Driving speed is altered by monocular Neutral Density filters : the Enright phenomenon

Introduction: An observer, looking sideways from a moving vehicle, while wearing a neutral density filter over one eye, can have a distorted perception of speed, known as the Enright phenomenon. The purpose of this study was to determine how the Enright phenomenon influences driving behaviour. Methods: A geometric model of the Enright phenomenon was developed. Ten young, visually normal, participants (mean age = 25.4 years) were tested on a straight section of a closed driving circuit and instructed to look out of the right side of the vehicle and drive at either 40 Km/h or 60 Km/h under the following binocular viewing conditions: with a 0.9 ND filter over the left eye (leading eye); 0.9 ND filter over the right eye (trailing eye); 0.9 ND filters over both eyes, and with no filters over either eye. The order of filter conditions was randomised and the speed driven recorded for each condition. Results: Speed judgments did not differ significantly between the two baseline conditions (no filters and both eyes filtered) for either speed tested. For the baseline conditions, when subjects were asked to drive at 60 Km/h they matched this speed well (61 ± 10.2 Km/h) but drove significantly faster than requested (51.6 ± 9.4 Km/h) when asked to drive at 40 Km/h. Subjects significantly exceeded baseline speeds by 8.7± 5.0 Km/h, when the trailing eye was filtered and travelled slower than baseline speeds by 3.7± 4.6 Km/h when the leading eye was filtered. Conclusions: This is the first quantitative study demonstrating how the Enright effect can influence perceptions of driving speed, and demonstrates that monocular filtering of an eye can significantly impact driving speeds, albeit to a lesser extent than predicted by geometric models of the phenomenon.

Integrating efficient filtration and visible-light photocatalysis by loading Ag-doped zeolite Y particles on aluminia nanofiber membrane

Filtration membrane technology has already been employed to remove various organic effluents produced from the textile, paper, plastic, leather, food and mineral processing industries. To improve membrane efficiency and alleviate membrane fouling, an integrated approach is adopted that combines membrane filtration and photocatalysis technology. In this study, alumina nanofiber (AF) membranes with pore size of about 10 nm (determined by the liquid-liquid displacement method) have been synthesized through an in situ hydrothermal reaction, which permitted a large flux and achieved high selectivity. Silver nanoparticles (Ag NPs) are subsequently doped on the nanofibers of the membranes. Silver nanoparticles can strongly absorb visible light due to the surface plasmon resonance (SPR) effect, and thus induce photocatalytic degradation of organic dyes, including anionic, cationic and neutral dyes, under visible light irradiation. In this integrated system, the dyes are retained on the membrane surface, their concentration in the vicinity of the Ag NPs are high and thus can be efficiently decomposed. Meanwhile, the usual flux deterioration caused by the accumulation of the filtered dyes in the passage pores can be avoided. For example, when an aqueous solution containing methylene blue is processed using an integrated membrane, a large flux of 200 L m-2 h-1 and a stable permeating selectivity of 85% were achieved. The combined photocatalysis and filtration function leads to superior performance of the integrated membranes, which have a potential to be used for the removal of organic pollutants in drinking water.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Current research in risk-aware business process management : overview, comparison, and gap analysis

The management of risks in business processes has been a subject of active research in the past few years. Many benefits can potentially be obtained by integrating the two traditionally-separated fields of risk management and business process management, including the ability to minimize risks in business processes (by design) and to mitigate risks at run time. In the past few years, an increasing amount of research aimed at delivering such an integrated system has been proposed. However, these research efforts vary in terms of their scope, goals, and functionality. Through systematic collection and evaluation of relevant literature, this paper compares and classifies current approaches in the area of risk-aware business process management in order to identify and explain relevant research gaps. The process through which relevant literature is collected, filtered, and evaluated is also detailed.

Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems

Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

Empirical analysis of the effect of dimension reduction and word order on semantic vectors

The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

A tool for internet chatroom surveillance

Internet chatrooms are common means of interaction and communications, and they carry valuable information about formal or ad-hoc formation of groups with diverse objectives. This work presents a fully automated surveillance system for data collection and analysis in Internet chatrooms. The system has two components: First, it has an eavesdropping tool which collects statistics on individual (chatter) and chatroom behavior. This data can be used to profile a chatroom and its chatters. Second, it has a computational discovery algorithm based on Singular Value Decomposition (SVD) to locate hidden communities and communication patterns within a chatroom. The eavesdropping tool is used for fine tuning the SVD-based discovery algorithm which can be deployed in real-time and requires no semantic information processing. The evaluation of the system on real data shows that (i) statistical properties of different chatrooms vary significantly, thus profiling is possible, (ii) SVD-based algorithm has up to 70-80% accuracy to discover groups of chatters.

Modeling and multiway analysis of chatroom tensors

This work identifies the limitations of n-way data analysis techniques in multidimensional stream data, such as Internet chat room communications data, and establishes a link between data collection and performance of these techniques. Its contributions are twofold. First, it extends data analysis to multiple dimensions by constructing n-way data arrays known as high order tensors. Chat room tensors are generated by a simulator which collects and models actual communication data. The accuracy of the model is determined by the Kolmogorov-Smirnov goodness-of-fit test which compares the simulation data with the observed (real) data. Second, a detailed computational comparison is performed to test several data analysis techniques including svd [1], and multi-way techniques including Tucker1, Tucker3 [2], and Parafac [3].

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

Ureaplasma parvum serovar 3 multiple banded antigen size variation after chronic intra-amniotic infection/colonization

Ureaplasma species are the microorganisms most frequently associated with adverse pregnancy outcomes. The multiple banded antigen (MBA), a surface-exposed lipoprotein, is a key virulence factor of ureaplasmas. The MBA demonstrates size variation, which we have shown previously to be correlated with the severity of chorioamnion inflammation. We aimed to investigate U. parvum serovar 3 pathogenesis in vivo, using a sheep model, by investigating: MBA variation after long term (chronic) and short term (acute) durations of in utero ureaplasma infections, and the severity of chorioamnionitis and inflammation in other fetal tissues. Inocula of 2x107 colony-forming-units (CFU) of U. parvum serovar 3 (Up) or media controls (C) were injected intra-amniotically into pregnant ewes at one of three time points: day 55 (69d Up, n=8; C69, n=4); day 117 (7d Up, n=8; C7, n=2); and day 121 (3d Up, n=8; C3, n=2) of gestation (term=145-150d). At day 124, preterm fetuses were delivered surgically. Samples of chorioamnion, fetal lung, and umbilical cord were: (i) snap frozen for subsequent ureaplasma culture, and (ii) fixed, embedded, sectioned and stained by haematoxylin and eosin stain for histological analysis. Selected fetal lung clinical ureaplasma isolates were cloned and filtered to obtain cultures from a single CFU. Passage 1 and clone 2 ureaplasma cultures were tested by western blot to demonstrate MBA variation. In acute durations of ureaplasma infection no MBA variants (3d Up) or very few MBA variants (7d Up) were present when compared to the original inoculum. However, numerous MBA size variants were generated in vivo (alike within contiguous tissues, amniotic fluid and fetal lung, but different variants were present within chorioamnion), during chronic, 69d exposure to ureaplasma infection. For the first time we have shown that the degree of ureaplasma MBA variation in vivo increased with the duration of gestation.

Why are children the most important audience for pornography in Australia?

Who watches pornography in Australia? If you listen to public debates about the genre the answer is clear – it’s children. Children are accessing pornography on smartphones (Murray and Tin 2011). Children are taking ‘lewd’ photographs of themselves, creating their own pornography (Nelligan and Etheridge 2011). Indigenous Australian children must be protected by banning pornography (the Age 2011). Pornographic magazines are placed where children can see them (O'Rourke 2011). Exposure to pornography is damaging children (Sundstrom 2011). The Australian Government insists that the Internet must be filtered to protect children from pornography (Collerton 2010). And if indeed any adults are watching pornography in Australia, then it’s child pornography (MacDonald 2011; Ralston and Howden 2011).In story after story, public debate about pornography focuses on children as its audience. There is no suggestion that children are numerically the largest audience of pornography in Australia. But emphatically the suggestion is that children are the most important audience to be taken into account when thinking about the genre. This chapter explores why this is the case, and notes the political advantages and disadvantages of focusing on children as the most important audience for pornography in Australia.

Oriented graphitic carbon films for hydrogen gas sensors

An oriented graphitic nanostructured carbon film has been employed as a conductometric hydrogen gas sensor. The carbon film was energetically deposited using a filtered cathodic vacuum arc with a -75 V bias applied to a stainless steel grid placed 1cm from the surface of the Si substrate. The substrate was heated to 400°C prior to deposition. Electron microscopy showed evidence that the film consisted largely of vertically oriented graphitic sheets and had a density of 2.06 g/cm3. 76% of the atoms were bonded in sp2 or graphitic configurations. A change in the device resistance of >; 1.5% was exhibited upon exposure to 1 % hydrogen gas (in synthetic, zero humidity air) at 100°C. The time for the sensor resistance to increase by 1.5 % under these conditions was approximately 60 s and the baseline (zero hydrogen exposure) resistance remained constant to within 0.01% during and after the hydrogen exposures.

Pt/anodized TiO2/SiC-based MOS device for hydrocarbon sensing

Pt/anodized TiO2/SiC based metal-oxide-semiconductor (MOS) devices were fabricated and characterized for their sensitivity towards propene (C3H6). Titanium (Ti) thin films were deposited onto the SiC substrates using a filtered cathodic vacuum arc (FCVA) method. Fluoride ions containing neutral electrolyte (0.5 wt% NH4F in ethylene glycol)were used to anodize the Ti films. The anodized films were subsequently annealed at 600 °C for 4 hrs in an oxygen rich environment to obtain TiO2. The current-voltage(I-V) characteristics of the Pt/TiO2/SiC devices were measured in different concentrations of propene. Exposure to the analyte gas caused a change in the Schottky barrier height and hence a lateral shift in the I-V characteristics. The effective change in the barrier height for 1% propene was calculated as 32.8 meV at 620°C. The dynamic response of the sensors was also investigated and a voltage shift of 157 mV was measured at 620°C during exposure to 1% propene.

Human milk xanthine oxidase and neonatal salivary nucleotide precursors generate hydrogen peroxide; a novel pathway with potential role in regulating oral microflora

Background: Xanthine oxidase (XO) is a complex molybdeno-flavoprotein occurring with high activity in the milk fat globule membrane (MFGM) in all mammalian milk and is involved in the final stage of degradation of purine nucleotides. It catalyzes the sequential oxidation of hypoxanthine to xanthine and uric acid, accompanied by production of hydrogen peroxide and superoxide anion. Human saliva has been extensively described for its composition of proteins, electrolytes, cortisol, melatonin and some metabolites such as amino acids, but little is known about nucleotide metabolites. Method: Saliva was collected with swabs from babies; at full-term 1-4 days, 6-weeks, 6-months and 12-months. Unstimulated fasting (morning) saliva samples were collected directly from 77 adults. Breast milk was collected from 24 new mothers. Saliva was extracted from swabs and ultra-filtered. Nucleotide metabolites were analyzed by RP-HPLC with UV-photodiode array and ESI-MS/MS. XO activity was measured as peroxide production from hypoxanthine. Bacterial inhibition over time was assessed using CFU/mL or OD. Results: Median concentrations (μmol/L) of salivary nucleobases and nucleosides for neonates/6-weeks/6-months/12-months/adult respectively were: uracil 5.3/0.8/1.4/0.7/0.8, hypoxanthine 27/7.0/1.1/0.8/2.0, xanthine 19/7.0/2.0/2.0/2.0, adenosine 12/7.0/0.9/0.8/0.1, inosine 11/5.0/0.3/0.4/0.2, guanosine 7.0/6.0/0.5/0.4/0.1, uridine 12/0.8/0.3/0.9/0.4. Deoxynucleosides and dihydropyrimidines concentrations were essentially negligible. XO activity (Vmax:mean ± SD) in breast milk was 8.9 ± 6.2 μmol/min/L and endogenous peroxide was 27 ± 12 μmol/L; mixing breast milk with neonate saliva generated ~40 μmol/L peroxide,which inhibited Staphylococcus aureus. Conclusions: Salivary metabolites, particularly xanthine/hypoxanthine, are high in neonates, transitioning to low adult levels between 6-weeks to 6-months (p < 0.001). Peroxide occurs in breast milk and is boosted during suckling as an antibacterial system.

Urinary biomolecular indicators of exercise-induced over exertion injury

Poor health and injury represent major obstacles to the future economic security of Australia. The national economic cost of work-related injury is estimated at $57.5 billion p/a. Since exposure to high physical demands is a major risk factor for musculoskeletal injury, monitoring and managing such physical activity levels in workers is a potentially important injury prevention strategy. Current injury monitoring practices are inadequate for the provision of clinically valuable information about the tissue specific responses to physical exertion. Injury of various soft tissue structures can manifest over time through accumulation of micro-trauma. Such micro-trauma has a propensity to increase the risk of acute injuries to soft-tissue structures such as muscle or tendon. As such, the capacity to monitor biomarkers that result from the disruption of these tissues offers a means of assisting the pre-emptive management of subclinical injury prior to acute failure or for evaluation of recovery processes. Here we have adopted an in-vivo exercise induced muscle damage model allowing the application of laboratory controlled conditions to assist in uncovering biochemical indicators associated with soft-tissue trauma and recovery. Importantly, urine was utilised as the diagnostic medium since it is non-invasive to collect, more acceptable to workers and less costly to employers. Moreover, it is our hypothesis that exercise induced tissue degradation products enter the circulation and are subsequently filtered by the kidney and pass through to the urine. To test this hypothesis a range of metabolomic and proteomic discovery-phase techniques were used, along with targeted approaches. Several small molecules relating to tissue damage were identified along with a series of skeletal muscle-specific protein fragments resulting from exercise induced soft-tissue damage. Each of the potential biomolecular markers appeared to be temporally present within urine. Moreover, the regulation of abundance seemed to be associated with functional recovery following the injury. This discovery may have important clinical applications for monitoring of a variety of inflammatory myopathies as well as novel applications in monitoring of the musculoskeletal health status of workers, professional athletes and/or military personnel to reduce the onset of potentially debilitating musculoskeletal injuries within these professions.