High frequency of BRAF mutations in nevi

To evaluate the timing of mutations in BRAF (v-raf murine sarcoma viral oncogene homolog B1) during melanocytic neoplasia, we carried out mutation analysis on microdissected melanoma and nevi samples. We observed mutations resulting in the V599E amino-acid substitution in 41 of 60 (68%) melanoma metastases, 4 of 5 (80%) primary melanomas and, unexpectedly, in 63 of 77 (82%) nevi. These data suggest that mutational activation of the RAS/RAF/MAPK pathway in nevi is a critical step in the initiation of melanocytic neoplasia but alone is insufficient for melanoma tumorigenesis.

Factors associated with recall of media reports about vitamin D and sun protection

Objective: To assess the recall of media reports about vitamin D and associated factors. Methods: Analysis of cross-sectional telephone interview data (2,001 Queensland adults, 18-70 years) on vitamin D and personal sun protection, recall of media reports and participant characteristics. Results: 83.7% of participants had heard of vitamin D, 47.5% through the media. Only 513 (25.6%) participants recalled the media content within four main themes: vitamin D is beneficial/comes from the sun (47.0%); some people aren’t getting enough vitamin D, need more sun (27.9%); need to balance sun exposure and skin protection (11.5%); or other (13.6%). Only 65 of the 950 participants (6.8%) reported a change to their behaviour(s) due to the media report. Conclusion: Although the media were the main source of information about vitamin D for almost 50% of participants, recall of the content and direct effect on behaviour was low. Only a small minority recalled a balanced media report of beneficial and harmful aspects of sun exposure. Implications Health professionals often supply media with background information. To achieve best public health practice for sun protection and vitamin D, information to foster balanced media reports should be provided.

Bioimpedance in the assessment of unilateral lymphedema of a limb: the optimal frequency

Background: Bioimpedance techniques provide a reliable method of assessing unilateral lymphedema in a clinical setting. Bioimpedance devices are traditionally used to assess body composition at a current frequency of 50 kHz. However, these devices are not transferable to the assessment of lymphedema, as the sensitivity of measuring the impedance of extracellular fluid is frequency dependent. It has previously been shown that the best frequency to detect extracellular fluid is 0 kHz (or DC). However, measurement at this frequency is not possible in practice due to the high skin impedance at DC, and an estimate is usually determined from low frequency measurements. This study investigated the efficacy of various low frequency ranges for the detection of lymphedema. Methods and Results: Limb impedance was measured at 256 frequencies between 3 kHz and 1000 kHz for a sample control population, arm lymphedema population, and leg lymphedema population. Limb impedance was measured using the ImpediMed SFB7 and ImpediMed L-Dex® U400 with equipotential electrode placement on the wrists and ankles. The contralateral limb impedance ratio for arms and legs was used to calculate a lymphedema index (L-Dex) at each measurement frequency. The standard deviation of the limb impedance ratio in a healthy control population has been shown to increase with frequency for both the arm and leg. Box and whisker plots of the spread of the control and lymphedema populations show that there exists good differentiation between the arm and leg L-Dex measured for lymphedema subjects and the arm and leg L-Dex measured for control subjects up to a frequency of about 30 kHz. Conclusions: It can be concluded that impedance measurements above a frequency of 30 kHz decrease sensitivity to extracellular fluid and are not reliable for early detection of lymphedema.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Adaptive and optimal under frequency load shedding

Power systems in many countries are stressed towards their stability limit. If these stable systems experience any unexpected serious contingencies, or disturbances, there is a significant risk of instability, which may lead to wide-spread blackout. Frequency is a reliable indicator for such instability condition exists on the power system; therefore under-frequency load shedding technique is used to stable the power system by curtail some load. In this paper, the SFR-UFLS model redeveloped to generate optimal load shedding method is that optimally shed load following one single particular contingency event. The proposed optimal load shedding scheme is then tested on the 39-bus New England test system to show the performance against random load shedding scheme.

Effects of corrugation frequency and aspect ratio on natural convection within an enclosure having sinusoidal corrugation over a heated top surface

Natural convection of a two-dimensional laminar steady-state incompressible fluid flow in a modified rectangular enclosure with sinusoidal corrugated top surface has been investigated numerically. The present study has been carried out for different corrugation frequencies on the top surface as well as aspect ratios of the enclosure in order to observe the change in hydrodynamic and thermal behavior with constant corrugation amplitude. A constant flux heat source is flush mounted on the top sinusoidal wall, modeling a wavy sheet shaded room exposed to sunlight. The flat bottom surface is considered as adiabatic, while the both vertical side walls are maintained at the constant ambient temperature. The fluid considered inside the enclosure is air having Prandtl number of 0.71. The numerical scheme is based on the finite element method adapted to triangular non-uniform mesh element by a non-linear parametric solution algorithm. The results in terms of isotherms, streamlines and average Nusselt numbers are obtained for the Rayleigh number ranging from 10^3 to 10^6 with constant physical properties for the fluid medium considered. It is found that the convective phenomena are greatly influenced by the presence of the corrugation and variation of aspect ratios.

Improving recall in appearance-based visual SLAM using visual expectation

In this paper, we present a new algorithm for boosting visual template recall performance through a process of visual expectation. Visual expectation dynamically modifies the recognition thresholds of learnt visual templates based on recently matched templates, improving the recall of sequences of familiar places while keeping precision high, without any feedback from a mapping backend. We demonstrate the performance benefits of visual expectation using two 17 kilometer datasets gathered in an outdoor environment at two times separated by three weeks. The visual expectation algorithm provides up to a 100% improvement in recall. We also combine the visual expectation algorithm with the RatSLAM SLAM system and show how the algorithm enables successful mapping

Reflecting on the ‘Dream Circle’ : urban Indigenous education processes designed for student and community empowerment

The ‘Dream Circle’ is a space designed by and operated through Indigenous educator footprints as a safe space for the school’s deadly jarjums (Indigenous children). The ‘Dream Circle’ uses a kinnected methodology drawing on the rich vein of Murri cultural knowledges and Torres Strait Islander supports within the local community to provide a safe and supportive circle. The ‘Dream Circle’ operates on a school site in the Logan area as an after school homework and cultural studies class. The ‘Dream Circle’ embodies practices and ritualises processes which ensure cultural safety and integrity. In this way the ‘Dream Circle’ balances the measures that Sarra (2005) purports are the stronger, smarter realities needed for positive change in Indigenous education.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Three carrier ambiguity resolution : distance-independent performance demonstrated using semi-generated triple frequency GPS signals

In spite of significant research in the development of efficient algorithms for three carrier ambiguity resolution, full performance potential of the additional frequency signals cannot be demonstrated effectively without actual triple frequency data. In addition, all the proposed algorithms showed their difficulties in reliable resolution of the medium-lane and narrow-lane ambiguities in different long-range scenarios. In this contribution, we will investigate the effects of various distance-dependent biases, identifying the tropospheric delay to be the key limitation for long-range three carrier ambiguity resolution. In order to achieve reliable ambiguity resolution in regional networks with the inter-station distances of hundreds of kilometers, a new geometry-free and ionosphere-free model is proposed to fix the integer ambiguities of the medium-lane or narrow-lane observables over just several minutes without distance constraint. Finally, the semi-simulation method is introduced to generate the third frequency signals from dual-frequency GPS data and experimentally demonstrate the research findings of this paper.

The'dream'of multi-agency crime prevention : pitfalls in policy and practice

During the 1980s, terms such as interagency or multi-agency cooperation, collaboration, coordination, and interaction have became permanent features of both crime prevention rhetoric and government crime policy. The concept of having the government, local authorities, and the community working in partnership has characterized both left and right politics for over a decade. The U.S. National Advisory Commission on Criminal Justice Standards and Goals in the U.S.. Circulars 8/84 and 44/90 released by the U.K. Home Office, and the British Morgan Report-coupled with the launch of government strategies in France, the Netherlands, England and Wales, Australia, and, more recently, in Belgium, New Zealand, and Canada-have all emphasized the importance of agencies working together to prevent or reduce crime. This paper draws upon recent Australian research and critically analyzes multi-agency crime prevention. It suggests that agency conflicts and power struggles may be exacerbated by neo-liberal economic theory, by the politics of crime prevention management, and by policies that aim to combine situational and social prevention endeavors. Furthermore, it concludes that indigenous peoples are excluded by crime prevention strategies that fail to define and interpret crime and its prevention in culturally appropriate ways.

Documentary as history, memory, dream and film

A century ago, as the Western world embarked on a period of traumatic change, the visual realism of photography and documentary film brought print and radio news to life. The vision that these new mediums threw into stark relief was one of intense social and political upheaval: the birth of modernity fired and tempered in the crucible of the Great War. As millions died in this fiery chamber and the influenza pandemic that followed, lines of empires staggered to their fall, and new geo-political boundaries were scored in the raw, red flesh of Europe. The decade of 1910 to 1919 also heralded a prolific period of artistic experimentation. It marked the beginning of the social and artistic age of modernity and, with it, the nascent beginnings of a new art form: film. We still live in the shadow of this violent, traumatic and fertile age; haunted by the ghosts of Flanders and Gallipoli and its ripples of innovation and creativity. Something happened here, but to understand how and why is not easy; for the documentary images we carry with us in our collective cultural memory have become what Baudrillard refers to as simulacra. Detached from their referents, they have become referents themselves, to underscore other, grand narratives in television and Hollywood films. The personal histories of the individuals they represent so graphically–and their hope, love and loss–are folded into a national story that serves, like war memorials and national holidays, to buttress social myths and values. And, as filmic images cross-pollinate, with each iteration offering a new catharsis, events that must have been terrifying or wondrous are abstracted. In this paper we first discuss this transformation through reference to theories of documentary and memory–this will form a conceptual framework for a subsequent discussion of the short film Anmer. Produced by the first author in 2010, Anmer is a visual essay on documentary, simulacra and the symbolic narratives of history. Its form, structure and aesthetic speak of the confluence of documentary, history, memory and dream. Located in the first decade of the twentieth century, its non-linear narratives of personal tragedy and poetic dreamscapes are an evocative reminder of the distance between intimate experience, grand narratives, and the mythologies of popular films. This transformation of documentary sources not only played out in the processes of the film’s production, but also came to form its theme.

Validation of a food behavior questionnaire for male blue collar workers

During nutrition intervention programs, some form of dietary assessment is usually necessary. This dietary assessment can be for: initial screening; development of appropriate programs and activities; or, evaluation. Established methods of dietary assessment are not always practical, nor cost effective in such interventions, therefore an abbreviated dietary assessment tool is needed. The Queensland Nutrition Project developed such a tool for male Blue Collar Workers, the Food Behaviour Questionnaire, consisting of 27 food behaviour related questions. This tool has been validated in a sample of 23 men, through full dietary assessment obtained via food frequency questionnaires and 24 hour dietary recalls. Those questions which correlated poorly with the full dietary assessment were deleted from the tool. In all, 13 questions was all that was required to distinguish between high and low dietary intakes of particular nutrients. Three questions when combined had correlations with refined sugar between 0.617 and 0.730 (p<0.005); four questions when combined had correlations with dietary fibre as percentage of energy of 0.45 (p<0.05); five questions when combined had a correlation with total fat of 0.499 (p<0.05); and, 4 questions when combined had a correlation with saturated fat of between 0.451 and 0.589 (p<0.05). A significant correlation could not be found for food behaviour questions with respect to dietary sodium. Correlations for fat as a function of energy could not be found.