A Moran eigenvector spatial filtering specification of entropy measures

Regional science investigations of geographical disparities in socio-economic development sometimes utilize entropy, which measures a phenomenon's distributional uniformity across geographical space. Entropy also is widely utilized to measure random phenomenon dispersion, and often used to identify the most probable allocation of a phenomenon in space. Its common formulation is with empirical frequencies, following Shannon. Batty introduces spatial entropy assuming equal probability over space. His specification considers probabilities as fundamentally being spatially independent, which does not hold in most empirical geographical analyses. Hence, an entropy measure can be further modified by controlling extra variation caused by spatial autocorrelation. This paper proposes a Moran eigenvector spatial filtering (MESF) entropy specification that accounts for spatial autocorrelation when modelling georeferenced data. Using eigenvectors from a transformed spatial weights matrix, MESF identifies and isolates spatially autocorrelated components within a georeferenced variable. Coupling it with a non-normal distribution, such as a binomial or beta probability model, which researchers often employ to describe empirical probabilities, expands its utility. The proposed method is examined with an application to regional income inequality in Poland during 2005–2012. This application demonstrates that accounting for spatial autocorrelation further enhances an entropy measure, showing that the MESF specification provides a flexible method for controlling spatial autocorrelation in an entropy formulation.     

Hepatitis C in Special Patient Cohorts: New Opportunities in Decompensated Liver Cirrhosis,End-Stage Renal Disease and Transplant Medicine

Worldwide, hepatitis C virus (HCV) is a common infection. Due to new antiviral approaches and the approval of direct-acting antiviral agents (DAA), HCV therapy has become more comfortable. Nevertheless, there are special patient groups, in whom treatment of HCV is still challenging. Due to only few data available, tolerability and efficacy of DAAs in special patient cohorts still remain unclear. Such special patient cohorts comprise HCV in patients with decompensated liver disease (Child-Pugh Class B or C), patients with chronic kidney disease, and patients on waiting lists to renal/liver transplantation or those with HCV recurrence after liver transplantation. HCV infection in these patient cohorts has been shown to be associated with increased morbidity and mortality and may lead to reduced graft survival after transplantation. Successful eradication of HCV results in a better outcome concerning liver-related complications and in a better clinical outcome of these patients. In this review, we analyze available data and results from recently published literature and provide an overview of current recommendations of HCV-therapy regimen in these special patient cohorts.     

Effect of fungal hyphae on the access of bacteria to phenanthrene in soil

The effect of fungal hyphae on the mobilization of soil-dwelling bacteria and their access to hydrophobic phenanthrene in soil was tested in columns containing air-filled agricultural soil. The experimental design included a spatial separation between zones of bacterial inoculation and contamination. Motile Pseudomonas putida PpG7 (NAH7) and fast-growing, hydrophilic Pythium ultimum were used as the model phenanthrene-degrading and vector organisms, respectively. Efficient translocation of strain PpG7 in the range of centimetres in presence of P. ultimum indicated that the fungal mycelia bridged air-filled pores and thereby provided a continuous network of water-paths that enabled bacteria to spread in the soil. Biodegradation of the soil-associated phenanthrene was found only in the presence of the fungal mycelia, hence proving that the fungal network facilitated the access of the bacteria to the contaminant. Our data suggest that the specific stimulation of indigenous fungi is a promising method to mobilize pollutant degrading bacteria and thereby improve soil bioremediation in-situ.     

A void fraction model for annular flow in horizontal tubes

An important feature of detailed system simulation models for unitary air conditioners is the calculation of charge inventory. Void fraction determination in the two-phase regions of the heat exchangers is the primary challenge associated with charge inventory calculations. Annular flow is one of the predominant flow regimes encountered in horizontal heat exchangers. Analytical annular flow models typically fail to accurately represent void fraction. Thus, many of the available void fraction models are empirically based. To improve the prediction capabilities of void fraction models, a mechanistic void fraction model has been developed for annular flow in horizontal tubes. The present model considers the effect of momentum eddy diffusivity damping at the liquid-vapor interface. Two approaches are presented for determining the wall shear stress. The modeling results are compared to predictions from various void fraction models found in the literature. The present model is found to work well at moderate mass fluxes.     

Free volume distribution at the Teflon AF/silicon interfaces probed by a slow positron beam

We performed positron annihilation lifetime spectroscopy experiments at Teflon AF^®/silicon interfaces as function of the positron implantation energy to determine the free volume hole size distribution in the interfacial region and to investigate the width of the interphase. While no interphase was detected in very short chained solvent-free, thermally evaporated Teflon AF^®, an interphase of some tens of nm in extension was observed for high molecular weight spin-coated Teflon AF^® films. Influences of the native oxide layer on the data evaluation could be ruled out.     

Development of a set of simple bacterial biosensors for quantitative and rapid measurements of arsenite and arsenate in potable water

Testing for arsenic pollution is commonly performed with chemical test kits of unsatisfying accuracy. Bacterial biosensors are an interesting alternative as they are easily produced, simple, and highly accurate devices. Here, we describe the development of a set of bacterial biosensors based on a nonpathogenic laboratory strain of Escherichia coli, the natural resistance mechanism of E. coli against arsenite and arsenate, and three reporter proteins: bacterial luciferase, beta-galactosidase and Green Fluorescent Protein (GFP). The biosensors were genetically optimized to reduce background expression in the absence of arsenic. In calibration experiments with the biosensors and arsenite-amended potable water, arsenite concentrations at 4 microg of As/L (0.05 microM) were routinely and accurately measured. The currently most quantitative system expressed the bacterial luciferase as reporter protein, responding proportional with a concentration range between 8 and 80 microg of As/L. Sensor cells could be stored as frozen batches, resuspended in plain media, and exposed to the aqueous test sample, and light emission was measured after 30-min incubation. Field testing for arsenite was achieved with a system that contained beta-galactosidase, producing a visible blue color at arsenite concentrations above 8 microg/L. For this sensor, a protocol was developed in which the sensor cells were dried on a paper strip and placed in the aqueous test solution for 30 min after which time color development was allowed to take place. The GFP sensor showed good potential for continuous rather than end point measurements. In all cases, growth of the biosensors and production of the strip test was achieved by very simple means with common growth media, and quality control of the sensors was performed by isolating the respective plasmids with the genetic constructs according to simple standard genetic technologies. Therefore, the biosensor cells and protocols may offer a realistic alternative for measuring arsenic contamination in potable water.     

Serotonin transporter gene variants in alcohol-dependent subjects with dissocial personality disorder

BACKGROUND: We tested the hypothesis that a functional biallelic repetitive element in the 5' regulatory region of the human serotonin transporter gene (SLC6A4) confers susceptibility to serotonin-related personality traits underlying alcohol dependence with dissocial behavior. METHODS: The association study was focused on 64 alcohol-dependent subjects with a dissocial personality disorder (according to ICD-10) who were derived from 315 German alcohol-dependent subjects. The Tridimensional Personality Questionnaire (TPQ) was applied to assess personality dimensions in 101 alcohol-dependent men, including 39 dissocial alcoholics. RESULTS: Our association analyses revealed a trend towards a higher frequency of the short (S) allele of the SLC6A4 polymorphism in dissocial alcoholics compared to 216 German controls (chi 2 = 2.81, df = 1, p = 0.094). Dissocial alcoholics carrying the S/S genotype exhibited significant lower scores of harm avoidance compared to those lacking it (U-test, p = 0.015). Significantly higher novelty seeking scores were obtained in dissocial alcoholics carrying the S allele relative to those lacking it (U-test, p = 0.021). CONCLUSIONS: Our tentative association findings in dissocial alcoholics suggest that the S allele of the 5' regulatory SLC6A4 polymorphism confers susceptibility to a temperamental profile of high novelty seeking and low harm avoidance that has been postulated to underlie dissocial (type-2) alcoholism according to Cloninger's neurogenetic theory of personality.