Shrinkage empirical likelihood estimator in longitudinal analysis with time-dependent covariates-application to modeling the health of Filipino children

The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.

Modelling of ellipsoidal nanowires : control and application

The properties of ellipsoidal nanowires are yet to be examined. They have likely applications in sensing, solar cells, microelectronics and cloaking devices. Little is known of the qualities that ellipse nanowires exhibit as we vary the aspect ratio with different dielectric materials and how varying these attributes affects plasmon coupling and propagation. It is known that the distance a plasmon can travel is further if it is supported by a thicker circular nanowire, while thinner nanowires are expected to be able to increase QD coupling. Ellipsoidal nanowires may be a good compromise due to their ability to have both thin and thick dimensions. Furthermore it has been shown that the plasmon resonances along the main axis of an ellipsoidal particle is governed by the relative aspect ratio of the ellipsoid, which may lead to further control of the plasmon. Research was done by the use of COMSOL Multiphysics by looking at the fundamental plasmon mode supported by an ellipsoidal nanowire and then studying this mode for various geometrical parameters, materials and illumination wavelength. Accordingly it was found that ellipsoidal nanowires exhibit a minimum for the wavenumber and a maximum for the propagation distance at roughly the same dimensions - Highlighting that there is an aspect ratio for which there is poor coupling but low loss. Here we investigate these and related attributes.

Distance education and the application of academagogy : a case study

The education sector has dramatically changed in the past half decade. In a time of globalisation of education and tightening budgets, various paradigm shifts and challenges have rapidly changed learning and teaching. These include: meeting student expectation for more engaging, more interactive learning experiences, the increased focus to deliver content online, and the complexities of fast-changing technologies. Rising to these challenges and responding to them is a complex and multi-faceted task. This paper discusses educational theories and issues and explores current educational practices in the context of teaching undergraduate students via distance education in the university context. A case study applies a framework drawn from engineering education using the learner-centric concept of academagogy. Results showed that academagogy actively empowers students to build effective learning, and engages facilitators in meaningful teaching and delivery methods.

Facile mutant identification via a single parental backcross method and application of whole genome sequencing based mapping pipelines

Forward genetic screens have identified numerous genes involved in development and metabolism, and remain a cornerstone of biological research. However, to locate a causal mutation, the practice of crossing to a polymorphic background to generate a mapping population can be problematic if the mutant phenotype is difficult to recognize in the hybrid F2 progeny, or dependent on parental specific traits. Here in a screen for leaf hyponasty mutants, we have performed a single backcross of an Ethane Methyl Sulphonate (EMS) generated hyponastic mutant to its parent. Whole genome deep sequencing of a bulked homozygous F2 population and analysis via the Next Generation EMS mutation mapping pipeline (NGM) unambiguously determined the causal mutation to be a single nucleotide polymorphisim (SNP) residing in HASTY, a previously characterized gene involved in microRNA biogenesis. We have evaluated the feasibility of this backcross approach using three additional SNP mapping pipelines; SHOREmap, the GATK pipeline, and the samtools pipeline. Although there was variance in the identification of EMS SNPs, all returned the same outcome in clearly identifying the causal mutation in HASTY. The simplicity of performing a single parental backcross and genome sequencing a small pool of segregating mutants has great promise for identifying mutations that may be difficult to map using conventional approaches.

Application of gene silencing in plants

Recent studies of gene silencing in plants have revealed two RNA-mediated epigenetic processes, RNA-directed RNA degradation and RNA-directed DNA methylation. These natural processes have provided new avenues for developing high-efficiency, high-throughput technology for gene suppression in plants.

Application of gene silencing in plants

Recent studies of gene silencing in plants have revealed two RNA-mediated epigenetic processes, RNA-directed RNA degradation and RNA-directed DNA methylation. These natural processes have provided new avenues for developing high-efficiency, high-throughput technology for gene suppression in plants.

Application of lean production to reducing operational waste in a tile manufacturing process

Roofing tile manufacturing is a mass production process with high operational and inventory wastes and costs. Due to huge operational costs, excessive inventory and wastes, and quality problems, roofing tile manufacturers are trying to implement lean manufacturing practice in their operations in order to remain competitive in an ncreasingly competitive global market. The aim of this research is to evaluate the possibility of reducing the operational and inventory costs of the tile manufacturing process through waste minimization. This paper analyses the current waste situation in a tile manufacturing process and develops current and future value stream mapping for such a process with a view to implementing lean principles in manufacturing. The focus of the approach is on cost reduction by eliminating non-value-added activities.

Offer to settle in an originating application : is it an offer under the UCPR?

Sheryl Jackson looks at the decision of Justice McMeekin in Northbound Property Group Pty Ltd v Carosi (No.2) [2013] QSC 189.

Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions

Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.

Silver deposits in cutaneous burn scar tissue is a common phenomenon following application of a silver dressing

BACKGROUND Silver dressings have been widely and successfully used to prevent cutaneous wounds, including burns, chronic ulcers, dermatitis and other cutaneous conditions, from infection. However, in a few cases, skin discolouration or argyria-like appearances have been reported. This study investigated the level of silver in scar tissue post-burn injury following application of Acticoat, a silver dressing. METHODS A porcine deep dermal partial thickness burn model was used. Burn wounds were treated with this silver dressing until completion of re-epithelialization, and silver levels were measured in a total of 160 scars and normal tissues. RESULTS The mean level of silver in scar tissue covered with silver dressings was 136 microg/g, while the silver level in normal skin was less than 0.747 microg/g. A number of wounds had a slate-grey appearance, and dissection of the scars revealed brown-black pigment mostly in the middle and deep dermis within the scar. The level of silver and the severity of the slate-grey discolouration were correlated with the length of time of the silver dressing application. CONCLUSIONS These results show that silver deposition in cutaneous scar tissue is a common phenomenon, and higher levels of silver deposits and severe skin discolouration are correlated with an increase in the duration of this silver dressing application.

Silver absorption on burns after the application of Acticoat : data from pediatric patients and a porcine burn model

Silver dressings have been widely used to successfully prevent burn wound infection and sepsis. However, a few case studies have reported the functional abnormality and failure of vital organs, possibly caused by silver deposits. The aim of this study was to investigate the serum silver level in the pediatric burn population and also in several internal organs in a porcine burn model after the application of Acticoat. A total of 125 blood samples were collected from 46 pediatric burn patients. Thirty-six patients with a mean of 13.4% TBSA burns had a mean peak serum silver level of 114 microg/L, whereas 10 patients with a mean of 1.85% TBSA burns had an undetectable level of silver (<5.4 microg/L). Overall, serum silver levels were closely related to burn sizes. However, the highest serum silver was 735 microg/L in a 15-month-old toddler with 10% TBSA burns and the second highest was 367 microg/L in a 3-year old with 28% TBSA burns. In a porcine model with 2% TBSA burns, the mean peak silver level was 38 microg/L at 2 to 3 weeks after application of Acticoat and was then significantly reduced to an almost undetectable level at 6 weeks. Of a total of four pigs, silver was detected in all four livers (1.413 microg/g) and all four hearts (0.342 microg/g), three of four kidneys (1.113 microg/g), and two of four brains (0.402 microg/g). This result demonstrated that although variable, the level of serum silver was positively associated with the size of burns, and significant amounts of silver were deposited in internal organs in pigs with only 2% TBSA burns, after application of Acticoat.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

Development of Contact Lenses from a Biomaterial Point of View – Materials, Manufacture, and Clinical Application

Rigid lenses, which were originally made from glass (between 1888 and 1940) and later from polymethyl methacrylate or silicone acrylate materials, are uncomfortable to wear and are now seldom fitted to new patients. Contact lenses became a popular mode of ophthalmic refractive error correction following the discovery of the first hydrogel material – hydroxyethyl methacrylate – by Czech chemist Otto Wichterle in 1960. To satisfy the requirements for ocular biocompatibility, contact lenses must be transparent and optically stable (for clear vision), have a low elastic modulus (for good comfort), have a hydrophilic surface (for good wettability), and be permeable to certain metabolites, especially oxygen, to allow for normal corneal metabolism and respiration during lens wear. A major breakthrough in respect of the last of these requirements was the development of silicone hydrogel soft lenses in 1999 and techniques for making the surface hydrophilic. The vast majority of contact lenses distributed worldwide are mass-produced using cast molding, although spin casting is also used. These advanced mass-production techniques have facilitated the frequent disposal of contact lenses, leading to improvements in ocular health and fewer complications. More than one-third of all soft contact lenses sold today are designed to be discarded daily (i.e., ‘daily disposable’ lenses).