S-100 Overlays: A Brave New World?

Marine Information Overlay (MIO) is a generic term used to describe chart and navigation related information that supplement the content that is already contained in an ENC. This includes both static and dynamic information such as tide/water level, current flow, meteorological, oceanographic, and environmental protection. With the advent of S-100 and S-101, there is increased interest in providing a wide variety of ‘new’ overlay information. This paper provides a brief history of S-57 MIOs. Examples of navigational and non-navigation MIOs are given in terms of how currently used, by who, and for what purpose. Recommendations are provided for making a transition from S-57 MIOs to S-100 overlays that can be used with the ‘Next Generation’ ENC. More specifically, what has been proposed, how should they work, who will provide, and some future challenges/opportunities related to implementation

Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data

A major goal of molecular biology is determining the mechanisms that control the transcription of genes. Motif Enrichment Analysis (MEA) seeks to determine which DNA-binding transcription factors control the transcription of a set of genes by detecting enrichment of known binding motifs in the genes' regulatory regions. Typically, the biologist specifies a set of genes believed to be co-regulated and a library of known DNA-binding models for transcription factors, and MEA determines which (if any) of the factors may be direct regulators of the genes. Since the number of factors with known DNA-binding models is rapidly increasing as a result of high-throughput technologies, MEA is becoming increasingly useful. In this paper, we explore ways to make MEA applicable in more settings, and evaluate the efficacy of a number of MEA approaches.We first define a mathematical framework for Motif Enrichment Analysis that relaxes the requirement that the biologist input a selected set of genes. Instead, the input consists of all regulatory regions, each labeled with the level of a biological signal. We then define and implement a number of motif enrichment analysis methods. Some of these methods require a user-specified signal threshold, some identify an optimum threshold in a data-driven way and two of our methods are threshold-free. We evaluate these methods, along with two existing methods (Clover and PASTAA), using yeast ChIP-chip data. Our novel threshold-free method based on linear regression performs best in our evaluation, followed by the data-driven PASTAA algorithm. The Clover algorithm performs as well as PASTAA if the user-specified threshold is chosen optimally. Data-driven methods based on three statistical tests-Fisher Exact Test, rank-sum test, and multi-hypergeometric test--perform poorly, even when the threshold is chosen optimally. These methods (and Clover) perform even worse when unrestricted data-driven threshold determination is used.Our novel, threshold-free linear regression method works well on ChIP-chip data. Methods using data-driven threshold determination can perform poorly unless the range of thresholds is limited a priori. The limits implemented in PASTAA, however, appear to be well-chosen. Our novel algorithms--AME (Analysis of Motif Enrichment)-are available at http://bioinformatics.org.au/ame/

A multi-analytical approach to studying customers motivations to use innovative totally autonomous vehicles

Increasing technological innovation means level 5 fully autonomous vehicle pods (AVPs) that do not require a human driver are approaching reality. However, the adoption of AVPs continues to lag behind predictions. In this paper, we draw on Mowen's (2000) 3M model taking a multi-analytical approach utilising PLS-SEM and fuzzy set qualitative comparative analysis, to investigate how personality trait sets motivate consumers to adopt AVPs. Based on a survey of 551 US respondents, we identify four necessary traits and five combinations of traits that predict adoption. We contribute to consumer psychology theory by advancing the understanding of the motivational mechanisms of consumers’ adoption of autonomous vehicles that are triggered and operationalised by personality traits and conceptualising innovativeness as a complex multidimensional construct. From a managerial perspective, our findings highlight the significance of incorporating elements that are congruent with target customers’ personality traits, when designing, manufacturing and commercializing innovative products

Understanding pre-teen consumers social media engagement

Social media (SM) platforms are frequently used by pre-teen (8–12-year old) consumers for curating their self-identity, developing social relationships and for learning. This paper identifies the building blocks that drive pre-teen SM engagement. We use the Gioia method to analyse interview data collected from 32 pre-teens and parents, in France. Findings show that the primary building blocks are FoMO (Fear of Missing Out) and social inclusive experience, being noticed online, multiplicity, excessive use (without guidelines) and self-regulation. Identity constructs (self-identity and social-identity) are used to explain SM engagement – and to empirically define core conceptual building blocks (aggregate dimensions) that drive SM engagement. We contribute to consumer theory by developing a holistic research framework to examine pre-teen SM engagement. Self-identity and social-identity theories help explain the factors that drive pre-teen SM engagement and explain push/pull influences of parents and schools in encouraging or discouraging certain behaviour. We build on current research into SM usage, drawing from the fragmented existing literature, to reveal causes of both excessive screen-time and SM usage among pre-teen consumers, which may indicate antecedents of future adult behaviour. Practical and regulatory policy issues are considered and addressed

Machining distortion in asymmetrical residual stress profiles

This paper presents the results from a set of experimental and computational studies of the effect of asymmetrical residual stress on machining distortion of Al-7050 alloy. Aluminum coupons were physically bolted together for heat treatment to generate the asymmetrical residual stress profiles; which were measured using neutron diffraction method in the bulk of the samples after the heat treatment stage, and after the first machining stage to investigate the residual stress redistribution. A machining distortion model was successfully implemented to investigate comprehensibly the impact of the layer material removal in terms of depths of cut on the redistribution of the residual stress profile into the part, and how this redistribution influences the distortions in the coupon. This investigation allowed determining a robust machining approach capable of predicting the final desired distortion tolerance after clamping, irrespective of the highly asymmetric residual stress condition of the coupon. On machine inspection and CMM measurements were also done to validate the outcomes of the machining distortion model

Perfect weddings abroad

Approximately 16% of UK couples are currently married abroad. However, academic or practitioner focused research that explores the complex nature of a couple’s buying preferences or the development of innovative marketing strategies by businesses operating within the weddings abroad niche sector, is almost non-existent. This exploratory paper examines the role and relevance of marketing within the weddings abroad sector. The complex nature of customer needs in this high emotional and involvement experience, are identified and explored. A case study of Perfect Weddings Abroad Ltd highlights distinctive features and characteristics. Social networking and the use of home-workers, with a focus on reassurance and handholding are important tools used to develop relationships with customers. These tools and techniques help increase the tangibility of a weddings abroad package. Clusters of complementary services that are synergistic and provide sources of competitive advantage are identified and an agenda for future research is developed

Tool wear inspection of polycrystalline cubic boron nitride inserts

In industry, highly frequent inspection of tooling used to machine safety critical components is common place. Worn or damaged tools produce undesirable surface finishes leading often to early failure of the part due to fatigue crack growth. In the development stages of polycrystalline boron nitride tools, the tool wear inspection technique is an off-line run-to-failure method. This approach interrupts the cutting process intermittently, to measure the tool wear using optical and scanning microscopy. This method is time consuming and expensive, causing bottlenecks in production. The overall aim in industry is to develop an on-line, automated system capable of informing the operator of the tool’s imminent failure. This paper focuses on treating this process as a preventative maintenance problem by studying whether acoustic emission can be used as an indirect measurement of tool wear at any given time. Acoustic emission measurements taken from the machining process of face turning are investigated here. Basic analysis in the frequency domain using principle component analysis reveals a number of interesting insights into the process. Relationships between the sharpness of the tool and the magnitude of the frequencies suggests promising link between acoustic emission and tool wear

Population pharmacokinetic and pharmacodynamic properties of intramuscular quinine in Tanzanian children with severe Falciparum malaria.

Although artesunate is clearly superior, parenteral quinine is still used widely for the treatment of severe malaria. A loading-dose regimen has been recommended for 30 years but is still often not used. A population pharmacokinetic study was conducted with 75 Tanzanian children aged 4 months to 8 years with severe malaria who received quinine intramuscularly; 69 patients received a loading dose of 20 mg quinine dihydrochloride (salt)/kg of body weight. Twenty-one patients had plasma quinine concentrations detectable at baseline. A zero-order absorption model with one-compartment disposition pharmacokinetics described the data adequately. Body weight was the only significant covariate and was implemented as an allometric function on clearance and volume parameters. Population pharmacokinetic parameter estimates (and percent relative standard errors [%RSE]) of elimination clearance, central volume of distribution, and duration of zero-order absorption were 0.977 liters/h (6.50%), 16.7 liters (6.39%), and 1.42 h (21.5%), respectively, for a typical patient weighing 11 kg. Quinine exposure was reduced at lower body weights after standard weight-based dosing; there was 18% less exposure over 24 h in patients weighing 5 kg than in those weighing 25 kg. Maximum plasma concentrations after the loading dose were unaffected by body weight. There was no evidence of dose-related drug toxicity with the loading dosing regimen. Intramuscular quinine is rapidly and reliably absorbed in children with severe falciparum malaria. Based on these pharmacokinetic data, a loading dose of 20 mg salt/kg is recommended, provided that no loading dose was administered within 24 h and no routine dose was administered within 12 h of admission. (This study has been registered with Current Controlled Trials under registration number ISRCTN 50258054.)

Causal theories, models and evidence in economics-some reflections from the natural sciences

Models have been extensively analysed in economic methodology, notably their degree of ability to provide explanations. This paper takes a complementary, comparative approach, examining theory development in the natural sciences. Examples show how diverse types of evidence combine with causal hypotheses to generate empirically based causal theories—a cumulative process occurring over a long timescale. Models are typically nested within this broader theory. This could be a good model for research in economics, providing a methodology that ensures good correspondence with the target system—especially as economics research is largely empirical, and has effective methods for causal inference. This paper analyses the key features of three successful theories in the natural sciences, and draws out some lessons that may be useful to economists. Some examples of good practice in economics are noted, e.g. involving money and banking, and the growth of the state. On the other hand, the widespread pre-crisis use of dynamic stochastic general equilibrium (DSGE) models that ignored the financial sector raises the question, how to realise what has been omitted? Nesting models in an empirically based causal theory could solve this. Furthermore, some phenomena have clear explanations, but mainstream theory obscures them, as with the Lucas puzzle about the direction of international capital flows. And, the prevailing theories about capitalist growth do not explain the basic evidence on its temporal and spatial distribution. Economics could beneficially learn from the natural sciences