The effect of load weight on balance control during lateral box transfers

Few studies have endeavoured to measure balance control during manual material handling. This study examined the effects of load weight during a stationary manual material handling task. In total, 36 healthy participants completed 180° lateral transfer tasks of a loaded (5% of body weight) and an unloaded box. The projection of the centre of mass onto the base of support, as measured via a passive-marker 3-D motion analysis system, was used to quantify balance control. Muscle activities of lower extremity muscles were also measured. When moving the loaded box, individuals ventured ≥ 1 cm closer to the edges of the base of support and increased centre of mass movement up to 14%. In addition, muscle electromyographic activity on both sides of the shank increased. In summary, during loaded configurations, vulnerability to loss of balance was increased and individuals appeared to adapt by increasing co-contraction of the shank muscles suggesting increased ankle stiffness. STATEMENT OF RELEVANCE: Industries requiring manual material handling have a particularly high rate of injuries due to falls. This study suggests that larger load weights during lateral material handling tasks adversely affect balance control and may create a vulnerability to imbalance throughout the entire manoeuvre.     

Picbreeder: a case study in collaborative evolutionary exploration of design space

For domains in which fitness is subjective or difficult to express formally, interactive evolutionary computation (IEC) is a natural choice. It is possible that a collaborative process combining feedback from multiple users can improve the quality and quantity of generated artifacts. Picbreeder, a large-scale online experiment in collaborative interactive evolution (CIE), explores this potential. Picbreeder is an online community in which users can evolve and share images, and most importantly, continue evolving others' images. Through this process of branching from other images, and through continually increasing image complexity made possible by the underlying neuroevolution of augmenting topologies (NEAT) algorithm, evolved images proliferate unlike in any other current IEC system. This paper discusses not only the strengths of the Picbreeder approach, but its challenges and shortcomings as well, in the hope that lessons learned will inform the design of future CIE systems.     

Visual comparability of 3D regular sampling and reconstruction

The Body-Centered Cubic (BCC) and Face-Centered Cubic (FCC) lattices have been analytically shown to be more efficient sampling lattices than the traditional Cartesian Cubic (CC) lattice, but there has been no estimate of their visual comparability. Two perceptual studies (each with N = 12 participants) compared the visual quality of images rendered from BCC and FCC lattices to images rendered from the CC lattice. Images were generated from two signals: the commonly used Marschner-Lobb synthetic function and a computed tomography scan of a fish tail. Observers found that BCC and FCC could produce images of comparable visual quality to CC, using 30-35 percent fewer samples. For the images used in our studies, the L(2) error metric shows high correlation with the judgement of human observers. Using the L(2) metric as a proxy, the results of the experiments appear to extend across a wide range of images and parameter choices.     

Quality metrics in high-dimensional data visualization: an overview and systematization

In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alternative visualizations (e.g., alternative projections or ordering), allowing the user to concentrate on the most promising visualizations suggested by the quality metrics. Over the last decade, this approach has witnessed a remarkable development but few reflections exist on how these methods are related to each other and how the approach can be developed further. For this purpose, we provide an overview of approaches that use quality metrics in high-dimensional data visualization and propose a systematization based on a thorough literature review. We carefully analyze the papers and derive a set of factors for discriminating the quality metrics, visualization techniques, and the process itself. The process is described through a reworked version of the well-known information visualization pipeline. We demonstrate the usefulness of our model by applying it to several existing approaches that use quality metrics, and we provide reflections on implications of our model for future research.     

Evaluation of artery visualizations for heart disease diagnosis

Heart disease is the number one killer in the United States, and finding indicators of the disease at an early stage is critical for treatment and prevention. In this paper we evaluate visualization techniques that enable the diagnosis of coronary artery disease. A key physical quantity of medical interest is endothelial shear stress (ESS). Low ESS has been associated with sites of lesion formation and rapid progression of disease in the coronary arteries. Having effective visualizations of a patient's ESS data is vital for the quick and thorough non-invasive evaluation by a cardiologist. We present a task taxonomy for hemodynamics based on a formative user study with domain experts. Based on the results of this study we developed HemoVis, an interactive visualization application for heart disease diagnosis that uses a novel 2D tree diagram representation of coronary artery trees. We present the results of a formal quantitative user study with domain experts that evaluates the effect of 2D versus 3D artery representations and of color maps on identifying regions of low ESS. We show statistically significant results demonstrating that our 2D visualizations are more accurate and efficient than 3D representations, and that a perceptually appropriate color map leads to fewer diagnostic mistakes than a rainbow color map.     

BallotMaps: detecting name bias in alphabetically ordered ballot papers

The relationship between candidates' position on a ballot paper and vote rank is explored in the case of 5000 candidates for the UK 2010 local government elections in the Greater London area. This design study uses hierarchical spatially arranged graphics to represent two locations that affect candidates at very different scales: the geographical areas for which they seek election and the spatial location of their names on the ballot paper. This approach allows the effect of position bias to be assessed; that is, the degree to which the position of a candidate's name on the ballot paper influences the number of votes received by the candidate, and whether this varies geographically. Results show that position bias was significant enough to influence rank order of candidates, and in the case of many marginal electoral wards, to influence who was elected to government. Position bias was observed most strongly for Liberal Democrat candidates but present for all major political parties. Visual analysis of classification of candidate names by ethnicity suggests that this too had an effect on votes received by candidates, in some cases overcoming alphabetic name bias. The results found contradict some earlier research suggesting that alphabetic name bias was not sufficiently significant to affect electoral outcome and add new evidence for the geographic and ethnicity influences on voting behaviour. The visual approach proposed here can be applied to a wider range of electoral data and the patterns identified and hypotheses derived from them could have significant implications for the design of ballot papers and the conduct of fair elections.     

The effect on lower spine muscle activation of walking on a narrow beam in virtual reality

To what extent do people behave in immersive virtual environments as they would in similar situations in a physical environment? There are many ways to address this question, ranging from questionnaires, behavioral studies, and the use of physiological measures. Here, we compare the onsets of muscle activity using surface electromyography (EMG) while participants were walking under three different conditions: on a normal floor surface, on a narrow ribbon along the floor, and on a narrow platform raised off the floor. The same situation was rendered in an immersive virtual environment (IVE) Cave-like system, and 12 participants did the three types of walking in a counter-balanced within-groups design. The mean number of EMG activity onsets per unit time followed the same pattern in the virtual environment as in the physical environment-significantly higher for walking on the platform compared to walking on the floor. Even though participants knew that they were in fact really walking at floor level in the virtual environment condition, the visual illusion of walking on a raised platform was sufficient to influence their behavior in a measurable way. This opens up the door for this technique to be used in gait and posture related scenarios including rehabilitation.     

GPU-accelerated minimum distance and clearance queries

We present practical algorithms for accelerating distance queries on models made of trimmed NURBS surfaces using programmable Graphics Processing Units (GPUs). We provide a generalized framework for using GPUs as coprocessors in accelerating CAD operations. By supplementing surface data with a surface bounding-box hierarchy on the GPU, we answer distance queries such as finding the closest point on a curved NURBS surface given any point in space and evaluating the clearance between two solid models constructed using multiple NURBS surfaces. We simultaneously output the parameter values corresponding to the solution of these queries along with the model space values. Though our algorithms make use of the programmable fragment processor, the accuracy is based on the model space precision, unlike earlier graphics algorithms that were based only on image space precision. In addition, we provide theoretical bounds for both the computed minimum distance values as well as the location of the closest point. Our algorithms are at least an order of magnitude faster and about two orders of magnitude more accurate than the commercial solid modeling kernel ACIS.     

Binding conformation prediction between human acetylcholinesterase and cytochrome c using molecular modeling methods

The acetylcholinesterase (AChE) is important to terminate acetylcholine-mediated neurotransmission at cholinergic synapses. The pivotal role of AChE in apoptosome formation through the interactions with cytochrome c (Cyt c) was demonstrated in recent study. In order to investigate the proper binding conformation between the human AChE (hAChE) and human Cyt c (hCyt c), macro-molecular docking simulation was performed using DOT 2.0 program. The hCyt c was bound to peripheral anionic site (PAS) on hAChE and binding mode of the docked conformation was very similar to the reported crystal structure of the AChE and fasciculin-II (Fas-II) complex. Two 10ns molecular dynamics (MD) simulations were carried out to refine the binding mode of docked structure and to observe the differences of the binding conformations between the absent (Apo) and presence (Holo) of heme group. The key hydrogen bonding residues between hAChE and hCyt c proteins were found in Apo and Holo systems, as well as each Tyr341 and Trp286 residue of hAChE was participated in cation-pi (π) interactions with Lys79 of hCyt c in Apo and Holo systems, respectively. From the present study, although the final structures of the Apo and Holo systems have similar binding pattern, several differences were investigated in flexibilities, interface interactions, and interface accessible surface areas. Based on these results, we were able to predict the reasonable binding conformation which is indispensable for apoptosome formation.