Myopic anisometropia : ocular characteristics and aetiological considerations

Anisometropia represents a unique example of ocular development, where the two eyes of an individual, with an identical genetic background and seemingly subject to identical environmental influences, can grow asymmetrically to produce significantly different refractive errors. This review provides an overview of the research examining myopic anisometropia, the ocular characteristics underlying the condition and the potential aetiological factors involved. Various mechanical factors are discussed, including corneal structure, intraocular pressure and forces generated during near work that may contribute to development of anisomyopia. Potential visually guided mechanisms of unequal ocular growth are also explored, including the influence of astigmatism, accommodation, higher-order aberrations and the choroidal response to altered visual experience. The association between binocular vision, ocular dominance and asymmetric refraction is also considered, along with a review of the genetic contribution to the aetiology of myopic anisometropia. Despite a significant amount of research into the biomechanical, structural and optical characteristics of anisometropic eyes, there is still no unifying theory, which adequately explains how two eyes within the same visual system grow to different endpoints.

Teaching and assessment of prescribing medicines : a multidisciplinary review

Background Prescribing is a complex task, requiring specific knowledge and skills, and the execution of effective, context-specific clinical reasoning. Prescribing errors can result in significant morbidity and mortality. For all professions with prescribing rights, a clear need exists to ensure students graduate with a well-defined set of prescribing skills, which will contribute to competent prescribing.

Rules of thumb for comparing multinomial logit and multinomial probit coefficients

A rule of thumb is suggested for comparing multinomial logit coefficients with multinomial probit coefficients in the special case where the normal errors are distributed N(0,1). The rule is a generalization of the '1.6' rule for comparing logit and probit coefficients. © 1989.

Approximate solutions to stochastic dynamic programs

This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified. © 1997 Cambridge University Press.

Restructuring arts and cultural funding in Tanzania : expectations and impasses

In 1984, the Tanzanian government established the Tanzania Culture Trust Fund (TCTF) – well known as ‘Mfuko’ – with the support of the Swedish government. The focus of Mfuko was to enable the arts and cultural sector to strengthen its position through grant allocations. However, rural artists have limited opportunity to access financial support to strengthen their works. The challenge remains: how to restructure arts and cultural funding in line with cutting dependence on foreign aid. This article reports on the research findings of a case study based on ‘Strategies for youth employment in Tanzania: A creative industries approach’. The study was undertaken in Dar-Es-Salaam, Bagamoyo, Dodoma, Lindi and Morogoro from July to October, 2012. This study employed mixed me thods incorporating questionnaires, interviews, and focus groups. This paper argues that lack of deliberate initiatives to restructure arts and cultural funding (in line with cutting dependence on foreign assistance) have prevented artists from fulfilling their desire for better lives. Hence, the severe lack of financial support to the artists remains a challenge to meeting the Millennium Development Goals and Tanzania Development Vision 2025. Although this discussion is specific to Tanzania, the significance and contribution of this case may apply to other developing countries.

Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Executive function and postural instability in people with Parkinson’s disease

The specific aspects of cognition contributing to balance and gait have not been clarified in people with Parkinson’s disease (PD). Twenty PD participants and twenty age- and gender-matched healthy controls were assessed on cognition and clinical mobility tests. General cognition was assessed with the Mini Mental State Exam and the Addenbrooke’s Cognitive Exam. Executive function was evaluated using the Trail Making Tests (TMT-A and TMT-B) and a computerized cognitive battery which included a series of choice reaction time (CRT) tests. Clinical gait and balance measures included the Tinetti, Timed Up & Go, Berg Balance and Functional Reach tests. PD participants performed significantly worse than the controls on the tests of cognitive and executive function, balance and gait. PD participants took longer on Trail Making Tests, CRT-Location and CRT-Colour (inhibition response). Furthermore, executive function, particularly longer times on CRT-Distracter and greater errors on the TMT-B were associated with worse balance and gait performance in the PD group. Measures of general cognition were not associated with balance and gait measures in either group. For PD participants, attention and executive function were impaired. Components of executive function, particularly those involving inhibition response and distracters, were associated with poorer balance and gait performance in PD.

Chemotherapeutic compounds targeting the DNA double-strand break repair pathways : the good, the bad, and the promising

The repair of DNA double-strand breaks (DSBs) is a critical cellular mechanism that exists to ensure genomic stability. DNA DSBs are the most deleterious type of insult to a cell’s genetic material and can lead to genomic instability, apoptosis, or senescence. Incorrectly repaired DNA DSBs have the potential to produce chromosomal translocations and genomic instability, potentially leading to cancer. The prevalence of DNA DSBs in cancer due to unregulated growth and errors in repair opens up a potential therapeutic window in the treatment of cancers. The cellular response to DNA DSBs is comprised of two pathways to ensure DNA breaks are repaired: homologous recombination and non-homologous end joining. Identifying chemotherapeutic compounds targeting proteins involved in these DNA repair pathways has shown promise as a cancer therapy for patients, either as a monotherapy or in combination with genotoxic drugs. From the beginning, there have been a number of chemotherapeutic compounds that have yielded successful responses in the clinic, a number that have failed (CGK-733 and iniparib), and a number of promising targets for future studies identified. This review looks in detail at how the cell responds to these DNA DSBs and investigates the chemotherapeutic avenues that have been and are currently being explored to target this repair process.

Disentangling the cognitive components supporting Austin Maze performance in left versus right temporal lobe epilepsy

Neuropsychological tests requiring patients to find a path through a maze can be used to assess visuospatial memory performance in temporal lobe pathology, particularly in the hippocampus. Alternatively, they have been used as a task sensitive to executive function in patients with frontal lobe damage. We measured performance on the Austin Maze in patients with unilateral left and right temporal lobe epilepsy (TLE), with and without hippocampal sclerosis, compared to healthy controls. Performance was correlated with a number of other neuropsychological tests to identify the cognitive components that may be associated with poor Austin Maze performance. Patients with right TLE were significantly impaired on the Austin Maze task relative to patients with left TLE and controls, and error scores correlated with their performance on the Block Design task. The performance of patients with left TLE was also impaired relative to controls; however, errors correlated with performance on tests of executive function and delayed recall. The presence of hippocampal sclerosis did not have an impact on maze performance. A discriminant function analysis indicated that the Austin Maze alone correctly classified 73.5% of patients as having right TLE. In summary, impaired performance on the Austin Maze task is more suggestive of right than left TLE; however, impaired performance on this visuospatial task does not necessarily involve the hippocampus. The relationship of the Austin Maze task with other neuropsychological tests suggests that differential cognitive components may underlie performance decrements in right versus left TLE.

Decision strategies for automated visual collision avoidance

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

Empirical modelling of rolling shutter effect

We propose and evaluate a novel methodology to identify the rolling shutter parameters of a real camera. We also present a model for the geometric distortion introduced when a moving camera with a rolling shutter views a scene. Unlike previous work this model allows for arbitrary camera motion, including accelerations, is exact rather than a linearization and allows for arbitrary camera projection models, for example fisheye or panoramic. We show the significance of the errors introduced by a rolling shutter for typical robot vision problems such as structure from motion, visual odometry and pose estimation.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

An application of the Driver Behaviour Questionnaire in a large Australian organisational fleeting setting : can it predict crashes and demerit point loss?

This study reports on the utilisation of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours of a large sample of Australian fleet drivers (N = 3414). Surveys were completed by employees before they commenced a one day safety workshop intervention. Factor analysis techniques identified a three factor solution similar to previous research, which was comprised of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Two items traditionally related with highway-code violations were found to be associated with aggressive driving behaviours among the current sample. Multivariate analyses revealed that exposure to the road, errors and self-reported offences predicted crashes at work in the last 12 months, while gender, highway violations and crashes predicted offences incurred while at work. Importantly, those who received more fines at work were at an increased risk of crashing the work vehicle. However, overall, the DBQ demonstrated limited efficacy at predicting these two outcomes. This paper outlines the major findings of the study in regards to identifying and predicting aberrant driving behaviours and also highlights implications regarding the future utilisation of the DBQ within fleet settings.

Contrast transfer function correction applied to cryo-electron tomography and sub-tomogram averaging

Cryo-electron tomography together with averaging of sub-tomograms containing identical particles can reveal the structure of proteins or protein complexes in their native environment. The resolution of this technique is limited by the contrast transfer function (CTF) of the microscope. The CTF is not routinely corrected in cryo-electron tomography because of difficulties including CTF detection, due to the low signal to noise ratio, and CTF correction, since images are characterised by a spatially variant CTF. Here we simulate the effects of the CTF on the resolution of the final reconstruction, before and after CTF correction, and consider the effect of errors and approximations in defocus determination. We show that errors in defocus determination are well tolerated when correcting a series of tomograms collected at a range of defocus values. We apply methods for determining the CTF parameters in low signal to noise images of tilted specimens, for monitoring defocus changes using observed magnification changes, and for correcting the CTF prior to reconstruction. Using bacteriophage PRDI as a test sample, we demonstrate that this approach gives an improvement in the structure obtained by sub-tomogram averaging from cryo-electron tomograms.

Augmenting and assisting model elicitation tasks with 3D virtual world context metadata

Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Theories of situated cognition indicate that interactive 3D representations of real work environments engage and prime the cognitive state of the viewer. In this paper, our major contribution is to augment a previous process elicitation methodology with virtual world context metadata, drawn from a 3D simulation of the workplace. We present a conceptual and formal approach for representing this contextual metadata, integrated into a process similarity measure that provides hints for the business analyst to use in later modelling steps. Finally, we conclude with examples from two use cases to illustrate the potential abilities of this approach.