Efficient Algorithms for Answering the m-Closest Keywords Query

As an important type of spatial keyword query, the m-closest keywords (mCK) query finds a group of objects such that they cover all query keywords and have the smallest diameter, which is defined as the largest distance between any pair of objects in the group. The query is useful in many applications such as detecting locations of web resources. However, the existing work does not study the intractability of this problem and only provides exact algorithms, which are computationally expensive.

In this paper, we prove that the problem of answering mCK queries is NP-hard. We first devise a greedy algorithm that has an approximation ratio of 2. Then, we observe that an mCK query can be approximately answered by finding the circle with the smallest diameter that encloses a group of objects together covering all query keywords. We prove that the group enclosed in the circle can answer the mCK query with an approximation ratio of 2 over 3. Based on this, we develop an algorithm for finding such a circle exactly, which has a high time complexity. To improve efficiency, we propose another two algorithms that find such a circle approximately, with a ratio of 2 over √3 + ε. Finally, we propose an exact algorithm that utilizes the group found by the 2 over √3 + ε)-approximation algorithm to obtain the optimal group. We conduct extensive experiments using real-life datasets. The experimental results offer insights into both efficiency and accuracy of the proposed approximation algorithms, and the results also demonstrate that our exact algorithm outperforms the best known algorithm by an order of magnitude.

The BRUTUS Automatic Cryptanalytic Framework: Testing CAESAR Authenticated Encryption Candidates for Weaknesses

This report summarizes our results from security analysis covering all 57 competitions for authenticated encryption: security, applicability, and robustness (CAESAR) first-round candidates and over 210 implementations. We have manually identified security issues with three candidates, two of which are more serious, and these ciphers have been withdrawn from the competition. We have developed a testing framework, BRUTUS, to facilitate automatic detection of simple security lapses and susceptible statistical structures across all ciphers. From this testing, we have security usage notes on four submissions and statistical notes on a further four. We highlight that some of the CAESAR algorithms pose an elevated risk if employed in real-life protocols due to a class of adaptive-chosen-plaintext attacks. Although authenticated encryption with associated data are often defined (and are best used) as discrete primitives that authenticate and transmit only complete messages, in practice, these algorithms are easily implemented in a fashion that outputs observable ciphertext data when the algorithm has not received all of the (attacker-controlled) plaintext. For an implementor, this strategy appears to offer seemingly harmless and compliant storage and latency advantages. If the algorithm uses the same state for secret keying information, encryption, and integrity protection, and the internal mixing permutation is not cryptographically strong, an attacker can exploit the ciphertext–plaintext feedback loop to reveal secret state information or even keying material. We conclude that the main advantages of exhaustive, automated cryptanalysis are that it acts as a very necessary sanity check for implementations and gives the cryptanalyst insights that can be used to focus more specific attack methods on given candidates.

Undergraduate Student perceptions of a Restorative Dentistry OSCE

Objectives: The Objective Structured Clinical Exam (OSCE) is a widely accepted assessment method in undergraduate dental education. It aims to test higher order skills, attitudes and aspects of professionalism which other summative assessments such as MCQs and other written examinations are less able to do. The aim of this study was to evaluate the perceptions of 4th year undergraduate dental students of an OSCE undertaken in the Conservation Department.
Methods: On completion of the OSCE examination 51 fourth year undergraduate students were asked to complete an anonymised questionnaire. The questionnaire was made 22 questions, and requiring the students to provide both open and closed responses.
Results: A lot of positive aspects to the OSCE were observed in responses, students felt that the OSCE was a meaningful way for assessing their clinical skills (85%), it reflected real life conditions (79%) and that it was a fair method of assessment (75%).
A number of negative aspects were also noted. Most students felt the OSCE was stressful (72%) and they felt nervous during the examination (77%). Of the undergraduates asked 42% did not feel confident doing the OSCE.
A number of students felt it would be helpful to have additional information given to them on the OSCE prior to the assessment process.
Conclusion: In general the students found the OSCE a fair, meaningful form of assessment which reflected real life clinical situations, providing them with an opportunity to show their clinical knowledge and practical skills. A number study cohort did not feel confident during the OSCE and felt nervous and stressed by the experience. The information gained from the reflective nature of the feedback questionnaire has proved invaluable in the design of subsequent diets of the OSCE examination. 

Paving the way for the use of the SDQ in economic evaluations of school-based population health interventions: an empirical analysis of the external validity of SDQ mapping algorithms to the CHU9D in an educational setting

Purpose
The Strengths and Difficulties Questionnaire (SDQ) is a behavioural screening tool for children. The SDQ is increasingly used as the primary outcome measure in population health interventions involving children, but it is not preference based; therefore, its role in allocative economic evaluation is limited. The Child Health Utility 9D (CHU9D) is a generic preference-based health-related quality of-life measure. This study investigates the applicability of the SDQ outcome measure for use in economic evaluations and examines its relationship with the CHU9D by testing previously published mapping algorithms. The aim of the paper is to explore the feasibility of using the SDQ within economic evaluations of school-based population health interventions.
Methods
Data were available from children participating in a cluster randomised controlled trial of the school-based roots of empathy programme in Northern Ireland. Utility was calculated using the original and alternative CHU9D tariffs along with two SDQ mapping algorithms. t tests were performed for pairwise differences in utility values from the preference-based tariffs and mapping algorithms.
Results
Mean (standard deviation) SDQ total difficulties and prosocial scores were 12 (3.2) and 8.3 (2.1). Utility values obtained from the original tariff, alternative tariff, and mapping algorithms using five and three SDQ subscales were 0.84 (0.11), 0.80 (0.13), 0.84 (0.05), and 0.83 (0.04), respectively. Each method for calculating utility produced statistically significantly different values except the original tariff and five SDQ subscale algorithm.
Conclusion
Initial evidence suggests the SDQ and CHU9D are related in some of their measurement properties. The mapping algorithm using five SDQ subscales was found to be optimal in predicting mean child health utility. Future research valuing changes in the SDQ scores would contribute to this research.

Farm animal welfare:Assessing risks attributable to the prenatal environment

An ever-expanding scientific literature highlights the impact of the prenatal environment on many areas of biology. Across all major farmed species, experimental studies have clearly shown that prenatal experiences can have a substantial impact on outcomes relevant to later health, welfare and productivity. In particular, stress or sub-optimal nutrition experienced by the mother during pregnancy has been shown to have wide-ranging and important effects on how her offspring cope with their social, physical and infectious environment. Variation in the conditions for development provided by the reproductive tract or egg, for instance by altered nutritional supply or hormonal exposure, may therefore explain a large degree of variation in many welfare- and productivity-relevant traits. The scientific literature suggests a number of management practices for pre-birth/hatch individuals that could compromise their later welfare. Such studies may have relevance for the welfare of animals under human care, depending on the extent to which real life conditions involve exposure to these practices. Overall, the findings highlight the importance of extending the focus on animal welfare to include the prenatal period, an aspect which until recently has been largely neglected. © 2012 Universities Federation for Animal Welfare The Old School.

Effects of defined mixtures of persistent organic pollutants (POPs) on multiple cellular responses in the human hepatocarcinoma cell line, HepG2, using high content analysis screening

Persistent organic pollutants (POPs) are toxic substances, highly resistant to environmental degradation, which can bio-accumulate and have long-range atmospheric transport potential. Most studies focus on single compound effects, however as humans are exposed to several POPs simultaneously, investigating exposure effects of real life POP mixtures on human health is necessary. A defined mixture of POPs was used, where the compound concentration reflected its contribution to the levels seen in Scandinavian human serum (total mix). Several sub mixtures representing different classes of POP were also constructed. The perfluorinated (PFC) mixture contained six perfluorinated compounds, brominated (Br) mixture contained seven brominated compounds, chlorinated (Cl) mixture contained polychlorinated biphenyls and also p,p'-dichlorodiphenyldichloroethylene, hexachlorobenzene, three chlordanes, three hexachlorocyclohexanes and dieldrin. Human hepatocarcinoma (HepG2) cells were used for 2h and 48h exposures to the seven mixtures and analysis on a CellInsight™ NXT High Content Screening platform. Multiple cytotoxic endpoints were investigated: cell number, nuclear intensity and area, mitochondrial mass and membrane potential (MMP) and reactive oxygen species (ROS). Both the Br and Cl mixtures induced ROS production but did not lead to apoptosis. The PFC mixture induced the ROS production and likely induced cell apoptosis accompanied by the dissipation of MMP. Synergistic effects were evident for ROS induction when cells were exposed to the PFC+Br mixture. No significant effects were detected in the Br+Cl, PFC+Cl or total mixtures, which contain the same concentrations of chlorinated compounds as the Cl mixture plus additional compounds; highlighting the need for further exploration of POP mixtures in risk assessment.

Protocol for a pilot randomised controlled trial of an intervention to increase the use of traffic light food labelling in UK shoppers (the FLICC trial)

Background: Traffic light labelling of foods—a system that incorporates a colour-coded assessment of the level of total fat, saturated fat, sugar and salt on the front of packaged foods—has been recommended by the UK Government and is currently in use or being phased in by many UK manufacturers and retailers. This paper describes a protocol for a pilot randomised controlled trial of an intervention designed to increase the use of traffic light labelling during real-life food purchase decisions.

Methods/design: The objectives of this two-arm randomised controlled pilot trial are to assess recruitment, retention and data completion rates, to generate potential effect size estimates to inform sample size calculations for the main trial and to assess the feasibility of conducting such a trial. Participants will be recruited by email from a loyalty card database of a UK supermarket chain. Eligible participants will be over 18 and regular shoppers who frequently purchase ready meals or pizzas. The intervention is informed by a review of previous interventions encouraging the use of nutrition labelling and the broader behaviour change literature. It is designed to impact on mechanisms affecting belief and behavioural intention formation as well as those associated with planning and goal setting and the adoption and maintenance of the behaviour of interest, namely traffic light label use during purchases of ready meals and pizzas. Data will be collected using electronic sales data via supermarket loyalty cards and web-based questionnaires and will be used to estimate the effect of the intervention on the nutrition profile of purchased ready meals and pizzas and the behavioural mechanisms associated with label use. Data collection will take place over 48 weeks. A process evaluation including semi-structured interviews and web analytics will be conducted to assess feasibility of a full trial.

Discussion: The design of the pilot trial allows for efficient recruitment and data collection. The intervention could be generalised to a wider population if shown to be feasible in the main trial.

Generating Data Augmented Spectroscopic Data For Performance Enhancement

The application of chemometrics in food science has revolutionized the field by allowing the creation of models able to automate a broad range of applications such as food authenticity and food fraud detection. In order to create effective and general models able to address the complexity of real life problems, a vast amount of varied training samples are required. Training dataset has to cover all possible types of sample and instrument variability. However, acquiring a varied amount of samples is a time consuming and costly process, in which collecting samples representative of the real world variation is not always possible, specially in some application fields. To address this problem, a novel framework for the application of data augmentation techniques to spectroscopic data has been designed and implemented. This is a carefully designed pipeline of four complementary and independent blocks which can be finely tuned depending on the desired variance for enhancing model's robustness: a) blending spectra, b) changing baseline, c) shifting along x axis, and d) adding random noise.
This novel data augmentation solution has been tested in order to obtain highly efficient generalised classification model based on spectroscopic data. Fourier transform mid-infrared (FT-IR) spectroscopic data of eleven pure vegetable oils (106 admixtures) for the rapid identification of vegetable oil species in mixtures of oils have been used as a case study to demonstrate the influence of this pioneering approach in chemometrics, obtaining a 10% improvement in classification which is crucial in some applications of food adulteration.