The estrogen receptor 1 G594A polymorphism is associated with migraine susceptibility in two independent case/control groups

Migraine is a painful and debilitating disorder with a significant genetic component. Steroid hormones, in particular estrogen, have long been considered to play a role in migraine, as variations in hormone levels are associated with migraine onset in many sufferers of the disorder. Steroid hormones mediate their activity via hormone receptors, which have a wide tissue distribution. Estrogen receptors have been localized to the brain in regions considered to be involved in migraine pathogenesis. Hence it is possible that genetic variation in the estrogen receptor gene may play a role in migraine susceptibility. This study thus examined the estrogen receptor 1 (ESRα) gene for a potential role in migraine pathogenesis and susceptibility. A population-based cohort of 224 migraine sufferers and 224 matched controls were genotyped for the G594A polymorphism located in exon 8 of the ESR1 gene. Statistical analysis indicated a significant difference between migraineurs and non-migraineurs in both the allele frequencies (P=0.003) and genotype distributions (P=0.008) in this sample. An independent follow-up study was then undertaken using this marker in an additional population-based cohort of 260 migraine sufferers and 260 matched controls. This resulted in a significant association between the two groups with regard to allele frequencies (P=8×10−6) and genotype distributions (P=4×10−5). Our findings support the hypothesis that genetic variation in hormone receptors, in particular the ESR1 gene, may play a role in migraine.

High efficiency auxiliary power converters

The auxiliary load DC-DC converters of the Sunshark solar car have never been examined. An analysis of the current design reveals it is complicated, and inefficient. Some simple measures to greatly improve the efficiency are present which will achieve an overall worthwhile power saving. Two switch-mode power supply DC-DC converter designs are presented. One is a constant current supply for the LED brake and turn indicators, which allows them to be powered directly from the main DC bus, and switched only as necessary. The second is a low power flyback converter, which employs synchronous rectification among other techniques to achieve good efficiency and regulation over a large range of output powers. Practical results from both converters, and an indication of the overall improvement in system efficiency will be offered.

High rates of muscle glycogen resynthesis after exhaustive exercise when carbohydrate is coingested with caffeine

We determined the effect of coingestion of caffeine (Caff) with carbohydrate (CHO) on rates of muscle glycogen resynthesis during recovery from exhaustive exercise in seven trained subjects who completed two experimental trials in a randomized, double-blind crossover design. The evening before an experiment subjects performed intermittent exhaustive cycling and then consumed a low-CHO meal. The next morning subjects rode until volitional fatigue. On completion of this ride subjects consumed either CHO [4 g/kg body mass (BM)] or the same amount of CHO + Caff (8 mg/kg BM) during 4 h of passive recovery. Muscle biopsies and blood samples were taken at regular intervals throughout recovery. Muscle glycogen levels were similar at exhaustion [?75 mmol/kg dry wt (dw)] and increased by a similar amount (?80%) after 1 h of recovery (133 ± 37.8 vs. 149 ± 48 mmol/kg dw for CHO and Caff, respectively). After 4 h of recovery Caff resulted in higher glycogen accumulation (313 ± 69 vs. 234 ± 50 mmol/kg dw, P < 0.001). Accordingly, the overall rate of resynthesis for the 4-h recovery period was 66% higher in Caff compared with CHO (57.7 ± 18.5 vs. 38.0 ± 7.7 mmol·kg dw-1·h-1, P < 0.05). After 1 h of recovery plasma Caff levels had increased to 31 ± 11 ?M (P < 0.001) and at the end of the recovery reached 77 ± 11 ?M (P < 0.001) with Caff. Phosphorylation of CaMKThr286 was similar after exercise and after 1 h of recovery, but after 4 h CaMKThr286 phosphorylation was higher in Caff than CHO (P < 0.05). Phosphorylation of AMP-activated protein kinase (AMPK)Thr172 and AktSer473 was similar for both treatments at all time points. We provide the first evidence that in trained subjects coingestion of large amounts of Caff (8 mg/kg BM) with CHO has an additive effect on rates of postexercise muscle glycogen accumulation compared with consumption of CHO alone.

Prognostic value of TP53, KRAS and EGFR mutations in nonsmall cell lung cancer : the EUELC cohort

Nonsmall cell lung cancer samples from the European Early Lung Cancer biobank were analysed to assess the prognostic significance of mutations in the TP53, KRAS and EGFR genes. The series included 11 never-smokers, 86 former smokers, 152 current smokers and one patient without informed smoking status. There were 110 squamous cell carcinomas (SCCs), 133 adenocarcinomas (ADCs) and seven large cell carcinomas or mixed histologies. Expression of p53 was analysed by immunohistochemistry. DNA was extracted from frozen tumour tissues. TP53 mutations were detected in 48.8% of cases and were more frequent among SCCs than ADCs (p<0.0001). TP53 mutation status was not associated with prognosis. G to T transversions, known to be associated with smoking, were marginally more common among patients who developed a second primary lung cancer or recurrence/metastasis (progressive disease). EGFR mutations were almost exclusively found in never-smoking females (p=0.0067). KRAS mutations were detected in 18.5% of cases, mainly ADC (p<0.0001), and showed a tendency toward association with progressive disease status. These results suggest that mutations are good markers of different aetiologies and histopathological forms of lung cancers but have little prognostic value, with the exception of KRAS mutation, which may have a prognostic value in ADC. Copyright©ERS 2012.

Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study : assessing the viability and sustainability of the dairy industry

Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.

Experience, recursive awareness and understanding in autism spectrum disorders : insights of parents and teachers in Singapore

Provision of an individually responsive education requires a comprehensive understanding of the inner worlds of learners, such as their feelings and thoughts. However, this is difficult to achieve when learners, such as those with Autism Spectrum Disorders (ASD) and cognitive difficulties, have problems with communication. To address this issue, the current exploratory descriptive study sought the views of 133 Singaporean parents and teachers of school-age learners with ASD and cognitive difficulties regarding the inner experience of their children and students. The findings highlight the variety of abilities and difficulties found in how these learners experience their own mental states and understand those of others. These abilities and difficulties are characterized according to type of mental state and analysed in line with three qualia, those of experience, recursive awareness and understanding. The findings indicate that learners show a greater awareness of their own mental states compared to their ability to understand these same mental states in others. Educational implications are discussed.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

The velocity synchronous discrete Fourier transform for order tracking in the field of rotating machinery

Diagnostics of rotating machinery has developed significantly in the last decades, and industrial applications are spreading in different sectors. Most applications are characterized by varying velocities of the shaft and in many cases transients are the most critical to monitor. In these variable speed conditions, fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In the past, this issue was often solved by synchronously sampling data by means of phase locked circuits governing the acquisition; however, thanks to the spread of cheap and powerful microprocessors, this procedure is nowadays rarer; sampling is usually performed at constant time intervals, and the conversion to the order domain is made by means of digital signal processing techniques. In the last decades different algorithms have been proposed for the extraction of an order spectrum from a signal sampled asynchronously with respect to the shaft rotational velocity; many of them (the so called computed order tracking family) use interpolation techniques to resample the signal at constant angular increments, followed by a common discrete Fourier transform to shift from the angular domain to the order domain. A less exploited family of techniques shifts directly from the time domain to the order spectrum, by means of modified Fourier transforms. This paper proposes a new transform, named velocity synchronous discrete Fourier transform, which takes advantage of the instantaneous velocity to improve the quality of its result, reaching performances that can challenge the computed order tracking.

Large-scale analysis of formations in soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

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.

Review of the fire performance of LSF walls

Load bearing LSF walls are commonly made of cold-formed steel frames, gypsum plasterboards and insulation, and their fire performance is an important aspect of design. Many experimental and numerical studies have been conducted on the fire performance of LSF walls at the Queensland University of Technology (QUT). These studies have shown that increasing the number or thickness or quality of gypsum plasterboards has improved the fire resistance ratings (FRR) of LSF walls while the use of cavity insulation has reduced their FRR. Therefore new LSF wall systems with external insulation sandwiched between two layers of plasterboards were proposed, which provided higher FRR than cavity insulated walls. There are also other parameters that can improve the fire performance of LSF walls such as the steel type, stud geometry and depth, type of screw fasteners used, joints in the plasterboard and the plasterboard fall off time. This paper presents a review of the fire performance of LSF walls as a function of these parameters based on our research at QUT. Their effects on both the thermal and structural performance of LSF walls are discussed in detail and suitable improvements are recommended, for example, improved plasterboard joint types.

Experimental study on the fire performance of superior LSF wall systems

Load bearing Light Gauge Steel Frame (LSF) walls are commonly made of conventional lipped channel sections and gypsum plasterboards. Recently, innovative steel sections such as hollow flange channel sections have been proposed as studs in LSF wall frames with a view to improve their fire resistance ratings. A series of full scale fire tests was then undertaken to investigate the fire performance of the new LSF wall systems under standard fire conditions. Test wall frames made of hollow flange section studs were lined with fire resistant gypsum plasterboards on both sides, and were subjected to increasing temperatures as given by the standard fire curve on one side. Both uninsulated and cavity insulated walls were tested with varying load ratios from 0.2 to 0.6. This paper presents the details of this experimental study on the fire performance of LSF walls and the results. Test results showed that the walls made of the new hollow flange channel section studs have a superior fire performance in comparison to that of lipped channel section stud walls. They also showed that the fire performance of cavity insulated walls was inferior to that of uninsulated walls. The reasons for this fire behaviour are described in this paper.