Raman spectroscopic study of the hydroxy-arsenate mineral pharmacolite Ca(HAsO4)•2H2O : implications for aquifer and sediment remediation

The removal of arsenate anions from aqueous media, sediments and wasted soils is of environmental significance. The reaction of gypsum with the arsenate anion results in pharmacolite mineral formation, together with related minerals. Raman and infrared spectroscopy have been used to study the mineral pharmacolite Ca(HAsO4)•2H2O. The mineral is characterised by an intense Raman band at 865 cm-1 assigned to the (AsO4)3- symmetric stretching mode. The equivalent infrared band is found at 864 cm-1. The low intensity Raman band at 886 cm-1 provides evidence for (AsO3OH)2-. A series of overlapping bands in the 300 to 450 cm-1 are attributed to ν2 and ν4 bending modes. Prominent Raman bands at around 3187 cm-1 are assigned to water OH stretching vibrations and the two sharp bands at 3425 and 3526 cm-1 to the OH stretching vibrations of (HOAsO3) units.

The application of neural networks to induction machine control

Neural networks (NNs) are discussed in connection with their possible use in induction machine drives. The mathematical model of the NN as well as a commonly used learning algorithm is presented. Possible applications of NNs to induction machine control are discussed. A simulation of an NN successfully identifying the nonlinear multivariable model of an induction-machine stator transfer function is presented. Previously published applications are discussed, and some possible future applications are proposed.

Construction, application and validation of selection evaluation model (SEM) for intelligent HVAC control system

Design teams are confronted with the quandary of choosing apposite building control systems to suit the needs of particular intelligent building projects, due to the availability of innumerable ‘intelligent’ building products and a dearth of inclusive evaluation tools. This paper is organised to develop a model for facilitating the selection evaluation for intelligent HVAC control systems for commercial intelligent buildings. To achieve these objectives, systematic research activities have been conducted to first develop, test and refine the general conceptual model using consecutive surveys; then, to convert the developed conceptual framework into a practical model; and, finally, to evaluate the effectiveness of the model by means of expert validation. The results of the surveys are that ‘total energy use’ is perceived as the top selection criterion, followed by the‘system reliability and stability’, ‘operating and maintenance costs’, and ‘control of indoor humidity and temperature’. This research not only presents a systematic and structured approach to evaluate candidate intelligent HVAC control system against the critical selection criteria (CSC), but it also suggests a benchmark for the selection of one control system candidate against another.

Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

Further notes on the application of zero-inflated models in highway safety

The intent of this note is to succinctly articulate additional points that were not provided in the original paper (Lord et al., 2005) and to help clarify a collective reluctance to adopt zero-inflated (ZI) models for modeling highway safety data. A dialogue on this important issue, just one of many important safety modeling issues, is healthy discourse on the path towards improved safety modeling. This note first provides a summary of prior findings and conclusions of the original paper. It then presents two critical and relevant issues: the maximizing statistical fit fallacy and logic problems with the ZI model in highway safety modeling. Finally, we provide brief conclusions.

Research and application of Building Information Modelling (BIM) in the Architecture, Engineering and Construction (AEC) industry : a review and direction for future research

With an increasing level of collaboration amongst researchers, software developers and industry practitioners in the past three decades, building information modelling (BIM) is now recognized as an emerging technological and procedural shift within the architect, engineering and construction (AEC) industry. BIM is not only considered as a way to make a profound impact on the professions of AEC, but is also regarded as an approach to assist the industry to develop new ways of thinking and practice. Despite the widespread development and recognition of BIM, a succinct and systematic review of the existing BIM research and achievement is scarce. It is also necessary to take stock on existing applications and have a fresh look at where BIM should be heading and how it can benefit from the advances being made. This paper first presents a review of BIM research and achievement in AEC industry. A number of suggestions are then made for future research in BIM. This paper maintains that the value of BIM during design and construction phases is well documented over the last decade, and new research needs to expand the level of development and analysis from design/build stage to postconstruction and facility asset management. New research in BIM could also move beyond the traditional building type to managing the broader range of facilities and built assets and providing preventative maintenance schedules for sustainable and intelligent buildings

Application of reinforcement learning in an open railway access market price negotiation

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

Application of reliability-centred maintenance technology on electric trains

This paper demonstrates the application of the reliability-centred maintenance (RCM) process to analyse and develop preventive maintenance tasks for electric multiple units (EMU) in the East Rail of the Kowloon-Canton Railway Corporation (KCRC). Two systems, the 25 kV electrical power supply and the air-conditioning system of the EMU, have been chosen for the study. RCM approach on the two systems is delineated step by step in the paper. This study confirms the feasibility and effectiveness of RCM applications on the maintenance of electric trains.

Parallel linear system solution and its application to railway power network simulation

The Streaming SIMD extension (SSE) is a special feature embedded in the Intel Pentium III and IV classes of microprocessors. It enables the execution of SIMD type operations to exploit data parallelism. This article presents improving computation performance of a railway network simulator by means of SSE. Voltage and current at various points of the supply system to an electrified railway line are crucial for design, daily operation and planning. With computer simulation, their time-variations can be attained by solving a matrix equation, whose size mainly depends upon the number of trains present in the system. A large coefficient matrix, as a result of congested railway line, inevitably leads to heavier computational demand and hence jeopardizes the simulation speed. With the special architectural features of the latest processors on PC platforms, significant speed-up in computations can be achieved.

A new method to quantify the application thickness of sunscreen on skin

Proper application of sunscreen is essential as an effective public health strategy for skin cancer prevention. Insufficient application is common among sunbathers, results in decreased sun protection and may therefore lead to increased UV damage of the skin. However, no objective measure of sunscreen application thickness (SAT) is currently available for field-based use. We present a method to detect SAT on human skin for determining the amount of sunscreen applied and thus enabling comparisons to manufacturer recommendations. Using a skin swabbing method and subsequent spectrophotometric analysis, we were able to determine SAT on human skin. A swabbing method was used to derive SAT on skin (in mg sunscreen per cm2 of skin area) through the concentration–absorption relationship of sunscreen determined in laboratory experiments. Analysis differentiated SATs between 0.25 and 4 mg cm−2 and showed a small but significant decrease in concentration over time postapplication. A field study was performed, in which the heterogeneity of sunscreen application could be investigated. The proposed method is a low cost, noninvasive method for the determination of SAT on skin and it can be used as a valid tool in field- and population-based studies.

Generation evolution in GA application on railway traffic control

This paper presents a Genetic Algorithms (GA) approach to resolve traffic conflicts at a railway junction. The formulation of the problem for the suitable application of GA will be discussed and three neighborhoods have been proposed for generation evolution. The performance of the GA is evaluated by computer simulation. This study paves the way for more applications of artificial intelligence techniques on a rather conservative industry.

The application of profluorescent nitroxides to detect reactive oxygen species derived from combustion-generated particulate matter: Cigarette smoke – a case study

Reactive oxygen species (ROS) and related free radicals are considered to be key factors underpinning the various adverse health effects associated with exposure to ambient particulate matter. Therefore, measurement of ROS is a crucial factor for assessing the potential toxicity of particles. In this work, a novel profluorescent nitroxide, BPEAnit, was investigated as a probe for detecting particle-derived ROS. BPEAnit has a very low fluorescence emission due to inherent quenching by the nitroxide group, but upon radical trapping or redox activity, a strong fluorescence is observed. BPEAnit was tested for detection of ROS present in mainstream and sidestream cigarette smoke. In the case of mainstream cigarette smoke, there was a linear increase in fluorescence intensity with an increasing number of cigarette puffs, equivalent to an average of 101 nmol ROS per cigarette based on the number of moles of the probe reacted. Sidestream cigarette smoke sampled from an environmental chamber exposed BPEAnit to much lower concentrations of particles, but still resulted in a clearly detectible increase in fluorescence intensity with sampling time. It was calculated that the amount of ROS was equivalent to 50 ± 2 nmol per mg of particulate matter; however, this value decreased with ageing of the particles in the chamber. Overall, BPEAnit was shown to provide a sensitive response related to the oxidative capacity of the particulate matter. These findings present a good basis for employing the new BPEAnit probe for the investigation of particle-related ROS generated from cigarette smoke as well as from other combustion sources.

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

Application of chemometrics to analysis of soil pollutants

This overview focuses on the application of chemometrics techniques for the investigation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs) and metals because these two important and very diverse groups of pollutants are ubiquitous in soils. The salient features of various studies carried out in the micro- and recreational environments of humans, are highlighted in the context of the various multivariate statistical techniques available across discipline boundaries that have been effectively used in soil studies. Particular attention is paid to techniques employed in the geosciences that may be effectively utilized for environmental soil studies; classical multivariate approaches that may be used in isolation or as complementary methods to these are also discussed. Chemometrics techniques widely applied in atmospheric studies for identifying sources of pollutants or for determining the importance of contaminant source contributions to a particular site, have seen little use in soil studies, but may be effectively employed in such investigations. Suitable programs are also available for suggesting mitigating measures in cases of soil contamination, and these are also considered. Specific techniques reviewed include pattern recognition techniques such as Principal Components Analysis (PCA), Fuzzy Clustering (FC) and Cluster Analysis (CA); geostatistical tools include variograms, Geographical Information Systems (GIS), contour mapping and kriging; source identification and contribution estimation methods reviewed include Positive Matrix Factorisation (PMF), and Principal Component Analysis on Absolute Principal Component Scores (PCA/APCS). Mitigating measures to limit or eliminate pollutant sources may be suggested through the use of ranking analysis and multi criteria decision making methods (MCDM). These methods are mainly represented in this review by studies employing the Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and its associated graphic output, Geometrical Analysis for Interactive Aid (GAIA).