Average Rms Deviation Research Articles

EFFECT OF INNER BOUNDARIES GEOMETRY ON NATURALCONVECTION HEAT TRANSFER IN HORIZONTAL ANNULI

An analytical modeling of natural convection in physically-based analysis is developed for investigate free convective heat transfer in horizontal eccentric annulus between a circular outer cylinder and heated different shape inner envelope with used four models of the shapes of the inner cross section of (circular, triangular, square and hexagon inner boundary). The main objective of this paper was taking a composite model based on asymptotic solutions for three limiting cases: pure conduction, laminar boundary layer convection and transition flow convection. Laminar conditions up to Rayleigh number RaPi of 5×104 were investigated. By using data from MATLAB simulations for a wide range of two cylinder temperature difference in order to study the effects of annulus diameter ratio, Rayleigh number, and the cross section geometries of inner cylinder on the Nusslte number and the ratio of thermal conductivity. The numerical result illustrated for the circular the increasing the Rayleigh number leading to slightly increasing the non-dimensional Nusslte number with various value of annulus diameter ratio and when used the high annulus perimeter ratio (Po/Pi( about (4.5,2.6,1.6 and 1.175). There is rapid increasing in the non-dimensional ratio of thermal conductivity with increasing the Rayleigh number at the high values of (Po/Pi(, and the result showed that the non-dimensional ratio of thermal conductivity and the Nusslte number values of the (triangular, square and hexagon) less than in the case of circular inner boundary, but the hexagon model showed the Nusslte number more that than in the (triangular and square). the mathematical results compared with model developed by pervious numerical the model and data are in good agreement, with an average RMS difference of 10.6% for the circular annulus of dimensional Nusselt number (NuPi) and less than 4.9 % and 9.8% for the square inner geometry non-dimensional ratio thermal conductivity.

Dynamic Locational Marginal Emissions via Implicit Differentiation

Locational marginal emissions rates (LMEs) estimate the rate of change in emissions due to a small change in demand in a transmission network, and are an important metric for assessing the impact of various energy policies or interventions. In this work, we develop a new method for computing the LMEs of an electricity system via implicit differentiation. The method is model agnostic; it can compute LMEs for any convex optimization-based dispatch model, including some of the complex dispatch models employed by system operators in real electricity systems. In particular, this method lets us derive LMEs for dynamic dispatch models, i.e., models with temporal constraints such as ramping and storage. Using real data from the U.S. electricity system, we validate the proposed method against a state-of-the-art merit-order-based method and show that incorporating dynamic constraints improves model accuracy by 8.2%. Finally, we use simulations on a realistic 240-bus model of WECC to demonstrate the flexibility of the tool and the importance of incorporating dynamic constraints. Namely, static LMEs and dynamic LMEs exhibit a normalized average RMS deviation of 28.40%, implying dynamic constraints are essential to accurately modeling emissions rates.

An Improved Stacked Auto Encoder based Data Compression Technique for WSNs

Abstract: Because of the limited energy available to sensor nodes in wireless sensor networks (WSNs), data compression is critical in these networks. The majority of the time, data communication results in energy consumption; however, by minimizing data transmission and reception, the lifetime of sensor nodes may usually be extended significantly. To compress sensor data, we present a new Improved Stacked RBM Auto-Encoder model, which is built of two layers: an encode layer and a decode layer, which is described in detail in this work. Data from sensors is compressed and decompressed in the encode layer; data from sensors is reconstructed and compressed in the decode layer. The encode layer and the decode layer are both made up of four conventional Restricted Boltzmann Machines that are used throughout the system (RBMs). We also present an energy optimization strategy that, by trimming the parameters of the model, can further minimize the energy consumption of the model storage and calculation. We evaluate the model's performance by comparing it to the data acquired by Intel Lab in the environment. Assuming that the model's compression ratio is 10, the average Percentage RMS Difference value is 9.84 percent, and the average temperature reconstruction error value is 0.312 degrees Celsius. It is possible to minimize the energy consumption of node communication in WSNs by 92 percent. When compared to the traditional method, the proposed model achieves higher compression efficiency and reconstruction accuracy while maintaining the same compression ratio as the old method. The results of our experiments demonstrate that the new neural network model can not only be applied to data compression for WSNs, but it also has high compression efficiency and an excellent transfer learning capability. Keywords: Data Compression; Stacked-Autocoder; transfer learning; energy, consumption optimization

A novel cooling geometry for subsea variable speed drives

Experimental and theoretical analyses are conducted to evaluate the passive cooling performance of a novel geometry for subsea variable speed drives, a common piece of equipment in deep-sea oil exploration. Relying on the sea water as a low-temperature thermal reservoir, the new design forms an enclosed, annular space with centrally located modular boards that compose the power electronics inverter. Buoyancy-induced motion of a dielectric coolant conveys the heat dissipated by the electronic boards to the sea water through the outer and innermost walls of the annular enclosure. A thermal network model is implemented and used to optimize the enclosure geometry through a genetic algorithm, which served as a reference for a scaled experimental setup. A Computational Fluid Dynamics (CFD) simulation of the conjugate heat transfer yielded temperature distributions on the electronic boards and temperature and fluid velocity fields inside the enclosure. A comparison between the experimental data and the modeling results indicated a good agreement, with average RMS deviations of a modified Nusselt number of 7.0% and 8.5% for the thermal network and CFD analysis, respectively. For a 140-W operating point dissipation rate in the scaled test setup, the thermal network and the CFD models presented maximal deviations of 4°C and 2.3°C with respect to the heat sink temperature measurements.

Upper Limbs Kinematics Estimation Using Affordable Visual-Inertial Sensors

This study aims at developing and evaluating an affordable and user-friendly motion capture system for human upper limbs’ joint kinematics estimation. The objective is to provide quantitative assessments during the clinical evaluation of poststroke patients performing daily living activities. The proposed system is based on the simultaneous use of affordable inertial measurement units, and a set of augmented reality markers tracked with an affordable RGB camera. Two practical calibration processes were developed to calibrate the sensors modules and then to determine their location on body segments. Then, all measured quantities were fused into a constrained extended Kalman filter based on an upper limbs’ biomechanical model. The proposed system was validated with nine healthy volunteers performing five daily living activities. Joint angles estimated using the proposed affordable system were compared with a gold standard stereophotogrammetric system. The results showed a low average rms difference (2.7°) along with a high average correlation (0.87). <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article was motivated by the problem of assessing human upper limbs’ mobility during a rehabilitation process. Existing systems are often inaccurate and/or not affordable. This article suggests a new approach by combining measurements from inertial measurement units and augmented reality markers into an adaptive filter that is taking into account the kinematics model of the human arm and its limitation to filter out unfeasible solutions. The system is also making use of a new very practical calibration method not requiring any external equipment while remaining very affordable. Experimental results suggest that the proposed system is able to estimate more accurately than state-of-the-art joint angles of the upper limbs.

Pre-operative simulation of post-operative multifocal vision.

While multifocal intraocular lenses (MIOLs) are increasingly implanted to correct for presbyopia, how one sees with a multifocal correction is hard to explain and imagine. The current study evaluates the quality of various visual simulating technologies by comparing vision with simulated MIOLs pre-operatively and the implanted MIOLs post-operatively in the same patients. Two simulation platforms were used: (1) a custom-developed adaptiveoptics (AO) system, with two visual simulator devices: a spatial light modulator (SLM) and an optotunable lens operating under temporal multiplexing (SimVis); and (2) a wearable, binocular, large field of view SimVis2Eyes clinical simulator (SimVis Gekko, 2Eyes Vision, Madrid, Spain). All devices were programmed to simulate a trifocal diffractive MIOL (POD F, FineVision, PhysIOL). Eight patients were measured pre-operatively simulating the trifocal lens and post-operatively with implantation of the same MIOL. Through-focus decimal visual acuity (TF VA) was measured (1) monocularly in monochromatic light using a four-alternative-forced-choice procedure in the AO system; and (2) binocularly using a clinical optotype in white light. Visual simulations pre-operatively predict well the TF VA performance found post-operatively in patients implanted with the real IOL. The average RMS difference between TF curves with the different visual simulators was 0.05 ± 0.01. The average RMS difference between the TF VA curves with the SimVis pre-operatively and the real MIOL post-operatively was 0.06 ± 0.01 in both platforms, and it was higher in cataract eyes (0.08 ± 0.01, on average across simulators) than in eyes with clear lens. In either group the shape of the TF curves is similar across simulators and pre- and post-operatively. TF curves cross-correlated significantly between simulators (lag k = 0, rho = 0.889), as well as with results with the real MIOL implanted (lag k = 0, rho = 0.853). Visual simulations are useful programmable tools to predict visual performance with MIOLs, both in an AO environment and in a clinical simulator. Pre-operative visual simulations and post-operative data are in good agreement.

Simplified Triceps Surae Muscle Volume Assessment in Older Adults.

Triceps surae (TS) muscle volume can be estimated in young adults by only considering the maximal anatomical cross-sectional area (ACSAmax) and the length of the muscle due to the presence of a constant muscle-specific shape factor. This study aimed to investigate if this simplified muscle volume assessment is also applicable in older adults or if muscle-specific shape changes with aging. MRI sequences were taken from the dominant leg of 21 older female adults. The boundaries of all three TS muscles (SOL, soleus; GM, gastrocnemius medialis; GL, gastrocnemius lateralis) were manually outlined in transverse image sequences, and muscle volume for each muscle was calculated as the integral of the obtained cross-sectional areas of the contours along the whole length of the muscle (measured volume) and, in addition, by using the average muscle-specific shape factors of each muscle obtained from the ratio of the measured volume and the product of ACSAmax and the muscle length (estimated volume). There were no differences in the measured and estimated muscle volumes (SOL: 357.7 ± 61.8 vs. 358.8 ± 65.3 cm3; GM: 179.5 ± 32.8 vs. 179.8 ± 33.3 cm3; GL: 90.2 ± 15.9 vs. 90.4 ± 14.8 cm3). However, when using the reported shape factors of younger adults instead, we found a significant (p < 0.05) overestimation of muscle volume for SOL and GM with average RMS differences of 6.1 and 7.6%, respectively. These results indicate that corrections of muscle-specific shape factors are needed when using the previously proposed simplified muscle volume assessment as aging may not only be accompanied with muscle atrophy but also changes in the shape of skeletal muscle.

Advanced predictions of solidification in cryogenic natural gas and LNG processing

The formation and deposition of solids during the cryogenic processing of natural gas is a perennial risk for operators. Several tools are available for predicting the temperatures at which heavy hydrocarbon solids will form in cryogenic processing equipment; of these the Kohn and Luks Solids Solubility Program (KLSSP) from GPA Midstream has become an industry standard tool for predicting solid-fluid equilibria (SFE) in cryogenic processes. However, although it describes well many of the data sets generated as part of the GPA’s research program in the 1970s and 1980s, the KLSSP suffers from limitations including fixed ranges of temperature, mixture composition, no dependence on pressure and a limited set of possible freeze-out components. Here, a new software tool called ThermoFAST is presented, which overcomes these limitations and has been endorsed by GPA Midstream to replace the KLSSP. This model uses a cubic equation of state and efficient flash algorithms to enable rapid calculations of solid-liquid, solid-vapour, and solid-liquid-vapour equilibrium conditions in addition to normal vapour-liquid phase envelopes. The model has been tuned to the available solid-fluid equilibrium literature data for 58 binary mixtures and is able to represent them with an average root-mean-squared temperature deviation of only 1.7 K. It was thoroughly tested against available SLE data for multi-component LNG mixtures, and improved the accuracy of predicted melting temperatures by a factor of 7 relative to KLSSP, with an average rms deviation of only 2.0 K. The rapid flash algorithm was used to identify 26 distinct transition pathways involving solidification phenomena in LNG-relevant fluids: this includes the prediction of retrograde solidification in multiple systems (including the methane + benzene binary) where a decrease in system temperature produces a reduction in the amount of solid phase present.

Motion Estimation From Surface Electromyogram Using Adaboost Regression and Average Feature Values

The method to estimate joint motion quickly and accurately from surface electromyogram (sEMG) has been explored by many researchers. However, the effect of different grabbing loads is ignored by most of them, which limits its clinical and daily applicability. In order to eliminate this effect in the course of motion estimation, an Adaboost-AF method based on Adaboost regression was proposed to identify the load information and estimate motion intention. This method is composed of three parts: the sEMG preprocessing part, the load identification part, and the motion intention estimation part. The average value of sEMG feature signal, which is obtained during sEMG preprocessing part, was used to identify the load information. Five features, root mean square (rms), waveform length, difference absolute standard deviation value, the integral signal of sEMG (IEMG), and low-pass filtered signal of sEMG (LPFEMG) similar to sEMG envelope were explored whether the average value of features signal can be used to identify the load under different speeds. After the load was identified, the Adaboost regression framework with the decision tree as the weak learner was applied to be the motion intention estimation part. Experimental results showed that the average rms difference between an actual angle and estimated angle by using the Adaboost-AF method was 0.1193 ± 0.0148, and the average execution time for a section of data with 17.58 s was 0.3932 ± 0.0610s. (Scikit-learn packet was adopted, and the version number was V0.21. The running software was Spyder, Python3.6.) This paper shows that the method based on the average value of sEMG feature signals can eliminate the influence of different loads without adding new sensors; IEMG and LPFEMG from the biceps brachii muscle show the optimal loads identification performance; the proposed Adaboost-AF method takes the influence of different loads into account and ensures the rapid and accurate estimation performance of motion intention.

Data Compression Based on Stacked RBM-AE Model for Wireless Sensor Networks.

Data compression is very important in wireless sensor networks (WSNs) with the limited energy of sensor nodes. Data communication results in energy consumption most of the time; the lifetime of sensor nodes is usually prolonged by reducing data transmission and reception. In this paper, we propose a new Stacked RBM Auto-Encoder (Stacked RBM-AE) model to compress sensing data, which is composed of a encode layer and a decode layer. In the encode layer, the sensing data is compressed; and in the decode layer, the sensing data is reconstructed. The encode layer and the decode layer are composed of four standard Restricted Boltzmann Machines (RBMs). We also provide an energy optimization method that can further reduce the energy consumption of the model storage and calculation by pruning the parameters of the model. We test the performance of the model by using the environment data collected by Intel Lab. When the compression ratio of the model is 10, the average Percentage RMS Difference value is 10.04%, and the average temperature reconstruction error value is 0.2815 °C. The node communication energy consumption in WSNs can be reduced by 90%. Compared with the traditional method, the proposed model has better compression efficiency and reconstruction accuracy under the same compression ratio. Our experiment results show that the new neural network model can not only apply to data compression for WSNs, but also have high compression efficiency and good transfer learning ability.

In vivo validation of patellofemoral kinematics during overground gait and stair ascent

BackgroundThe patellofemoral (PF) joint is a common site for non-specific anterior knee pain. The pathophysiology of patellofemoral pain may be related to abnormal motion of the patella relative to the femur, leading to increased stress at the patellofemoral joint. Patellofemoral motion cannot be accurately measured using conventional motion capture. Research questionThe aim of this study was to determine the accuracy of a biplane radiography system for measuring in vivo PF motion during walking and stair ascent. MethodsFour subjects had three 1.0 mm diameter tantalum beads implanted into the patella. Participants performed three trials each of over ground walking and stair ascent while biplane radiographs were collected at 100 Hz. Patella motion was tracked using radiostereophotogrammetric analysis (RSA) as a “gold standard”, and compared to a volumetric CT model-based tracking algorithm that matched digitally reconstructed radiographs to the original biplane radiographs. ResultsThe average RMS difference between the RSA and model-based tracking was 0.41 mm and 1.97° when there was no obstruction from the contralateral leg. These differences increased by 34% and 40%, respectively, when the patella was at least partially obstructed by the contralateral leg. The average RMS difference in patellofemoral joint space between tracking methods was 0.9 mm or less. SignificancePrevious validations of biplane radiographic systems have estimated tracking accuracy by moving cadaveric knees through simulated motions. These validations were unable to replicate in vivo kinematics, including patella motion due to muscle activation, and failed to assess the imaging and tracking challenges related to contralateral limb obstruction. By replicating the muscle contraction, movement velocity, joint range of motion, and obstruction of the patella by the contralateral limb, the present study provides a realistic estimate of patellofemoral tracking accuracy for future in vivo studies.

Combined measurement and modeling of specimen-specific knee mechanics for healthy and ACL-deficient conditions

Quantifying the mechanical environment at the knee is crucial for developing successful rehabilitation and surgical protocols. Computational models have been developed to complement in vitro studies, but are typically created to represent healthy conditions, and may not be useful in modeling pathology and repair. Thus, the objective of this study was to create finite element (FE) models of the natural knee, including specimen-specific tibiofemoral (TF) and patellofemoral (PF) soft tissue structures, and to evaluate joint mechanics in intact and ACL-deficient conditions. Simulated gait in a whole joint knee simulator was performed on two cadaveric specimens in an intact state and subsequently repeated following ACL resection. Simulated gait was performed using motor-actuated quadriceps, and loads at the hip and ankle. Specimen-specific FE models of these experiments were developed in both intact and ACL-deficient states. Model simulations compared kinematics and loading of the experimental TF and PF joints, with average RMS differences [max] of 3.0° [8.2°] and 2.1° [8.4°] in rotations, and 1.7 [3.0] and 2.5 [5.1] mm in translations, for intact and ACL-deficient states, respectively. The timing of peak quadriceps force during stance and swing phase of gait was accurately replicated within 2° of knee flexion and with an average error of 16.7% across specimens and pathology. Ligament recruitment patterns were unique in each specimen; recruitment variability was likely influenced by variations in ligament attachment locations. ACL resections demonstrated contrasting joint mechanics in the two specimens with altered knee motion shown in one specimen (up to 5mm anterior tibial translation) while increased TF joint loading was shown in the other (up to 400N).

An efficient method for estimating soft tissue deformation based on intraoperative stereo image features and point-based registration

Estimation of soft tissue deformation occurring during image-guided surgery using an easily implemented and accurate method is necessary. Using a stereo camera, this study focuses on two efficient methods for estimating soft tissue deformation. Two methods were proposed to overcome limitations associated with the typical methods used for estimating soft tissue deformation, such as dependence on accuracy of the operator and indentation of skin. The first method is based on Triclops SDK, and the second method is based on projecting a pattern to acquire P-Lands (Projected Landmarks). Based on the proposed methods, surface information is acquired in the form of point clouds of surface point coordinates to the submillimeter accuracy. The reconstructed predeformation three-dimensional (3D) point cloud obtained for each method is registered with a modified iterative closest point algorithm to a postdeformation 3D point cloud obtained from the same region of interest. Results were compared with an MRI–MRI registration method as a control. Results are provided as RMS differences between the initial and final coordinates of corresponding points. The average RMS difference for the typical method is 3.53 mm, that for the Triclops SDK method is 2.32 mm, and that for the P-Lands projection method is 2.06 mm. The MRI-MRI registration had an average RMS difference of 1.12 mm. Using MRI-MRI registration as the gold standard, the average error obtained for the typical method was 2.41 mm, that for the first method was 1.2 mm, and that for the second method was 0.94 mm. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 294–303, 2013

FTS high resolution spectra of 16O3 in 3500 and 5500 cm−1 regions. First example of new theoretical modelling for a polyad of strongly coupled states

The infrared spectrum of 16O3 has been revisited in the ranges 3300–3600cm−1 and 5200–5600cm−1, recorded by the Fourier Transform Spectrometer of Reims, with an improved signal/noise ratio. In the lower spectral range the weak 2ν1+2ν2 band is observed and assigned for the first time. This allowed for completing the triad of strongly interacting (220), (121), and (022) states. The resonance interaction parameters for this triad were derived from the molecular potential energy surface using high-order Contact Transformation method. This involves Darling–Dennison resonances between (220) and (022) vibration A-states, and Coriolis resonances between (121) B-state and A-states. Altogether 18 coupling parameters were fixed to these theoretically predicted values that allowed avoiding problems of ambiguities while fitting strongly correlated parameters. The remaining small perturbations of a few Ka=5 transitions of the ν1+2ν2+ν3 band were explained by accidental Coriolis resonance of (121) with the (050) dark state. This mixed half theoretical/half empirical model (with 39 fitted and 77 theoretically constrained parameters) developed in this work for the first time allows an excellent description of 1897 line positions with the rms deviation ∼0.001cm−1 closed to the experimental precision. The intensities of two new hot bands ν2+4ν3−ν3 and ν1+ν2+3ν3−ν1 that fall in this range were also observed and modelled, thanks to a better signal to noise ratio.In addition, the 5200–5600cm−1 region has also been revisited, showing for the first time the (321) state which was considered as “dark” one in the previous analysis. Effective Hamiltonian parameters were derived for strongly coupled (213)/(114)/(321) upper states including (080) as a dark one.The transition moment parameters of all newly observed and assigned bands were derived resulting to average rms deviation for intensities of ∼8% and 13% for the cold and the hot bands, respectively, in the lower range and of ∼15% for the bands in the upper range that is close to experimental accuracy for weak transitions.

Mitral annulus segmentation from four-dimensional ultrasound using a valve state predictor and constrained optical flow

Measurement of the shape and motion of the mitral valve annulus has proven useful in a number of applications, including pathology diagnosis and mitral valve modeling. Current methods to delineate the annulus from four-dimensional (4D) ultrasound, however, either require extensive overhead or user-interaction, become inaccurate as they accumulate tracking error, or they do not account for annular shape or motion. This paper presents a new 4D annulus segmentation method to account for these deficiencies. The method builds on a previously published three-dimensional (3D) annulus segmentation algorithm that accurately and robustly segments the mitral annulus in a frame with a closed valve. In the 4D method, a valve state predictor determines when the valve is closed. Subsequently, the 3D annulus segmentation algorithm finds the annulus in those frames. For frames with an open valve, a constrained optical flow algorithm is used to the track the annulus. The only inputs to the algorithm are the selection of one frame with a closed valve and one user-specified point near the valve, neither of which needs to be precise. The accuracy of the tracking method is shown by comparing the tracking results to manual segmentations made by a group of experts, where an average RMS difference of 1.67±0.63mm was found across 30 tracked frames.

The Influence of Age on the Refractive Index of the Human Corneal Stroma Resected Using a Mechanical Microkeratome

To measure the refractive index (RI) of the human corneal stroma in vivo using an objective Abbé refractometer (VCH-1) and to determine if RI of the stroma is related to age. The VCH-1 was calibrated against a standard subjective Abbé refractometer using 7 randomly selected turbid semiliquid media. VCH-1 was used to measure RI at the central midstroma immediately after lifting the flap in neophyte patients preselected for laser-assisted in situ keratomileusis. Surgical procedures continued as preplanned after measuring the RI; in binocular cases, measurements were taken from the right eye only. Flaps were created using a mechanical microkeratome. The VCH-1 was capable of measuring the RIs of all 7 turbid semiliquid media. The average RMS difference between RI estimates according to the VCH-1 and standard subjective Abbé refractometer was 0.003. The mean RI (± SD) of the stroma was 1.369 (± 0.008; range, 1.356-1.390), and the mean age (± SD) of the subjects was 33.7 years (± 8.86; range, 18-56 years). A significant linear correlation was found between age and RI. Least squares regression lines equating RI with age (x, years) was of the form: RI = 1.35711 + 0.00034x (r = +0.383, n = 36, P = 0.011). RI of the stroma in vivo has a tendency to be increased in older patients when the stroma is resected using a mechanical microkeratome.

Structural Investigation of Rimantadine Inhibition of the AM2-BM2 Chimera Channel of Influenza Viruses

The M2 channel of influenza A is a target of the adamantane family antiviral drugs. Two different drug-binding sites have been reported: one inside the pore, and the other is a lipid-facing pocket. A previous study showed that a chimera of M2 variants from influenza A and B that contains only the pore-binding site is sensitive to amantadine inhibition, suggesting that the primary site of inhibition is inside the pore. To obtain atomic details of channel-drug interaction, we determined the structures of the chimeric channel with and without rimantadine. Inside the channel and near the N-terminal end, methyl groups of Val27 and Ala30 from four subunits form a hydrophobic pocket around the adamantane, and the drug amino group appears to be in polar contact with the backbone oxygen of Ala30. The structures also reveal differences between the drug-bound and -unbound states of the channel that can explain drug resistance.

Comparative Assessment of Bone Pose Estimation Using Point Cluster Technique and OpenSim

Estimating the position of the bones from optical motion capture data is a challenge associated with human movement analysis. Bone pose estimation techniques such as the Point Cluster Technique (PCT) and simulations of movement through software packages such as OpenSim are used to minimize soft tissue artifact and estimate skeletal position; however, using different methods for analysis may produce differing kinematic results which could lead to differences in clinical interpretation such as a misclassification of normal or pathological gait. This study evaluated the differences present in knee joint kinematics as a result of calculating joint angles using various techniques. We calculated knee joint kinematics from experimental gait data using the standard PCT, the least squares approach in OpenSim applied to experimental marker data, and the least squares approach in OpenSim applied to the results of the PCT algorithm. Maximum and resultant RMS differences in knee angles were calculated between all techniques. We observed differences in flexion/extension, varus/valgus, and internal/external rotation angles between all approaches. The largest differences were between the PCT results and all results calculated using OpenSim. The RMS differences averaged nearly 5° for flexion/extension angles with maximum differences exceeding 15°. Average RMS differences were relatively small (< 1.08°) between results calculated within OpenSim, suggesting that the choice of marker weighting is not critical to the results of the least squares inverse kinematics calculations. The largest difference between techniques appeared to be a constant offset between the PCT and all OpenSim results, which may be due to differences in the definition of anatomical reference frames, scaling of musculoskeletal models, and/or placement of virtual markers within OpenSim. Different methods for data analysis can produce largely different kinematic results, which could lead to the misclassification of normal or pathological gait. Improved techniques to allow non-uniform scaling of generic models to more accurately reflect subject-specific bone geometries and anatomical reference frames may reduce differences between bone pose estimation techniques and allow for comparison across gait analysis platforms.

Toward a Robust Search Method for the Protein-Drug Docking Problem

Predicting the binding mode(s) of a drug molecule to a target receptor is pivotal in structure-based rational drug design. In contrast to most approaches to solve this problem, the idea in this paper is to analyze the search problem from a computational perspective. By building on top of an existing docking tool, new methods are proposed and relevant computational results are proven. These methods and results are applicable for other place-and-join frameworks as well. A fast approximation scheme for the docking of rigid fragments is described that guarantees certain geometric approximation factors. It is also demonstrated that this can be translated into an energy approximation for simple scoring functions. A polynomial time algorithm is developed for the matching phase of the docked rigid fragments. It is demonstrated that the generic matching problem is NP-hard. At the same time, the optimality of the proposed algorithm is proven under certain scoring function conditions. The matching results are also applicable for some of the fragment-based de novo design methods. On the practical side, the proposed method is tested on 829 complexes from the PDB. The results show that the closest predicted pose to the native structure has the average RMS deviation of 1.06 A.

Mitral Annulus Segmentation From 3D Ultrasound Using Graph Cuts

The shape of the mitral valve annulus is used in diagnostic and modeling applications, yet methods to accurately and reproducibly delineate the annulus are limited. This paper presents a mitral annulus segmentation algorithm designed for closed mitral valves which locates the annulus in three-dimensional ultrasound using only a single user-specified point near the center of the valve. The algorithm first constructs a surface at the location of the thin leaflets, and then locates the annulus by finding where the thin leaflet tissue meets the thicker heart wall. The algorithm iterates until convergence metrics are satisfied, resulting in an operator-independent mitral annulus segmentation. The accuracy of the algorithm was assessed from both a diagnostic and surgical standpoint by comparing the algorithm's results to delineations made by a group of experts on clinical ultrasound images of the mitral valve, and to delineations made by an expert with a surgical view of the mitral annulus on excised porcine hearts using an electromagnetically tracked pointer. In the former study, the algorithm was statistically indistinguishable from the best performing expert (p=0.85) and had an average RMS difference of 1.81+/-0.78 mm to the expert average. In the latter, the average RMS difference between the algorithm's annulus and the electromagnetically tracked points across six hearts was 1.19+/-0.17 mm .