Observations of HONO by laser-induced fluorescence at the South Pole during ANTCI 2003

Observations of nitrous acid (HONO) by laser-induced fluorescence (LIF) at the South Pole taken during the Antarctic Troposphere Chemistry Investigation (ANTCI), which took place over the time period of Nov. 15, 2003 to Jan. 4, 2004, are presented here. The median observed mixing ratio of HONO 10 m above the snow was 5.8 pptv (mean value 6.3 pptv) with a maximum of 18.2 pptv on Nov 30th, Dec 1st, 3rd, 15th, 17th, 21st, 22nd, 25th, 27th and 28th. The measurement uncertainty is ±35%. The LIF HONO observations are compared to concurrent HONO observations performed by mist chamber/ion chromatography (MC/IC). The HONO levels reported by MC/IC are about 7.2 ± 2.3 times higher than those reported by LIF. Citation: Liao, W., A. T. Case, J. Mastromarino, D. Tan, and J. E. Dibb (2006), Observations of HONO by laser-induced fluorescence at the South Pole during ANTCI 2003, Geophys. Res. Lett., 33, L09810, doi:10.1029/2005GL025470

Scalable Mining of Common Routes in Mobile Communication Network Traffic Data

A probabilistic method for inferring common routes from mobile communication network traffic data is presented. Besides providing mobility information, valuable in a multitude of application areas, the method has the dual purpose of enabling efficient coarse-graining as well as anonymisation by mapping individual sequences onto common routes. The approach is to represent spatial trajectories by Cell ID sequences that are grouped into routes using locality-sensitive hashing and graph clustering. The method is demonstrated to be scalable, and to accurately group sequences using an evaluation set of GPS tagged data

Assessing the integrity of steel structural components with stress raisers using the Theory of Critical Distances

This paper assesses and evaluates the detrimental effect of standard and complex geometrical features on the static strength of samples made of Q460 steel. The experimental results generated by testing four types of notched specimens were analyzed using the Theory of Critical Distances (TCD). The considered configurations included uniaxial tension tests on standard notched round bars and double-side U-notched flat plate specimens. In particular, our attention was focused on the fracture behavior of two specimens containing complex geometrical features subjected to pure-shear and tensile-shear local stress states. The common feature of these two notched specimens was that cracks were seen to initiate, within the material, away from the stress raisers, even though obvious stress concentrations existed at notch tip. The performed validation exercise confirms the accuracy and reliability of the linear-elastic TCD in estimating the fracture initiation position and static strength of standard notched round bars and double-side U-notched flat plate specimens. In the meantime, the linear-elastic method proposed in this paper can also be used as an effective approach to assess the fracture behavior of metallic components having complex geometry

On the Connection Between Momentum Cutoff and Operator Cutoff Regularizations

Operator cutoff regularization based on the original Schwinger's proper-time formalism is examined. By constructing a regulating smearing function for the proper-time integration, we show how this regularization scheme simulates the usual momentum cutoff prescription yet preserves gauge symmetry even in the presence of the cutoff scales. Similarity between the operator cutoff regularization and the method of higher (covariant) derivatives is also observed. The invariant nature of the operator cutoff regularization makes it a promising tool for exploring the renormalization group flow of gauge theories in the spirit of Wilson-Kadanoff blocking transformation.Comment: 28 pages in plain TeX, no figures. revised and expande

Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition

This paper contributes to the challenge of skeleton-based human action recognition in videos. The key step is to develop a generic network architecture to extract discriminative features for the spatio-temporal skeleton data. In this paper, we propose a novel module, namely Logsig-RNN, which is the combination of the log-signature layer and recurrent type neural networks (RNNs). The former one comes from the mathematically principled technology of signatures and log-signatures as representations for streamed data, which can manage high sample rate streams, non-uniform sampling and time series of variable length. It serves as an enhancement of the recurrent layer, which can be conveniently plugged into neural networks. Besides we propose two path transformation layers to significantly reduce path dimension while retaining the essential information fed into the Logsig-RNN module. (The network architecture is illustrated in Figure 1 (Right).) Finally, numerical results demonstrate that replacing the RNN module by the LogsigRNN module in SOTA networks consistently improves the performance on both Chalearn gesture data and NTU RGB+D 120 action data in terms of accuracy and robustness. In particular, we achieve the state-of-the-art accuracy on Chalearn2013 gesture data by combining simple path transformation layers with the Logsig-RNN

Chinese immigrant parents' vaccination decision making for children: A qualitative analysis

Background: While immunization coverage rates for childhood routine vaccines in Hong Kong are almost 100%, the uptake rates of optional vaccines remain suboptimal. Understanding parental decision-making for children's vaccination is important, particularly among minority groups who are most vulnerable and underserved. This study explored how a subsample of new immigrant mothers from mainland China, a rapidly-growing subpopulation in Hong Kong, made decisions on various childhood and adolescent vaccines for their offspring, and identified key influences affecting their decision making. Methods. Semi-structured in-depth interviews were conducted with 23 Chinese new immigrant mothers recruited by purposive sampling. All interviews were audio-taped, transcribed and analyzed using a Grounded Theory approach. Results: Participants' conversation revealed five underlying themes which influenced parents' vaccination decision-making: (1) Institutional factors, (2) Insufficient vaccination knowledge and advice, (3) Affective impacts on motivation, (4) Vaccination barriers, and (5) Social influences. The role of social norms appeared overwhelmingly salient influencing parents' vaccination decision making. Institutional factors shaped parent's perceptions of vaccination necessity. Fear of vaccine-targeted diseases was a key motivating factor for parents adopting vaccination. Insufficient knowledge about vaccines and targeted diseases, lack of advice from health professionals and, if provided, suspicions regarding the motivations for such advice were common issues. Vaccination cost was a major barrier for many new immigrant parents. Conclusions: Social norms play a key role influencing parental vaccination decision-making. Insight gained from this study will help inform healthcare providers in vaccination communication and policymakers in future vaccination programme. © 2014 Wang et al.; licensee BioMed Central Ltd.Link_to_subscribed_fulltex

The cosmological origin of Higgs particles

A proposal of the cosmological origin of Higgs particles is given. We show, that the Higgs field could be created from the vacuum quantum conformal fluctuation of Anti-de Sitter space-time, the spontaneous breaking of vacuum symmetry, and the mass of Higgs particle are related to the cosmological constant of our universe,especially the theoretical estimated mass m$_{H}$ of Higgs particles is m$_{H}=\sqrt{-2\mu ^{2}}$ =$\sqrt{|\Lambda /\pi}$.Comment: 7 pages,no figure

Anxiety, worry and cognitive risk estimate in relation to protective behaviors during the 2009 influenza A/H1N1 pandemic in Hong Kong: Ten cross-sectional surveys

Background: Few studies have investigated associations between psychological and behavioral indices throughout a major epidemic. This study was aimed to compare the strength of associations between different cognitive and affective measures of risk and self-reported protective behaviors in a series of ten cross-sectional surveys conducted throughout the first wave of influenza A/H1N1 pandemic.Methods: All surveys were conducted using questionnaire-based telephone interviews, with random digit dialing to recruit adults from the general population. Measures of anxiety and worry (affective) and perceived risk (cognitive) regarding A/H1N1 were made in 10 serial surveys. Multivariate logistic regression models were used to estimate the cognitive/affective-behavioral associations in each survey while multilevel logistic models were conducted to estimate the average effects of each cognitive/affective measure on adoption of protective behaviors throughout the ten surveys.Results: Excepting state anxiety, other affective measures including " anticipated worry" , " experienced worry" and " current worry" specific to A/H1N1 risk were consistently and strongly associated with adoption of protective behaviors across different survey periods. However, the cognitive-behavioral associations were weaker and inconsistent across the ten surveys. Perceived A/H1N1 severity relative to SARS had stronger associations with adoption of protective behaviors in the late epidemic periods than in the early epidemic periods.Conclusion: Risk-specific worries appear to be significantly associated with the adoption of protective behaviors at different epidemic stages, whereas cognitive measures may become more important in understanding people's behavioral responses later in epidemics. Future epidemic-related psycho-behavioral research should include more affective-loaded measures of risk. © 2014 Liao et al.; licensee BioMed Central Ltd.published_or_final_versio