we describe the Gridkit middleware which augments the basic service-oriented architecture to address this particular deficiency. We particularly focus on the communications infrastructure support required to support multiple interaction types in a unified, principled and extensible manner-which we present in terms of the novel concept of pluggable overlay networks

Metabolic Profiling of Dividing Cells in Live Rodent Brain by Proton Magnetic Resonance Spectroscopy (1HMRS) and LCModel Analysis

RATIONALE: Dividing cells can be detected in the live brain by positron emission tomography or optical imaging. Here we apply proton magnetic resonance spectroscopy (1HMRS) and a widely used spectral fitting algorithm to characterize the effect of increased neurogenesis after electroconvulsive shock in the live rodent brain via spectral signatures representing mobile lipids resonating at approximately 1.30 ppm. In addition, we also apply the same 1HMRS methodology to metabolically profile glioblastomas with actively dividing cells growing in RCAS-PDGF mice. METHODS: 1HMRS metabolic profiles were acquired on a 9.4T MRI instrument in combination with LCModel spectral analysis of: 1) rat brains before and after ECS or sham treatments and 2) RCAS-PDGF mice with glioblastomas and wild-type controls. Quantified 1HMRS data were compared to post-mortem histology. RESULTS: Dividing cells in the rat hippocampus increased approximately 3-fold after ECS compared to sham treatment. Quantification of hippocampal metabolites revealed significant decreases in N-acetyl-aspartate but no evidence of an elevated signal at approximately 1.3 ppm (Lip13a+Lip13b) in the ECS compared to the sham group. In RCAS-PDGF mice a high density (22%) of dividing cells characterized glioblastomas. Nile Red staining revealed a small fraction (3%) of dying cells with intracellular lipid droplets in the tumors of RCAS-PDGF mice. Concentrations of NAA were lower, whereas lactate and Lip13a+Lip13b were found to be significantly higher in glioblastomas of RCAS-PDGF mice, when compared to normal brain tissue in the control mice. CONCLUSIONS: Metabolic profiling using 1HMRS in combination with LCModel analysis did not reveal correlation between Lip13a+Lip13b spectral signatures and an increase in neurogenesis in adult rat hippocampus after ECS. However, increases in Lip13a+Lip13b were evident in glioblastomas suggesting that a higher density of actively dividing cells and/or the presence of lipid droplets is necessary for LCModel to reveal mobile lipids