The highly abundant urinary metabolite urobilin interferes with the bicinchoninic acid assay

Estimation of total protein concentration is an essential step in any protein- or peptide-centric analysis pipeline. This study demonstrates that urobilin, a breakdown product of heme and a major constituent of urine, interferes considerably with the bicinchoninic acid (BCA) assay. This interference is probably due to the propensity of urobilin to reduce cupric ions (Cu2+) to cuprous ions (Cu1+), thus mimicking the reduction of copper by proteins, which the assay was designed to do. In addition, it is demonstrated that the Bradford assay is more resistant to the influence of urobilin and other small molecules. As such, urobilin has a strong confounding effect on the estimate of total protein concentrations obtained by BCA assay and thus this assay should not be used for urinary protein quantification. It is recommended that the Bradford assay be used instead.

Regulating integrated advertising

This chapter approaches integrated advertising as a practice that is continuous with advertising history, rather than a phenomenon associated with new technologies. Competition for technology-enabled audiences in expanding media and entertainment markets is nonetheless an important factor in the turn to integrated advertising and marketing strategies in recent years. While integrated advertising provides solutions for advertisers, it is problematic for media consumers because it is not always distinguishable from surrounding program content and clearly identifiable as advertising. It creates opportunities for advertisers to fly below the radar of citizen and consumer awareness of commercial and political influences in media content, and for this reason has been constrained by regulation. Media regulators have come to play an important role in striking a balance between public and private interests in commercial media by setting and adjudicating the limits of integrated advertising practices. This chapter looks at how broadcasting regulators have responded to the challenges of regulating integrated advertising in commercial radio in three different territories (United States, United Kingdom and Australia). It draws attention to the ways in which integrated advertising simultaneously drives innovation in media genres and forms, as well as de-regulation of the influence exercised by advertisers in commercial media content.

Awareness of risky behaviour among Chinese drivers

Background In China, as in many developing countries, rapid increases in car ownership and new drivers have been coupled with a large trauma burden. The World Health Organization has identified key risk factors including speeding, drink-driving, helmet and restraint non-use, overloaded vehicles, and fatigued-driving in many rapidly motorising countries, including China. Levels of awareness of these risk factors among road users are not well understood. Although research identifies speeding as the major factor contributing to road crashes in China, there appears to be widespread acceptance of it among the broader community. Purpose To assess self-reported speeding and awareness of crash risk factors among Chinese drivers in Beijing. Methods Car drivers (n=299) were recruited from car washing locations and car parks to complete an anonymous questionnaire. Perceptions of the relative risk of drink-driving, fatigued-driving and speeding, and attitudes towards speeding and self-reported driving speeds were assessed. Results Overall, driving speeds of >10km/hr above posted limits on two road types (60 and 80 km/hour zones) were reported by more than one third of drivers. High-range speeding (i.e., >30 km/hour in a 60 km/hour zone and >40 km/hour in an 80 km/hour zone) was reported by approximately 5% of the sample. Attitudinal measures indicated that approximately three quarters of drivers reported attitudes that were not supportive of speeding. Drink-driving was identified as the most risky behaviour; 18% reported the perception that drink-driving had the same level of danger as speeding and 82% reported it as more dangerous. For fatigued-driving, 1% reported the perception that it was not as dangerous as speeding; 27.4% reported it as the same level and 71.6% perceived it as more dangerous. Conclusion Driving speeds well above posted speed limits were commonly reported by drivers. Speeding was rated as the least dangerous on-road behaviour, compared to drink-driving and fatigued-driving. One third of drivers reported regularly engaging in speeds at least 10km/hr above posted limits, despite speeding being the major reported contributor to crashes. Greater awareness of the risks associated with speeding is needed to help reduce the road trauma burden in China and promote greater speed limit compliance.

A recommendation approach dealing with multiple market segments

A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

Ontology-based product's reputation model

Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

Effectiveness of pilot car operations in reducing speeds in a long-term rural highway work zone

Pilot cars are used in one-lane two-way work zones to guide traffic and keep their speeds within posted limits. While many studies have examined the effectiveness of measures to reduce vehicle speeds in work zones, little is known about the reductions achievable through the use of pilot cars. This paper examines the effectiveness of a pilot car in reducing travel speeds in a rural highway work zone in Queensland, Australia. Analysis of speed data covering a period of five days showed that a pilot car reduced average speeds at the treatment location, but not downstream. The proportion of vehicles speeding through the activity area was also reduced, particularly those traveling at 10 km/h or more above the posted limit. Motorists were more likely to speed during the day, under a 40 kh/h limit, when traffic volumes were higher and when there were fewer vehicles in the traffic stream. Medium vehicles were less likely to speed in the presence of a pilot car than light vehicles. To maximize these benefits, it is necessary to ensure that the pilot car itself is not speeding.

Physiotherapists have accurate expectations of their patients’ future health-related quality of life after first assessment in a subacute rehabilitation setting

BACKGROUND Expectations held by health professionals and their patients are likely to affect treatment choices in subacute inpatient rehabilitation settings for older adults. There is a scarcity of empirical evidence evaluating whether health professionals expectations of the quality of their patients' future health states are accurate. METHODS A prospective longitudinal cohort investigation was implemented to examine agreement (kappa coefficients, exact agreement, limits-of-agreement, and intraclass-correlation coefficients) between physiotherapists' (n = 23) prediction of patients' discharge health-related quality of life (reported on the EQ-5D-3L) and the actual health-related quality of life self-reported by patients (n = 272) at their discharge assessment (using the EQ-5D-3L). The mini-mental state examination was used as an indicator of patients' cognitive ability. RESULTS Overall, 232 (85%) patients had all assessment data completed and were included in analysis. Kappa coefficients (exact agreement) ranged between 0.37-0.57 (58%-83%) across EQ-5D-3L domains in the lower cognition group and 0.53-0.68 (81%-85%) in the better cognition group. CONCLUSIONS Physiotherapists in this subacute rehabilitation setting predicted their patients' discharge health-related quality of life with substantial accuracy. Physiotherapists are likely able to provide their patients with sound information regarding potential recovery and health-related quality of life on discharge. The prediction accuracy was higher among patients with better cognition than patients with poorer cognition.

Modelling for the electricity distribution network

Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

Comprehensive Addictive Behaviors and Disorders, Volume 3 : Interventions for Addiction

"Interventions for Addiction examines a wide range of responses to addictive behaviors, including psychosocial treatments, pharmacological treatments, provision of health care to addicted individuals, prevention, and public policy issues. Its focus is on the practical application of information covered in the two previous volumes of the series, Comprehensive Addictive Behaviors and Disorders. Readers will find information on treatments beyond commonly used methods, including Internet-based and faith-based therapies, and criminal justice interventions. The volume features extensive coverage of pharmacotherapies for each of the major drugs of abuse-including disulfiram, buprenorphine, naltrexone, and others-as well as for behavioral addictions. In considering public policy, the book examines legislative efforts, price controls, and limits on advertising, as well as World Health Organization (WHO) efforts. Interventions for Addiction is one of three volumes comprising the 2,500-page series, Comprehensive Addictive Behaviors and Disorders. This series provides the most complete collection of current knowledge on addictive behaviors and disorders to date. In short, it is the definitive reference work on addictions."--publisher website

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics

The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.

Climate Change and the Resilience of Commodity Food Production in Australia

The current view of Australian state and national governments about the effects of climate change on agriculture is that farmers – through the adoption of mitigation and adaptation strategies – will remain resilient, and agricultural production will continue to expand. The assumption is that neoliberalism will provide the best ‘free market’ options for climate change mitigation and adaptation in farming. In contrast, we argue that neoliberalism will increase the move towards productivis (‘high-tech’) agriculture – the very system that has caused major environmental damage to the Australian continent. High-tech farming is highly dependent upon access to water and fossil fuels, both of which would appear to be the main limits to production in future decades. Productivist agriculture is a system highly reliant upon fertilizers and fuels that are derived from the petrochemical industry, and are currently increasing in cost as the price of oil increases.

Heat strain and hydration status of surface mine blast crew workers

Objective Dehydration and symptoms of heat illness are common among the surface mining workforce. This investigation aimed to determine whether heat strain and hydration status exceeded recommended limits. Methods Fifteen blast crew personnel operating in the tropics were monitored across a 12-hour shift. Heart rate, core body temperature, and urine-specific gravity were continuously recorded. Participants self-reported fluid consumption and completed a heat illness symptom inventory. Results Core body temperature averaged 37.46 +/- 0.13[degrees]C, with the group maximum 37.98 +/- 0.19[degrees]C. Mean urine-specific gravity was 1.024 +/- 0.007, with 78.6% of samples 1.020 or more. Seventy-three percent of workers reported at least one symptom of heat illness during the shift. Conclusions Core body temperature remained within the recommended limits; however, more than 80% of workers were dehydrated before commencing the shift, and tended to remain so for the duration.