Assessment of freestanding membranes prepared from Antheraea pernyi silk fibroin as a potential vehicle for corneal epithelial cell transplantation

Freestanding membranes created from Bombyx mori silk fibroin (BMSF) offer a potential vehicle for corneal cell transplantation since they are transparent and support the growth of human corneal epithelial cells (HCE). Fibroin derived from the wild silkworm Antheraea pernyi (APSF) might provide a superior material by virtue of containing putative cell- attachment sites that are absent from BMSF. Thus we have investigated the feasibility of producing transparent, freestanding membranes from APSF and have analysed the behaviour of HCE cells on this material. No significant differences in cell numbers or phenotype were observed in short term HCE cell cultures established on either fibroin. Production of transparent freestanding APSF membranes, however, proved to be problematic as cast solutions of APSF were more prone to becoming opaque, displayed significantly lower permeability and were more brittle than BMSF-membranes. Cultures of HCE cells established on either membrane developed a normal stratified morphology with cytokeratin pair 3/12 being immuno-localized to the superficial layers. We conclude that while it is feasible to produce transparent freestanding membranes from APSF, the technical difficulties associated with this biomaterial, along with an absence of enhanced cell growth, currently favours the continued development of BMSF as a preferred vehicle for corneal cell transplantation. Nevertheless, it remains possible that refinement of techniques for processing APSF might yet lead to improvements in the handling properties and performance of this material.

An international survey of daily disposable contact lens prescribing

Purpose The aim was to determine the extent of daily disposable contact lens prescribing worldwide and to characterise the associated demographics and fitting patterns. Methods Up to 1,000 survey forms were sent to contact lens fitters in up to 40 countries between January and March every year for five consecutive years (2007 to 2011). Practitioners were asked to record data relating to the first 10 contact lens fits or refits performed after receiving the survey form. Survey data collected since 1996 were also analysed for seven nations to assess daily disposable lens fitting trends since that time. Results Data were collected in relation to 97,289 soft lens fits, of which 23,445 (24.1 per cent) were with daily disposable lenses and 73,170 (75.9 per cent) were with reusable lenses. Daily disposable lens prescribing ranged from 0.6 per cent of all soft lenses in Nepal to 66.2 per cent in Qatar. Compared with reusable lens fittings, daily disposable lens fittings can be characterised as follows: older age (30.0 ± 12.5 versus 29.3 ± 12.3 years for reusable lenses); males are over-represented; a greater proportion of new fits versus refits; 85.9 per cent hydrogel; lower proportion of toric and presbyopia designs and a higher proportion of part-time wear. There has been a continuous increase in daily disposable lens prescribing between 1996 and 2011. The proportion of daily disposable lens fits (as a function of all soft lens fits) is positively related to the gross domestic product at purchasing power parity per capita (r2 = 0.55, F = 46.8, p < 0.0001). Conclusions The greater convenience and other benefits of daily disposable lenses have resulted in this modality capturing significant market share. The contact lens field appears to be heading toward a true single-use-only, disposable lens market.

International survey of rigid contact lens fitting

Purpose To determine the extent of rigid contact lens fitting worldwide and to characterize the associated demographics and fitting patterns. Methods Survey forms were sent to contact lens fitters in up to 40 countries between January and March every year for five consecutive years (2007 to 2011). Practitioners were asked to record data relating to the first 10 contact lens fits or refits performed after receiving the survey form. Survey data collected between 1996 and 2011 were also analyzed to assess rigid lens fitting trends in seven nations during this period. Results Data were obtained for 12,230 rigid and 100,670 soft lens fits between 2007 and 2011. Overall, rigid lenses represented 10.8% of all contact lens fits, ranging from 0.2% in Lithuania to 37% in Malaysia. Compared with soft lens fits, rigid lens fits can be characterized as follows: older age (rigid, 37.3 ± 15.0 years; soft, 29.8 ± 12.4 years); fewer spherical and toric fits; more bifocal/multifocal fits; less frequent replacement (rigid, 7%; soft, 85%); and less part-time wear (rigid, 4%; soft, 10%). High-Dk (contact lens oxygen permeability) (36%) and mid-Dk (42%) materials are predominantly used for rigid lens fitting. Orthokeratology represents 11.5% of rigid contact lens fits. There has been a steady decline in rigid lens fitting between 1996 and 2011. Conclusions Rigid contact lens prescribing is in decline but still represents approximately 10% of all contact lenses fitted worldwide. It is likely that rigid lenses will remain as a viable, albeit increasingly specialized, form of vision correction.

Hybrid model for motorway travel time estimation considering increased detector spacing

Travel time estimation and prediction on motorways has long been a topic of research. Prediction modeling generally assumes that the estimation is perfect. No matter how good is the prediction modeling- the errors in estimation can significantly deteriorate the accuracy and reliability of the prediction. Models have been proposed to estimate travel time from loop detector data. Generally, detectors are closely spaced (say 500m) and travel time can be estimated accurately. However, detectors are not always perfect, and even during normal running conditions few detectors malfunction, resulting in increase in the spacing between the functional detectors. Under such conditions, error in the travel time estimation is significantly large and generally unacceptable. This research evaluates the in-practice travel time estimation model during different traffic conditions. It is observed that the existing models fail to accurately estimate travel time during large detector spacing and congestion shoulder periods. Addressing this issue, an innovative Hybrid model that only considers loop data for travel time estimation is proposed. The model is tested using simulation and is validated with real Bluetooth data from Pacific Motorway Brisbane. Results indicate that during non free flow conditions and larger detector spacing Hybrid model provides significant improvement in the accuracy of travel time estimation.

Experimental verification of the modified spring-mass theory of fiber Bragg grating accelerometers using transverse forces

A fiber Bragg grating (FBG) accelerometer using transverse forces is more sensitive than one using axial forces with the same mass of the inertial object, because a barely stretched FBG fixed at its two ends is much more sensitive to transverse forces than axial ones. The spring-mass theory, with the assumption that the axial force changes little during the vibration, cannot accurately predict its sensitivity and resonant frequency in the gravitational direction because the assumption does not hold due to the fact that the FBG is barely prestretched. It was modified but still required experimental verification due to the limitations in the original experiments, such as the (1) friction between the inertial object and shell; (2) errors involved in estimating the time-domain records; (3) limited data; and (4) large interval ∼5 Hz between the tested frequencies in the frequency-response experiments. The experiments presented here have verified the modified theory by overcoming those limitations. On the frequency responses, it is observed that the optimal condition for simultaneously achieving high sensitivity and resonant frequency is at the infinitesimal prestretch. On the sensitivity at the same frequency, the experimental sensitivities of the FBG accelerometer with a 5.71 gram inertial object at 6 Hz (1.29, 1.19, 0.88, 0.64, and 0.31 nm/g at the 0.03, 0.69, 1.41, 1.93, and 3.16 nm prestretches, respectively) agree with the static sensitivities predicted (1.25, 1.14, 0.83, 0.61, and 0.29 nm/g, correspondingly). On the resonant frequency, (1) its assumption that the resonant frequencies in the forced and free vibrations are similar is experimentally verified; (2) its dependence on the distance between the FBG’s fixed ends is examined, showing it to be independent; (3) the predictions of the spring-mass theory and modified theory are compared with the experimental results, showing that the modified theory predicts more accurately. The modified theory can be used more confidently in guiding its design by predicting its static sensitivity and resonant frequency, and may have applications in other fields for the scenario where the spring-mass theory fails.

New graduate occupational therapists' perceptions of near-misses and mistakes in the workplace

Purpose - The purpose of this paper is to explore the perceptions of near-misses and mistakes among new graduate occupational therapists from Australia and Aotearoa/New Zealand (NZ), and their knowledge of current incident reporting systems. Design/methodology/approach - New graduate occupational therapists in Australia and Aotearoa/NZ in their first year of practice (n=228) participated in an online electronic survey that examined five areas of work preparedness. Near-misses and mistakes was one focus area. Findings - The occurrence and disclosure of practice errors among new graduate occupational therapists are similar between Australian and Aotearoa/NZ participants. Rural location, structured supervision and registration status significantly influenced the perceptions and reporting of practice errors. Structured supervision significantly impacted on reporting procedure knowledge. Current registration status was strongly correlated with perceptions that the workplace encouraged event reporting. Research limitations/ implications - Areas for further investigation include investigating the perceptions and knowledge of practice errors within a broader profession and the need to explore definitional aspects and contextual factors of adverse events that occur in allied health settings. Selection bias may be a factor in this study. Practical implications - Findings have implications for university and workplace structures, such as clinical management, supervision, training about practice errors and reporting mechanisms in allied health. Originality/value - Findings may enable the development of better strategies for detecting, managing and preventing practice errors in the allied health professions.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

The competent prescriber: 12 core competencies for safe prescribing

Prescribing errors remain a significant cause of patient harm. Safe prescribing is not just about writing a prescription, but involves many cognitive and decision-making steps. A set of national prescribing competencies for all prescribers (including non-medical) is needed to guide education and training curricula, assessment and credentialing of individual practitioners. We have identified 12 core competencies for safe prescribing which embody the four stages of the prescribing process – information gathering, clinical decision making, communication, and monitoring and review. These core competencies, along with their learning objectives and assessment methods, provide a useful starting point for teaching safe and effective prescribing.

Cataract surgery in eyes with low corneal astigmatism : implantation of the AcrySof IQ Toric SN6AT2 intraocular lens

Purpose The aim of this study is to assess the refractive and visual outcomes following cataract surgery and implantation of the AcrySof IQ Toric SN6AT2 intraolcular lens (IOL) (Alcon Laboratories, Inc) in patients with low corneal astigmatism. Materials and Methods A retrospective, consecutive, single surgeon series of ninety-eight eyes of 88 patients following cataract surgery and implantation of the AcrySof IQ Toric SN6AT2 IOL in eyes with low preoperative corneal astigmatism. Postoperative measurements were obtained at one month post surgery. Main outcome measures were monocular distance visual acuity and residual refractive astigmatism. Results The mean preoperative corneal astigmatic power vector (APV) was 0.38 ± 0.09 D. Following surgery and implantation of the toric IOL, mean postoperative refractive APV was 0.13 ± 0.10 D. Mean postoperative distance uncorrected visual acuity (UCVA) was 0.08 ± 0.09 logMAR. Postoperative spherical equivalent refraction (SER) resulted in a mean of - 0.23 ± 0.22 D, with 96% of eyes falling within 0.50 D of the target SER. Conclusions The AcrySof IQ Toric SN6AT2 IOL is a safe and effective option for eyes undergoing cataract surgery with low amounts of preoperative corneal astigmatism.

Measuring exposure to solar ultraviolet radiation using a dosimetric technique : understanding participant compliance issues

Personal ultraviolet dosimeters have been used in epidemiological studies to understand the risks and benefits of individuals' exposure to solar ultraviolet radiation (UVR). We investigated the types and determinants of non-compliance associated with a protocol for use of polysulphone UVR dosimeters. In the AusD Study, 1,002 Australian adults (aged 18-75 years) were asked to wear a new dosimeter on their wrist each day for 10 consecutive days to quantify their daily exposure to solar UVR. Of the 10,020 dosimeters distributed, 296 (3%) were not returned or used (Type I non-compliance) and other usage errors were reported for 763 (8%) returned dosimeters (Type II non-compliance). Type I errors were more common in participants with predominantly outdoor occupations. Type II errors were reported more frequently on the first day of measurement; weekend days or rainy days; and among females; younger people; more educated participants or those with outdoor occupations. Half (50%) the participants reported a non-compliance error on at least one day during the 10-day period. However, 92% of participants had at least 7 days of usable data without any apparent non-compliance issues. The factors identified should be considered when designing future UVR dosimetry studies.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Key-private proxy re-encryption under LWE

Proxy re-encryption (PRE) is a highly useful cryptographic primitive whereby Alice and Bob can endow a proxy with the capacity to change ciphertext recipients from Alice to Bob, without the proxy itself being able to decrypt, thereby providing delegation of decryption authority. Key-private PRE (KP-PRE) specifies an additional level of confidentiality, requiring pseudo-random proxy keys that leak no information on the identity of the delegators and delegatees. In this paper, we propose a CPA-secure PK-PRE scheme in the standard model (which we then transform into a CCA-secure scheme in the random oracle model). Both schemes enjoy highly desirable properties such as uni-directionality and multi-hop delegation. Unlike (the few) prior constructions of PRE and KP-PRE that typically rely on bilinear maps under ad hoc assumptions, security of our construction is based on the hardness of the standard Learning-With-Errors (LWE) problem, itself reducible from worst-case lattice hard problems that are conjectured immune to quantum cryptanalysis, or “post-quantum”. Of independent interest, we further examine the practical hardness of the LWE assumption, using Kannan’s exhaustive search algorithm coupling with pruning techniques. This leads to state-of-the-art parameters not only for our scheme, but also for a number of other primitives based on LWE published the literature.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.