Coupling an aerosol box model with one-dimensional flow: a tool for understanding observations of new particle formation events

Field observations of new particle formation and the subsequent particle growth are typically only possible at a fixed measurement location, and hence do not follow the temporal evolution of an air parcel in a Lagrangian sense. Standard analysis for determining formation and growth rates requires that the time-dependent formation rate and growth rate of the particles are spatially invariant; air parcel advection means that the observed temporal evolution of the particle size distribution at a fixed measurement location may not represent the true evolution if there are spatial variations in the formation and growth rates. Here we present a zero-dimensional aerosol box model coupled with one-dimensional atmospheric flow to describe the impact of advection on the evolution of simulated new particle formation events. Wind speed, particle formation rates and growth rates are input parameters that can vary as a function of time and location, using wind speed to connect location to time. The output simulates measurements at a fixed location; formation and growth rates of the particle mode can then be calculated from the simulated observations at a stationary point for different scenarios and be compared with the ‘true’ input parameters. Hence, we can investigate how spatial variations in the formation and growth rates of new particles would appear in observations of particle number size distributions at a fixed measurement site. We show that the particle size distribution and growth rate at a fixed location is dependent on the formation and growth parameters upwind, even if local conditions do not vary. We also show that different input parameters used may result in very similar simulated measurements. Erroneous interpretation of observations in terms of particle formation and growth rates, and the time span and areal extent of new particle formation, is possible if the spatial effects are not accounted for.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

Preferential location of lidocaine and etidocaine in lecithin bilayers as determined by EPR, fluorescence and H-2 NMR

We have examined the effect of the uncharged species of lidocaine (LDC) and etidocaine (EDC) on the acyl chain moiety of egg phosphatidylcholine liposomes. Changes in membrane organization caused by both anesthetics were detected through the use of EPR spin labels (5, 7 and 12 doxyl stearic acid methyl ester) or fluorescence probes (4, 6, 10, 16 pyrene-fatty acids). The disturbance caused by the LA was greater when the probes were inserted in more external positions of the acyl chain and decreased towards the hydrophobic core of the membrane. The results indicate a preferential insertion of LDC at the polar interface of the bilayer and in the first half of the acyl chain, for EDC. Additionally, 2 H NMR spectra of multilamellar liposomes composed by acyl chain-perdeutero DMPC and EPC (1:4 mol%) allowed the determination of the segmental order (S-mol) and dynamics (T-1) of the acyl chain region. In accordance to the fluorescence and EPR results, changes in molecular orientation and dynamics are more prominent if the LA preferential location is more superficial, as for LDC while EDC seems to organize the acyl chain region between carbons 2-8, which is indicative of its positioning. We propose that the preferential location of LDC and EDC inside the bilayers creates a ""transient site"", which is related to the anesthetic potency since it could modulate the access of these molecules to their binding site(s) in the voltage-gated sodium channel. (C) 2007 Elsevier B.V. All rights reserved.

Optimal retail location and CO2 emissions

In this paper, the p-median model is used to find the location of retail stores that minimizes CO2 emissions from consumer travel. The optimal location is then compared with the existing retail location,and the excess CO2 emissions compared with the optimal solution is calculated. The results show that by using the environmentally optimal location, CO2 emissions from consumer travel could be reduced by approximately 25percent. 

How do different densities in a network affect the optimal location of service centers?

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

An empirical test of the gravity p-median model

A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

How does the use of different road networks effect the optimal location of facilities in rural areas?

The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. Distance measure can vary if the accuracy of the road network varies. The rst aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to nd an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an asymmetrically distributed population, Dalecarlia. The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.

Testing the gravity p-median model empirically

Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

Robust extended Kalman filter based technique for location management in PCS networks

Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using Robust Extended Kalman Filter as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.

A conceptual model for recruitment and retention : allied health workforce enhancement in Western Victoria, Australia

Attracting and retaining allied health professionals in rural areas is a recognised problem in both Australia and overseas. Predicted increases in health needs will require strategic actions to enhance the rural workforce and its ability to deliver the required services. A range of factors in different domains has been associated with recruitment and retention in the allied health workforce. For example, factors can be related to the nature of the work, the personal needs, or the way an organisation is led. Some factors cannot be changed (eg geographical location of extended family) whereas others can be influenced (eg education, support, management styles). Recruitment and retention of allied health professionals is a challenging problem that deserves attention in all domains and preparedness to actively change established work practices, both individually as well as collectively, in order to cater for current and predicted health needs. Changes to enhance workforce outcomes can be implemented and evaluated using a cyclic model. The Allied Health Workforce Enhancement Project of the Greater Green Triangle University Department of Rural Health (GGT UDRH) is working towards increasing the number of allied health professionals in the south west of Victoria. Based on themes identified in the literature, an interactive model is being developed that addresses recruitment and retention factors in three domains: (1) personal or individual; (2) organisation; and (3) community.

Robust extended kalman filter applied to location tracking and trajectory prediction for PCS networks

Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using robust extended Kalman filter (REKF) as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model and more effective in comparison with the standard Kalman filter.

Location, location, location: exploring the importance of place for arts organisations

Many arts managers and marketers are looking intently at the importance of high-speed communication and other technologies for the creation of virtual places. These places in cyberspace can only be accessed via a computer terminal and high-speed telecommunications tools. This paper asserts that there is still much for managers and marketers to learn about the importance of physical spaces for the arts. We use a model of place and apply it to three Australian arts organisations located in heritage buildings. One organisation failed, the other changed ownership, the third moved location. The findings demonstrate the importance of place and of strategy in determining place. We note the tension between the strategy, the venue, the objects, and the essential task and call for further analysis of place(s) for the arts.

Location based power control for mobile devices in a cellular network

This paper provides location estimation based power control strategy for cellular radio systems via a location based interference management scheme. Our approach considers the carrier-to-interference as dependent on the transmitter and receiver separation distance and therefore an accurate estimation of the precise locations can provide the power critical mobile user to control the transition power accordingly. In this fully
distributed algorithms, we propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user’s closest mobile base station from the user’s location, heading and altitude. Our analysis demonstrates that this algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations and hence enable the user to transmit at the rate that is sufficient for the interference management. Our power control
algorithms based on this estimation converges to the desired power trajectory. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation.

Longitudinal evaluation of a risk-factor model for adolescent suicidality

This research developed two best-fitting structural equation models of risk factors for adolescent depression and suicidality: a core model, which included parenting factors, gender, depression, and suicidality, and an extended model, which also encompassed personality traits (Introversion and Impulsivity) and mood factors (Anxiety and Anger). Further, this research investigated the consistency of model fit across time (Le., 1 month & 12 months) and samples, and explored the effectiveness of the ReachOut! Internet site as a psychoeducational prevention strategy for adolescent depression and suicidality. Gender, age, and location differences were also explored. Participants were 185 Year-9 students and 93 Year-10 students aged 14 - 16 years, from seven secondary schools in regional and rural Victoria. Students were given a survey which included the Parental Bonding Instrument (Parker, Tupling, & Brown, 1979), the Millon Adolescent Personality Inventory (Millon, Green, & Meagher, 1982), the Profile of Mood States Inventory (McNair & Lorr, 1964), items on suicidal behaviour including some questions from the Revised Adolescent Suicide Questionnaire (Pearce & Martin, 1994), and questions on loss and general demographics. Results supported an indirect model of risk factors, with family factors directly influencing personality factors, which in turn influenced mood factors, including depression, which then influenced suicidality. At the theoretical level, results supported Attachment Theory (Bowlby, 1969), demonstrating that perceived parenting styles that are warm and not overly controlling are more conducive to an adolescent's emotional well-being than are parenting styles that are cold and controlling. Further, results supported Millon's theory of personality (1981), demonstrating that parenting style influences a child's personality. Short-term intervention effects from the internet site were a decrease in Introversion for the full sample, and decreased Inhibition and Suicidality for a high-risk subgroup. Long-term age effects were decreased Inhibition and increased Anxiety for the fall sample. There was also a probable intervention effect for Depression for the high-risk subgroup. No location differences for the risk factors were found between regional and rural areas.