Object Identification by Signal Gain and Correlation

In this study, “ring rotation invariant transform” techniques are used to add more salient feature to the original images. The “ring rotation invariant transform” can solve image rotation problem, which transfers a ring signal to several signal vectors in the complex domain, whereby to generate invariant magnitude. Matrix correlation is employed to combine these magnitudes to generate the various discriminators, by which to identify objects. For managing image-shifting problem, one pixel in sample image is compared with surrounding pixels of unknown image. The comparison approaching in this study is by the basis of pixel-to-pixel-comparisons.

Soft-ANN based correlation for air-water two-phase flow pressure drop estimation in a vertical mini-channel

In this paper, an Artificial Neural Network soft matrix correlation to estimate the pressure drop of air-water two-phase flow is developed. The applicability of the model is extended by using dimensionless physical numbers as inputs (Air-Reynolds number, Water-Reynolds number, and the ratio of Air Inertial Forces to Water Inertial Forces), so the model can be implemented for vertical pipes with the proper combination of diameter-velocity-density-viscosity allowing estimations of dimensional numbers within the range of: Air-Reynolds numbers (430–6100), Water-Reynolds number (2400–7200), and Air-Water-Inertial forces ratio (1.6–1834), including the diameter range from 3 to 28 mm. Experimental measurements of frictional pressure drop of water-air mixtures are determined at different conditions. A search of the most suitable density, viscosity, and friction models was conducted and used in the model. The performance of the proposed ANN correlation is compared against published expressions showing good approximation to experimental data; results indicate that the most used correlations are within a mean relative error ( mre) of 23.9–30.7%, while the proposed ANN has a mre = 0.9%. Two additional features are discussed: i) the applicability and generality of the ANN using untrained data, ii) the applicability in laminar, transitional, and turbulent flow regimen. To take the approach beyond a robust performance mapping, the methodology to translate the ANN into a programmable equation is presented.

Multi-omics of the esophageal microenvironment identifies signatures associated with progression of Barrett’s esophagus

Background The enrichment of Gram-negative bacteria of oral origin in the esophageal microbiome has been associated with the development of metaplasia. However, to date, no study has comprehensively assessed the relationships between the esophageal microbiome and the host. Methods Here, we examine the esophageal microenvironment in gastro-esophageal reflux disease and metaplasia using multi-omics strategies targeting the microbiome and host transcriptome, followed by targeted culture, comparative genomics, and host-microbial interaction studies of bacterial signatures of interest. Results Profiling of the host transcriptome from esophageal mucosal biopsies revealed profound changes during metaplasia. Importantly, five biomarkers showed consistent longitudinal changes with disease progression from reflux disease to metaplasia. We showed for the first time that the esophageal microbiome is distinct from the salivary microbiome and the enrichment of Campylobacter species as a consistent signature in disease across two independent cohorts. Shape fitting and matrix correlation identified associations between the microbiome and host transcriptome profiles, with a novel co-exclusion relationship found between Campylobacter and napsin B aspartic peptidase. Targeted culture of Campylobacter species from the same cohort revealed a subset of isolates to have a higher capacity to survive within primary human macrophages. Comparative genomic analyses showed these isolates could be differentiated by specific genomic features, one of which was validated to be associated with intracellular fitness. Screening for these Campylobacter strain-specific signatures in shotgun metagenomics data from another cohort showed an increase in prevalence with disease progression. Comparative transcriptomic analyses of primary esophageal epithelial cells exposed to the Campylobacter isolates revealed expression changes within those infected with strains with high intracellular fitness that could explain the increased likelihood of disease progression. Conclusions We provide a comprehensive assessment of the esophageal microenvironment, identifying bacterial strain-specific signatures with high relevance to progression of metaplasia.

Serum levels of inhibitory costimulatory molecules and correlations with levels of innate immune cytokines in patients with pulmonary tuberculosis

Objective To analyze serum levels of inhibitory costimulatory molecules and their correlations with innate immune cytokine levels in patients with pulmonary tuberculosis (PTB). Methods Data for 280 PTB patients and 280 healthy individuals were collected. Serum levels of immune molecules were measured using ELISA. Univariate, multivariate, subgroup, matrix correlation, and receiver operating characteristic curve analyses were performed. Results Host, environment, lifestyle, clinical features, and medical history all influenced PTB. Serum levels of soluble programmed death ligand 1 (sPD-L1), soluble T-cell immunoglobulin- and mucin-domain–containing molecule 3 (sTim-3), soluble galectin-9 (sGal-9), interleukin (IL)-4, and IL-33 were significantly higher in patients with PTB, while levels of IL-12, IL-23, IL-18, and interferon (IFN)-γ were significantly lower. Serum levels of sTim-3 were higher in alcohol users. Levels of sTim-3 were negatively correlated with those of IL-12. Levels of IL-12, IL-23, and IL-18 were positively correlated with those of IFN-γ, while levels of IL-12 were negatively correlated with those of IL-4. The areas under the curve of sPD-L1, sTim-3, sGal-9, IL-12, IL-23, IL-18, IFN-γ, IL-4, and IL-33 for identifying PTB were all >0.77. Conclusions Inhibitory costimulatory molecules may be targets for controlling PTB. Immune molecules may be helpful for diagnosis of PTB.

A Comparison of Principal Component Analysis and Maximum Likelihood Factor Analysis in Bank Health Ratio

The use of factor analysis methods to reduce variable dimensions is generally known and has been used in various disciplines. The two famous extraction methods of factor analysis are principal component analysis and maximum likelihood. This study aimed to compare both, principal component analysis and maximum likelihood. By their constructed matrix correlation, applied to bank financial ratios. The study is developed from an initial set of 22 ratios of healthy indexed banks. The use of bank financial data aims to identify the structure of the financial ratio of healthy indexed banks. There are 10 variables satisfying the criteria of factor analysis techniques to be considered in the analysis. Both principal component analysis and maximum likelihood suggest three factors that can be used to represent 10 variables.Keywords: factor analysis; principal component analysis; maximum likelihood; financial ratios; bank health.

Criteria for optimal operation of automobiles on alternative fuels

The article deals with some criteria that substantiate the design and operational performance of automobiles running on alternative fuels; economic efficiency of operation of such vehicles, their ecological conformity; the level of complexity of the design of converted automobiles; labor intensity of their maintenance, repair, etc. ; traction-speed and other different, in comparison with the basic, properties of automobiles while working on alternative fuel (AF); energy consumption and (or) cost price of AF; efficiency of power plant and (or) car on AF; the degree of commissioning (mass production) and further prospects for the development of the design of such automobiles; state of support developed structures at the national (local) level. An expert assessment of the adopted criteria in the order of their importance is made. Along with the analysis of scores, which are presented in points, it is used the ranking method to study the results of the survey of experts. This allows applying the values of the established optimal criteria to justify the operation of vehicles during their work on the AF. The analysis of the matrix correlation shows that the numerical estimates set by the accepted criteria are characterized by a high degree of correlation, and experts are generally unanimous in assessing their importance. The most important criteria for the operation of automobiles on the AF are economic efficiency, traction and speed and other, different compared to the basic, the properties of automobiles while working on the AF. Other criteria are also quite important, the weights for them are much higher than 7%, and they also should be taken into account while conducting an in-depth analysis and synthesis of indicators of optimal operation of automobiles on the AF. In addition, it is important that the group of criteria that characterize only one type of automobile when working on the AF (for example, the degree of commissioning) experts gave only about 17% of the importance.

HPLC-MS/MS Method for the Detection of Selected Toxic Metabolites Produced by Penicillium spp. in Nuts

Penicillium spp. are emerging as producers of mycotoxins and other toxic metabolites in nuts. A HPLC-MS/MS method was developed to detect 19 metabolites produced by Penicillium spp. on chestnuts, hazelnuts, walnuts and almonds. Two extraction methods were developed, one for chestnuts and one for the other three nuts. The recovery, LOD, LOQ and matrix effect were determined for each analyte and matrix. Correlation coefficients were always >99.99%. In walnuts, a strong signal suppression was observed for most analytes and patulin could not be detected. Six strains: Penicillium bialowiezense, P. brevicompactum, P. crustosum, P. expansum, P. glabrum and P. solitum, isolated from chestnuts, were inoculated on four nuts. Chestnuts favored the production of the largest number of Penicillium toxic metabolites. The method was used for the analysis of 41 commercial samples: 71% showed to be contaminated by Penicillium-toxins. Cyclopenin and cyclopenol were the most frequently detected metabolites, with an incidence of 32% and 68%, respectively. Due to the risk of contamination of nuts with Penicillium-toxins, future studies and legislation should consider a larger number of mycotoxins.