Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

Barrier coverage with wireless sensors aims at detecting intruders who attempt to cross a specific area, where wireless sensors are distributed remotely at random. This paper considers limited-power sensors with adjustable ranges deployed along a linear domain to form a barrier to detect intruding incidents. We introduce three objectives to minimize: 1) total power consumption while satisfying full coverage; 2) the number of active sensors to improve the reliability; and 3) the active sensor nodes' maximum sensing range to maintain fairness. We refer to the problem as the tradeoff barrier coverage (TBC) problem. With the aim of obtaining a better tradeoff among the three objectives, we present a multiobjective optimization framework based on multiobjective evolutionary algorithm (MOEA)/D, which is called problem specific MOEA/D (PS-MOEA/D). Specifically, we define a 2-tuple encoding scheme and introduce a cover-shrink algorithm to produce feasible and relatively optimal solutions. Subsequently, we incorporate problem-specific knowledge into local search, which allows search procedures for neighboring subproblems collaborate each other. By considering the problem characteristics, we analyze the complexity and incorporate a strategy of computational resource allocation into our algorithm. We validate our approach by comparing with four competitors through several most-used metrics. The experimental results demonstrate that PS-MOEA/D is effective and outperforms the four competitors in all the cases, which indicates that our approach is promising in dealing with TBC

Carbon monoxide and stroke: A time series study of ambient air pollution and emergency hospitalizations

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Quercetin Inhibited Murine Leukemia WEHI-3 Cells In Vivo and Promoted Immune Response

[[abstract]]Enhanced flavonoid consumption is closely related with a reduced cancer incidence as shown in epidemiological studies. Quercetin (3,5,7,3',4'-pentahydroxylflavone) is one of the active components of flavonoids which exist in natural plants, particularly in onions and fruits. It was reported that quercetin induced apoptosis in human cancer cell lines, including human leukemia HL-60 cells, but there is no available information as to its effects on leukemia cells in vivo. The purpose of the present studies was to focus on the in vivo effects or quercetin on leukemia WEHI-3 cells. The effects of quercetin on WEHI-3 cells injected into BALB/c mice were examined. Quercetin decreased the percentage of Mac-3 and CD11b markers, suggesting that the differentiation of the precursors of macrophages and T cells was inhibited. There was no effect on CD3 levels but increased CD19 levels. Quercetin decreased the weight of the spleen and liver compared with the olive oil treated animals. Quercetin stimulated macrophage phagocytosis or cells isolated from peritoneum. Quercetin also promoted natural killer cell activity. Based on pathological examination, an effect of quercetin was observed in the spleen of mice previously injected with WEHI-3 cells. Apparently, quercetin affects WEHI-3 cells in vivo. Copyright (C) 2009 John Wiley & Sons, Ltd

Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs

Real-world graphs generally have only one kind of tendency in their connections. These connections are either homophily-prone or heterophily-prone. While graphs with homophily-prone edges tend to connect nodes with the same class (i.e., intra-class nodes), heterophily-prone edges tend to build relationships between nodes with different classes (i.e., inter-class nodes). Existing GNNs only take the original graph during training. The problem with this approach is that it forgets to take into consideration the ``missing-half" structural information, that is, heterophily-prone topology for homophily-prone graphs and homophily-prone topology for heterophily-prone graphs. In our paper, we introduce Graph cOmplementAry Learning, namely GOAL, which consists of two components: graph complementation and complemented graph convolution. The first component finds the missing-half structural information for a given graph to complement it. The complemented graph has two sets of graphs including both homophily- and heterophily-prone topology. In the latter component, to handle complemented graphs, we design a new graph convolution from the perspective of optimisation. The experiment results show that GOAL consistently outperforms all baselines in eight real-world datasets.Comment: Accepted by ICML 202

Parental emotional management benefits family relationships: A randomized controlled trial in Hong Kong, China

There is a shortage of culturally appropriate, brief, preventive interventions designed to be sustainable and acceptable for community participants in nonwestern cultures. Parents’ ability to regulate their emotions is an important factor for psychological well-being of the family. In Chinese societies, emotional regulation may be more important in light of the cultural desirability of maintaining harmonious family relationships. The objectives of our randomized controlled trial were to test the effectiveness of our Effective Parenting Programme (EPP) to increase the use of emotional management strategies (primary outcome) and enhance the parent-child relationship (secondary outcome). We utilized design characteristics that promoted recruitment, retention, and intervention sustainability. We randomized a community sample of 412 Hong Kong middle- and low-income mothers of children aged 6–8 years to the EPP or attention control group. At 3, 6 and 12- month follow up, the Effective Parent Program group reported greater increases in the use of emotion management strategies during parent-child interactions, with small to medium effect size, and lower negative affect and greater positive affect, subjective happiness, satisfaction with the parent–child relationship, and family harmony, compared to the control group, with small to medium effect size. Our results provided evidence of effectiveness for a sustainable, preventive, culturally appropriate, cognitive behaviorally-based emotion management program, in a non-clinical setting for Chinese mothers.postprin

First Simultaneous Lidar Observations of Thermosphere‐Ionosphere Fe and Na (TIFe and TINa) Layers at McMurdo (77.84°S, 166.67°E), Antarctica With Concurrent Measurements of Aurora Activity, Enhanced Ionization Layers, and Converging Electric Field

We report the first simultaneous, common‐volume lidar observations of thermosphere‐ionosphere Fe (TIFe) and Na (TINa) layers in Antarctica. We also report the observational discovery of nearly one‐to‐one correspondence between TIFe and aurora activity, enhanced ionization layers, and converging electric fields. Distinctive TIFe layers have a peak density of ~384 cm−3 and the TIFe mixing ratio peaks around 123 km, ~5 times the mesospheric layer maximum. All evidence shows that Fe+ ion‐neutralization is the major formation mechanism of TIFe layers. The TINa mixing ratio often exhibits a broad peak at TIFe altitudes, providing evidence for in situ production via Na+ neutralization. However, the tenuous TINa layers persist long beyond TIFe disappearance and reveal gravity wave perturbations, suggesting a dynamic background of neutral Na, but not Fe, above 110 km. The striking differences between distinct TIFe and diffuse TINa suggest differential transport between Fe and Na, possibly due to mass separation

Ambient carbon monoxide and the risk of hospitalization due to chronic obstructive pulmonary disease

Data from recent experimental and clinical studies have indicated that lower concentrations of inhaled carbon monoxide might have beneficial antiinflammatory effects. Inhaled carbon monoxide has the potential to be a therapeutic agent for chronic obstructive pulmonary diseases (COPD). However, population-based epidemiologic studies of environmentally relevant carbon monoxide exposure have generated mixed findings. We conducted a time-series study in Hong Kong to estimate the association of short-term exposure to ambient carbon monoxide with emergency hospitalizations for COPD. We collected daily emergency hospital admission data and air pollution data from January 2001 to December 2007. We used log-linear Poisson models to estimate the associations between daily hospital admissions for COPD and the average daily concentrations of carbon monoxide while controlling for the traffic-related copollutants nitrogen dioxide and particulate matter with an aerodynamic diameter less than 2.5 μm. Results showed that ambient carbon monoxide was negatively associated with the risk of hospitalizations for COPD. After adjustment for levels nitrogen dioxide or particulate matter with an aerodynamic diameter less than 2.5 μm, the negative associations of carbon monoxide with COPD hospitalizations became stronger. The risk estimates were similar for female and male subjects. In conclusion, short-term exposure to ambient carbon monoxide was associated with a decreased risk of hospitalization for COPD, which suggests that carbon monoxide exposure provides some acute protection of against exacerbation of COPD.postprin

Subcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition

Background: Subcellular location prediction of proteins is an important and well-studied problem in bioinformatics. This is a problem of predicting which part in a cell a given protein is transported to, where an amino acid sequence of the protein is given as an input. This problem is becoming more important since information on subcellular location is helpful for annotation of proteins and genes and the number of complete genomes is rapidly increasing. Since existing predictors are based on various heuristics, it is important to develop a simple method with high prediction accuracies. Results: In this paper, we propose a novel and general predicting method by combining techniques for sequence alignment and feature vectors based on amino acid composition. We implemented this method with support vector machines on plant data sets extracted from the TargetP database. Through fivefold cross validation tests, the obtained overall accuracies and average MCC were 0.9096 and 0.8655 respectively. We also applied our method to other datasets including that of WoLF PSORT. Conclusion: Although there is a predictor which uses the information of gene ontology and yields higher accuracy than ours, our accuracies are higher than existing predictors which use only sequence information. Since such information as gene ontology can be obtained only for known proteins, our predictor is considered to be useful for subcellular location prediction of newly-discovered proteins. Furthermore, the idea of combination of alignment and amino acid frequency is novel and general so that it may be applied to other problems in bioinformatics. Our method for plant is also implemented as a web-system and available on http://sunflower.kuicr.kyoto-u.ac.jp/~tamura/slpfa.html webcite