Let's talk about genes, and I dont mean trousers:encouraging cancer genetics literacy amongst children

Acquiring genetic literacy is one of the most important things a person can do to promote their own and their family’s health. Family history—genetics and the shared environment—is a significant risk factor for cancer as well as other common diseases, such as cardiovascular disease and diabetes. A good understanding of family health history should increasingly be used to personalise health messages and promote healthy lifestyles. The Let’s Talk About Genes project explored whether it was feasible and acceptable to engage young children in Wales with family history as it relates specifically to cancer, so they increase their cancer genetics literacy over time and become more aware of general health issues that relate to cancer

Rapid Sampling for Visualizations with Ordering Guarantees

Visualizations are frequently used as a means to understand trends and gather insights from datasets, but often take a long time to generate. In this paper, we focus on the problem of rapidly generating approximate visualizations while preserving crucial visual proper- ties of interest to analysts. Our primary focus will be on sampling algorithms that preserve the visual property of ordering; our techniques will also apply to some other visual properties. For instance, our algorithms can be used to generate an approximate visualization of a bar chart very rapidly, where the comparisons between any two bars are correct. We formally show that our sampling algorithms are generally applicable and provably optimal in theory, in that they do not take more samples than necessary to generate the visualizations with ordering guarantees. They also work well in practice, correctly ordering output groups while taking orders of magnitude fewer samples and much less time than conventional sampling schemes.Comment: Tech Report. 17 pages. Condensed version to appear in VLDB Vol. 8 No.

Optimizing Query Predicates with Disjunctions for Column Stores

Since its inception, database research has given limited attention to optimizing predicates with disjunctions. What little past work there is has focused on optimizations for traditional row-oriented databases. A key difference in predicate evaluation for row stores and column stores is that while row stores apply predicates to one record at a time, column stores apply predicates to sets of records. Not only must the execution engine decide the order in which to apply the predicates, but it must also decide how many times each predicate should be applied and on which sets of records it should be applied to. In our work, we tackle exactly this problem. We formulate, analyze, and solve the predicate evaluation problem for column stores. Our results include proofs about various properties of the problem, and in turn, these properties have allowed us to derive the first polynomial-time (i.e., O(n log n)) algorithm ShallowFish which evaluates predicates optimally for all predicate expressions with a depth of 2 or less. We capture the exact property which makes the problem more difficult for predicate expressions of depth 3 or greater and propose an approximate algorithm DeepFish which outperforms ShallowFish in these situations. Finally, we show that both ShallowFish and DeepFish outperform the corresponding state of the art by two orders of magnitude

Intimate partner violence (IPV) in male and female orthopaedic trauma patients:a multi-centre, cross-sectional prevalence study

Objectives Identify the proportion of patients attending fracture clinics who had suffered intimate partner violence (IPV) within the past year. Design Powered cross-sectional study using validated participant self-reported questionnaires. Setting and participants Adult trauma patients (no gender/age exclusions) attending one of three Scottish adult fracture clinics over 16-month period (from October 2016 to January 2018). Primary outcome measure Number of participants answering 'yes' to the Woman Abuse Screening Tool question: 'In your current relationship over the past twelve months, has your partner ever abused you physically/emotionally/sexually?' Results Of 336 respondents, 46% (156/336 known) were women with 65% aged over 40 (212/328 known). The overall prevalence of IPV within the preceding 12 months was 12% 39/336) for both male and female patients. The lifetime prevalence of IPV among respondents was 20% (68/336). 38% of patients who had experienced IPV within the past 12 months had been physically abused (11/29). None of the patients were being seen for an injury caused by abuse. Two-thirds of respondents thought that staff should ask routinely about IPV (55%, 217/336), but only 5% had previously been asked about abuse (18/336). Conclusions This is the first study worldwide investigating the prevalence of IPV in fracture clinics for both male and female patients. 12-month prevalence of IPV in fracture clinic patients is significant and not affected by gender in this study. Patients appear willing to disclose abuse within this setting and are supportive of staff asking about abuse. This presents an opportunity to identify those at risk within this vulnerable population.</p

Ready Student One: Exploring the predictors of student learning in virtual reality

Immersive virtual reality (VR) has enormous potential for education, but classroom resources are limited. Thus, it is important to identify whether and when VR provides sufficient advantages over other modes of learning to justify its deployment. In a between-subjects experiment, we compared three methods of teaching Moon phases (a hands-on activity, VR, and a desktop simulation) and measured student improvement on existing learning and attitudinal measures. While a substantial majority of students preferred the VR experience, we found no significant differences in learning between conditions. However, we found differences between conditions based on gender, which was highly correlated with experience with video games. These differences may indicate certain groups have an advantage in the VR setting.Comment: 28 pages, 7 figures, 4 tables. Published in PLOS ONE March 25, 202

Study on the Context-Aware Middleware for Ubiquitous Greenhouses Using Wireless Sensor Networks

Wireless Sensor Network (WSN) technology is one of the important technologies to implement the ubiquitous society, and it could increase productivity of agricultural and livestock products, and secure transparency of distribution channels if such a WSN technology were successfully applied to the agricultural sector. Middleware, which can connect WSN hardware, applications, and enterprise systems, is required to construct ubiquitous agriculture environment combining WSN technology with agricultural sector applications, but there have been insufficient studies in the field of WSN middleware in the agricultural environment, compared to other industries. This paper proposes a context-aware middleware to efficiently process data collected from ubiquitous greenhouses by applying WSN technology and used to implement combined services through organic connectivity of data. The proposed middleware abstracts heterogeneous sensor nodes to integrate different forms of data, and provides intelligent context-aware, event service, and filtering functions to maximize operability and scalability of the middleware. To evaluate the performance of the middleware, an integrated management system for ubiquitous greenhouses was implemented by applying the proposed middleware to an existing greenhouse, and it was tested by measuring the level of load through CPU usage and the response time for users’ requests when the system is working