Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground

We provide a comprehensive evaluation of salient object detection (SOD) models. Our analysis identifies a serious design bias of existing SOD datasets which assumes that each image contains at least one clearly outstanding salient object in low clutter. The design bias has led to a saturated high performance for state-of-the-art SOD models when evaluated on existing datasets. The models, however, still perform far from being satisfactory when applied to real-world daily scenes. Based on our analyses, we first identify 7 crucial aspects that a comprehensive and balanced dataset should fulfill. Then, we propose a new high quality dataset and update the previous saliency benchmark. Specifically, our SOC (Salient Objects in Clutter) dataset, includes images with salient and non-salient objects from daily object categories. Beyond object category annotations, each salient image is accompanied by attributes that reflect common challenges in real-world scenes. Finally, we report attribute-based performance assessment on our dataset.Comment: ECCV 201

p22phox C242T Single-Nucleotide Polymorphism Inhibits Inflammatory Oxidative Damage to Endothelial Cells and Vessels.

BACKGROUND: The NADPH oxidase, by generating reactive oxygen species, is involved in the pathophysiology of many cardiovascular diseases and represents a therapeutic target for the development of novel drugs. A single-nucleotide polymorphism, C242T of the p22(phox) subunit of NADPH oxidase, has been reported to be negatively associated with coronary heart disease and may predict disease prevalence. However, the underlying mechanisms remain unknown. METHODS AND RESULTS: With the use of computer molecular modeling, we discovered that C242T single-nucleotide polymorphism causes significant structural changes in the extracellular loop of p22(phox) and reduces its interaction stability with Nox2 subunit. Gene transfection of human pulmonary microvascular endothelial cells showed that C242T p22(phox) significantly reduced Nox2 expression but had no significant effect on basal endothelial O2 (.-) production or the expression of Nox1 and Nox4. When cells were stimulated with tumor necrosis factor-α (or high glucose), C242T p22(phox) significantly inhibited tumor necrosis factor-α-induced Nox2 maturation, O2 (.-) production, mitogen-activated protein kinases and nuclear factor κB activation, and inflammation (all P<0.05). These C242T effects were further confirmed using p22(phox) short-hairpin RNA-engineered HeLa cells and Nox2(-/-) coronary microvascular endothelial cells. Clinical significance was investigated by using saphenous vein segments from non-coronary heart disease subjects after phlebotomies. TT (C242T) allele was common (prevalence of ≈22%) and, in comparison with CC, veins bearing TT allele had significantly lower levels of Nox2 expression and O2 (.-) generation in response to high-glucose challenge. CONCLUSIONS: C242T single-nucleotide polymorphism causes p22(phox) structural changes that inhibit endothelial Nox2 activation and oxidative response to tumor necrosis factor-α or high-glucose stimulation. C242T single-nucleotide polymorphism may represent a natural protective mechanism against inflammatory cardiovascular diseases

Damage localization based on symbolic time series analysis

Copyright © 2014 John Wiley & Sons, Ltd. The objective of this paper is to localize damage in a single or multiple state at early stages of development on the basis of the principles of symbolic dynamics. Symbolic time series analysis (STSA) of noise-contaminated responses is used for feature extraction to detect and localize a gradually evolving deterioration in the structure according to the changes in the statistical behaviour of symbol sequences. Basically, in STSA, statistical features of the symbol sequence can be used to describe the dynamic status of the system. Symbolic dynamics has some useful characteristics making it highly demanded for implementation in real-time observation application such as SHM. First, it significantly reduces the dimension of information and provides information-rich representation of the underlying data. Second, symbolic dynamics and the set of statistical measures built upon it represent a solid framework to address the main challenges of the analysis of nonstationary time data. Finally, STSA often allows capturing the main features of the underlying system whilst alleviating the effects of harmful noise. The method presented in this paper consists of four primary steps: (i) acquisition of the time series data; (ii) creating the symbol space to produce symbol sequences on the basis of the wavelet transformed version of time series data; (iii) developing the symbol probability vectors to achieve anomaly measures; and (iv) localizing damage on the basis of any sudden variation in anomaly measure of different locations. The method was applied on a flexural beam and a 2-D planar truss bridge subjected to varying Gaussian excitation in presence of 2% white noise to examine the efficiency and limitations of the method. Simulation results under various damage conditions confi rmed the efficiency of the proposed approach for localization of gradually evolving deterioration in the structure; however, for the future work, the method needs to be verified by experimental data

An overview of distributed microgrid state estimation and control for smart grids

© 2015 by the authors; licensee MDPI, Basel, Switzerland. Given the significant concerns regarding carbon emission from the fossil fuels, global warming and energy crisis, the renewable distributed energy resources (DERs) are going to be integrated in the smart grid. This grid can spread the intelligence of the energy distribution and control system from the central unit to the long-distance remote areas, thus enabling accurate state estimation (SE) and wide-area real-time monitoring of these intermittent energy sources. In contrast to the traditional methods of SE, this paper proposes a novel accuracy dependent Kalman filter (KF) based microgrid SE for the smart grid that uses typical communication systems. Then this article proposes a discrete-time linear quadratic regulation to control the state deviations of the microgrid incorporating multiple DERs. Therefore, integrating these two approaches with application to the smart grid forms a novel contributions in green energy and control research communities. Finally, the simulation results show that the proposed KF based microgrid SE and control algorithm provides an accurate SE and control compared with the existing method

Factorial structure of the Chinese version of the 12-item General Health Questionnaire in adolescents

Aims. To evaluate the underlying factor structure of the Chinese version of General Health Questionnaire-12 using exploratory and confirmatory factor analyses in Chinese adolescents and find out which factor model proposed by previous empirical research is the best-fit model. Background. The 12-item General Health Questionnaire has been extensively used with adolescents in the West. Yet, it has not been used with adolescents in a Hong Kong Chinese context. Design. A cross-sectional study was employed. Method. Chinese students between the ages of 12-19 from four secondary schools were invited to participate in the study using the multiple-stage stratified random sampling method during the period from December 2007-February, 2008. The total sample size included in the final analysed was 1883. Results. The General Health Questionnaire-12 was found to be internally consistent. The results of exploratory factor analysis showed that there are two factors underlying the General Health Questionnaire-12. Of nine factor models were tested by means of confirmatory factor analysis, only three factor model: the eight-item two-factor model, 12-item three-factor model and 10-item two-factor model, demonstrated good model fit across all model fit indices. Conclusion. This study addressed a gap in the literature by evaluating the factorial structure of the Chinese version of General Health Questionnaire-12 using exploratory and confirmatory factor analyses in Chinese adolescents. The findings revealed that the eight-item two-factor model is the best-fit model. Relevance to clinical practice. The adolescent mental health problem is alarming and aggravating and warrants special attention. It is essential for community nurses to differentiate psychological distress in adolescents and to identify those adolescents who are at a higher risk of suffering from mental health problems. The availability of a valid and reliable instrument that measures adolescents' psychological distress is crucial before any nursing interventions to promote their mental health can be appropriately planned, implemented and evaluated. © 2009 Blackwell Publishing Ltd.postprin

Lattice Boltzmann modeling of boiling heat transfer: The boiling curve and the effects of wettability

A hybrid thermal lattice Boltzmann (LB) model is presented to simulate thermal multiphase flows with phase change based on an improved pseudopotential LB approach (Li et al., 2013). The present model does not suffer from the spurious term caused by the forcing-term effect, which was encountered in some previous thermal LB models for liquid–vapor phase change. Using the model, the liquid–vapor boiling process is simulated. The boiling curve together with the three boiling stages (nucleate boiling, transition boiling, and film boiling) is numerically reproduced in the LB community for the first time. The numerical results show that the basic features and the fundamental characteristics of boiling heat transfer are well captured, such as the severe fluctuation of transient heat flux in the transition boiling and the feature that the maximum heat transfer coefficient lies at a lower wall superheat than that of the maximum heat flux. Furthermore, the effects of the heating surface wettability on boiling heat transfer are investigated. It is found that an increase in contact angle promotes the onset of boiling but reduces the critical heat flux, and makes the boiling process enter into the film boiling regime at a lower wall superheat, which is consistent with the findings from experimental studies

Model Updating for Loading Capacity Estimation of Concrete Structures using Ambient Vibration

This paper presents a model updating approach for determining the loading capacity of a concrete structure utilising measured ambient vibration responses. The proposed method uses Operational Modal Analysis (OMA) with the Enhanced Frequency Domain Decomposition (EFDD) technique to identify the natural frequencies and mode shapes of an experimental replica specimen of a Sydney Harbour Bridge concrete jack arch component. For vibration testing, the structure is excited with ambient vibration recordings from the actual Sydney Harbour Bridge using a vibro tactile transducer. The vibration responses of the structure are measured using an array of strategically placed accelerometers. A numerical model is developed and updated using the vibrational characteristics with the aim of estimating the load capacity of the structure. The results show that the proposed updating method using partitioning has great potential to be used for determining the loading capacity of a structure as part of a Structural Health Monitoring (SHM) system

Containment of fast scanning computer network worms

This paper presents a mechanism for detecting and containing fast scanning computer network worms. The countermeasure mechanism, termed NEDAC, uses a behavioural detection technique that observes the absence of DNS resolution in newly initiated outgoing connections. Upon detection of abnormal behaviour by a host, based on the absence of DNS resolution, the detection system then invokes a data link containment system to block traffic from the host. The concept has been demonstrated using a developed prototype and tested in a virtualised network environment. An empirical analysis of network worm propagation has been conducted based on the characteristics of reported contemporary vulnerabilities to test the capabilities of the countermeasure mechanism. The results show that the developed mechanism is sensitive in detecting and blocking fast scanning worm infection at an early stage

Finite control set model predictive control-a powerful control algorithm for grid-connected power converters

© 2016 IEEE. This paper presents a detailed description of Finite Control Set Model Predictive Control applied to power converters. Some key features related to this methodology are presented and compared with model predictive control based space vector modulation methods. The basic models, principles, control diagrams, and simulation results are presented to provide a comparison between them. The analysis is performed on a three-phase/ two-level voltage source inverter, which is one of the most common converter topologies used in industry. Among the conclusions are the feasibility and great potential of Finite Control Set Model Predictive Control due to the advanced signal-processing capability, particularly for power systems with a reduced number of switching states and more complicated principles

Realization of a Tunable Artificial Atom at a Supercritically Charged Vacancy in Graphene

The remarkable electronic properties of graphene have fueled the vision of a graphene-based platform for lighter, faster and smarter electronics and computing applications. One of the challenges is to devise ways to tailor its electronic properties and to control its charge carriers. Here we show that a single atom vacancy in graphene can stably host a local charge and that this charge can be gradually built up by applying voltage pulses with the tip of a scanning tunneling microscope (STM). The response of the conduction electrons in graphene to the local charge is monitored with scanning tunneling and Landau level spectroscopy, and compared to numerical simulations. As the charge is increased, its interaction with the conduction electrons undergoes a transition into a supercritical regime 6-11 where itinerant electrons are trapped in a sequence of quasi-bound states which resemble an artificial atom. The quasi-bound electron states are detected by a strong enhancement of the density of states (DOS) within a disc centered on the vacancy site which is surrounded by halo of hole states. We further show that the quasi-bound states at the vacancy site are gate tunable and that the trapping mechanism can be turned on and off, providing a new mechanism to control and guide electrons in grapheneComment: 18 pages and 5 figures plus 14 pages and 15 figures of supplementary information. Nature Physics advance online publication, Feb 22 (2016