Masculinity, sexuality, theology and child sexual abuse by personnel in Christian institutions

There growing recognition that a contributor to the repeat crises of child sexual abuse (CSA) by personnel in Christian institutions (PICIs), is the often gendered culture of Christian institutions themselves. This work explores theological discursive constructions of masculinity and sexuality and their implications for addressing CSA by PICIs. The perspectives discussed here are of PICIs who participated in a research project conducted in Australia. From these perspectives male gendered and sexual performance is constructed through discourse as both an explanation and solution to offending behaviour. Similarly, sexuality is viewed as God-given, heteronormative and legitimately expressed only within the bounds of marriage. This work draws on Foucault and feminist discourses as they relate to CSA by PICIs and institutional discourses. This work offers a perspective of PICIs that may not otherwise be heard in the common discourses of CSA in Christian Institutions.

MIMO enhanced slotted cooperation in urban vehicular networks

The requirement of isolated relays is one of the prime obstacles in utilizing sequential slotted cooperative protocols for Vehicular Ad-hoc Networks (VANET). Significant research advancement has taken place to improve the diversity multiplexing trade-off (DMT) of cooperative protocols in conventional mobile networks without much attention on vehicular ad-hoc networks. We have extended the concept of sequential slotted amplify and forward (SAF) protocols in the context of urban vehicular ad-hoc networks. Multiple Input Multiple Output (MIMO) reception is used at relaying vehicular nodes to isolate the relays effectively. The proposed approach adds a pragmatic value to the sequential slotted cooperative protocols while achieving attractive performance gains in urban VANETs. We have analysed the DMT bounds and the outage probabilities of the proposed scheme. The results suggest that the proposed scheme can achieve an optimal DMT similar to the DMT upper bound of the sequential SAF. Furthermore, the outage performance of the proposed scheme outperforms the SAF protocol by 2.5 dB at a target outage probability of 10-4.

Combining initial segments of lists

We propose a new way to build a combined list from K base lists, each containing N items. A combined list consists of top segments of various sizes from each base list so that the total size of all top segments equals N. A sequence of item requests is processed and the goal is to minimize the total number of misses. That is, we seek to build a combined list that contains all the frequently requested items. We first consider the special case of disjoint base lists. There, we design an efficient algorithm that computes the best combined list for a given sequence of requests. In addition, we develop a randomized online algorithm whose expected number of misses is close to that of the best combined list chosen in hindsight. We prove lower bounds that show that the expected number of misses of our randomized algorithm is close to the optimum. In the presence of duplicate items, we show that computing the best combined list is NP-hard. We show that our algorithms still apply to a linearized notion of loss in this case. We expect that this new way of aggregating lists will find many ranking applications.

Second-order quantile methods for experts and combinatorial games

We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.

Bikeshare's impact on active travel: Evidence from the United States, Great Britain, and Australia

Over 800 cities globally now offer bikeshare programs. One of their purported benefits is increased physical activity. Implicit in this claim is that bikeshare replaces sedentary modes of transport, particularly car use. This paper estimates the median changes in physical activity levels as a result of bikeshare in the cities of Melbourne, Brisbane, Washington, D.C., London, and Minneapolis/St. Paul. This study is the first known multi-city evaluation of the active travel impacts of bikeshare programs. To perform the analysis, data on mode substitution (i.e. the modes that bikeshare replaces) were used to determine the extent of shift from sedentary to active transport modes (e.g. when a car trip is replaced by bikeshare). Potentially offsetting these gains, reductions in physical activity when walking trips are replaced by bikeshare was also estimated. Finally a Markov Chain Monte Carlo analysis was conducted to estimate confidence bounds on estimated impacts on active travel given uncertainties in data sources. The results indicate that on average 60% of bikeshare trips replace sedentary modes of transport (from 42% in Minneapolis/St. Paul to 67% in Brisbane). When bikeshare replaces a walking trip, there is a reduction in active travel time because walking a given distance takes longer than cycling. Considering the active travel balance sheet for the cities included in this analysis, bikeshare activity in 2012 has an overall positive impact on active travel time. This impact ranges from an additional 1.4 million minutes of active travel for the Minneapolis/St. Paul bikeshare program, to just over 74 million minutes of active travel for the London program The analytical approach adopted to estimate bikeshare’s impact on active travel may act as the basis for future bikeshare evaluations or feasibility studies.

Response of segmented bored transit tunnels to surface blast

Increasing threat of terrorism highlights the importance of enhancing the resilience of underground tunnels to all hazards. This paper develops, applies and compares the Arbitrary Lagrangian Eulerian (ALE) and Smooth Particle Hydrodynamics (SPH) techniques to treat the response of buried tunnels to surface explosions. The results and outcomes of the two techniques were compared, along with results from existing test data. The comparison shows that the ALE technique is a better method for describing the tunnel response for above ground explosion with regards to modeling accuracy and computational efficiency. The ALE technique was then applied to treat the blast response of different types of segmented bored tunnels buried in dry sand. Results indicate that the most used modern ring type segmented tunnels were more flexible for in-plane response, however, they suffered permanent drifts between the rings. Hexagonal segmented tunnels responded with negligible drifts in the longitudinal direction, but the magnitudes of in-plane drifts were large and hence hazardous for the tunnel. Interlocking segmented tunnels suffered from permanent drifts in both the longitudinal and transverse directions. Multi-surface radial joints in both the hexagonal and interlocking segments affected the flexibility of the tunnel in the transverse direction. The findings offer significant new information in the behavior of segmented bored tunnels to guide their future implementation in civil engineering applications.

Socially critical pedagogy and the 'production of skilled performers': Further considerations of teaching and learning in physical education

The growing call for physical educators to move beyond the bounds of performance has been a powerful discourse. However, it is a discourse that has tended to be heavy on theory but light on practical application. This paper discusses recent work in the area of skill acquisition and what this might mean for pedagogical practices in physical education. The acquisition of motor skill has traditionally been a core objective for physical educators, and there has been a perception that child-centred pedagogies have failed in the achievement of this traditional yardstick. However, drawing from the work of Rovegno and Kirk (1995) and Langley (1995; 1997), and making links with current work in the motor learning area, it is possible to show that skill acquisition is not necessarily compromised by child-centred pedagogy. Indeed, working beyond Mosston's discovery threshold and using models such as Games for Understanding, can provide deeper skill-learning experiences as well as being socially just.

Statistically assisted fluid registration algorithm - SAFIRA

In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in [2] and re-formulated using Lagrangian mechanics in [3]. Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the non-statistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the regularizing (i.e., the non-conservative Lagrangian) terms, creating four versions of the algorithm. We evaluated the accuracy of each algorithm variant using the manually labeled LPBA40 dataset, which provides us with ground truth anatomical segmentations. We also compared the power of the different algorithms using tensor-based morphometry -a technique to analyze local volumetric differences in brain structure- applied to 46 3D brain scans from healthy monozygotic twins.

Influence of pipe length and flow rate on nano-particle deposition in laminar circular pipe flows

The Lagrangian particle tracking provides an effective method for simulating the deposition of nano- particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. The aim of this paper is to study the deposition of nano-particles in cylindrical tubes under laminar condition using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different pipe lengths and flow rates are examined. The results show good agreement between the calculated deposition efficiency and different analytic correlations in the literature. Furthermore, for the nano-particles with higher diameters and when the effect of inertia has a higher importance, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.

The fossil calibration database - A new resource for divergence dating

Fossils provide the principal basis for temporal calibrations, which are critical to the accuracy of divergence dating analyses. Translating fossil data into minimum and maximum bounds for calibrations is the most important, and often least appreciated, step of divergence dating. Properly justified calibrations require the synthesis of phylogenetic, paleontological, and geological evidence and can be difficult for non-specialists to formulate. The dynamic nature of the fossil record (e.g., new discoveries, taxonomic revisions, updates of global or local stratigraphy) requires that calibration data be updated continually lest they become obsolete. Here, we announce the Fossil Calibration Database (http://fossilcalibrations.org), a new open-access resource providing vetted fossil calibrations to the scientific community. Calibrations accessioned into this database are based on individual fossil specimens and follow best practices for phylogenetic justification and geochronological constraint. The associated Fossil Calibration Series, a calibration-themed publication series at Palaeontologia Electronica, will serve as one key pipeline for peer-reviewed calibrations to enter the database.

Four mammal fossil calibrations: Balancing competing palaeontological and molecular considerations

With the introduction of relaxed-clock molecular dating methods, the role of fossil calibration has expanded from providing a timescale, to also informing the models for molecular rate variation across the phylogeny. Here I suggest fossil calibration bounds for four mammal clades, Monotremata (platypus and echidnas), Macropodoidea (kangaroos and potoroos), Caviomorpha-Phiomorpha (South American and African hystricognath rodents), and Chiroptera (bats). In each case I consider sources of uncertainty in the fossil record and provide a molecular dating analysis to examine how the suggested calibration priors are further informed by other mammal fossil calibrations and molecular data.

Numerical investigation of aerosol particle transport and deposition in realistic lung airway

Different human activities like combustion of fossil fuels, biomass burning, industrial and agricultural activities, emit a large amount of particulates into the atmosphere. As a consequence, the air we inhale contains significant amount of suspended particles, including organic and inorganic solids and liquids, as well as various microorganism, which are solely responsible for a number of pulmonary diseases. Developing a numerical model for transport and deposition of foreign particles in realistic lung geometry is very challenging due to the complex geometrical structure of the human lung. In this study, we have numerically investigated the airborne particle transport and its deposition in human lung surface. In order to obtain the appropriate results of particle transport and deposition in human lung, we have generated realistic lung geometry from the CT scan obtained from a local hospital. For a more accurate approach, we have also created a mucus layer inside the geometry, adjacent to the lung surface and added all apposite mucus layer properties to the wall surface. The Lagrangian particle tracking technique is employed by using ANSYS FLUENT solver to simulate the steady-state inspiratory flow. Various injection techniques have been introduced to release the foreign particles through the inlet of the geometry. In order to investigate the effects of particle size on deposition, numerical calculations are carried out for different sizes of particles ranging from 1 micron to 10 micron. The numerical results show that particle deposition pattern is completely dependent on its initial position and in case of realistic geometry; most of the particles are deposited on the rough wall surface of the lung geometry instead of carinal region.

Commercial friendships between gay sales associates and straight female customers in luxury settings: A proposed theoretical framework

This study investigates friendships between gay sales associates and heterosexual female customers in luxury retail settings. By employing grounded theory methodology, the study integrates theories and findings from diverse literature streams into an original conceptual framework to illustrate the resources gay sales associates and straight female customers receive from and provide to each other during retail exchanges. The study explains why gay male–straight female friendships are uniquely suited for luxury consumption settings. Female customers characterize their friendships with gay sales associates as providing honesty, security, trust, and comfort, which stems from the absence of sexual interest and a lack of inter-female competition. Gay sales associates receive acceptance for who they are and for their displays of unconventional masculinity in retail settings. They also obtain a temporary rite from their female customers, a so-called mandate of privacy, which permits both parties to ignore the bounds of modesty and accept a degree of intimacy. Such intimacy facilitates transactions that require both personalization and customer–employee closeness, such as the selling of high-end apparel, accessories, and jewelry.

Development and validation of a multilevel model for predicting workload under routine and nonroutine conditions in an air traffic management center

Objective: The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Background: Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. Method: A multilevel workload model was developed in Study 1 with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters. The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Results: Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. Conclusion: The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Application: Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs. Tactical uses include the dynamic reallocation of resources to meet changes in demand.

Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.