Targeting injury prevention strategies to adolescents of Pacific Islander descent : what will work?

Background: Ethnicity is rarely considered in injury prevention program development, even though this is known to impact on participation in injury risk behaviour. An understanding of injury, risk behaviour and risk and protective factors specific to adolescents of Pacific Islander descent will inform the development of prevention strategies appropriate to this group.----- Aims: To determine patterns of injury and associated risk behaviour among adolescents of Pacific Islander descent, and to understand the risk and protective factors that influence injury rates among this group.----- Methods: A total of 875 Year 9 students from five Queensland high schools completed a survey during health classes. Seventy-one students (n = 38 male) identified as Pacific Islander. The survey consisted of scales examining injury, risk taking behaviour, and relationships with family, school and police.----- Results: The leading causes of injury among adolescents of Pacific Islander descent were sports (48%) and transport (e.g. 45% reported bicycle injuries). Interpersonal violence related injuries were also relatively frequent, with 28% having been injured in a fight. Reports of alcohol use were relatively low (20% c.f. 40% of the remaining sample), however reports of other risk behaviours were relatively high (e.g. 43% c.f. 25% of remaining sample reported a group fight).----- Discussion and conclusions: Conclusions will be drawn regarding risk-related injuries reported by adolescents of Pacific Islander descent and those of other ethnic backgrounds. Additionally, risk and protective factors relating to family, school and police will be explored, in order to inform prevention strategies appropriate to this group.

Load on osseointegrated fixation of a transfemoral amputee during a fall : loading, descent, impact and recovery analysis

Falling represents a health risk for lower limb amputees fitted with an osseointegrated fixation mainly because of the potential damage to the fixation. The purpose of this study was to characterise a real forward fall that occurred inadvertently to a transfemoral amputee fitted with an osseointegrated fixation while attending a gait measurement session to assess the load applied on the residuum. The objective was to analyse the load applied on the fixation with an emphasis on the sequence of events, the pattern and the magnitude of the forces and moments. The load was measured directly at 200 Hz using a six-channel transducer. Complementary video footage was also studied. The fall was divided into four phases: loading (240 ms), descent (620 ms), impact (365 ms) and recovery (2495 ms). The main impact forces and moments occurred 870 ms and 915 ms after the heel contact, and corresponded to 133 %BW and 17 %BWm, or 1.2 and 11.2 times the maximum forces and moments applied during the previous steps of the participant, respectively. This study provided key information to engineers and clinicians facing the challenge to design equipment, and rehabilitation and exercise programs to restore safely the locomotion of lower limb amputees.

Adaptive online gradient descent

We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori knowledge of the lower bound on the second derivatives of the observed functions. We then provide an algorithm, Adaptive Online Gradient Descent, which interpolates between the results of Zinkevich for linear functions and of Hazan et al for strongly convex functions, achieving intermediate rates between [square root T] and [log T]. Furthermore, we show strong optimality of the algorithm. Finally, we provide an extension of our results to general norms.

Extracting deck trend to plan descent trajectory for safe landing of UAVs

This paper outlines a feasible scheme to extract deck trend when a rotary-wing unmanned aerial vehicle (RUAV)approaches an oscillating deck. An extended Kalman filter (EKF) is de- veloped to fuse measurements from multiple sensors for effective estimation of the unknown deck heave motion. Also, a recursive Prony Analysis (PA) procedure is proposed to implement online curve-fitting of the estimated heave mo- tion. The proposed PA constructs an appropriate model with parameters identified using the forgetting factor recursive least square (FFRLS)method. The deck trend is then extracted by separating dominant modes. Performance of the proposed procedure is evaluated using real ship motion data, and simulation results justify the suitability of the proposed method into safe landing of RUAVs operating in a maritime environment.

Transport injury risks in Queensland adolescents of Pacific Islander descent

Ethnicity is rarely considered in the development of injury prevention programs, despite its known impact on participation in risk behaviour. This study sought to understand engagement in transport related risk behaviours, patterns of injury and perceptions of risk among early adolescents who self-identify as being from a Pacific Islander background. In total 5 high schools throughout Queensland, Australia were recruited, of which 498 Year 9 students (13-14 years) completed questionnaires relating to their perceptions of risk and recent injury experience (specifically those transport behaviours that were medically treated and those that were not medically treated). The transport related risk behaviours captured in the survey were bicycle use, motorcycle use and passenger safety (riding with a drink driver and riding with a dangerous driver). The results are explored in terms of the prevalence of engagement in risky transport related behaviour among adolescents’ of Pacific Islander background compared to others of the same age. The results of this study provide an initial insight into the target participants’ perspective of risk in a road safety context as well as their experience of such behaviour and related injuries. This information may benefit future intervention programs specific to adolescents’ of Pacific Islander background.

Prediction of multilocus identity-by-descent

Previous studies have enabled exact prediction of probabilities of identity-by-descent (IBD) in randommating populations for a few loci (up to four or so), with extension to more using approximate regression methods. Here we present a precise predictor of multiple-locus IBD using simple formulas based on exact results for two loci. In particular, the probability of non-IBD X ABC at each of ordered loci A, B, and C can be well approximated by XABC = XABXBC/XB and generalizes to X123. . .k = X12X23. . .Xk-1,k/ Xk-2, where X is the probability of non-IBD at each locus. Predictions from this chain rule are very precise with population bottlenecks and migration, but are rather poorer in the presence of mutation. From these coefficients, the probabilities of multilocus IBD and non-IBD can also be computed for genomic regions as functions of population size, time, and map distances. An approximate but simple recurrence formula is also developed, which generally is less accurate than the chain rule but is more robust with mutation. Used together with the chain rule it leads to explicit equations for non-IBD in a region. The results can be applied to detection of quantitative trait loci (QTL) by computing the probability of IBD at candidate loci in terms of identity-by-state at neighboring markers.

Adaptive online gradient descent

We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori knowledge of the lower bound on the second derivatives of the observed functions. We then provide an algorithm, Adaptive Online Gradient Descent, which interpolates between the results of Zinkevich for linear functions and of Hazan et al for strongly convex functions, achieving intermediate rates between [square root T] and [log T]. Furthermore, we show strong optimality of the algorithm. Finally, we provide an extension of our results to general norms.

Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis

Genome-wide association studies (GWAS) have identified around 60 common variants associated with multiple sclerosis (MS), but these loci only explain a fraction of the heritability of MS. Some missing heritability may be caused by rare variants that have been suggested to play an important role in the aetiology of complex diseases such as MS. However current genetic and statistical methods for detecting rare variants are expensive and time consuming. 'Population-based linkage analysis' (PBLA) or so called identity-by-descent (IBD) mapping is a novel way to detect rare variants in extant GWAS datasets. We employed BEAGLE fastIBD to search for rare MS variants utilising IBD mapping in a large GWAS dataset of 3,543 cases and 5,898 controls. We identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9×10-6). Network analysis of cases and controls sharing haplotypes on chromosome 19 further strengthened the association as there are more large networks of cases sharing haplotypes than controls. This linkage region includes a cluster of zinc finger genes of unknown function. Analysis of genome wide transcriptome data suggests that genes in this zinc finger cluster may be involved in very early developmental regulation of the CNS. Our study also indicates that BEAGLE fastIBD allowed identification of rare variants in large unrelated population with moderate computational intensity. Even with the development of whole-genome sequencing, IBD mapping still may be a promising way to narrow down the region of interest for sequencing priority. © 2013 Lin et al.

Profligate Descent : The Cultural Transformations of Evolutionary Narrative

This dissertation traces a set of historical transformations the Darwinian evolutionary narrative has undergone toward the end of the twentieth century, especially as reflected in Anglo-American popular science books and novels. The study has three objectives. First, it seeks to understand the organizing logic of evolutionary narratives and the role that assumptions about gender and sexuality play in that logic. Second, it asks what kinds of cultural anxieties evolutionary theory raises and how evolutionary narratives negotiate them. Third, it examines the possibilities and limits of narrative transformation both as a historical phenomenon and as a theoretical question. This interdisciplinary dissertation is situated at the intersection of science studies, cultural studies, literary studies, and gender studies. Its understanding of science as a cultural practice that both emerges from and contributes to cultural expectations and institutional structures follows the tradition of science studies. Its focus on the question of popular appeal and the mechanisms of cultural change arises from cultural studies. Its view of narrative as a structural phenomenon is grounded in literary studies in general and feminist narrative theory in particular. Its understanding of gender and sexuality as implicated in discourses of epistemic authority builds on the view of gender and sexuality as contingent cultural categories central to gender studies. The primary material consists of over 25 British and American popular science books and novels, published roughly between 1990 and 2005. In order to highlight historical transformations, these texts are read in the context of Darwin s The Origin of Species and The Descent of Man, on the one hand, and such sociobiological classics as E. O. Wilson s On Human Nature and Richard Dawkins s The Selfish Gene, on the other. The research method combines feminist narrative analysis with cultural and historical contextualization, emphasizing discursive abruptions, recurrent narrative patterns, and underlying continuities. The dissertation demonstrates that the relationship between Darwin s evolutionary narrative and late twentieth-century evolutionary narratives is characterized by reemphasis, omissions, and continuous rewriting. In particular, contemporary evolutionary discourse extends the role assigned to reproduction both sexual and narrative in Darwin s writing, generating a narrative logic that imagines the desire to reproduce as the driving force of evolution and posits the reproductive sex act as the endlessly repeated narrative event that keeps the story going. The study argues that the popular appeal of evolutionary accounts of gender, sexuality, and human nature may arise, to an extent, from this reproductive narrative dynamic. This narrative dynamic, however, is not logically invulnerable. Since the continuation of the evolutionary narrative relies on successful reproduction, the possibility of reproductive failure poses a constant risk to narrative futurity, arousing cultural anxieties that evolutionary narratives need to address. The study argues that evolutionary narratives appease such anxieties by evoking a range of cultural narratives, especially romantic, religious, and national narratives. Furthermore, the study shows that the event-based logic of evolutionary narratives privileges observable acts over emotions, pleasures, identities, and desires, thus engendering a set of conceptual exclusions that limits the imaginative scope of evolution as a cultural narrative.

Differentially private stochastic gradient descent algorithm for multiparty classification

We consider the problem of developing privacy-preserving machine learning algorithms in a dis-tributed multiparty setting. Here different parties own different parts of a data set, and the goal is to learn a classifier from the entire data set with-out any party revealing any information about the individual data points it owns. Pathak et al [7]recently proposed a solution to this problem in which each party learns a local classifier from its own data, and a third party then aggregates these classifiers in a privacy-preserving manner using a cryptographic scheme. The generaliza-tion performance of their algorithm is sensitive to the number of parties and the relative frac-tions of data owned by the different parties. In this paper, we describe a new differentially pri-vate algorithm for the multiparty setting that uses a stochastic gradient descent based procedure to directly optimize the overall multiparty ob-jective rather than combining classifiers learned from optimizing local objectives. The algorithm achieves a slightly weaker form of differential privacy than that of [7], but provides improved generalization guarantees that do not depend on the number of parties or the relative sizes of the individual data sets. Experimental results corrob-orate our theoretical findings.

Fuel-optimal G-MPSP Guidance for Powered Descent Phase of Soft Lunar Landing

A fuel optimal nonlinear sub-optimal guidance scheme is presented in this paper for soft landing of a lunar craft during the powered descent phase. The recently developed Generalized Model Predictive Static Programming (G-MPSP) is used to compute the required magnitude and angle of the thrust vector. Both terminal position and velocity vector are imposed as hard constraints, which ensures high position accuracy and facilitates initiation of vertical descent at the end of the powered descent phase. A key feature of the G-MPSP algorithm is that it converts the nonlinear dynamic programming problem into a low-dimensional static optimization problem (of the same dimension as the output vector). The control history update is done in closed form after computing a time-varying weighting matrix through a backward integration process. This feature makes the algorithm computationally efficient, which makes it suitable for on-board applications. The effectiveness of the proposed guidance algorithm is demonstrated through promising simulation results.