The impact of spatial structure on the accuracy of contour maps of small data sets

Spatial analysis of insect counts provides important information about how insect species respond to the heterogeneity of a given sampling space. Contour mapping is widely used to visualize spatial pest distribution patterns in anthropogenic environments, and in this study we outlined recommendations regarding semivariogram analysis of small data sets (N < 50). Second, we examined how contour maps based upon linear kriging were affected by the spatial structure of the given data set, as error estimation of contour maps appears to have received little attention in the entomological domain. We used weekly trap catches of the warehouse beetle, Trogoderma variabile, and the accuracy assessment was based upon data sets that had either a random spatial structure or were characterized by asymptotic spatial dependence. Asymptotic spatial dependence (typically described with a semivariogram analysis) means that trap catches at locations close to each other are more similar than trap catches at locations further apart. Trap catches were poorly predicted for data sets with a random spatial structure, while there was a significant correlation between observed and predicted trap catches for the spatially rearranged data sets. Therefore, for data sets with a random spatial structure we recommend visualization of the insect counts as scale-sized dots rather than as contour maps.     

An EPROM-based programmable contour generator for use in flow cytometry

An erasable programmable read-only memory (EPROM) contour generator has been fabricated to produce contours for use in flow cytometry. Contours are analog waveforms representing the fluorescence or light-scatter intensity distribution along a cell or object. The generator has particular utility in the development and testing of slit-scan instrumentation and analysis algorithms. Contours are generated without the requirement of specimens or full operation of the flow instrumentation. The generator provides control of contour height, width, offset, and rate. The EPROM may be custom programmed to produce contours for specific test applications or for reproducing "real" contour events. The generator is useful in situations where constant repetitive contours of predetermined characteristics are required.     

Non-Bayesian contour synthesis

Recent research has witnessed an explosive increase in models that treat percepts as optimal probabilistic inference. The ubiquity of partial camouflage and occlusion in natural scenes, and the demonstrated capacity of the visual system to synthesize coherent contours and surfaces from fragmented image data, has inspired numerous attempts to model visual interpolation processes as rational inference. Here, we report striking new forms of visual interpolation that generate highly improbable percepts. We present motion displays depicting simple occlusion sequences that elicit vivid percepts of illusory contours (ICs) in displays for which they play no necessary explanatory role. These ICs define a second, redundant occluding surface, even though all of the image data can be fully explained by an occluding surface that is clearly visible. The formation of ICs in these images therefore entails an extraordinarily improbable co-occurrence of two occluding surfaces that arise from the same local occlusion events. The perceived strength of the ICs depends on simple low-level image properties, which suggests that they emerge as the outputs of mechanisms that automatically synthesize contours from the pattern of occlusion and disocclusion of local contour segments. These percepts challenge attempts to model visual interpolation as a form of rational inference and suggest the need to consider a broader space of computational problems and/or implementation level constraints to understand their genesis.     

A size dependent folding contour for cytochrome C

The paper describes an experimental construct of the folding route of the heme protein cytochrome-C. The construct highlights a slowing down near the nose of the folding funnel caused by the multiplicity of the energy traps near the native conformation created as a result of complex heme-peptide interaction. Interestingly the hydrodynamic size, the size heterogeneity and peroxidase activity serve as a triple measure of the distance of this near equilibrium departure from native conformation. Accordingly, the folding process is marked with a gradual and reversible reduction of mean hydrodynamic size, size heterogeneity and peroxidase activity (higher in unfolded state). The Dynamic Light Scattering based straightforward illustration of hydrodynamic size variation may serve as a model to slow folding observed in case of heme proteins, the heme itself serving as a natural facilitator for the native peptide conformation.     

Temporalis fascia grafts for facial and nasal contour augmentation

For the past 70 years, fascial grafts have been used in reconstructive surgery mainly because of their tensile strength. Although the thigh (fasciae latae) has been the principal donor site, fascia taken from the temporalis muscle has the advantages of (1) ease of harvest under local anesthesia, (2) usually being in the same operative field, (3) minimal postoperative discomfort, and (4) negligible residual scar deformity. These grafts can be effectively used as the sole source of contour augmentation of facial depressions in primary as well as secondary rhinoplasty. Such grafts undergo an initial uniform shrinkage (approximately 20 percent) during the first 4 to 6 weeks postoperatively due to compaction and condensation of the fibrous tissue of the fascia, after which the grafts stabilize and become firm. Concavities should be overcorrected accordingly. No inflammation or encapsulation has been seen clinically or histologically in 18 patients followed for periods ranging from 6 to 18 months.     

Allograft selection for distal femur through cutting contour registration

Allograft reconstruction is an acceptable procedure for the recovery of normal anatomy after the bone tumor resection. During the past few years, several automated methods have been proposed to select the best anatomically matching allograft from the virtual donor bone bank. The surface-based automated method uses the contralateral healthy bone to obtain the normal surface shape of the diseased bone, which could achieve good matching of the defect and the selected allograft. However, the surface-based method focuses on the matching of the whole bone so that the matching of the contact surface between the allograft and the recipient bone may not be optimal. To deal with the above problem, we propose a cutting contour based method for the allograft selection. Cutting contour from the recipient bone could reflect the structural information of the defect and is seldom influenced by tumor. Thus the cutting contour can be used as the matching template to find the optimal alignment of the recipient bone and the allograft. The proposed method is validated using the data of distal femurs where bone transplantation is commonly performed. Experimental results show that the proposed method generally outperforms the surface-based method within modest extra time. Overall, our contour-based method is an effective complementary technique for allograft selection in the virtual bone bank.     

Blood pressure waveform contour analysis for assessing peripheral resistance changes in sepsis

Background

This paper proposes a methodology for helping bridge the gap between the complex waveform information frequently available in an intensive care unit and the simple, lumped values favoured for rapid clinical diagnosis and management. This methodology employs a simple waveform contour analysis approach to compare aortic, femoral and central venous pressure waveforms on a beat-by-beat basis and extract lumped metrics pertaining to the pressure drop and pressure-pulse amplitude attenuation as blood passes through the various sections of systemic circulation.

Results

Validation encompasses a comparison between novel metrics and well-known, analogous clinical metrics such as mean arterial and venous pressures, across an animal model of induced sepsis. The novel metric O_fe?→?vc, the direct pressure offset between the femoral artery and vena cava, and the clinical metric, ΔMP, the difference between mean arterial and venous pressure, performed well. However, O_fe?→?vc reduced the optimal average time to sepsis detection after endotoxin infusion from 46.2 min for ΔMP to 11.6 min, for a slight increase in false positive rate from 1.8 to 6.2%. Thus, the novel O_fe?→?vc provided the best combination of specificity and sensitivity, assuming an equal weighting to both, of the metrics assessed.

Conclusions

Overall, the potential of these novel metrics in the detection of diagnostic shifts in physiological behaviour, here driven by sepsis, is demonstrated.

     

Effect of pre-impact movement strategies on the impact forces resulting from a lateral fall

Approximately 90% of hip fractures in older adults result from falls, mostly from landing on or near the hip. A three-dimensional, 11-segment, forward dynamic biomechanical model was developed to investigate whether segment movement strategies prior to impact can affect the impact forces resulting from a lateral fall. Four different pre-impact movement strategies, with and without using the ipsilateral arm to break the fall, were implemented using paired actuators representing the agonist and antagonist muscles acting about each joint. Proportional-derivative feedback controller controlled joint angles and velocities so as to minimize risk of fracture at any of the impact sites. It was hypothesized that (a) the use of active knee, hip and arm joint torques during the pre-contact phase affects neither the whole body kinetic energy at impact nor the peak impact forces on the knee, hip or shoulder and (b) muscle strength and reaction time do not substantially affect peak impact forces. The results demonstrate that, compared with falling laterally as a rigid body, an arrest strategy that combines flexion of the lower extremities, ground contact with the side of the lower leg along with an axial rotation to progressively present the posterolateral aspects of the thigh, pelvis and then torso, can reduce the peak hip impact force by up to 56%. A 30% decline in muscle strength did not markedly affect the effectiveness of that fall strategy. However, a 300-ms delay in implementing the movement strategy inevitably caused hip impact forces consistent with fracture unless the arm was used to break the fall prior to the hip impact.     

The influence of muscle activation on impact dynamics during lateral falls on the hip

Muscle activation has been demonstrated to influence impact dynamics during scenarios including running, automotive impacts, and head impacts. This study investigated the effects of targeted muscle activation magnitude on impact dynamics during low energy falls on the hip with human volunteers. Fifteen university-aged participants (eight females, seven males) underwent 12 lateral pelvis release trials. Half of the trials were muscle-‘relaxed’; in the remaining ‘contracted’ trials participants isometrically contracted their gluteus medius to 20–30% of maximal voluntary contraction before the drop was initiated onto a force plate. Peak force applied to the femur-pelvis complex averaged 9.3% higher in contracted compared to relaxed trials (F = 6.798, p = .022). Muscle activation effects were greater for females, resulting in (on average) an 18.5% increase in effective pelvic stiffness (F = 5.838, p = .046) and a 23.4% decrease in time-to-peak-force (F = 5.109, p = .042). In the relaxed trials, muscle activation naturally increased during the impact event, reaching levels of 12.8, 7.5, 11.1, and 19.1% MVC at the time of peak force for the gluteus medias, vastus lateralis, erector spinae, and external oblique, respectively. These findings demonstrated that contraction of trunk and hip musculature increased peak impact force across sexes. In females, increases in the magnitude and rate of loading were accompanied (and likely driven) by increases in system stiffness. Accordingly, incorporating muscle activation contributions into biomechanical models that investigate loading dynamics in the femur and/or pelvis during lateral impacts may improve estimate accuracy.     

Computational modeling and exploration of contour integration for visual saliency

We propose a computational model of contour integration for visual saliency. The model uses biologically plausible devices to simulate how the representations of elements aligned collinearly along a contour in an image are enhanced. Our model adds such devices as a dopamine-like fast plasticity, local GABAergic inhibition and multi-scale processing of images. The fast plasticity addresses the problem of how neurons in visual cortex seem to be able to influence neurons they are not directly connected to, for instance, as observed in contour closure effect. Local GABAergic inhibition is used to control gain in the system without using global mechanisms which may be non-plausible given the limited reach of axonal arbors in visual cortex. The model is then used to explore not only its validity in real and artificial images, but to discover some of the mechanisms involved in processing of complex visual features such as junctions and end-stops as well as contours. We present evidence for the validity of our model in several phases, starting with local enhancement of only a few collinear elements. We then test our model on more complex contour integration images with a large number of Gabor elements. Sections of the model are also extracted and used to discover how the model might relate contour integration neurons to neurons that process end-stops and junctions. Finally, we present results from real world images. Results from the model suggest that it is a good current approximation of contour integration in human vision. As well, it suggests that contour integration mechanisms may be strongly related to mechanisms for detecting end-stops and junction points. Additionally, a contour integration mechanism may be involved in finding features for objects such as faces. This suggests that visual cortex may be more information efficient and that neural regions may have multiple roles.     

Arterial pressure contour analysis for estimating human vascular properties.

The form of an arterial blood pressure curve during the diastolic portion of the cardiac cycle was here employed to identify parameters in a third-order model of the vascular system. Calculated elastic and intertial characteristics of this fitted model then became clinically accessible indices of corresponding real vascular properties. This technique incurred no risk and little discomfort for the patient. Tested in theory, in animal experimentation, and in human observations, our procedure utilized a Gauss-Newton algorithm via digital computer to provide rapid model solutions from different starting values, from multiple measurements sites, and from normal or diseased patients. Model parameters thus determined defined ranges of normal variation and suggested a less compliant arterial bed in hypertensive than in normotensive patients.     

Optimality of human contour integration

For processing and segmenting visual scenes, the brain is required to combine a multitude of features and sensory channels. It is neither known if these complex tasks involve optimal integration of information, nor according to which objectives computations might be performed. Here, we investigate if optimal inference can explain contour integration in human subjects. We performed experiments where observers detected contours of curvilinearly aligned edge configurations embedded into randomly oriented distractors. The key feature of our framework is to use a generative process for creating the contours, for which it is possible to derive a class of ideal detection models. This allowed us to compare human detection for contours with different statistical properties to the corresponding ideal detection models for the same stimuli. We then subjected the detection models to realistic constraints and required them to reproduce human decisions for every stimulus as well as possible. By independently varying the four model parameters, we identify a single detection model which quantitatively captures all correlations of human decision behaviour for more than 2000 stimuli from 42 contour ensembles with greatly varying statistical properties. This model reveals specific interactions between edges closely matching independent findings from physiology and psychophysics. These interactions imply a statistics of contours for which edge stimuli are indeed optimally integrated by the visual system, with the objective of inferring the presence of contours in cluttered scenes. The recurrent algorithm of our model makes testable predictions about the temporal dynamics of neuronal populations engaged in contour integration, and it suggests a strong directionality of the underlying functional anatomy.