Do East Asians Achieve Greater Knee Flexion than Caucasian North Americans, and are East Asian Kneeling and Squatting Styles Kinetically Different from North American Norms?

High flexion postures (specifically, kneeling and squatting) are used with greater regularity in East Asian (Chinese, Japanese, Korean, and Vietnamese) cultures for many activities of daily living (ADL). Furthermore, the favored style of kneeling and squatting is different between ethnicities: Caucasians typically flex their forefoot while kneeling and squatting, whereas East Asians tend to keep the top or bottom of the foot flat to the ground. Most, but not all, research suggests that East Asians are able to achieve a greater knee flexion angle during high flexion postures, but it is unknown if any differences between ethnicity extends to kinetic outcomes. A direct comparison between ethnicities with respect to kinetics has not been made. Where a difference in maximal attainable flexion angle exists, it is unclear whether the cause is cultural or innate. Therefore, this thesis project aimed to answer three related questions: 1) Do East Asian populations achieve a greater flexion angle than North American Caucasians; 2) If there is in fact a difference, is it a result of cultural upbringing or innate ability?; and, 3) Do different styles of kneeling and squatting alter the moments of force at the knee? To accomplish these aims, 43 participants were recruited from the University of Waterloo and fit into one of three groups: Caucasian, born and raised in North America (20 participants); East Asian, born and raised in North America (18 participants); or, East Asian, born in East Asia, living in North America for less than two years (five participants) (however, the East Asian born in East Asia group was excluded from statistical processing since the group size was considerably smaller). Kinetic, kinematic, neuromuscular, and passive range of motion data were collected and compared between different ethnicity groups. East Asians did not achieve a greater mean knee flexion angle during kneeling compared to Caucasians (Canadian born East Asians=152.01° (±4.85°); Caucasians=153.07° (±7.46°), p=0.2859), but a greater mean flexion angle was found during squatting (Canadian born East Asians =147.96° (±6.62°); Caucasians = 141.69° (±17.48°), p=0.0014). Between Caucasians and Canadian born East Asians, there was also no difference in peak knee flexion angle during passive range of motion testing (Canadian born East Asians = 152.05° (±8.16°); Caucasians = 149.54° (±7.75°)), which indicates that there is no difference in ability to achieve greater high flexion between groups. Finally, it was found that different styles of squatting altered the kinetics at the knee, but different styles of kneeling were not significantly different. Flat foot squatting, a posture more commonly seen in East Asian cultures, had significantly (p<0.05) lower flexion and adduction moments at the knee than heels raised squatting (which is more commonly used by Caucasian North Americans) during descent, ascent, and static squatting. The mean static flexion moment (which is similar in magnitude to the peak flexion moment during descent and ascent) for flat foot squatting was 4.37 (±1.47) %BW*Ht, and for heels raised squatting was 5.99 (±1.84) %BW*Ht. The mean static frontal plane moment for flat foot squatting was -0.45 (±1.33) and for heels raised squatting was 0.59 (±1.02). (Negative values indicate an external abduction moment and positive values indicate an external adduction moment.) When performing high flexion postures, reduced knee moments are desirable since higher moments are associated with greater joint loading and injury risk

The digital brain switch: managing rapid transitions between role identities in a digital world

In this paper, we present initial findings from an EPSRC-sponsored multi-disciplinary research project investigating how digital technologies and social media affect role transitions across work-life domains. The research uses an innovative combination of visual diaries and narrative interviews to capture micro-transitions (‘switches’) and explore these with participants in the context of their overall lives. Findings from a pilot study with academics are reported here in terms of: emergent digital boundary management strategies; triggers for rapid switching and the effects of this; and the function of meta roles and multi-role cognitions. The research contributes to current thinking in work-life literature in terms of devising innovative methods, focusing on the micro- transitional and in considering the role of the digital and social media in boundary management

Scaling relations of X-ray Luminous Clusters in the Hyper Suprime-Cam Subaru Strategic Program Field

We present the XMM-Newton X-ray analysis of 19 X-ray luminous galaxy clusters of low-to-mid redshift ($< 0.4$) selected from the MCXC cluster catalogue in the Hyper Supri%survey as the first work in our series paper. We derive the hydrostatic equilibrium mass and study scaling relations using i) the whole sample, ii) only relaxed clusters and iii) only disturbed clusters. When considering the whole sample, the $Y_{\rm X}$-$M_{\rm tot}$ and $M_{\rm gas}$-$M_{\rm tot}$ relations agree with self-similarity. In terms of morphology, relaxed clusters show a flatter relation in $L_{\rm X,ce}$-$M_{\rm tot}$, $L_{\rm X,bol}$-$M_{\rm tot}$, $L_{\rm X,ce}$-$T$, $L_{\rm bol,ce}$-$T$, $M_{\rm gas}$-$M_{\rm tot}$ and $Y_{\rm X}$-$M_{\rm tot}$. The $L_{\rm bol,ce}$-$M_{\rm tot}$, $L_{\rm X,ce}$-$M_{\rm tot}$ $L_{\rm bol,ce}$-$T$ and $L_{\rm X,ce}$-$T$ relations show a slope $\sim$3$\sigma$ steeper. The residuals in the $M_{\rm gas}$-$M_{\rm tot}$ and $T$-$M_{\rm tot}$ relations and the intrinsic covariance between $M_{\rm gas}$ and $T$ show hints of positive correlation, casting doubt on whether the $Y_{\rm X}$ parameter is a truly low scatter mass proxy. The $M_{\rm gas}$-$M_{\rm tot}$ and $T$-$M_{\rm tot}$ plots color-coded with the offset of the $L_{\rm X,ce}$-$M_{\rm tot}$ relation show these two relations to be brightness dependent but not the $L_{\rm X,ce}$-$T$ relation, suggesting relations involving $M_{\rm tot}$ are biased due to sample selection based on luminosity. Following the work which studied an optical sample and combining our result with literature studies, we find the $M_{\rm tot}$ derived not using mass proxies deviate from $L_{\rm X}$ $\propto$ $M_{\rm gas}^{2}M_{\rm tot}^{-1}$ and $M_{\rm tot}$ based on hydrostatic equilibrium are more massive than what is expected by their relation using caustic masses. This indicates mass bias plays an important role in scaling relations.Comment: Accepted for publication in MNRAS, 16 pages, 19 figure

Similarity measures for mid-surface quality evaluation

Mid-surface models are widely used in engineering analysis to simplify the analysis of thin-walled parts, but it can be difficult to ensure that the mid-surface model is representative of the solid part from which it was generated. This paper proposes two similarity measures that can be used to evaluate the quality of a mid-surface model by comparing it to a solid model of the same part. Two similarity measures are proposed; firstly a geometric similarity evaluation technique based on the Hausdorff distance and secondly a topological similarity evaluation method which uses geometry graph attributes as the basis for comparison. Both measures are able to provide local and global similarity evaluation for the models. The proposed methods have been implemented in a software demonstrator and tested on a selection of representative models. They have been found to be effective for identifying geometric and topological errors in mid-surface models and are applicable to a wide range of practical thin-walled designs

Learning Support and Trivial Prototypes for Interpretable Image Classification

Prototypical part network (ProtoPNet) methods have been designed to achieve interpretable classification by associating predictions with a set of training prototypes, which we refer to as trivial prototypes because they are trained to lie far from the classification boundary in the feature space. Note that it is possible to make an analogy between ProtoPNet and support vector machine (SVM) given that the classification from both methods relies on computing similarity with a set of training points (i.e., trivial prototypes in ProtoPNet, and support vectors in SVM). However, while trivial prototypes are located far from the classification boundary, support vectors are located close to this boundary, and we argue that this discrepancy with the well-established SVM theory can result in ProtoPNet models with inferior classification accuracy. In this paper, we aim to improve the classification of ProtoPNet with a new method to learn support prototypes that lie near the classification boundary in the feature space, as suggested by the SVM theory. In addition, we target the improvement of classification results with a new model, named ST-ProtoPNet, which exploits our support prototypes and the trivial prototypes to provide more effective classification. Experimental results on CUB-200-2011, Stanford Cars, and Stanford Dogs datasets demonstrate that ST-ProtoPNet achieves state-of-the-art classification accuracy and interpretability results. We also show that the proposed support prototypes tend to be better localised in the object of interest rather than in the background region

Methods for monitoring work-life balance in a digital world

Digital technologies - smart phones, email, social networking, etc. - are fundamentally changing our relationship with work. Digital technologies enable us to be always connected. However, the question remains as to how digital technologies affect our work-life balance. In this position paper, we report on some methods we are using to study how to continuously monitor and observe work-life balance, and discuss the advantages/disadvantages of these methods. Work-life balance is a relatively under-explored area in the quantified self literature; this paper therefore contributes to broader discussions on quantified self but from a domain that has received little attention to date

Nucleotide sequence analyses of the MRP1 gene in four populations suggest negative selection on its coding region

BACKGROUND: The MRP1 gene encodes the 190 kDa multidrug resistance-associated protein 1 (MRP1/ABCC1) and effluxes diverse drugs and xenobiotics. Sequence variations within this gene might account for differences in drug response in different individuals. To facilitate association studies of this gene with diseases and/or drug response, exons and flanking introns of MRP1 were screened for polymorphisms in 142 DNA samples from four different populations. RESULTS: Seventy-one polymorphisms, including 60 biallelic single nucleotide polymorphisms (SNPs), ten insertions/deletions (indel) and one short tandem repeat (STR) were identified. Thirty-four of these polymorphisms have not been previously reported. Interestingly, the STR polymorphism at the 5' untranslated region (5'UTR) occurs at high but different frequencies in the different populations. Frequencies of common polymorphisms in our populations were comparable to those of similar populations in HAPMAP or Perlegen. Nucleotide diversity indices indicated that the coding region of MRP1 may have undergone negative selection or recent population expansion. SNPs E10/1299 G>T (R433S) and E16/2012 G>T (G671V) which occur at low frequency in only one or two of four populations examined were predicted to be functionally deleterious and hence are likely to be under negative selection. CONCLUSION: Through in silico approaches, we identified two rare SNPs that are potentially negatively selected. These SNPs may be useful for studies associating this gene with rare events including adverse drug reactions

A Mixed Method Inquiry of Gas Flaring Consequences, Mitigation Strategies and Policy Implication for Environmental Sustainability in Nigeria

The issue of gas flaring in Nigeria has become a topical one in view of the devastating effect it has in the socio-economic lives of the people in the affected areas. This paper investigates the environmental implication and mitigating strategies of the victims in Nigeria. Mix method was adopted by conducting 60 semi-structured interviews in three communities. The data was transcribed and analyzed using ATLAS.ti and content analysis. Findings show that gas flaring is the major problem facing the Niger Delta communities having negative effects on resident’s health, source of income and farm produce without any legal framework to curb it. Findings also show that people mitigate by using self-strategies such as nose mask, fertilizer for farm produce and boiling of drinking water. Data collected from government shows that there is an annual increase in gas production but gas flaring decreases at a slower rate as depicted in the graph. The paper is the first to conduct research on the coping strategy of the victims of gas flaring in Niger Delta and the importance of technology in eradicating gas flaring. The study recommended technology transfer from technologically advanced countries in capturing the associated gas instead of flaring it. Keywords: Gas flaring, Environmental legislation, Health, Ecological Sustainability, Mitigating Strategy, Government. DOI: 10.7176/JEES/9-2-0

Accuracy of Kinovea Software in Estimating Body Segment Movements During Falls Captured on Standard Video: Effects of Fall Direction, Camera Perspective and Video Calibration Technique

Falls are a major cause of unintentional injuries. Understanding the movements of the body during falls is important to the design of fall prevention and management strategies, including exercise programs, mobility aids, fall detectors, protective gear, and safer environments. Video footage of real-life falls is increasingly available, and may be used with digitization software to extract kinematic features of falls. We examined the validity of this approach by conducting laboratory falling experiments, and comparing linear and angular positions and velocities measured from 3D motion capture to estimates from Kinovea 2D digitization software based on standard surveillance video (30 Hz, 640x480 pixels). We also examined how Kinovea accuracy depended on fall direction, camera angle, filtering cut-off frequency, and calibration technique. For a camera oriented perpendicular to the plane of the fall (90 degrees), Kinovea position data filtered at 10 Hz, and video calibration using a 2D grid, mean root mean square errors were 0.050 m or 9% of the signal amplitude and 0.22 m/s (7%) for vertical position and velocity, and 0.035 m (6%) and 0.16 m/s (7%) for horizontal position and velocity. Errors in angular measures averaged over 2-fold higher in sideways than forward or backward falls, due to out-of-plane movement of the knees and elbows. Errors in horizontal velocity were 2.5-fold higher for a 30 than 90 degree camera angle, and 1.6-fold higher for calibration using participants’ height (1D) instead of a 2D grid. When compared to 10 Hz, filtering at 3 Hz caused velocity errors to increase 1.4-fold. Our results demonstrate that Kinovea can be applied to 30 Hz video to measure linear positions and velocities to within 9% accuracy. Lower accuracy was observed for angular kinematics of the upper and lower limb in sideways falls, and for horizontal measures from 30 degree cameras or 1D height-based calibration