Spectrometric and voltammetric studies of the interaction between quercetin and bovine serum albumin using warfarin as site marker with the aid of chemometrics

The interaction of quercetin, which is a bioflavonoid, with bovine serum albumin (BSA) was investigated under pseudo-physiological conditions by the application of UV–vis spectrometry, spectrofluorimetry and cyclic voltammetry (CV). These studies indicated a cooperative interaction between the quercetin–BSA complex and warfarin, which produced a ternary complex, quercetin–BSA–warfarin. It was found that both quercetin and warfarin were located in site I. However, the spectra of these three components overlapped and the chemometrics method – multivariate curve resolution-alternating least squares (MCR-ALS) was applied to resolve the spectra. The resolved spectra of quercetin–BSA and warfarin agreed well with their measured spectra, and importantly, the spectrum of the quercetin–BSA–warfarin complex was extracted. These results allowed the rationalization of the behaviour of the overlapping spectra. At lower concentrations ([warfarin] < 1 × 10−5 mol L−1), most of the site marker reacted with the quercetin–BSA, but free warfarin was present at higher concentrations. Interestingly, the ratio between quercetin–BSA and warfarin was found to be 1:2, suggesting a quercetin–BSA–(warfarin)2 complex, and the estimated equilibrium constant was 1.4 × 1011 M−2. The results suggest that at low concentrations, warfarin binds at the high-affinity sites (HAS), while low-affinity binding sites (LAS) are occupied at higher concentrations.

An examination of the relationship between workload and fatigue within and across consecutive days of work: Is the relationshiop static or dynamic?

Cognitive-energetical theories of information processing were used to generate predictions regarding the relationship between workload and fatigue within and across consecutive days of work. Repeated measures were taken on board a naval vessel during a non-routine and a routine patrol. Data were analyzed using growth curve modeling. Fatigue demonstrated a non-monotonic relationship within days in both patrols – fatigue was high at midnight, started decreasing until noontime and then increased again. Fatigue increased across days towards the end of the non-routine patrol, but remained stable across days in the routine patrol. The relationship between workload and fatigue changed over consecutive days in the non-routine patrol. At the beginning of the patrol, low workload was associated with fatigue. At the end of the patrol, high workload was associated with fatigue. This relationship could not be tested in the routine patrol, however it demonstrated a non-monotonic relationship between workload and fatigue – low and high workloads were associated with the highest fatigue. These results suggest that the optimal level of workload can change over time and thus have implications for the management of fatigue.

Development and validation of 3-Minute Nutrition Screening (3-MinNS) tool for acute hospital patients in Singapore

It is important to detect and treat malnutrition in hospital patients so as to improve clinical outcome and reduce hospital stay. The aim of this study was to develop and validate a nutrition screening tool with a simple and quick scoring system for acute hospital patients in Singapore. In this study, 818 newly admitted patients aged above 18 years old were screened using five parameters that contribute to the risk of malnutrition. A dietitian blinded to the nutrition screening score assessed the same patients using the reference standard, Subjective Global Assessment (SGA) within 48 hours. The sensitivity and specificity were established using the Receiver Operator Characteristics (ROC) curve and the best cutoff scores determined. The nutrition parameter with the largest Area Under the ROC Curve (AUC) was chosen as the final screening tool, which was named 3-Minute Nutrition Screening (3-MinNS). The combination of the parameters weight loss, intake and muscle wastage (3-MinNS), gave the largest AUC when compared with SGA. Using 3-MinNS, the best cutoff point to identify malnourished patients is three (sensitivity 86%, specificity 83%). The cutoff score to identify subjects at risk of severe malnutrition is five (sensitivity 93%, specificity 86%). 3-Minute Nutrition Screening is a valid, simple and rapid tool to identify patients at risk of malnutrition in Singapore acute hospital patients. It is able to differentiate patients at risk of moderate malnutrition and severe malnutrition for prioritization and management purposes.

Distracted

Distracted is a luminous, interactive, computational media installation of sound, light and translucent sculptural materials. The work is inspired by scientific ice core samples taken in Antarctica. The sculpture is capable of displaying data taken from these ice core samples, and responding to the proximity of an audience. Rather than simply using the interface as a didactic display device, we have chosen a more poetic approach of generating visual effects from the data that are evocative of the ice, fluids and the notion of change. The data has also been used in the composition of an evolving soundscape. As well as data from ice core samples, such as the Vostok ice core, we have incorporated data from the Keeling Curve that shows the annual rise and fall of atmospheric carbon dioxide, following the pattern of the Northern Hemisphere winter. These effects combine with changes caused directly by audience members as they come within close proximity to the work.

A Vision Based Target Detection System for Docking of an Autonomous Underwater Vehicle

This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

The influence of oblique viewing on axial and peripheral refraction for emmetropes and myopes

Refraction may be affected by the forces of lids and extraocular muscles when eye direction and head direction are not aligned (oblique viewing) which might potentially influence past findings on peripheral refraction of the eye. We investigated the effect of oblique viewing on axial and peripheral refraction. In a first experiment, cycloplegic axial refractions were determined when subjects' heads were positioned to look straight-ahead through an open-view autorefractor and when the heads were rotated to the right or left by 30° with compensatory eye rotation (oblique viewing). Subjects were 16 young emmetropes (18–35 years), 22 young myopes (19–36 years) and 15 old emmetropes (45–60 years). In a second experiment, cycloplegic peripheral refraction measurements were taken out to ±34° horizontally from fixation while the subjects rotated their heads to match the peripheral refraction angles (eye in primary position with respect to the head) or the eyes were rotated with respect to the head (oblique viewing). Subjects were 10 emmetropes and 10 myopes. We did not find any significant changes in axial or peripheral refraction upon oblique viewing for any of the subject groups. In general for the range of horizontal angles used, it is not critical whether or not the eye is rotated with respect to the head during axial or peripheral refraction.

The X-Factor and its relationship to golfing performance

It is often postulated that an increased hip to shoulder differential angle (`X-Factor') during the early downswing better utilises the stretch-shorten cycle and improves golf performance. The current study aims to examine the potential relationship between the X-Factor and performance during the tee-shot. Seven golfers with handicaps between 0 and 10 strokes comprised the low-handicap group, whilst the high-handicap group consisted of eight golfers with handicaps between 11 and 20 strokes. The golfers performed 20 drives and three-dimensional kinematic data were used to quantify hip and shoulder rotation and the subsequent X-Factor. Compared with the low-handicap group, the high-handicap golfers tended to demonstrate greater hip rotation at the top of the backswing and recorded reduced maximum X-Factor values. The inconsistencies evident in the literature may suggest that a universal method of measuring rotational angles during the golf swing would be beneficial for future studies, particularly when considering potential injury.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Multivariate methods to identify cancer-related symptom clusters

Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

Peripheral ocular monochromatic aberrations

Aberrations affect image quality of the eye away from the line of sight as well as along it. High amounts of lower order aberrations are found in the peripheral visual field and higher order aberrations change away from the centre of the visual field. Peripheral resolution is poorer than that in central vision, but peripheral vision is important for movement and detection tasks (for example driving) which are adversely affected by poor peripheral image quality. Any physiological process or intervention that affects axial image quality will affect peripheral image quality as well. The aim of this study was to investigate the effects of accommodation, myopia, age, and refractive interventions of orthokeratology, laser in situ keratomileusis and intraocular lens implantation on the peripheral aberrations of the eye. This is the first systematic investigation of peripheral aberrations in a variety of subject groups. Peripheral aberrations can be measured either by rotating a measuring instrument relative to the eye or rotating the eye relative to the instrument. I used the latter as it is much easier to do. To rule out effects of eye rotation on peripheral aberrations, I investigated the effects of eye rotation on axial and peripheral cycloplegic refraction using an open field autorefractor. For axial refraction, the subjects fixated at a target straight ahead, while their heads were rotated by ±30º with a compensatory eye rotation to view the target. For peripheral refraction, the subjects rotated their eyes to fixate on targets out to ±34° along the horizontal visual field, followed by measurements in which they rotated their heads such that the eyes stayed in the primary position relative to the head while fixating at the peripheral targets. Oblique viewing did not affect axial or peripheral refraction. Therefore it is not critical, within the range of viewing angles studied, if axial and peripheral refractions are measured with rotation of the eye relative to the instrument or rotation of the instrument relative to the eye. Peripheral aberrations were measured using a commercial Hartmann-Shack aberrometer. A number of hardware and software changes were made. The 1.4 mm range limiting aperture was replaced by a larger aperture (2.5 mm) to ensure all the light from peripheral parts of the pupil reached the instrument detector even when aberrations were high such as those occur in peripheral vision. The power of the super luminescent diode source was increased to improve detection of spots passing through the peripheral pupil. A beam splitter was placed between the subjects and the aberrometer, through which they viewed an array of targets on a wall or projected on a screen in a 6 row x 7 column matrix of points covering a visual field of 42 x 32. In peripheral vision, the pupil of the eye appears elliptical rather than circular; data were analysed off-line using custom software to determine peripheral aberrations. All analyses in the study were conducted for 5.0 mm pupils. Influence of accommodation on peripheral aberrations was investigated in young emmetropic subjects by presenting fixation targets at 25 cm and 3 m (4.0 D and 0.3 D accommodative demands, respectively). Increase in accommodation did not affect the patterns of any aberrations across the field, but there was overall negative shift in spherical aberration across the visual field of 0.10 ± 0.01m. Subsequent studies were conducted with the targets at a 1.2 m distance. Young emmetropes, young myopes and older emmetropes exhibited similar patterns of astigmatism and coma across the visual field. However, the rate of change of coma across the field was higher in young myopes than young emmetropes and was highest in older emmetropes amongst the three groups. Spherical aberration showed an overall decrease in myopes and increase in older emmetropes across the field, as compared to young emmetropes. Orthokeratology, spherical IOL implantation and LASIK altered peripheral higher order aberrations considerably, especially spherical aberration. Spherical IOL implantation resulted in an overall increase in spherical aberration across the field. Orthokeratology and LASIK reversed the direction of change in coma across the field. Orthokeratology corrected peripheral relative hypermetropia through correcting myopia in the central visual field. Theoretical ray tracing demonstrated that changes in aberrations due to orthokeratology and LASIK can be explained by the induced changes in radius of curvature and asphericity of the cornea. This investigation has shown that peripheral aberrations can be measured with reasonable accuracy with eye rotation relative to the instrument. Peripheral aberrations are affected by accommodation, myopia, age, orthokeratology, spherical intraocular lens implantation and laser in situ keratomileusis. These factors affect the magnitudes and patterns of most aberrations considerably (especially coma and spherical aberration) across the studied visual field. The changes in aberrations across the field may influence peripheral detection and motion perception. However, further research is required to investigate how the changes in aberrations influence peripheral detection and motion perception and consequently peripheral vision task performance.

An empirical investigation of the level effect in Australian interest rates

An extensive literature examines the dynamics of interest rates, with particular attention given to the positive relationship between interest-rate volatility and the level of interest rates—the so-called level effect. This paper examines the interaction between the estimated level effect and competing parameterisations of interest-rate volatility for the Australian yield curve. We adopt a new methodology that estimates elasticity in a multivariate setting that explicitly accommodates the correlations that exist between various yield factors. Results show that significant correlations exist between the residuals of yield factors and that such correlations do indeed impact on model estimates. Within the multivariate setting, the level of the short rate is shown to be a crucial determinant of the conditional volatility of all three yield factors. Measures of model fit suggest that, in addition to the usual level effect, the incorporation of GARCH effects and possible regime shifts is important

Unmanned Aerial Vehicles UAVs attitude, height, motion estimation and control using visual systems

This paper presents an implementation of an aircraft pose and motion estimator using visual systems as the principal sensor for controlling an Unmanned Aerial Vehicle (UAV) or as a redundant system for an Inertial Measure Unit (IMU) and gyros sensors. First, we explore the applications of the unified theory for central catadioptric cameras for attitude and heading estimation, explaining how the skyline is projected on the catadioptric image and how it is segmented and used to calculate the UAV’s attitude. Then we use appearance images to obtain a visual compass, and we calculate the relative rotation and heading of the aerial vehicle. Additionally, we show the use of a stereo system to calculate the aircraft height and to measure the UAV’s motion. Finally, we present a visual tracking system based on Fuzzy controllers working in both a UAV and a camera pan and tilt platform. Every part is tested using the UAV COLIBRI platform to validate the different approaches, which include comparison of the estimated data with the inertial values measured onboard the helicopter platform and the validation of the tracking schemes on real flights.

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.