A novel computational approach for simultaneous tracking and feature extraction of C. elegans populations in fluid environments.

The nematode Caenorhabditis elegans (C. elegans) is a genetic model widely used to dissect conserved basic biological mechanisms of development and nervous system function. C. elegans locomotion is under complex neuronal regulation and is impacted by genetic and environmental factors; thus, its analysis is expected to shed light on how genetic, environmental, and pathophysiological processes control behavior. To date, computer-based approaches have been used for analysis of C. elegans locomotion; however, none of these is both high resolution and high throughput. We used computer vision methods to develop a novel automated approach for analyzing the C. elegans locomotion. Our method provides information on the position, trajectory, and body shape during locomotion and is designed to efficiently track multiple animals (C. elegans) in cluttered images and under lighting variations. We used this method to describe in detail C. elegans movement in liquid for the first time and to analyze six unc-8, one mec-4, and one odr-1 mutants. We report features of nematode swimming not previously noted and show that our method detects differences in the swimming profile of mutants that appear at first glance similar.     

A computational model for tracking subsurface tissue deformationduring stereotactic neurosurgery

Recent advances in the field of sterotactic neurosurgery have made it possible to coregister preoperative computed tomography (CT) and magnetic resonance (MR) images with instrument locations in the operating field. However, accounting for intraoperative movement of brain tissue remains a challenging problem. While intraoperative CT and MR scanners record concurrent tissue motion, there is motivation to develop methodologies which would be significantly lower in cost and more widely available. The approach the authors present is a computational model of brain tissue deformation that could be used in conjunction with a limited amount of concurrently obtained operative data to estimate subsurface tissue motion. Specifically, the authors report on the initial development of a finite element model of brain tissue adapted from consolidation theory. Validations of the computational mathematics in two and three dimensions are shown with errors of 1%-2% for the discretizations used. Experience with the computational strategy for estimating surgically induced brain tissue motion in vivo is also presented. While the predicted tissue displacements differ from measured values by about 15%, they suggest that exploiting a physics-based computational framework for updating preoperative imaging databases during the course of surgery has considerable merit. However, additional model and computational developments are needed before this approach can become a clinical reality     

SDR receiver computational model for application in power control

Software-defined radio (SDR) permits dynamic switches of the employed radio access technology (RAT), over-the-air (OTA) software updates, software and hardware reuse. This extended flexibility comes at the price of a higher computing complexity and, in particular, the energy consumption at the receiver. The analysis of the computational profile of signal processing algorithms is of great importance in SDR for understanding the implication on the energy consumption. Several signal processing algorithms show a different profile as a function of the signal quality perceived at the receiver antenna. Therefore, power control policies have an implication on the computational performance of SDR receivers. Understanding the behaviour of these algorithms allows trading transmitted power against receiver energy consumption. This paper presents a model for characterizing the computational profile of Turbo and LDPC decoders and demonstrates is applicability in existing power control strategies.     

A novel computational method for predicting the transmembrane structure of G-protein coupled receptors: application to human C5aR and C3aR

A novel algorithm was applied to the sequences of bacteriorhodopsin (BRh), of rhodopsin (Rh), and of the two human anaphylatoxin receptors, C5a-receptor (hC5aR) and C3a-receptor (hC3aR), that predicts their transmembrane domains (TMD) according to energy criteria alone, on the basis of their sequences and a template structure for each. Two consecutive criteria were applied for the predictions: the first is hydrophobicity of a sequence of residues, which determines the candidate stretches of residues that form one of the transmembrane helices. The second criterion is an energy function composed of inter residue contact energies, of hydrophobic contributions due to membrane exposure and of the interactions of a few residues with the phospholipid head groups. The sequence of candidate residues for each helix is longer than that of the template, and is finally determined by threading each of the candidate stretches on each of the template helices and evaluating the energy for all possible configurations. Contact energies between residues were taken from a database (Miyazawa S and Jernigan RL (1996) J Mol Biol 256 623-44). The algorithm predicts well the TMD structure of BRh based on its own template, and the TMD structure of Rh conforms well with the model of Baldwin et al (Baldwin JM Schertler GFX and Unger VM (1997) J Biol Chem 272 144-64). Results for the construction of the TMD of hC5aR and hC3aR were compared, employing the template structure of Rh. Most of the results for these receptors are in accord with alignments and with mutation experiments on hC5aR and hC3aR. The predictions may serve as a basis for future mutagenesis experiments of these receptors.     

A computational model of the electromagnetic heating of biological tissue with application to hyperthermic cancer therapy

To investigate the potentialities of hyperthermia as a cancer therapy, computer simulations have been performed. This simulation consists of two tuccessive steps. First, the heat generated in a distribution of biological tissue when irradiated by a source of electromagnetic radiation is computed. The mathematical tool for determining the disbution of generated heat is the domain-integral-equation technique. This technique enables us to determine in a body with arbitrary distribution of permittivity and conductivity the electromagnetic field due to prescribed sources. The integral equation is solved numerically by an iterative minimization of the integrated square error. From the computed distribution of generated heat, the temperature distribution follows by solving numerically the pertaining heat transfer problem. The relevant differential equation together with initial and boundary conditions is solved numerically using a finite-element technique in space and a finite-difference technique in time. Numerical results pertaining to the temperature distribution in a model of the human pelvis are presented.     

A computational skin model: fold and wrinkle formation

This paper presents a computational model for studying the mechanical properties of skin with aging. In particular, attention is given to the folding capacity of skin, which may be manifested as wrinkles. The simulation provides visual results demonstrating the form and density of folds under the various conditions. This can help in the consideration of proper measures for a cosmetic product for the skin.     

A computational multiresolution BOLD fMRI model

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is a widely used method for brain mapping. BOLD fMRI signal detection is based on an intravoxel dephasing mechanism. This model involves bulk nuclear spin precession in a BOLD-induced inhomogeneous magnetic field within a millimeter-resolution voxel, that is, BOLD signal formation spans a huge spatial scale range from Angstrom to millimeter. In this letter, we present a computational model for multiresolution BOLD fMRI simulation, which consists of partitioning the nuclear spin pool into spin packets at a mesoscopic scale (～10(-6) m), and calculating multiresolution voxel signals by grouping spin packets at a macroscopic scale range (10(-5) to 10(-3) m). Under a small-angle approximation, we find that the BOLD signal intensity is related to its phase counterpart (or BOLD fieldmap) across two spatial resolution levels.     

A.C. small-signal model for bipolar transistors in saturation

A modified charge-control theory is used to derive a small-signal equivalent circuit which is valid in saturation. From this circuit can be deduced the fT(Ic) and the transconductance gfb(Ie), for example, which are compared with measurements. A short discussion of the results is given.     

Using Articulated Models for Tracking Multiple C. elegans in Physical Contact

We present a method for tracking and distinguishing multiple C. elegans in a video sequence, including when they are in physical contact with one another. The worms are modeled with an articulated model composed of rectangular blocks, arranged in a deformable configuration represented by a spring-like connection between adjacent parts. Dynamic programming is applied to reduce the computational complexity of the matching process. Our method makes it possible to identify two worms correctly before and after they touch each other, and to find the body poses for further feature extraction. All joint points in our model can be also considered to be the pseudo skeleton points of the worm body. It solves the problem that a previously presented morphological skeleton-based reversal detection algorithm fails when two worms touch each other. The algorithm has many applications in the study of physical interactions between C. elegans.     

Automatic tracking of individual fluorescence particles: application to the study of chromosome dynamics.

We present a new, robust, computational procedure for tracking fluorescent markers in time-lapse microscopy. The algorithm is optimized for finding the time-trajectory of single particles in very noisy dynamic (two- or three-dimensional) image sequences. It proceeds in three steps. First, the images are aligned to compensate for the movement of the biological structure under investigation. Second, the particle's signature is enhanced by applying a Mexican hat filter, which we show to be the optimal detector of a Gaussian-like spot in 1/omega2 noise. Finally, the optimal trajectory of the particle is extracted by applying a dynamic programming optimization procedure. We have used this software, which is implemented as a Java plug-in for the public-domain ImageJ software, to track the movement of chromosomal loci within nuclei of budding yeast cells. Besides reducing trajectory analysis time by several 100-fold, we achieve high reproducibility and accuracy of tracking. The application of the method to yeast chromatin dynamics reveals different classes of constraints on mobility of telomeres, reflecting differences in nuclear envelope association. The generic nature of the software allows application to a variety of similar biological imaging tasks that require the extraction and quantitation of a moving particle's trajectory.     

Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots.

We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.     

Validation and application of a computational model for wrist and hand movements using surface markers

A kinematic model is presented based on surface marker placement generating wrist, metacarpal arch, fingers and thumb movements. Standard calculations are used throughout the model and then applied to the specified marker placement. A static trial involving eight unimpaired participants was carried out to assess inter-rater reliability. The standard deviations across the data were comparable to manual goniometers. In addition, a test-retest trial of ten unimpaired participants is also reported to illustrate the variability of movement at the wrist joint, metacarpal arch, and index finger as an example of model output when repeating the same task many times. Light and heavyweight versions of the tasks are assessed and characteristics of individual movement strategies presented. The participant trial showed moderate correlation in radial/ulnar deviation of the wrist (r = 0.65), and strong correlation in both metacarpal arch joints (r = 0.75 and r = 0.85), the MCP (r = 0.79), and PIP (r = 0.87) joints of the index finger. The results indicate that individuals use repeated strategies of movement when lifting light and heavyweight versions of the same object, but showed no obvious repeated pattern of movement across the population.     

A computational framework for the statistical analysis of cardiac diffusion tensors: application to a small database of canine hearts

We propose a unified computational framework to build a statistical atlas of the cardiac fiber architecture from diffusion tensor magnetic resonance images (DT-MRIs). We apply this framework to a small database of nine ex vivo canine hearts. An average cardiac fiber architecture and a measure of its variability are computed using most recent advances in diffusion tensor statistics. This statistical analysis confirms the already established good stability of the fiber orientations and a higher variability of the laminar sheet orientations within a given species. The statistical comparison between the canine atlas and a standard human cardiac DT-MRI shows a better stability of the fiber orientations than their laminar sheet orientations between the two species. The proposed computational framework can be applied to larger databases of cardiac DT-MRIs from various species to better establish intraspecies and interspecies statistics on the anatomical structure of cardiac fibers. This information will be useful to guide the adjustment of average fiber models onto specific patients from in vivo anatomical imaging modalities.     

Filament behavior in a computational model of ventricular fibrillation in the canine heart

The aim of this paper was to quantify the behavior of filaments in a computational model of re-entrant ventricular fibrillation. We simulated cardiac activation in an anisotropic monodomain with excitation described by the Fenton-Karma model with Beeler-Reuter restitution, and geometry by the Auckland canine ventricle. We initiated re-entry in the left and right ventricular free walls, as well as the septum. The number of filaments increased during the first 1.5 s before reaching a plateau with a mean value of about 36 in each simulation. Most re-entrant filaments were between 10 and 20 mm long. The proportion of filaments touching the epicardial surface was 65%, but most of these were visible for much less than one period of re-entry. This paper shows that useful information about filament dynamics can be gleaned from models of fibrillation in complex geometries, and suggests that the interplay of filament creation and destruction may offer a target for antifibrillatory therapy.     

一种认知跟踪雷达LFM波形库建立方法

认知雷达是下一代雷达发展的方向之一。在对认知跟踪反馈环进行分析的基础上,提出了一种线性调频( LFM)信号波形库的建立方法。在应用交互多模型跟踪机动目标的背景下,通过所建的波形库对发射波形进行实时调用,达到减小跟踪误差的目的。研究了具有不同调频率参数与Fr-FT旋转角度组合的不同数量LFM信号波形库的建立,以最小化模型选择不确定性为目的推导波形选择准则,得到了不同的波形选择策略。仿真验证分析其跟踪精度可以看出,构建具有一定数量LFM波形的波形库可以提高认知跟踪雷达的性能。     

一种认知跟踪雷达LFM波形库建立方法

认知雷达是下一代雷达发展的方向之一。在对认知跟踪反馈环进行分析的基础上,提出了一种线性调频(LFM)信号波形库的建立方法。在应用交互多模型跟踪机动目标的背景下,通过所建的波形库对发射波形进行实时调用,达到减小跟踪误差的目的。研究了具有不同调频率参数与FrFT旋转角度组合的不同数量LFM信号波形库的建立,以最小化模型选择不确定性为目的推导波形选择准则,得到了不同的波形选择策略。仿真验证分析其跟踪精度可以看出,构建具有一定数量LFM波形的波形库可以提高认知跟踪雷达的性能。     

A linear rate control model for better target buffer level tracking in H.264

An improved rate control scheme with better buffer level tracking and more accurate mean absolute difference (MAD) prediction for H.264 video encoding is proposed in this work. Compared to the existing H.264 rate control scheme, the proposed scheme gives better buffer regulation with improved peak signal-to-noise ratio for basic unit level rate control. The bits required for encoding header information account for a significantly high percentage of the total bits, especially at lower bit rate and for low motion sequences. A linear relation between coded mean absolute difference and header bits is proposed for achieving effective rate control. The proposed scheme estimates the mean absolute difference adaptively from temporally colocated regions and INTER16x16 mode decision process. The estimated mean absolute difference is then used for calculating the quantization parameter for better target matching. A new linear rate control model is proposed, which works well especially for low motion sequences. The experimental results show that the proposed improvement in rate control algorithm significantly reduces the difference between actual and target buffer level while improving the quality of encoded video sequences.     

用于线虫药物筛选的微流控梯度芯片和自动化平台

作为一种在微米尺度操作流体的技术,微流控芯片具有反应体系小、通量高、自动化且操作灵活等优势,被越来越多地应用于细胞和微米尺度生物的研究中。秀丽隐杆线虫作为一种重要的模式生物被广泛地用于神经生物学、衰老及发育和药物筛选等研究中。提出了一种用于研究线虫和环境毒素相互作用的微流控自动化平台,该平台集成了基于微振荡原理的快速梯度形成的微流控芯片、自动化控制系统及基于OpenCV的线虫长度及摆动频率估计的自动化图像分析软件。通过染料和荧光实验验证了基于振荡原理的快速梯度形成芯片,该芯片可以在7 min内形成线性浓度梯度,并通过该芯片和平台验证了线性浓度梯度的双氧水对秀丽隐杆线虫活性的影响。     

A composite model of product development effectiveness: application to services

This paper explores the extent to which an enlarged, generic version of a "composite" model of concurrent product development previously tested for goods industries also applies to services. The model is comprised of four types of building blocks commonly used in theories of organization design. The operating core of the model includes a troika of practice sets dealing with the organization of cross-functional teams, discipline by structured development processes, and the use of enabling tools/technologies. Concurrent strategy focuses core operations on fast, reiterative cycles of product development. The model postulates that synergy among its constructs have an impact on product development effectiveness. This postulate is tested by multiple regression analysis of 62 large service enterprises in the New York area. All four components of the model had main effects on performance measured as time compression and cost reduction in product development, signature indicators of the effectiveness of concurrent methods of product development. Interaction effects were observed among the constructs of strategy, organization, and process, which suggest synergies. However, tools/technologies lacked significant interactions. With this exception, the results for services parallel those of other studies of goods industries. These findings suggest that concurrent methods of product development are robust, as well as reliable. A generic model of product development is important for managing innovation because goods and services are increasingly commingled in many enterprises and sold as a bundle. Thus, the four building blocks of the model are important for managers to consider deploying in synergistic ways to speed time to market and achieve cost efficiencies.     

高度机动目标的改进CS-Jerk模型

针对高度机动目标跟踪问题,通过对Jerk模型的分析,借鉴"当前"统计的思想,采用截断正态分布来表征目标机动加速度变化率(Jerk)特性,利用Jerk均值与方差之间的关系自适应调整过程噪声协方差矩阵,提出一种改进的"当前"统计Jerk模型(MCS-Jerk model);并通过理论分析指出了Jerk模型及其跟踪算法的缺陷以及改进的MCS-Jerk模型算法的有效性;仿真结果表明改进的模型及跟踪算法的高机动目标跟踪性能明显优于基于Jerk模型的跟踪算法。