Deterrence of drug driving: The impact of the ACT drug driving legislation and detection techniques

The study sought to explore the initial impact of the ACT's implementation of roadside oral fluid drug screening program. The results suggest that a number of individuals reported intentions to drug drive in the future. The classical deterrence theory variables of certainty of apprehension, severity and swiftness of sanctions were not predictive of intentions to drug drive in the future. In contrast, having avoided apprehension and having known of others that have avoided apprehension were predictive of intentions to drug drive in the future. Increasing perceptions of the certainty of apprehension, increased testing frequency, and increased awareness of the oral fluid drug screening program could potentially lead to reductions of drug driving and result in safer road environment for all ACT community members.

Process visualization techniques for multi-perspective process comparisons

Organizations executing similar business processes need to understand the differences and similarities in activities performed across work environments. Presently, research interest is directed towards the potential of visualization for the display of process models, to support users in their analysis tasks. Although recent literature in process mining and comparison provide several methods and algorithms to perform process and log comparison, few contributions explore novel visualization approaches. This paper analyses process comparison from a design perspective, providing some practical visualization techniques as anal- ysis solutions (/to support process analysis). The design of the visual comparison has been tackled through three different points of view: the general model, the projected model and the side-by-side comparison in order to support the needs of business analysts. A case study is presented showing the application of process mining and visualization techniques to patient treatment across two Australian hospitals.

Analytical study of implementation issues of NTRU

Nth-Dimensional Truncated Polynomial Ring (NTRU) is a lattice-based public-key cryptosystem that offers encryption and digital signature solutions. It was designed by Silverman, Hoffstein and Pipher. The NTRU cryptosystem was patented by NTRU Cryptosystems Inc. (which was later acquired by Security Innovations) and available as IEEE 1363.1 and X9.98 standards. NTRU is resistant to attacks based on Quantum computing, to which the standard RSA and ECC public-key cryptosystems are vulnerable to. In addition, NTRU has higher performance advantages over these cryptosystems. Considering this importance of NTRU, it is highly recommended to adopt NTRU as part of a cipher suite along with widely used cryptosystems for internet security protocols and applications. In this paper, we present our analytical study on the implementation of NTRU encryption scheme which serves as a guideline for security practitioners who are novice to lattice-based cryptography or even cryptography. In particular, we show some non-trivial issues that should be considered towards a secure and efficient NTRU implementation.

Excitation of bound plasmons along nanoscale stripe waveguides: A comparison of end and grating coupling techniques

In this paper we excite bound long range stripe plasmon modes with a highly focused laser beam. We demonstrate highly confined plasmons propagating along a 50 μm long silver stripe 750 nm wide and 30 nm thick. Two excitation techniques were studied: focusing the laser spot onto the waveguide end and focusing the laser spot onto a silver grating. By comparing the intensity of the out-coupling photons at the end of the stripe for both grating and end excitation we are able to show that gratings provide an increase of a factor of two in the output intensity and thus out-coupling of plasmons excited by this technique are easier to detect. Authors expect that the outcome of this paper will prove beneficial for the development of passive nano-optical devices based on stripe waveguides, by providing insight into the different excitation techniques available and the advantages of each technique.

Techniques to effectively buffer schedules in the face of uncertainties

Resource assignment and scheduling is a difficult task when job processing times are stochastic, and resources are to be used for both known and unknown demand. To operate effectively within such an environment, several novel strategies are investigated. The first focuses upon the creation of a robust schedule, and utilises the concept of strategically placed idle time (i.e. buffering). The second approach introduces the idea of maintaining a number of free resources at each time, and culminates in another form of strategically placed buffering. The attraction of these approaches is that they are easy to grasp conceptually, and mimic what practitioners already do in practice. Our extensive numerical testing has shown that these techniques ensure more prompt job processing, and reduced job cancellations and waiting time. They are effective in the considered setting and could easily be adapted for many real life problems, for instance those in health care. This article has more importantly demonstrated that integrating the two approaches is a better strategy and will provide an effective stochastic scheduling approach.

A review on prognostic techniques for non-stationary and non-linear rotating systems

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

Household carbon emission research: An analytical review of measurement, influencing factors and mitigation prospects

Greenhouse gas (GHG) emissions are simultaneously exhausting the world's supply of fossil fuels and threatening the global climate. In many developing countries, significant improvement in living standards in recent years due to the accelerating development of their economies has resulted in a disproportionate increase in household energy consumption. Therefore, a major reduction in household carbon emissions (HCEs) is essential if global carbon reduction targets are to be met. To do this, major Organisation for Economic Co-operation and Development (OECD) states have already implemented policies to alleviate the negative environmental effects of household behaviors and less carbon-intensive technologies are also proposed to promote energy efficiency and reduce carbon emissions. However, before any further remedial actions can be contemplated, though, it is important to fully understand the actual causes of such large HCEs and help researchers both gain deep insights into the development of the research domain and identify valuable research topics for future study. This paper reviews existing literature focusing on the domain of HCEs. This critical review provides a systematic understanding of current work in the field, describing the factors influencing HCEs under the themes of household income, household size, age, education level, location, gender and rebound effects. The main quantification methodologies of input–output models, life cycle assessment and emission coefficient methods are also presented, and the proposed measures to mitigate HCEs at the policy, technology and consumer levels. Finally, the limitations of work done to date and further research directions are identified for the benefit of future studies.

Analytical study of osteoporosis of maxilla in ovariectomized rats

The project applied analytical facilities to characterize the composition and mechanical properties of osteoporosis in maxillary bone using an ovariectomized rat model. It was found that osteoporotic jaw bone contained different amount of trace elements in comparison with the normal bone, which plays a significant role in bone quality. The knowledge generated from the study will assist the treatment of jaw bone fracture and dental implant placement.

Analysis of complex molecular systems: The impact of multivariate analysis for resolving the interactions of small molecules with biopolymers - a review

This review is focused on the impact of chemometrics for resolving data sets collected from investigations of the interactions of small molecules with biopolymers. These samples have been analyzed with various instrumental techniques, such as fluorescence, ultraviolet–visible spectroscopy, and voltammetry. The impact of two powerful and demonstrably useful multivariate methods for resolution of complex data—multivariate curve resolution–alternating least squares (MCR–ALS) and parallel factor analysis (PARAFAC)—is highlighted through analysis of applications involving the interactions of small molecules with the biopolymers, serum albumin, and deoxyribonucleic acid. The outcomes illustrated that significant information extracted by the chemometric methods was unattainable by simple, univariate data analysis. In addition, although the techniques used to collect data were confined to ultraviolet–visible spectroscopy, fluorescence spectroscopy, circular dichroism, and voltammetry, data profiles produced by other techniques may also be processed. Topics considered including binding sites and modes, cooperative and competitive small molecule binding, kinetics, and thermodynamics of ligand binding, and the folding and unfolding of biopolymers. Applications of the MCR–ALS and PARAFAC methods reviewed were primarily published between 2008 and 2013.

Determination of dimethyl sulfide in gas samples by single photon ionization time of flight mass spectrometry

It is difficult to determine sulfur-containing volatile organic compounds in the atmosphere because of their reactivity. Primary off-line techniques may suffer losses of analytes during the transportation from field to laboratory and sample preparation. In this study, a novel method was developed to directly measure dimethyl sulfide at parts-per-billion concentration levels in the atmosphere using vacuum ultraviolet single photon ionization time-of-flight mass spectrometry. This technique offers continuous sampling at a response rate of one measurement per second, or cumulative measurements over longer time periods. Laboratory prepared samples of different concentrations of dimethyl sulfide in pure nitrogen gas were analyzed at several sampling frequencies. Good precision was achieved using sampling periods of at least 60 seconds with a relative standard deviation of less than 25%. The detection limit for dimethyl sulfide was below the 3 ppb olfactory threshold. These results demonstrate that single photon ionization time-of-flight mass spectrometry is a valuable tool for rapid, real-time measurements of sulfur-containing organic compounds in the air.

Hybrid metaheuristic techniques for optimising sugarcane rail operations

Mixed integer programming and parallel-machine job shop scheduling are used to solve the sugarcane rail transport scheduling problem. Constructive heuristics and metaheuristics were developed to produce a more efficient scheduling system and so reduce operating costs. The solutions were tested on small and large size problems. High-quality solutions and improved CPU time are the result of developing new hybrid techniques which consist of different ways of integrating simulated annealing and Tabu search techniques.

Measuring load of phosphate in the environment by passive sampling techniques: An introduction

Phosphorus has a number of indispensable biochemical roles, but its natural deposition and the low solubility of phosphates as well as their rapid transformation to insoluble forms make the element commonly the growth-limiting nutrient, particularly in aquatic ecosystems. Famously, phosphorus that reaches water bodies is commonly the main cause of eutrophication. This undesirable process can severely affect many aquatic biotas in the world. More management practices are proposed but long-term monitoring of phosphorus level is necessary to ensure that the eutrophication won't occur. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing flow proportional load as well as representative average of concentrations of phosphorus in the environment. Although some types of passive samplers are commercially available, their uses are still scarcely reported in the literature. In Japan, there is limited application of passive sampling technique to monitor phosphorus even in the field of agricultural environment. This paper aims to introduce the relatively new P-sampling techniques and their potential to use in environmental monitoring studies.

Applications of passive sampling techniques in monitoring organic pollutants in the environment

As there are a myriad of micro organic pollutants that can affect the well-being of human and other organisms in the environment the need for an effective monitoring tool is eminent. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing time-integrated load as well as representative average of concentrations of pollutants in the environment. Those techniques have been applied to monitor many pollutants caused by agricultural activities, i.e. residues of pesticides, veterinary drugs and so on. Several types of passive samplers are commercially available and their uses are widely accepted. However, not many applications of those techniques have been found in Japan, especially in the field of agricultural environment. This paper aims to introduce the field of passive sampling and then to describe some applications of passive sampling techniques in environmental monitoring studies related to the agriculture industry.

Raman spectroscopy techniques for detection of energetic materials at high and low concentration

This thesis presents the development of a rapid, sensitive and reproducible spectroscopic method for the detection of TNT in forensic and environmental applications. Simple nano sensors prepared by cost effective methods were utilized as sensitive platforms for the detection of TNT by surface enhanced Raman spectroscopy. The optimization of the substrate and the careful selection of a suitable recognition molecule contributed to the significant improvements of sensitive and selective targeting over current detection methods. The work presented in this thesis paves the way for effective detection and monitoring of explosives residues in law enforcement and environmental health applications.