Sleep-related eye symptoms and their potential for identifying driver sleepiness

The majority of individuals appear to have insight into their own sleepiness, but there is some evidence that this does not hold true for all, for example treated patients with obstructive sleep apnoea. Identification of sleep-related symptoms may help drivers determine their sleepiness, eye symptoms in particular show promise. Sixteen participants completed four motorway drives on two separate occasions. Drives were completed during daytime and night-time in both a driving simulator and on the real road. Ten eye symptoms were rated at the end of each drive, and compared with driving performance and subjective and objective sleep metrics recorded during driving. ‘Eye strain’, ‘difficulty focusing’, ‘heavy eyelids’ and ‘difficulty keeping the eyes open’ were identified as the four key sleep-related eye symptoms. Drives resulting in these eye symptoms were more likely to have high subjective sleepiness and more line crossings than drives where similar eye discomfort was not reported. Furthermore, drivers having unintentional line crossings were likely to have ‘heavy eyelids’ and ‘difficulty keeping the eyes open’. Results suggest that drivers struggling to identify sleepiness could be assisted with the advice ‘stop driving if you feel sleepy and/or have heavy eyelids or difficulty keeping your eyes open’.

An investigation of Staphylococcus aureus and related species from flood affected and other environmental sources

This research investigated the microbial air quality of flooded houses in Brisbane suburbs following the January 2011 flood event. Flood waters can carry and spread human pathogenic bacteria, and these organisms can be dispersed into residential air by aerosolisation. This study found that the bacterial load was significantly different for indoor and outdoor areas of flood affected houses, but no significant differences were observed between flooded and non-flooded houses. This could be due to the rapid clean-up of flooded houses following the event. Molecular methods were used to identify and characterise staphylococcal species in residential air of flooded and non-flooded houses. A major finding was the diverse population of airborne staphylococci as well as the high rate of methicillin-resistance in these strains. By determining the genetic relatedness of residential air sourced staphylococci, a potential source for pathogenic strains can be identified.

Organizational work-related road safety situational analysis: More than just an audit tool

Although safety statistics indicate that road crashes are the most common form of work-related fatalities, many organizations fail to treat company vehicles in the same manner as other physical safety hazards within the workplace. Traditionally, work-related road safety has targeted primarily driver-related issues and not adequately addressed organizational processes, such as the organizations’ safety system and risk management processes and practice. This inadequacy generally stems from a lack of specific contextual knowledge and basic requirements to improve work-related road safety, including the supporting systems to ensure any intervention strategy or initiative’s ongoing effectiveness. Therefore, informed by previous research and based on a case study methodology, the Organizational Work-Related Road Safety Situational Analysis was developed to assess organizations’ current work-related road safety system, including policy, procedures, processes and practice. The situational analysis tool is similar to a safety audit however is more comprehensive in detail, application and provides sufficient evidence to enable organizations to mitigate and manage their work-related road safety risks. In addition, data collected from this process assists organizations in making informed decisions regarding intervention strategy design, development, implementation and ongoing effectiveness. This paper reports on the effectiveness of the situational analysis tool to assess WRRS systems across five differing and diverse organizations; including gas exploration and mining, state government, local government, and not for profit/philanthropy. The outcomes of this project identified considerable differences in the degree by which the organizations’ addressed work-related road safety across their vehicle fleet operations and provides guidelines for improving organizations’ work-related road safety systems.

Plasma-made silicon nanograss and related nanostructures

Plasma-made nanostructures show outstanding potential for applications in nanotechnology. This paper provides a concise overview on the progress of plasma-based synthesis and applications of silicon nanograss and related nanostructures. The materials described here include black silicon, Si nanotips produced using a self-masking technique as well as self-organized silicon nanocones and nanograss. The distinctive features of the Si nanograss, two-tier hierarchical and tilted nanograss structures are discussed. Specific applications based on the unique features of the silicon nanograss are also presented.

Tailoring the composition of self-assembled Si1−xCx quantum dots : simulation of plasma/ion-related controls

Precise control of composition and internal structure is essential for a variety of novel technological applications which require highly tailored binary quantum dots (QDs) with predictable optoelectronic and mechanical properties. The delicate balancing act between incoming flux and substrate temperature required for the growth of compositionally graded (Si1-xC x; x varies throughout the internal structure), core-multishell (discrete shells of Si and C or combinations thereof) and selected composition (x set) QDs on low-temperature plasma/ion-flux-exposed Si(100) surfaces is investigated via a hybrid numerical simulation. Incident Si and C ions lead to localized substrate heating and a reduction in surface diffusion activation energy. It is shown that by incorporating ions in the influx, a steady-state composition is reached more quickly (for selected composition QDs) and the composition gradient of a Si1-xCx QD may be fine tuned; additionally (with other deposition conditions remaining the same), larger QDs are obtained on average. It is suggested that ionizing a portion of the influx is another way to control the average size of the QDs, and ultimately, their internal structure. Advantages that can be gained by utilizing plasma/ion-related controls to facilitate the growth of highly tailored, compositionally controlled quantum dots are discussed as well.

Self-organized nanoarrays : plasma-related controls

The paper presents an investigation of self-organizational and -assembly processes of nanostructure growth on surfaces exposed to low-temperature plasmas. We have considered three main growth stages-initial, or sub-monolayer growth stage, separate nanostructure growth stage, and array growth stages with the characteristic sizes of several nm, several tens of nm, and several hundreds of nm, respectively, and have demonstrated, by the experimental data and hybrid multiscale numerical simulations, that the plasma parameters can strongly influence the surface processes and hence the kinetics of self-organization and -assembly. Our results show that plasma-controlled self-organization is a promising way to assemble large regular arrays of nanostructures. © 2008 IUPAC.

Comparison of block and event-related experimental designs in diffusion-weighted functional MRI

PURPOSE To compare diffusion-weighted functional magnetic resonance imaging (DfMRI), a novel alternative to the blood oxygenation level-dependent (BOLD) contrast, in a functional MRI experiment. MATERIALS AND METHODS Nine participants viewed contrast reversing (7.5 Hz) black-and-white checkerboard stimuli using block and event-related paradigms. DfMRI (b = 1800 mm/s2 ) and BOLD sequences were acquired. Four parameters describing the observed signal were assessed: percent signal change, spatial extent of the activation, the Euclidean distance between peak voxel locations, and the time-to-peak of the best fitting impulse response for different paradigms and sequences. RESULTS The BOLD conditions showed a higher percent signal change relative to DfMRI; however, event-related DfMRI showed the strongest group activation (t = 21.23, P < 0.0005). Activation was more diffuse and spatially closer to the BOLD response for DfMRI when the block design was used. DfMRIevent showed the shortest TTP (4.4 +/- 0.88 sec). CONCLUSION The hemodynamic contribution to DfMRI may increase with the use of block designs.

The importance of science fiction and other STEM-related mass media in young people’s decisions to enrol in university STEM courses

This paper presents Australian results from the Interests and Recruitment in Science (IRIS) study with respect to the influence of STEM-related mass media, including science fiction, on students’ decisions to enrol in university STEM courses. The study found that across the full cohort (N=2999), students tended to attribute far greater influence to science-related documentaries/channels such as Life on Earth and the Discovery Channel, etc. than to science-fiction movies or STEM-related TV dramas. Males were more inclined than females to consider science fiction/fantasy books and films and popular science books/magazines as having been important in their decisions. Students taking physics/astronomy tended to rate the importance of science fiction/fantasy books and films higher than students in other courses. The implications of these results for our understanding of influences on STEM enrolments are discussed.

Human errors in computer related abuses

The term “Human error” can simply be defined as an error which made by a human. In fact, Human error is an explanation of malfunctions, unintended consequents from operating a system. There are many factors that cause a person to have an error due to the unwanted error of human. The aim of this paper is to investigate the relationship of human error as one of the factors to computer related abuses. The paper beings by computer-relating to human errors and followed by mechanism mitigate these errors through social and technical perspectives. We present the 25 techniques of computer crime prevention, as a heuristic device that assists. A last section discussing the ways of improving the adoption of security, and conclusion.

The crude skin secretion of the pepper frog leptodactylus labyrinthicus is rich in metallo and serine peptidases

Peptidases are ubiquitous enzymes involved in diverse biological processes. Fragments from bioactive peptides have been found in skin secretions from frogs, and their presence suggests processing by peptidases. Thus, the aim of this work was to characterize the peptidase activity present in the skin secretion of Leptodactylus labyrinthicus. Zymography revealed the presence of three bands of gelatinase activity of approximately 60 kDa, 66 kDa, and 80 kDa, which the first two were calcium-dependent. These three bands were inhibited either by ethylenediaminetetraacetic acid (EDTA) and phenathroline; thus, they were characterized as metallopeptidases. Furthermore, the proteolytic enzymes identified were active only at pH 6.0–10.0, and their activity increased in the presence of CHAPS or NaCl. Experiments with fluorogenic substrates incubated with skin secretions identified aminopeptidase activity, with cleavage after leucine, proline, and alanine residues. This activity was directly proportional to the protein concentration, and it was inhibited in the presence of metallo and serine peptidase inhibitors. Besides, the optimal pH for substrate cleavage was determined to be 7.0–8.0. The results of the in gel activity assay showed that all substrates were hydrolyzed by a 45 kDa peptidase. Gly-Pro-AMC was also cleaved by a peptidase greater than 97 kDa. The data suggest the presence of dipeptidyl peptidases (DPPs) and metallopeptidases; however, further research is necessary. In conclusion, our work will help to elucidate the implication of these enzymatic activities in the processing of the bioactive peptides present in frog venom, expanding the knowledge of amphibian biology.

In Response: "Oral versus IV treatment for catheter-related bloodstream infections - by Burke A. Cunha"

In his letter Cunha suggests that oral antibiotic therapy is safer and less expensive than intravenous therapy via central venous catheters (CVCs) (1). The implication is that costs will fall and increased health benefits will be enjoyed resulting in a gain in efficiency within the healthcare system. CVCs are often used in critically ill patients to deliver antimicrobial therapy, but expose patients to a risk of catheter-related bloodstream infection (CRBSI). Our current knowledge about the efficiency (i.e. costeffectiveness) of allocating resources toward interventions that prevent CRBSI in patients requiring a CVC has already been reviewed (2). If for some patient groups antimicrobial therapy can be delivered orally, instead of through a CVC, then the costs and benefits of this alternate strategy should be evaluated...

A proteomic view into infection of greyback canegrubs (Dermolepida albohirtum) by Metarhizium anisopliae

Metarhizium anisopliae is a naturally occurring cosmopolitan fungus infecting greyback canegrubs (Dermolepida albohirtum). The main molecular factors involved in the complex interactions occurring between the greyback canegrubs and M. anisopliae (FI-1045) were investigated by comparing the proteomes of healthy canegrubs, canegrubs infected with Metarhizium and fungus only. Differentially expressed proteins from the infected canegrubs were subjected to mass spectrometry to search for pathogenicity related proteins. Immune-related proteins of canegrubs identified in this study include cytoskeletal proteins (actin), cell communication proteins, proteases and peptidases. Fungal proteins identified include metalloproteins, acyl-CoA, cyclin proteins and chorismate mutase. Comparative proteome analysis provided a view into the cellular reactions triggered in the canegrub in response to the fungal infection at the onset of biological control.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.