Foot morphological difference between habitually shod and unshod runners

Foot morphology and function has received increasing attention from both biomechanics researchers and footwear manufacturers. In this study, 168 habitually unshod runners (90 males whose age, weight & height were 23 +/- 2.4years, 66 +/- 7.1kg & 1.68 +/- 0.13m and 78 females whose age, weight & height were 22 +/- 1.8years, 55 +/- 4.7kg & 1.6 +/- 0.11m) (Indians) and 196 shod runners (130 males whose age, weight & height were 24 +/- 2.6years, 66 +/- 8.2kg & 1.72 +/- 0.18m and 66 females whose age, weight & height were 23 +/- 1.5years, 54 +/- 5.6kg & 1.62 +/- 0.15m)(Chinese) participated in a foot scanning test using the easy-foot-scan (a three-dimensional foot scanning system) to obtain 3D foot surface data and 2D footprint imaging. Foot length, foot width, hallux angle and minimal distance from hallux to second toe were calculated to analyze foot morphological differences. This study found that significant differences exist between groups (shod Chinese and unshod Indians) for foot length (female p = 0.001), width (female p = 0.001), hallux angle (male and female p = 0.001) and the minimal distance (male and female p = 0.001) from hallux to second toe. This study suggests that significant differences in morphology between different ethnicities could be considered for future investigation of locomotion biomechanics characteristics between ethnicities and inform last shape and design so as to reduce injury risks and poor performance from mal-fit shoes.

Weight bearing physical activity for performance and bone health in prepubertal girls

This study assessed the status of bone and cardiovascular health in young, prepubertal females (aged 9 to 11 years) during a school based intervention program involving weight bearing physical activity. A study of 10 months duration was conducted in four primary schools in the Melbourne suburbs. It involved a physical activity group (n=38) and an aged-matched control group (n=33). Baseline data including pubertal status, health-related fitness, bone mass and body composition were obtained pre and post the intervention programme. All children had their bone mineral density monitored. Bone mineral density and body composition measurements were performed by DXA using the Hologic QDR 2000 bone densitometer. At the completion of the program the activity group had accrued significantly greater bone mass at total body, lumbar spine, leg and femoral neck when expressed as BMC or BMD.

Australian feature films and distribution: Industry or cottage industry?

Feature films remain critical flagships to any national film industry. Australian feature films can be highly commercial endeavours that also perform symbolic functions by embodying the national imaginary in big screen based sound and imagery. They conduct a dialogue with domestic audiences as well as showcase key aspects of Australia in the global film festival circuit. As the pre-eminent filmmaking form, feature films also serve as important launchpads for the careers of many Australian writers, directors, actors and technical crew. In the wake of over a decade of diminished share of local box office obtained by Australian feature films, Australian Feature Films and Distribution: Industry or cottage industry, examines issues in the production sector affecting the performance of Australian feature films and some responses by the central funding and support screen agency, Screen Australia.

Generating product feature hierarchy from product reviews

User generated information such as product reviews have been booming due to the advent of web 2.0. In particular, rich information associated with reviewed products has been buried in such big data. In order to facilitate identifying useful information from product (e.g., cameras) reviews, opinion mining has been proposed and widely used in recent years. In detail, as the most critical step of opinion mining, feature extraction aims to extract significant product features from review texts. However, most existing approaches only find individual features rather than identifying the hierarchical relationships between the product features. In this paper, we propose an approach which finds both features and feature relationships, structured as a feature hierarchy which is referred to as feature taxonomy in the remainder of the paper. Specifically, by making use of frequent patterns and association rules, we construct the feature taxonomy to profile the product at multiple levels instead of single level, which provides more detailed information about the product. The experiment which has been conducted based upon some real world review datasets shows that our proposed method is capable of identifying product features and relations effectively.

HR-MAS NMR spectroscopy shows regional metabolite variation in bovine articular cartilage

Mechanical stress is an important external factor effecting the development and maintenance of articular cartilage. The metabolite profile of diseased cartilage has been well studied but there is limited information about the variation in metabolite profile of healthy cartilage. With the importance of load in maintaining healthy cartilage, regional differences in metabolite profile associated with differences in load may provide information on how load contributes to the maintenance of healthy cartilage. HR-MAS NMR spectroscopy allows the assessment of tissue samples without modification and was used for assessing the difference in metabolic profile between the load bearing and non-load bearing regions of the bovine articular cartilage. In this preliminary study, we examined cartilage from tibia and femur of four knee joints. Sixteen pairs of 1D-NOESY spectra were acquired. Principle component analysis (PCA) identified chemical shifts responsible for variance. SBASE (AMIX) and the Human Metabolome Database were used in conjunction with previous reported cartilage data for identifying metabolites associated with the PCA results. The major contributors to load-related differences in metabolite profile were N-acetyl groups, lactate and phosphocholine peaks. Integrals of these regions were further analysed using a Student's t-test. In load bearing cartilage regions. N-acetyl groups and phosphocholine were found at significantly higher concentration (p < 0.05 and p < 0.005, respectively) in both femur and tibia, while lactate was reduced in load bearing cartilage (p < 0.005). The results of this pilot HR-MAS NMR study demonstrate its ability to provide useful metabolite information for healthy cartilage.

Feature - No pain, no gain: Pleasure and suffering in technologies of leidenschaft

Training for bodybuilding competition is clearly a serious business that inflicts serious demands on the competitor. Not only did Francis commit time and money to compete, but he also arguably put winning before his physical well-being—enduring pain and suffering from his injury. Bodybuilding may seem like an extreme example, but it is not the only activity in which people suffer in pursuit of their goals. Boxers fight each other in the ring; soccer players risk knee and ankle injuries, sometimes playing despite being hurt; and mountaineers risk their lives in dangerous climbs. In the arts there are many examples of people suffering to achieve their goals: Beethoven kept composing, conducting, and performing despite his hearing loss; van Gogh grappled with depression but kept painting, finding fame only posthumously; and Mozart lived the final years of his life impoverished but still composing. These examples show that many great achievements come at a price: severe suffering...

vSpeak: Edge detection based feature extraction for sign to text conversion

This paper presents 'vSpeak', the first initiative taken in Pakistan for ICT enabled conversion of dynamic Sign Urdu gestures into natural language sentences. To realize this, vSpeak has adopted a novel approach for feature extraction using edge detection and image compression which gives input to the Artificial Neural Network that recognizes the gesture. This technique caters for the blurred images as well. The training and testing is currently being performed on a dataset of 200 patterns of 20 words from Sign Urdu with target accuracy of 90% and above.

Distinct subpopulations of gamma delta T cells are present in normal and tumor-bearing human liver

Gamma delta T cells are thought to mediate immune responses at epithelial surfaces. We have quantified and characterized hepatic and peripheral blood gamma delta T cells from 11 normal and 13 unresolved tumor-bearing human liver specimens. gamma delta T cells are enriched in normal liver (6.6% of T cells) relative to matched blood (0.9%; P = 0.008). The majority express CD4(-)CD8(-) phenotypes and many express CD56 and/or CD161. In vitro, hepatic gamma delta T cells can be induced to kill tumor cell lines and release interferon-gamma, tumor necrosis factor-alpha, interleukin-2 and interleukin-4. Analysis of V gamma and V delta chain usage indicated that V delta 3(+) cells are expanded in normal livers (21.2% of gamma delta T cells) compared to blood (0.5%; P = 0.001). Tumor-bearing livers had significant expansions and depletions of gamma delta T cell subsets but normal cytolytic activity. This study identifies novel populations of liver T cells that may play a role in immunity against tumors.

NKT cells from normal and tumor-bearing human livers are phenotypically and functionally distinct from murine NKT cells

A major group of murine NK T (NKT) cells express an invariant Vα14Jα18 TCR α-chain specific for glycolipid Ags presented by CD1d. Murine Vα14Jα18+ account for 30–50% of hepatic T cells and have potent antitumor activities. We have enumerated and characterized their human counterparts, Vα24Vβ11+ NKT cells, freshly isolated from histologically normal and tumor-bearing livers. In contrast to mice, human NKT cells are found in small numbers in healthy liver (0.5% of CD3+ cells) and blood (0.02%). In contrast to those in blood, most hepatic Vα24+ NKT cells express the Vβ11 chain. They include CD4+, CD8+, and CD4−CD8− cells, and many express the NK cell markers CD56, CD161, and/or CD69. Importantly, human hepatic Vα24+ T cells are potent producers of IFN-γ and TNF-α, but not IL-2 or IL-4, when stimulated pharmacologically or with the NKT cell ligand, α-galactosylceramide. Vα24+Vβ11+ cell numbers are reduced in tumor-bearing compared with healthy liver (0.1 vs 0.5%; p < 0.04). However, hepatic cells from cancer patients and healthy donors release similar amounts of IFN-γ in response to α-galactosylceramide. These data indicate that hepatic NKT cell repertoires are phenotypically and functionally distinct in humans and mice. Depletions of hepatic NKT cell subpopulations may underlie the susceptibility to metastatic liver disease.

CD1 expression and CD1-restricted T cell activity in normal and tumour-bearing human liver

CD1d-restricted natural killer T (NKT) cells expressing invariant Valpha14Jalpha18 T cell receptor alpha-chains are abundant in murine liver and are implicated in the control of malignancy, infection and autoimmunity. Invariant NKT cells have potent anti-metastatic effects in mice and phase I clinical trials involving their homologues in humans are ongoing. However, invariant NKT cells are less abundant in human liver ( approximately 0.5% of hepatic T cells) than in murine liver (up to 50%) and it is not known if other hepatic T cells are CD1-restricted. We have examined expression of CD1a, CD1b, CD1c and CD1d mRNA and protein in human liver and evaluated the reactivity of mononuclear cells (MNC) from histologically normal and tumour-bearing human liver specimens against these CD1 isoforms. Messenger RNA for all CD1 isotypes was detectable in all liver samples. CD1c and CD1d were expressed at the protein level by hepatic MNC. CD1d, only, was detectable at the cell surface, but CD1c and CD1d were found at an intracellular location in significant numbers of liver MNC. CD1b was not expressed by MNC from healthy livers but was detectable within MNC in all tumour samples tested. Hepatic T cells exhibited reactivity against C1R cells expressing transfected CD1c and CD1d, but neither CD1a nor CD1b. These cells secreted interferon-gamma (IFN-gamma) but not interleukin-4 (IL-4) upon stimulation. In contrast, similar numbers of peripheral T cells released 13- and 16-fold less IFN-gamma in response to CD1c and CD1d, respectively. CD1c and CD1d expression and T cell reactivity were not altered in tumour-bearing liver specimens compared to histologically normal livers. These data suggest that, in addition to invariant CD1d-restricted NKT cells, autoreactive T cells that recognise CD1c and CD1d and release inflammatory cytokines are abundant in human liver.

Automated feature engineering for HTTP tunnel detection

Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

Efficient content-based image retrieval based on multi-feature fusion

The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.