Robust Component-based Network Localization with Noisy Range Measurements

Accurate and robust localization is crucial for wireless ad-hoc and sensor networks. Among the localization techniques, component-based methods advance themselves for conquering network sparseness and anchor sparseness. But component-based methods are sensitive to ranging noises, which may cause a huge accumulated error either in component realization or merging process. This paper presents three results for robust component-based localization under ranging noises. (1) For a rigid graph component, a novel method is proposed to evaluate the graph's possible number of flip ambiguities under noises. In particular, graph's \emph{MInimal sepaRators that are neaRly cOllineaR (MIRROR)} is presented as the cause of flip ambiguity, and the number of MIRRORs indicates the possible number of flip ambiguities under noise. (2) Then the sensitivity of a graph's local deforming regarding ranging noises is investigated by perturbation analysis. A novel Ranging Sensitivity Matrix (RSM) is proposed to estimate the node location perturbations due to ranging noises. (3) By evaluating component robustness via the flipping and the local deforming risks, a Robust Component Generation and Realization (RCGR) algorithm is developed, which generates components based on the robustness metrics. RCGR was evaluated by simulations, which showed much better noise resistance and locating accuracy improvements than state-of-the-art of component-based localization algorithms.Comment: 9 pages, 15 figures, ICCCN 2018, Hangzhou, Chin

A Novel Ontology Approach to Support Design for Reliability considering Environmental Effects

Environmental effects are not considered sufficiently in product design. Reliability problems caused by environmental effects are very prominent. This paper proposes a method to apply ontology approach in product design. During product reliability design and analysis, environmental effects knowledge reusing is achieved. First, the relationship of environmental effects and product reliability is analyzed. Then environmental effects ontology to describe environmental effects domain knowledge is designed. Related concepts of environmental effects are formally defined by using the ontology approach. This model can be applied to arrange environmental effects knowledge in different environments. Finally, rubber seals used in the subhumid acid rain environment are taken as an example to illustrate ontological model application on reliability design and analysis

Gut dysbiosis contributes to chlamydial induction of hydrosalpinx in the upper genital tract

Chlamydia trachomatis is one of the most common sexually infections that cause infertility, and its genital infection induces tubal adhesion and hydrosalpinx. Intravaginal Chlamydia muridarum infection in mice can induce hydrosalpinx in the upper genital tract and it has been used for studying C. trachomatis pathogenicity. DBA2/J strain mice were known to be resistant to the chlamydial induction of hydrosalpinx. In this study, we took advantage of this feature of DBA2/J mice to evaluate the role of antibiotic induced dysbiosis in chlamydial pathogenicity. Antibiotics (vancomycin and gentamicin) were orally administrated to induce dysbiosis in the gut of DBA2/J mice. The mice with or without antibiotic treatment were evaluated for gut and genital dysbiosis and then intravaginally challenged by C. muridarum. Chlamydial burden was tested and genital pathologies were evaluated. We found that oral antibiotics significantly enhanced chlamydial induction of genital hydrosalpinx. And the antibiotic treatment induced severe dysbiosis in the GI tract, including significantly reduced fecal DNA and increased ratios of firmicutes over bacteroidetes. The oral antibiotic did not alter chlamydial infection or microbiota in the mouse genital tracts. Our study showed that the oral antibiotics-enhanced hydrosalpinx correlated with dysbiosis in gut, providing the evidence for associating gut microbiome with chlamydial genital pathogenicity

Serum metabolomics analysis in patients with alcohol dependence

ObjectiveAlcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.MethodsLiquid chromatography-mass spectrometry (LC–MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.ResultsThe serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.ConclusionThe metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD

Real estate investment risk analysis.

Study the risks and their determinant factors in real estate investment decisions and systematically summarize the techniques in the identification, assessment and management of such risks, in view of the practices in China.Master of Business Administratio

A novel concept and assessment method for trustworthiness of prognostics

The existence of the unavoidable uncertainties has a great effect on the prognostics accuracy and performance. However, their influences are rarely taken into account in the current prognostics performance evaluation. Consequently, the validity and/or trustiness degree of prognostics and health management system has not been comprehensively evaluated or measured. Considering the definition of prognostics performance and the characteristics of uncertainties, four prognostics performance metrics and two kinds of quantitative evaluation methods are proposed. On the basis of prognostics performance definition, a novel trustworthiness of prognostics concept is presented. Then, three kinds of assessment methods for trustworthiness of prognostics are provided. Finally, a case study has been carried out on the aviation hydraulic pump for verification purposes, in which the oil-return flow is monitored for predicting the degradation of the pump. The systematic application of trustworthiness of prognostics assessment is implemented based on the back propagation neural network prognostics algorithm. The results show that the proposed trustworthiness of prognostics concept and assessment methods can contribute to the systematic and comprehensive understanding of the performance of prognostics and health management system