Modeling predictors of risky drug use behavior among male street laborers in urban Vietnam

Background The application of theoretical frameworks for modeling predictors of drug risk among male street laborers remains limited. The objective of this study was to test a modified version of the IMB (Information-Motivation-Behavioral Skills Model), which includes psychosocial stress, and compare this modified version with the original IMB model in terms of goodness-of-fit to predict risky drug use behavior among this population. Methods In a cross-sectional study, social mapping technique was conducted to recruit 450 male street laborers from 135 street venues across 13 districts of Hanoi city, Vietnam, for face-to-face interviews. Structural equation modeling (SEM) was used to analyze data from interviews. Results Overall measures of fit via SEM indicated that the original IMB model provided a better fit to the data than the modified version. Although the former model was able to predict a lesser variance than the latter (55% vs. 62%), it was of better fit. The findings suggest that men who are better informed and motivated for HIV prevention are more likely to report higher behavioral skills, which, in turn, are less likely to be engaged in risky drug use behavior. Conclusions This was the first application of the modified IMB model for drug use in men who were unskilled, unregistered laborers in urban settings. An AIDS prevention program for these men should not only distribute information and enhance motivations for HIV prevention, but consider interventions that could improve self-efficacy for preventing HIV infection. Future public health research and action may also consider broader factors such as structural social capital and social policy to alter the conditions that drive risky drug use among these men.

Modeling bus rapid transit station bus queuing for operational analysis

This paper presents mathematical models for BRT station operation, calibrated using microscopic simulation modelling. Models are presented for station capacity and bus queue length. No reliable model presently exists to estimate bus queue length. The proposed bus queue model is analogous to an unsignalized intersection queuing model.

Modeling Bus Rapid Transit station bus queuing for Bus Rapid Transit station bus operation analysis

Stations on Bus Rapid Transit (BRT) lines ordinarily control line capacity because they act as bottlenecks. At stations with passing lanes, congestion may occur when buses maneuvering into and out of the platform stopping lane interfere with bus flow, or when a queue of buses forms upstream of the station blocking inflow. We contend that, as bus inflow to the station area approaches capacity, queuing will become excessive in a manner similar to operation of a minor movement on an unsignalized intersection. This analogy is used to treat BRT station operation and to analyze the relationship between station queuing and capacity. In the first of three stages, we conducted microscopic simulation modeling to study and analyze operating characteristics of the station under near steady state conditions through output variables of capacity, degree of saturation and queuing. A mathematical model was then developed to estimate the relationship between average queue and degree of saturation and calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Finally, simulation results were calibrated and validated.

Establishing definitions and modeling public transport travel time variability

Public transport travel time variability (PTTV) is essential for understanding deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyses the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and researching the transit systems.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Motion planning and stochastic control with experimental validation on a planetary rover

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This model is used to construct a control policy for navigation to a goal region in a terrain map built using an on-board RGB-D camera. The terrain includes flat ground, small rocks, and non-traversable rocks. We report the results of 200 simulated and 35 experimental trials that validate the approach and demonstrate the value of considering control uncertainty in maintaining platform safety.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

The enemy of music : modeling the behavior of a cultural industry in crisis

The purpose of this explorative study is to contribute to the understanding of current music industry dynamics. The situation is undeniably quite dramatic: Since the turn of the millennium, the global music industry has declined by $ US 6.2 billion in value—a fall of 16.3% in constant dollar terms. IFPI, the trade organization representing the international recording industry, identifies a number of exogenous factors as the main drivers of the downturn. This article suggests that other factors, in addition to those identified by IFPI, may have contributed to the current difficulties. A model is presented which indicates that business strategies which were designed to cope with the challenging business environment have reduced product diversity, damaged profitability, and contributed to the problem they were intended to solve.

Modeling perceived influences on journalism : evidence from a cross-national survey of journalists

Surveying 1,700 journalists from seventeen countries, this study investigates perceived influences on news work. Analysis reveals a dimensional structure of six distinct domains—political, economic, organizational, professional, and procedural influences, as well as reference groups. Across countries, these six dimensions build up a hierarchical structure where organizational, professional, and procedural influences are perceived as more powerful limits to journalists' work than political and economic influences.

Modeling the effectiveness of counterterrorism interventions

After the terrorist attacks in the United States on 11 September 2001, terrorism and counter-terrorism efforts moved to the front of popular consciousness and became the focus of national security for governments worldwide. With this increased attention came an urgent interest in understanding and identifying what works in fighting terrorism (Belasco 2010). For Australia, understanding the relative effectiveness of counter-terrorism efforts in nearby neighbours of Indonesia, Thailand and the Philippines is highly relevant for our country's national security. Indonesia, Thailand and the Philippines are all countries that are important to Australia not just because of geographic proximity, but also because of a history of economic ties and the role these countries play as Australia’s regional partners...

A stochastic neighborhood conditional autoregressive model for spatial data

A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. An extension of CAR model is proposed in this article where the selection of the neighborhood depends on unknown parameter(s). This extension is called a Stochastic Neighborhood CAR (SNCAR) model. The resulting model shows flexibility in accurately estimating covariance structures for data generated from a variety of spatial covariance models. Specific examples are illustrated using data generated from some common spatial covariance functions as well as real data concerning radioactive contamination of the soil in Switzerland after the Chernobyl accident.

Wetlands : a perspective for mapping, monitoring, and modeling

Experience gained from numerous projects conducted by the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring Systems Laboratory in Las Vegas, Nevada has provided insight to functional issues of mapping, monitoring, and modeling of wetland habitats. Three case studies in poster form describe these issues pertinent to managing wetland resources as mandated under Federal laws. A multiphase project was initiated by the EPA Alaska operations office to provide detailed wetland mapping of arctic plant communities in an area under petroleum development pressure. Existing classification systems did not meet EPA needs. Therefore a Habitat Classification System (HCS) derived from aerial photography was compiled. In conjunction with this photointerpretive keys were developed. These products enable EPA personnel to map large inaccessible areas of the arctic coastal plain and evaluate the sensitivity of various wetland habitats relative to petroleum development needs.

Thermodynamic modeling of ethanol fumigation in a diesel engine

Due to rapidly diminishing international supplies of fossil fuels, such as petroleum and diesel, the cost of fuel is constantly increasing, leading to higher costs of living, as a result of the significant reliance of many industries on motor vehicles. Many technologies have been developed to replace part or all of a fossil fuel with bio-fuels. One of the dual fuel technologies is fumigation of ethanol in diesel engines, which injects ethanol into the intake air stream of the engine. The advantage of this is that it avoids any costly modification of the engine high pressure diesel injection system, while reducing the volume of diesel required and potentially increasing the power output and efficiency. This paper investigates the performance of a diesel engine, converted to implement ethanol fumigation. The project will use both existing experimental data, along with generating computer modeled results using the program AVL Boost. The data from both experiments and the numerical simulation indicate desirable results for the peak pressure and the indicated mean effective pressure (IMEP). Increase in ethanol substitution resulted in elevated combustion pressure and an increase in the IMEP, while the variation of ethanol injection location resulted in negligible change. These increases in cylinder pressure led to a higher work output and total efficiency in the engine as the ethanol substitution was increased. In comparing the numerical and experimental results, the simulation showed a slight elevation, due to the inaccuracies in the heat release models. Future work is required to improve the combustion model and investigate the effect of the variation of the location of ethanol injection.

Use of simple pharmacokinetic modeling to characterize exposure of Australians to perfluorooctanoic acid and perfluorooctane sulfonic acid

Perflurooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) have been used for a variety of applications including fluoropolymer processing, fire-fighting foams and surface treatments since the 1950s. Both PFOS and PFOA are polyfluoroalkyl chemicals (PFCs), man-made compounds that are persistent in the environment and humans; some PFCs have shown adverse effects in laboratory animals. Here we describe the application of a simple one compartment pharmacokinetic model to estimate total intakes of PFOA and PFOS for the general population of urban areas on the east coast of Australia. Key parameters for this model include the elimination rate constants and the volume of distribution within the body. A volume of distribution was calibrated for PFOA to a value of 170ml/kgbw using data from two communities in the United States where the residents' serum concentrations could be assumed to result primarily from a known and characterized source, drinking water contaminated with PFOA by a single fluoropolymer manufacturing facility. For PFOS, a value of 230ml/kgbw was used, based on adjustment of the PFOA value. Applying measured Australian serum data to the model gave mean+/-standard deviation intake estimates of PFOA of 1.6+/-0.3ng/kgbw/day for males and females >12years of age combined based on samples collected in 2002-2003 and 1.3+/-0.2ng/kg bw/day based on samples collected in 2006-2007. Mean intakes of PFOS were 2.7+/-0.5ng/kgbw/day for males and females >12years of age combined based on samples collected in 2002-2003, and 2.4+/-0.5ng/kgbw/day for the 2006-2007 samples. ANOVA analysis was run for PFOA intake and demonstrated significant differences by age group (p=0.03), sex (p=0.001) and date of collection (p<0.001). Estimated intake rates were highest in those aged >60years, higher in males compared to females, and higher in 2002-2003 compared to 2006-2007. The same results were seen for PFOS intake with significant differences by age group (p<0.001), sex (p=0.001) and date of collection (p=0.016).

Estimating present day extreme water level exceedance probabilities around the coastline of Australia : tropical cyclone-induced storm surges

The incidence of major storm surges in the last decade have dramatically emphasized the immense destructive capabilities of extreme water level events, particularly when driven by severe tropical cyclones. Given this risk, it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood and erosion management, engineering and for future land-use planning and to ensure the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. Australia has a long history of coastal flooding from tropical cyclones. Using a novel integration of two modeling techniques, this paper provides the first estimates of present day extreme water level exceedance probabilities around the whole coastline of Australia, and the first estimates that combine the influence of astronomical tides, storm surges generated by both extra-tropical and tropical cyclones, and seasonal and inter-annual variations in mean sea level. Initially, an analysis of tide gauge records has been used to assess the characteristics of tropical cyclone-induced surges around Australia. However, given the dearth (temporal and spatial) of information around much of the coastline, and therefore the inability of these gauge records to adequately describe the regional climatology, an observationally based stochastic tropical cyclone model has been developed to synthetically extend the tropical cyclone record to 10,000 years. Wind and pressure fields derived for these synthetically generated events have then been used to drive a hydrodynamic model of the Australian continental shelf region with annual maximum water levels extracted to estimate exceedance probabilities around the coastline. To validate this methodology, selected historic storm surge events have been simulated and resultant storm surges compared with gauge records. Tropical cyclone induced exceedance probabilities have been combined with estimates derived from a 61-year water level hindcast described in a companion paper to give a single estimate of present day extreme water level probabilities around the whole coastline of Australia. Results of this work are freely available to coastal engineers, managers and researchers via a web-based tool (www.sealevelrise.info). The described methodology could be applied to other regions of the world, like the US east coast, that are subject to both extra-tropical and tropical cyclones.