Reflexive and automatic violence: A function of aberrant perceptual inhibition

It’s commonly assumed that psychiatric violence is motivated by delusions, but here the concept of a reversed impetus is explored, to understand whether delusions are formed as ad-hoc or post-hoc rationalizations of behaviour or in advance of the actus reus. The reflexive violence model proposes that perceptual stimuli has motivational power and this may trigger unwanted actions and hallucinations. The model is based on the theory of ecological perception, where opportunities enabled by an object are cues to act. As an apple triggers a desire to eat, a gun triggers a desire to shoot. These affordances (as they are called) are part of the perceptual apparatus, they allow the direct recognition of objects – and in emergencies they enable the fastest possible reactions. Even under normal circumstances, the presence of a weapon will trigger inhibited violent impulses. The presence of a victim will also, but under normal circumstances, these affordances don’t become violent because negative action impulses are totally inhibited, whereas in psychotic illness, negative action impulses are treated as emergencies and bypass frontal inhibitory circuits. What would have been object recognition becomes a blind automatic action. A range of mental illnesses can cause inhibition to be bypassed. At its most innocuous, this causes both simple hallucinations (where the motivational power of an object is misattributed). But ecological perception may have the power to trigger serious violence also –a kind that’s devoid of motives or planning and is often shrouded in amnesia or post-rational delusions.

An early feeding practices intervention for obesity prevention

Objective - Report long term outcomes of the NOURISH randomized controlled trial (RCT) that evaluated a universal intervention commencing in infancy to provide anticipatory guidance to first-time mothers on ‘protective’ complementary feeding practices which were hypothesized to reduce childhood obesity risk. Subjects and Methods - The NOURISH RCT enrolled 698 mothers (mean age 30.1 years, SD=5.3) with healthy term infants (51% female). Mothers were randomly allocated to usual care or to attend two 6-session, 12-week group education modules. Outcomes were assessed five times: baseline (infants 4.3 months); 6 months after module 1 (infants 14 months); 6 months after module 2 (infants 2 years) and at 3.5 and 5 years of age. Maternal feeding practices were self-reported using validated questionnaires. BMI Z-score was calculated from measured child height and weight. Linear Mixed Models evaluated intervention (group) effect across time. Results - Retention at 5 years of age was 61%. Across ages 2-5 years, intervention mothers reported less frequent use of non-responsive feeding practices on 6/9 scales. At 5 years they also reported more appropriate responses to food refusal on 7/12 items (Ps ≤.05). No statistically significant group effect was noted for anthropometric outcomes (BMI Z-score: P=.06), or the prevalence of overweight/obesity (control 13.3% vs. intervention 11.4%, P=.66). Conclusions - Anticipatory guidance on complementary feeding resulted in first-time mothers reporting increased use of protective feeding practices. These intervention effects were sustained up to five years of age and were paralleled by a non-significant trend for lower child BMI Z-scores at all post-intervention assessment points.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

Automatic image scaling for place recognition in changing environments

Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.

Extending the validity of the Feeding Practices and Structure Questionnaire

Background Feeding practices are commonly examined as potentially modifiable determinants of children’s eating behaviours and weight status. Although a variety of questionnaires exist to assess different feeding aspects, many lack thorough reliability and validity testing. The Feeding Practices and Structure Questionnaire (FPSQ) is a tool designed to measure early feeding practices related to non-responsive feeding and structure of the meal environment. Face validity, factorial validity, internal reliability and cross-sectional correlations with children’s eating behaviours have been established in mothers with 2-year-old children. The aim of the present study was to further extend the validity of the FPSQ by examining factorial, construct and predictive validity, and stability. Methods Participants were from the NOURISH randomised controlled trial which evaluated an intervention with first-time mothers designed to promote protective feeding practices. Maternal feeding practices (FP) and child eating behaviours were assessed when children were aged 2 years and 3.7 years (n=388). Confirmatory Factor analysis, group differences, predictive relationships, and stability were tested. Results The original 9-factor structure was confirmed when children were aged 3.7±0.3 years. Cronbach’s alpha was above the recommended 0.70 cut-off for all factors except Structured Meal Timing, Over Restriction and Distrust in Appetite which were 0.58, 0.67 and 0.66 respectively. Allocated group differences reflected behaviour consistent with intervention content and all feeding practices were stable across both time points (range of r= 0.45-0.70). There was some evidence for the predictive validity of factors with 2 FP showing expected relationships, 2 FP showing expected and unexpected relationships and 5 FP showing no relationship. Conclusions Reliability and validity was demonstrated for most subscales of the FPSQ. Future validation is warranted with culturally diverse samples and with fathers and other caregivers. The use of additional outcomes to further explore predictive validity is recommended as well as testing construct validity and test-retest reliability of the questionnaire.

Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging

Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

Automatic population HARDI white matter tract clustering by label fusion of multiple tract atlases

Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.

Automatic clustering and population analysis of white matter tracts using maximum density paths

We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.

Evaluation of protein bait laced with various insecticides on the Queensland fruit fly (Diptera: Tephritidae): Attraction, feeding, mortality and bait persistence

The use of malathion in fruit fly protein bait sprays has raised serious concerns due to its adverse effects on non-target organisms. This has necessitated the evaluation of novel reduced-risk compounds. This study evaluated the effects of spinosad, fipronil, malathion and chlorpyrifos mixed with fruit fly protein bait (Mauri Pinnacle protein®) on attraction, feeding and mortality of the Queensland fruit fly, Bactrocera tryoni (Froggatt). The effects of outdoor weathering of these mixtures on fly mortality were also determined. In field-cage experiment, protein-starved flies showed the same level of attraction to baits containing spinosad, fipronil, malathion, chlorpyrifos and protein alone used as control. Female protein-starved flies were deterred from feeding on baits containing malathion and chlorpyrifos compared to baits containing spinosad, fipronil and protein alone. Baits containing malathion and chlorpyrifos caused higher fly mortality and rapid fly knock down than spinosad and fipronil. However, spinosad acted slowly and caused an increase in fly mortality over time, causing up to 90% fly mortality after 72-h. Baits containing malathion and chlorpyrifos, applied on citrus leaves and weathered outdoors, had longer residual effectiveness in killing flies than spinosad and fipronil. Residual effectiveness of the spinosad bait mixture waned significantly after 3 days of outdoor weathering. Results suggest that spinosad and fipronil can be potential alternatives for malathion in protein bait sprays.

Dietary intake of children aged 12-16 months and associations with maternal feeding beliefs and practices

This thesis provides the first detailed data describing the dietary intake of first-born Australian children aged 12-16 months. Overall, quality of intake could improve, with toddlers being exposed to energy-dense, nutrient-poor foods which may adversely affect the development of long-term healthy food preferences and growth trajectory. The leaner, but healthy weight toddler who exhibited more frequent food refusal was described a fussy eater or prompted higher maternal concern. However these behaviours are consistent with typical child development during the second year of life. Mothers can be supported to understand food refusal as manifestation of children's ability to self-regulate energy intake.

Automatic surveillance in transportation hubs: No Longer just about catching the bad guy

As critical infrastructure such as transportation hubs continue to grow in complexity, greater importance is placed on monitoring these facilities to ensure their secure and efficient operation. In order to achieve these goals, technology continues to evolve in response to the needs of various infrastructure. To date, however, the focus of technology for surveillance has been primarily concerned with security, and little attention has been placed on assisting operations and monitoring performance in real-time. Consequently, solutions have emerged to provide real-time measurements of queues and crowding in spaces, but have been installed as system add-ons (rather than making better use of existing infrastructure), resulting in expensive infrastructure outlay for the owner/operator, and an overload of surveillance systems which in itself creates further complexity. Given many critical infrastructure already have camera networks installed, it is much more desirable to better utilise these networks to address operational monitoring as well as security needs. Recently, a growing number of approaches have been proposed to monitor operational aspects such as pedestrian throughput, crowd size and dwell times. In this paper, we explore how these techniques relate to and complement the more commonly seen security analytics, and demonstrate the value that can be added by operational analytics by demonstrating their performance on airport surveillance data. We explore how multiple analytics and systems can be combined to better leverage the large amount of data that is available, and we discuss the applicability and resulting benefits of the proposed framework for the ongoing operation of airports and airport networks.

A 4D automatic simulation tool for construction resource planning: A case study

Purpose Traditional construction planning relies upon the critical path method (CPM) and bar charts. Both of these methods suffer from visualization and timing issues that could be addressed by 4D technology specifically geared to meet the needs of the construction industry. This paper proposed a new construction planning approach based on simulation by using a game engine. Design/methodology/approach A 4D automatic simulation tool was developed and a case study was carried out. The proposed tool was used to simulate and optimize the plans for the installation of a temporary platform for piling in a civil construction project in Hong Kong. The tool simulated the result of the construction process with three variables: 1) equipment, 2) site layout and 3) schedule. Through this, the construction team was able to repeatedly simulate a range of options. Findings The results indicate that the proposed approach can provide a user-friendly 4D simulation platform for the construction industry. The simulation can also identify the solution being sought by the construction team. The paper also identifies directions for further development of the 4D technology as an aid in construction planning and decision-making. Research limitations/implications The tests on the tool are limited to a single case study and further research is needed to test the use of game engines for construction planning in different construction projects to verify its effectiveness. Future research could also explore the use of alternative game engines and compare their performance and results. Originality/value The authors proposed the use of game engine to simulate the construction process based on resources, working space and construction schedule. The developed tool can be used by end-users without simulation experience.

Identifying vertebral end plate lesions (schmorl's nodes) using a semi-automatic method

INTRODUCTION There is a large range in the reported prevalence of end plate lesions (EPLs), sometimes referred to as Schmorl's nodes in the general population (3.8-76%). One possible reason for this large range is the differences in definitions used by authors. Previous research has suggested that EPLs may potentially be a primary disturbance of growth plates that leads to the onset of scoliosis. The aim of this study was to develop a technique to measure the size, prevalence and location of EPLs on Computed Tomography (CT) images of scoliosis patients in a consistent manner. METHODS A detection algorithm was developed and applied to measure EPLs for five adolescent females with idiopathic scoliosis (average age 15.1 years, average major Cobb 60°). In this algorithm, the EPL definition was based on the lesion depth, the distance from the edge of the vertebral body and the gradient of the lesion edge. Existing low-dose, CT scans of the patients' spines were segmented semi-automatically to extract 3D vertebral endplate morphology. Manual sectioning of any attachments between posterior elements of adjacent vertebrae and, if necessary, endplates was carried out before the automatic algorithm was used to determine the presence and position of EPLs. RESULTS EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 73% of the EPLs were seen in the lumbar spines (11/15). A sensitivity study demonstrated that the algorithm was most sensitive to changes in the minimum gradient required at the lesion edge. CONCLUSION An imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs on CT images has been developed. Although the technique was tested on scoliosis patients, it can be used to analyse other populations without observer errors in EPL definitions.

Current management of transitional feeding issues in preterm neonates born in Queensland, Australia

Background: Many preterm neonates display difficulty establishing suck-feeding competence in the weeks following birth. Ineffective management of transitional feeding issues may cause patient complications, and can contribute to increased length of stay. Aims: Given that many neonatal nurseries appear to vary in their neonatal feeding management practices, the aim of this study was to investigate and document the routine level of support and intervention currently provided for preterm neonates with transitional feeding issues across the various level II (special care) nurseries (SCNs) in Queensland, Australia. Methods: A questionnaire was mailed to all Queensland SCNs in 2005 (n = 36). The questionnaire contained a series of closed-choice and short-answer questions designed to obtain information from each SCN regarding their current practices for managing transitional feeding issues in preterm neonates. Results were confirmed during a follow-up phone call. Results: Responses were obtained from 29 SCNs (80.6%). None of these nurseries reported having any formal, written policies regarding the management of transitional feeding issues in preterm neonates. Wide variations were reported in relation to the suck-feeding assessments and interventions used by staff within the various SCNs. Of the 29 nurseries, 4 (13.8%) reported using checklists or assessments to judge readiness for suck-feeds, and 5 (17.2%) reported using pulse oximetry to judge tolerance of suck-feeding attempts. Eighteen SCNs (62.1%) reported offering some form of active intervention to assist neonates with transitional feeding issues, with the most common intervention techniques reported being non-nutritive sucking during tube feeds, pre-feeding oral stimulation, and actively pacing suck-feeds. Twenty-two SCNs (75.4%) reported having access to a lactation consultant to assist mothers with breastfeeding issues. Conclusions: Differences were reported in the routine management of transitional feeding issues in preterm neonates across the various SCNs in Queensland. It is suggested that evidence based guidelines need to be developed, and that, in order to do this, further research studies are required to determine current best practice, as well as to answer remaining questions. © 2008 Elsevier Ireland Ltd. All rights reserved.