Measuring cost and affordability of healthy and less healthy diet globally

The INFORMAS food prices module proposes a step-wise framework to measure the cost and affordability of population diets. The price differential and the tax component of healthy and less healthy foods, food groups, meals and diets will be benchmarked and monitored over time. Results can be used to model or assess the impact of fiscal policies, such as ‘fat taxes’ or subsidies. Key methodological challenges include: defining healthy and less healthy foods, meals, diets and commonly consumed items; including costs of alcohol, takeaways, convenience foods and time; selecting the price metric; sampling frameworks; and standardizing collection and analysis protocols. The minimal approach uses three complementary methods to measure the price differential between pairs of healthy and less healthy foods. Specific challenges include choosing policy relevant pairs and defining an anchor for the lists. The expanded approach measures the cost of a healthy diet compared to the current (less healthy) diet for a reference household. It requires dietary principles to guide the development of the healthy diet pricing instrument and sufficient information about the population’s current intake to inform the current (less healthy) diet tool. The optimal approach includes measures of affordability and requires a standardised measure of household income that can be used for different countries. The feasibility of implementing the protocol in different countries is being tested in New Zealand, Australia and Fiji. The impact of different decision points to address challenges will be investigated in a systematic manner. We will present early insights and results from this work.

Developing standardized methods to assess cost of healthy and unhealthy (current) diets in Australia

Unhealthy diets contribute at least 14% to Australia's disease burden and are driven by ‘obesogenic’ food environments. Compliance with dietary recommendations is particularly poor amongst disadvantaged populations including low socioeconomic groups, those living in rural/remote areas and Aboriginal and Torres Strait Islanders. The perception that healthy foods are expensive is a key barrier to healthy choices and a major determinant of diet-related health inequities. Available state/regional/local data (limited and non-comparable) suggests that, despite basic healthy foods not incurring GST, the cost of healthy food is higher and has increased more rapidly than unhealthy food over the last 15 years in Australia. However, there were no nationally standardised tools or protocols to benchmark, compare or monitor food prices and affordability in Australia. Globally, we are leading work to develop and test approaches to assess the price differential of healthy and less-healthy (current) diets under the food price module of the International Network for Food and Obesity/non-communicable diseases (NCDs) Research, Monitoring and Action Support (INFORMAS). This presentation describes contextualization of the INFORMAS approach to develop standardised Australian tools, survey protocols and data collection and analysis systems. The ‘healthy diet basket’ was based on the Australian Foundation Diet, 1 The ‘current diet basket’ and specific items included in each basket, were based on recent national dietary survey data.2 Data collection methods were piloted. The final tools and protocols were then applied to measure the price and affordability of healthy and less healthy (current) diets of different household groups in diverse communities across the nation. We have compared results for different geographical locations/population subgroups in Australia and assessed these against international INFORMAS benchmarks. The results inform the development of policy and practice, including those relevant to mooted changes to the GST base, to promote nutrition and healthy weight and prevent chronic disease in Australia.

Ternary function and circuit design using ternary multiplexers

The recent trend towards minimizing the interconnections in large scale integration (LSI) circuits has led to intensive investigation in the development of ternary circuits and the improvement of their design. The ternary multiplexer is a convenient and useful logic module which can be used as a basic building block in the design of a ternary system. This paper discusses a systematic procedure for the simplification and realization of ternary functions using ternary multiplexers as building blocks. Both single level and multilevel multiplexing techniques are considered. The importance of the design procedure is highlighted by considering two specific applications, namely, the development of ternary adder/subtractor and TCD to ternary converter.

Going bush: Preparing pre-service teachers to teach in regional Western Australia

This paper reports on outcomes of Phases One and Two of the ALTC Competitive Research and Development Project "Developing Strategies at the Pre-Service Level to Address Critical Teacher Attraction and Retention Issues in Australian Rural, Regional and Remote Schools." This project funded over two years aims to strengthen the capacity and credibility of universities to prepare rural, regional and remote educators, similar to the capacity and credibility that has been created in preparing Australia's rural, regional and remote health workers. There is a strong recognition of the fundamental importance of quality teaching experiences rural, regional and remote schools and throughout this project over 200 pre-service teachers have participated in a curriculum module/object and completed a survey that encourages them to consider teaching in regional Western Australia. The project has mapped current Western Australian rural, regional and remote pre-service teacher education curriculum and field experience model. This mapping completed a comparison of national information with the identification of rural, regional and remote education curriculum and/or field experience models used nationally and internationally. In particular results from Phase One and Two will be presented reporting on the findings of the first year of the project.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

An absolute digital positioning numerical control system

A module containing all the functional components required for a digital absolute positioning process of one axis of a machine tool has been designed and constructed. Circuit realization makes use of integrated circuit elements.

Classification of Nonenzymatic Homologues of Protein Kinases

Protein Kinase-Like Non-kinases (PKLNKs), which are closely related to protein kinases, lack the crucial catalytic aspartate in the catalytic loop, and hence cannot function as protein kinase, have been analysed. Using various sensitive sequence analysis methods, we have recognized 82 PKLNKs from four higher eukaryotic organisms, namely, Homo sapiens, Mus musculus, Rattus norvegicus, and Drosophila melanogaster. On the basis of their domain combination and function, PKLNKs have been classified mainly into four categories: (1) Ligand binding PKLNKs, (2) PKLNKs with extracellular protein-protein interaction domain, (3) PKLNKs involved in dimerization, and (4) PKLNKs with cytoplasmic protein-protein interaction module. While members of the first two classes of PKLNKs have transmembrane domain tethered to the PKLNK domain, members of the other two classes of PKLNKs are cytoplasmic in nature. The current classification scheme hopes to provide a convenient framework to classify the PKLNKs from other eukaryotes which would be helpful in deciphering their roles in cellular processes.

GDNF Receptors: Veterans and Novices

Neurotrophic factors play essential role in the development and functioning of the nervous system and other organs. Glial cell line-Derived Neurotrophic Factor (GDNF) family ligands (GFLs) are of particular interest because they promote the survival of dopaminergic neurons in vitro, in Parkinson s disease animal models and in patients. GDNF is also a potent survival factor for the central motoneurons and thus is considered as a potential lead for the treatment of amyotrophic lateral sclerosis. The survival promoting receptor complex for GFLs consists of a ligand-specific co-receptor, GFRα and a signal transducing module, receptor tyrosine kinase RET. At least GDNF and persephin, a GFL, have established functions outside central nervous system. GDNF is crucial for enteric nervous system and kidney development as well as for spermatogenesis. Persephin controls calcitonin secretion. Communication between cells often occurs in the extracellular matrix (ECM), a meshwork, which is secreted and deposited by the cells and is mainly composed of fibrillar proteins and polymerized sugars. We evaluated the relationship between GFLs and extracellular matrix components and demonstrated that three GFLs - GDNF, neurturin and artemin bind heparan sulfates with nanomolar affinities. The fourth member of the family - persephin binds these polysaccharides thousand times less tightly. GDNF, neurturin and artemin also bind with high affinity to heparan sulfate proteoglycan (HSPG) isolated from the nervous system, syndecan-3. GDNF signals through HSPGs, evoking Src family kinase activation. This signaling induces cell spreading, hippocampal neurite outgrowth in vitro and cellular migration. Specifically, GDNF signaling through syndecan-3 is important for embryonic cortical neuron migration. Syndecan-3-deficient mice, similarly to mice lacking GDNF, have less GABAergic neurons in their cortex, as compared to the wild-type mice. This fact provides indirect evidence that GDNF interaction with syndecan-3 is important for cortical brain development. Noteworthy, in non-neuronal tissues GFLs may signal via other syndecans. We also present the structural model for a GDNF co-receptor, GFRα1. The X-ray structure of the GFRα1 domain 3 was solved with 1.8 Å resolution, revealing a new protein fold. Later we also solved the structure of the truncated GFRα1 in the complex with GDNF and this model was confirmed by site-directed mutagenesis. In summary, our work contributed to the structural characterization of GFRα-based receptor complex and revealed a new receptor for GDNF, neurturin and artemin the HSPG syndecan-3. This information is critically important for the development of GFRα/RET agonists for the treatment of neurodegenerative diseases.

System integration design in MEMS - A case study of micromachined load cell

One of the critical issues in large scale commercial exploitation of MEMS technology is its system integration. In MEMS, a system design approach requires integration of varied and disparate subsystems with one of a kind interface. The physical scales as well as the magnitude of signals of various subsystems vary widely. Known and proven integration techniques often lead to considerable loss in advantages the tiny MEMS sensors have to offer. Therefore, it becomes imperative to think of the entire system at the outset, at least in terms of the concept design. Such design entails various aspects of the system ranging from selection of material, transduction mechanism, structural configuration, interface electronics, and packaging. One way of handling this problem is the system-in-package approach that uses optimized technology for each function using the concurrent hybrid engineering approach. The main strength of this design approach is the fast time to prototype development. In the present work, we pursue this approach for a MEMS load cell to complete the process of system integration for high capacity load sensing. The system includes; a micromachined sensing gauge, interface electronics and a packaging module representing a system-in-package ready for end characterization. The various subsystems are presented in a modular stacked form using hybrid technologies. The micromachined sensing subsystem works on principles of piezo-resistive sensing and is fabricated using CMOS compatible processes. The structural configuration of the sensing layer is designed to reduce the offset, temperature drift, and residual stress effects of the piezo-resistive sensor. ANSYS simulations are carried out to study the effect of substrate coupling on sensor structure and its sensitivity. The load cell system has built-in electronics for signal conditioning, processing, and communication, taking into consideration the issues associated with resolution of minimum detectable signal. The packaged system represents a compact and low cost solution for high capacity load sensing in the category of compressive type load sensor.

An Input Triggered Polymorphic ASIC for H.264 Decoding

This paper reports the design of an input-triggered polymorphic ASIC for H.264 baseline decoder. Hardware polymorphism is achieved by selectively reusing hardware resources at system and module level. Complete design is done using ESL design tools following a methodology that maintains consistency in testing and verification throughout the design flow. The proposed design can support frame sizes from QCIF to 1080p.

Defects in the IFT-B component IFT172 cause Jeune and Mainzer-Saldino syndromes in humans

Intraflagellar transport (IFT) depends on two evolutionarily conserved modules, subcomplexes A (IFT-A) and B (IFT-B), to drive ciliary assembly and maintenance. All six IFT-A components and their motor protein, DYNC2H1, have been linked to human skeletal ciliopathies, including asphyxiating thoracic dystrophy (ATD; also known as Jeune syndrome), Sensenbrenner syndrome, and Mainzer-Saldino syndrome (MZSDS). Conversely, the 14 subunits in the IFT-B module, with the exception of IFT80, have unknown roles in human disease. To identify additional IFT-B components defective in ciliopathies, we independently performed different mutation analyses: candidate-based sequencing of all IFT-B-encoding genes in 1,467 individuals with a nephronophthisis-related ciliopathy or whole-exome resequencing in 63 individuals with ATD. We thereby detected biallelic mutations in the IFT-B-encoding gene IFT172 in 12 families. All affected individuals displayed abnormalities of the thorax and/or long bones, as well as renal, hepatic, or retinal involvement, consistent with the diagnosis of ATD or MZSDS. Additionally, cerebellar aplasia or hypoplasia characteristic of Joubert syndrome was present in 2 out of 12 families. Fibroblasts from affected individuals showed disturbed ciliary composition, suggesting alteration of ciliary transport and signaling. Knockdown of ift172 in zebrafish recapitulated the human phenotype and demonstrated a genetic interaction between ift172 and ift80. In summary, we have identified defects in IFT172 as a cause of complex ATD and MZSDS. Our findings link the group of skeletal ciliopathies to an additional IFT-B component, IFT172, similar to what has been shown for IFT-A.

Canadian Stroke Best Practice Recommendations: Mood, Cognition and Fatigue Following Stroke practice guidelines, update 2015

Every year, approximately 62 000 people with stroke and transient ischemic attack are treated in Canadian hospitals, and the evidence suggests one-third or more will experience vascular-cognitive impairment, and/or intractable fatigue, either alone or in combination. The 2015 update of the Canadian Stroke Best Practice Recommendations: Mood, Cognition and Fatigue Module guideline is a comprehensive summary of current evidence-based recommendations for clinicians in a range of settings, who provide care to patients following stroke. The three consequences of stroke that are the focus of the this guideline (poststroke depression, vascular cognitive impairment, and fatigue) have high incidence rates and significant impact on the lives of people who have had a stroke, impede recovery, and result in worse long-term outcomes. Significant practice variations and gaps in the research evidence have been reported for initial screening and in-depth assessment of stroke patients for these conditions. Also of concern, an increased number of family members and informal caregivers may also experience depressive symptoms in the poststroke recovery phase which further impact patient recovery. These factors emphasize the need for a system of care that ensures screening occurs as a standard and consistent component of clinical practice across settings as stroke patients transition from acute care to active rehabilitation and reintegration into their community. Additionally, building system capacity to ensure access to appropriate specialists for treatment and ongoing management of stroke survivors with these conditions is another great challenge.

Dynamic simulation of activated sludge based wastewater treatment processes: Case studies with Titagarh Sewage Treatment Plant, India

STOAT has been extensively used for the dynamic simulation of an activated sludge based wastewater treatment plant in the Titagarh Sewage Treatment Plant, near Kolkata, India. Some alternative schemes were suggested. Different schemes were compared for the removal of Total Suspended Solids (TSS), b-COD, ammonia, nitrates etc. A combination of IAWQ#1 module with the Takacs module gave best results for the existing scenarios of the Titagarh Sewage Treatment Plant. The modified Bardenpho process was found most effective for reducing the mean b-COD level to as low as 31.4 mg/l, while the mean TSS level was as high as 100.98 mg/l as compared to the mean levels of TSS (92 62 mg/l) and b-COD (92.0 mg/l) in the existing plant. Scheme 2 gave a better scenario for the mean TSS level bringing it down to a mean value of 0.4 mg/l, but a higher mean value for the b-COD level at 54.89 mg/l. The Scheme Final could reduce the mean TSS level to 2.9 mg/l and the mean b-COD level to as low as 38.8 mg/l. The Final Scheme looks to be a technically viable scheme with respect to the overall effluent quality for the plant. (C) 2009 Elsevier B.V. All rights reserved.

Kernel-based spatial-color modeling for fast moving object tracking

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

Place categorization and semantic mapping on a mobile robot

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.