A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other

In this report, we describe a simple correction for multiple testing of single-nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of pairwise LD between SNPs. This method provides a useful alternative to more computationally intensive permutation tests. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor "loadings" after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.

Commentary: Chronic SSRI stimulation of astrocytic 5-HT2B receptors change multiple gene expressions/editings and metabolism of glutamate, glucose and glycogen: A potential paradigm shift

Working on the serotonin (5-hydroxytryptamine, 5-HT) 5-HT2B receptor since several years, we have read with high interest the review by Hertz et al. (2015). Previous studies from our group demonstrated that a direct injection in mouse raphe nucleus of the 5-HT2B agonist BW723C86 has the ability to increase extracellular levels of serotonin, which can be blocked by the selective 5-HT2B receptor antagonist RS127445 (Doly et al., 2008, 2009). We also reported that an acute injection of paroxetine 2 mg/kg in mice knocked out for the 5-HT2B receptor gene or in wild type mice injected with RS127445 (0.5 mg/kg) triggers a strong reduction in extracellular accumulation of 5-HT in hippocampus (Diaz et al., 2012). Following these observations, we showed that acute and chronic BW723C86 injection (3 mg/kg) can mimic the fluoxetine (3 mg/kg) and paroxetine (1 mg/kg) behavioral and biochemical antidepressant effects in mice (Diaz and Maroteaux, 2011; Diaz et al., 2012)...

A flexible hierarchical approach for facial age estimation based on multiple features

Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

Recipe for success — Lessons learnt from using xAPI within the Connected Learning Analytics toolkit

An ongoing challenge for Learning Analytics research has been the scalable derivation of user interaction data from multiple technologies. The complexities associated with this challenge are increasing as educators embrace an ever growing number of social and content related technologies. The Experience API (xAPI) alongside the development of user specific record stores has been touted as a means to address this challenge, but a number of subtle considerations must be made when using xAPI in Learning Analytics. This paper provides a general overview to the complexities and challenges of using xAPI in a general systemic analytics solution - called the Connected Learning Analytics (CLA) toolkit. The importance of design is emphasised, as is the notion of common vocabularies and xAPI Recipes. Early decisions about vocabularies and structural relationships between statements can serve to either facilitate or handicap later analytics solutions. The CLA toolkit case study provides us with a way of examining both the strengths and the weaknesses of the current xAPI specification, and we conclude with a proposal for how xAPI might be improved by using JSON-LD to formalise Recipes in a machine readable form.

Sustainable building envelope design by considering energy cost and occupant satisfaction

The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

Understanding the information dynamics of medication administration in residential aged care facilities (RACFs): A prerequisite for design of effective ICT systems

Medication information is a critical part of the information required to ensure residents' safety in the highly collaborative care context of RACFs. Studies report poor medication information as a barrier to improve medication management in RACFs. Research exploring medication work practices in aged care settings remains limited. This study aimed to identify contextual and work practice factors contributing to breakdowns in medication information exchange in RACFs in relation to the medication administration process. We employed non-participant observations and semi-structured interviews to explore information practices in three Australian RACFs. Findings identified inefficiencies due to lack of information timeliness, manual stock management, multiple data transcriptions, inadequate design of essential documents such as administration sheets and a reliance on manual auditing procedures. Technological solutions such as electronic medication administration records offer opportunities to overcome some of the identified problems. However these interventions need to be designed to align with the collaborative team based processes they intend to support.

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

Energy and cities

Any plan for decoupling growth from fossil fuel use needs to prioritise locally appropriate, integrated and multi-faceted outcomes. Such transitions can be highly complex, given the physical and institutional characteristics of existing electricity infrastructure as well as various financial, technical and practical challenges. This Chapter applies a whole systems perspective to developing decoupling solutions, reflecting on the Dutch Sustainable Technology Development Program and Townsville City (Queensland, Australia). Key aspects considered include the need for demonstrating outcomes to multiple stakeholders, using pilot projects with integrated monitoring and evaluation, fostering collaborative approaches to energy management, cultivating cultures of ‘learning by doing’, and seeking synergies across multiple agendas.

Dancing practices from multiple perspectives: the increasingly complex role of the contemporary dancer

This paper will discuss the complexities of the role of contemporary dancer in this current epoch, with a particular focus on the multiple identities dancers embody within dance practice and how these accumulate to form a creative self-in-process or ‘moving identity’. Wider issues, such as training will be explored questioning how technical skills can be imparted alongside autonomous learning approaches to ensure that dancers are prepared to negotiate the entrepreneurial ecology of various dance sectors. Furthermore, the paper will examine the shifting relationship between choreographer and dancer from hierarchical to co-creative including how, in spite of the often collaborative nature of dance creation, the marketplace continues to celebrate the singular authorial position of the choreographer. Each of these elements will reflect back the complex issues of agency and creative self-hood that dancers must negotiate in an increasingly diverse and changeable arts environment.

A multi-criteria approach for hospital capacity analysis

Hospitals are critical elements of health care systems and analysing their capacity to do work is a very important topic. To perform a system wide analysis of public hospital resources and capacity, a multi-objective optimization (MOO) approach has been proposed. This approach identifies the theoretical capacity of the entire hospital and facilitates a sensitivity analysis, for example of the patient case mix. It is necessary because the competition for hospital resources, for example between different entities, is highly influential on what work can be done. The MOO approach has been extensively tested on a real life case study and significant worth is shown. In this MOO approach, the epsilon constraint method has been utilized. However, for solving real life applications, with a large number of competing objectives, it was necessary to devise new and improved algorithms. In addition, to identify the best solution, a separable programming approach was developed. Multiple optimal solutions are also obtained via the iterative refinement and re-solution of the model.

Multiple roles of transfer prices: One vs. two books

This paper investigates multiple roles of transfer prices for shipments of goods and services between entities of a multinational enterprise. At the center is the role of transfer pricing (TP) in tax manipulation, but other roles having to do with internal operations or strategic delegation, etc. are also considered. The interesting question is to what extent and how the different roles of TPs interfere with each other. The answer depends on whether companies use one or two books, i.e. whether they (can) apply different TPs for different purposes. We illustrate, in a stylized model, the competing aims of tax manipulation and strategic delegation. Finally, we briefly look at selected reform proposals, concluding that either TP problems are not addressed, or else new distortions will be introduced instead.

Ion exchange of sodium chloride and sodium bicarbonate solutions using strong acid cation resins in relation to coal seam water treatment

Coal seam gas production has resulted in the production of large volumes of associated water which contains dissolved salts dominated by sodium chloride and sodium bicarbonate. Ion exchange using synthetic resins has been proposed as a method for desalination of coal seam water to make it suitable for various beneficial reuse options. This study investigated the behaviour of solutions of sodium chloride and sodium bicarbonate with respect to exchange with Lanxess S108H strong acid cation (SAC) resin. Equilibrium isotherms were created for solutions of NaCl and NaHCO3 and an actual sample of coal seam water from the Surat Basin in southern Queensland. The exchange of sodium ions arising from sodium bicarbonate was found to be considerably more favourable than exchange of sodium ions from sodium chloride solutions. This latter behaviour was attributed to the secondary decomposition of bicarbonate species under acidic conditions which resulted in the evolution of carbon dioxide and formation of water. The isotherm profiles could not be satisfactorily fitted by a single isotherm model such as the Langmuir expression. Instead, two Langmuir equations had to be simultaneously applied in order to fit the sections of the isotherm attributable to sodium ion exchange from sodium bicarbonate and sodium chloride. The shape of the isotherm profile was dependent upon the ratio of sodium chloride to sodium bicarbonate in solution and there was a high degree of correlation between simulated and actual coal seam water solutions.

Autonomous greenhouse gas sampling using multiple robotic boats

Accurately quantifying total greenhouse gas emissions (e.g. methane) from natural systems such as lakes, reservoirs and wetlands requires the spatial-temporal measurement of both diffusive and ebullitive (bubbling) emissions. Traditional, manual, measurement techniques provide only limited localised assessment of methane flux, often introducing significant errors when extrapolated to the whole-of-system. In this paper, we directly address these current sampling limitations and present a novel multiple robotic boat system configured to measure the spatiotemporal release of methane to atmosphere across inland waterways. The system, consisting of multiple networked Autonomous Surface Vehicles (ASVs) and capable of persistent operation, enables scientists to remotely evaluate the performance of sampling and modelling algorithms for real-world process quantification over extended periods of time. This paper provides an overview of the multi-robot sampling system including the vehicle and gas sampling unit design. Experimental results are shown demonstrating the system’s ability to autonomously navigate and implement an exploratory sampling algorithm to measure methane emissions on two inland reservoirs.