School-based programs for increasing connectedness and reducing risk behavior : a systematic review

School connectedness has a significant impact on adolescent outcomes, including reducing risk taking behavior. This paper critically examines the literature on school-based programs targeting increased connectedness for reductions in risk taking. Fourteen articles describing seven different school-based programs were reviewed. Programs drew on a range of theories to increase school connectedness, and evaluations conducted for the majority of programs demonstrated positive changes in school connectedness, risk behavior, or a combination of the two. Many of the reviewed programs involved widespread school system change, however, which is frequently a complex and time consuming task. Future research is needed to examine the extent of intervention complexity required to result in change. This review also showed a lack of consistency in definitions and measurement of connectedness as well as few mediation analyses testing assumptions of impact on risk taking behavior through increases in school connectedness. Additionally, this review revealed very limited evaluation of the elements of multi-component programs that are most effective in increasing school connectedness and reducing adolescent risk taking.

Uptake of skin self-examination and clinical examination behavior by outdoor workers

This study investigated the association between outdoor work and response to a behavioural skin cancer early detection intervention among men 50 years or older. Overall, 495 men currently working in outdoor, mixed or indoor occupations were randomised to a video-based intervention or control group. At 7 months post intervention, indoor workers reported the lowest proportion of whole-body skin self-examination (wbSSE; 20%). However, at 13 months mixed workers engaged more commonly in wbSSE (36%) compared to indoor (31%) and outdoor (32%) workers. In adjusted analysis, the uptake of early detection behaviours during the trial did not differ between men working in different settings. Outdoor workers compared to men in indoor or mixed work settings were similar in their response to an intervention encouraging uptake of secondary skin cancer prevention behaviours during this intervention trial.

Fine-mapping identifies multiple prostate cancer risk loci on 5p15 some associating with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease.

Speaker attribution of multiple telephone conversations using a complete-linkage clustering approach

In this paper we propose and evaluate a speaker attribution system using a complete-linkage clustering method. Speaker attribution refers to the annotation of a collection of spoken audio based on speaker identities. This can be achieved using diarization and speaker linking. The main challenge associated with attribution is achieving computational efficiency when dealing with large audio archives. Traditional agglomerative clustering methods with model merging and retraining are not feasible for this purpose. This has motivated the use of linkage clustering methods without retraining. We first propose a diarization system using complete-linkage clustering and show that it outperforms traditional agglomerative and single-linkage clustering based diarization systems with a relative improvement of 40% and 68%, respectively. We then propose a complete-linkage speaker linking system to achieve attribution and demonstrate a 26% relative improvement in attribution error rate (AER) over the single-linkage speaker linking approach.

A Comprehensive Benchmarking Framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM

Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

Characterizing multi-agent team behavior from partial team tracings : evidence from the English Premier League

Real-world AI systems have been recently deployed which can automatically analyze the plan and tactics of tennis players. As the game-state is updated regularly at short intervals (i.e. point-level), a library of successful and unsuccessful plans of a player can be learnt over time. Given the relative strengths and weaknesses of a player’s plans, a set of proven plans or tactics from the library that characterize a player can be identified. For low-scoring, continuous team sports like soccer, such analysis for multi-agent teams does not exist as the game is not segmented into “discretized” plays (i.e. plans), making it difficult to obtain a library that characterizes a team’s behavior. Additionally, as player tracking data is costly and difficult to obtain, we only have partial team tracings in the form of ball actions which makes this problem even more difficult. In this paper, we propose a method to overcome these issues by representing team behavior via play-segments, which are spatio-temporal descriptions of ball movement over fixed windows of time. Using these representations we can characterize team behavior from entropy maps, which give a measure of predictability of team behaviors across the field. We show the efficacy and applicability of our method on the 2010-2011 English Premier League soccer data.

The effects of linguistic factors on student performance on economics multiple choice questions

This paper proposes a framework to analyse performance on multiple choice questions with the focus on linguistic factors. Item Response Theory (IRT) is deployed to estimate ability and question difficulty levels. A logistic regression model is used to detect Differential Item Functioning questions. Probit models testify relationships between performance and linguistic factors controlling the effects of question construction and students’ background. Empirical results have important implications. The lexical density of stems affects performance. The use of non-Economics specialised vocabulary has differing impacts on the performance of students with different language backgrounds. The IRT-based ability and difficulty help explain performance variations.

Efficient solution of multiple cracks in great number using eigen COD boundary integral equations with iteration procedure

A newly developed computational approach is proposed in the paper for the analysis of multiple crack problems based on the eigen crack opening displacement (COD) boundary integral equations. The eigen COD particularly refers to a crack in an infinite domain under fictitious traction acting on the crack surface. With the concept of eigen COD, the multiple cracks in great number can be solved by using the conventional displacement discontinuity boundary integral equations in an iterative fashion with a small size of system matrix to determine all the unknown CODs step by step. To deal with the interactions among cracks for multiple crack problems, all cracks in the problem are divided into two groups, namely the adjacent group and the far-field group, according to the distance to the current crack in consideration. The adjacent group contains cracks with relatively small distances but strong effects to the current crack, while the others, the cracks of far-field group are composed of those with relatively large distances. Correspondingly, the eigen COD of the current crack is computed in two parts. The first part is computed by using the fictitious tractions of adjacent cracks via the local Eshelby matrix derived from the traction boundary integral equations in discretized form, while the second part is computed by using those of far-field cracks so that the high computational efficiency can be achieved in the proposed approach. The numerical results of the proposed approach are compared not only with those using the dual boundary integral equations (D-BIE) and the BIE with numerical Green's functions (NGF) but also with those of the analytical solutions in literature. The effectiveness and the efficiency of the proposed approach is verified. Numerical examples are provided for the stress intensity factors of cracks, up to several thousands in number, in both the finite and infinite plates.

Interpersonal coupling in rowing : the mediating role of the environment

Evidence currently supports the view that intentional interpersonal coordination (IIC) is a self-organizing phenomenon facilitated by visual perception of co-actors in a coordinative coupling (Schmidt, Richardson, Arsenault, & Galantucci, 2007). The present study examines how apparent IIC is achieved in situations where visual information is limited for co-actors in a rowing boat. In paired rowing boats only one of the actors, [bow seat] gets to see the actions of the other [stroke seat]. Thus IIC appears to be facilitated despite the lack of important visual information for the control of the dyad. Adopting a mimetic approach to expert coordination, the present study qualitatively examined the experiences of expert performers (N=9) and coaches (N=4) with respect to how IIC was achieved in paired rowing boats. Themes were explored using inductive content analysis, which led to layered model of control. Rowers and coaches reported the use of multiple perceptual sources in order to achieve IIC. As expected(Kelso, 1995; Schmidt & O’Brien, 1997; Turvey, 1990), rowers in the bow of a pair boat make use of visual information provided by the partner in front of them [stroke]. However, this perceptual information is subordinate to perception Motor Learning and Control S111 of the relationship between the boat hull and water passing beside it. Stroke seat, in the absence of visual information about his/her partner, achieves coordination by picking up information about the lifting or looming of the boat’s stern along with water passage past the hull. In this case it appears that apparent or desired IIC is supported by the perception of extra-personal variables, in this case boat behavior; as this perceptual information source is used by both actors. To conclude, co-actors in two person rowing boats use multiple sources of perceptual information for apparent IIC that changes according to task constraints. Where visual information is restricted IIC is facilitated via extra-personal perceptual information and apparent IIC switches to intentional extra-personal coordination.

Mapping of multiple quantitative trait loci affecting bovine spongiform encephalopathy

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y ps) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches.

On the prediction of simultaneous inbreeding coefficients at multiple loci

A new deterministic method for predicting simultaneous inbreeding coefficients at three and four loci is presented. The method involves calculating the conditional probability of IBD (identical by descent) at one locus given IBD at other loci, and multiplying this probability by the prior probability of the latter loci being simultaneously IBD. The conditional probability is obtained applying a novel regression model, and the prior probability from the theory of digenic measures of Weir and Cockerham. The model was validated for a finite monoecious population mating at random, with a constant effective population size, and with or without selfing, and also for an infinite population with a constant intermediate proportion of selfing. We assumed discrete generations. Deterministic predictions were very accurate when compared with simulation results, and robust to alternative forms of implementation. These simultaneous inbreeding coefficients were more sensitive to changes in effective population size than in marker spacing. Extensions to predict simultaneous inbreeding coefficients at more than four loci are now possible.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. This paper first presents a brief review of the most inherent uncertainties of the SHM-oriented WSN platforms and then investigates their effects on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when employing merged data from multiple tests. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and Data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Experimental accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as clean data before being contaminated by different data pollutants in sequential manner to simulate practical SHM-oriented WSN uncertainties. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with SHM-WSN uncertainties. Finally, the use of the measurement channel projection for the time-domain OMA techniques and the preferred combination of the OMA techniques to cope with the SHM-WSN uncertainties is recommended.

Early adolescents’ helping behaviours when a friend is injured in a fight : the role of an extended Theory of Planned Behavior

This paper examines the role of first aid training in increasing adolescent helping behaviours when taught in a school-based injury prevention program, Skills for Preventing Injury in Youth (SPIY). The research involved the development and application of an extended Theory of Planned Behaviour (TPB), including “behavioural willingness in a fight situation,” “first aid knowledge” and “perceptions of injury seriousness”, to predict the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. From 35 Queensland high schools, 2500 Year 9 students (mean age = 13.5, 40% male) completed surveys measuring their attitudes, perceived behavioural control, subjective norms and behavioural intention, from the TPB, and added measures of behavioural willingness in a fight situation, perceptions of injury seriousness and first aid knowledge, to predict helping behaviours when a friend is injured in a fight. It is expected that the TPB will significantly contribute to understanding the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. Further analyses will determine whether the extension of the model significantly increases the variance explained in helping behaviours. The findings of this research will provide insight into the critical factors that may increase adolescent bystanders’ actions in injury situations.

Ureaplasma parvum multiple banded antigen (MBA) size variation - association with fetal inflammation in a sheep model (Published abstract)

Background: Ureaplasma species are the most prevalent isolates from women who deliver preterm. The MBA, a surface exposed lipoprotein, is a key virulence factor of ureaplasmas. We investigated MBA variation after chronic and acute intra-amniotic (IA) ureaplasma infections. Method: U. parvum serovar 3 (2x104 colony-forming-units) was injected IA into pregnant ewes at: 55 days gestation (d, term = 145d) (n=8); 117d (n=8) and 121d (n=8). Fetuses were delivered surgically (124d) and ureaplasmas cultured from amniotic fluid (AF), chorioamnion, fetal lung (FL) and umbilical cord were tested by western blot and PCR assays to demonstrate MBA and mba gene variation respectively. Tissue sections were sectioned and stained by haemotoxylin and eosin and inflammatory cell counts and pathology were reported (blinded to outcome). Results: Numerous MBA/mba variants were generated in vivo after chronic exposure to ureaplasma infection but after acute infection no variants (3d) or very few variants (7d) were generated. Identical MBA variants were detected within the AF and FL but different ureaplasma variants were detected within chorioamnion specimens. The severity of inflammation within chronically infected tissues varied between animals ranging from no inflammation to severe inflammation with/without fibrosis. Chorioamnion, FL and cord from the same animal demonstrated the same degree of inflammation. Conclusions: MBA/mba variation in vivo occurred after the initiation of the host immune response and we propose that ureaplasmas vary the MBA antigen to evade the host immune response. In some animals there was no inflammation despite colonisation with high numbers of ureaplasmas.