Decompression Studies Using Ultrasonic Imaging of Bubbles

Single bubbles ranging down in size to under 1 ?m (less than capillary size) can be noticed, localized, and measured in ultrasonic images of intact subjects using 7.5 MHz ultrasound for which the wavelength is 200 ?m. Subjects included humans, fish, and guinea pigs. A combined brightness modulation and deflection display was most effective. Bubble reality during decompression and association with symptoms has been demonstrated, as have asymptomatic bubbles, a tendency for bubble formation in fat, recompression bubble showers, and decompression without diving tables. In guinea pigs there were age and male-female differences in susceptibility. Adjacent tissue inert gas pressure, supersaturation, and time constant can be measured by adjusting ambient pressure until bubbles cease to grow. Present data generally favor a supersaturation rather than a phase equilibration model for bends onset. An increase in allowable supersaturation was observed when decompression was to altitude rather than to sea level. Goldfish were seen to survive bubbling that would kill the mammals studied, and some simultaneous observations by light and sound were made in transparent fish.     

Modeling the detachment and transport of bubbles from nucleation sites in small vessels

Decompression sickness is known to be due to the formation of bubbles in the body as a result of decompression. It is likely that these bubbles form from pre-existing nuclei, which, for bubbles in the bloodstream, are thought to be housed within blood vessel walls. Gas pockets emerging from these sites will be subject to forces due to blood flow, a portion of the gas eventually being swept away to form a free bubble in the bloodstream. These continue to grow and may grow to similar dimensions to the vessel, developing into elongated "gas plugs," potentially occluding the flow. In this correspondence, we derive a simple model to investigate whether this vessel occlusion is a serious concern.     

基于哈特曼原理的两相流气相参数研究北大核心CSCD

本文提出哈特曼光线追踪的方法来测量气液两相流的气相参数,并进行了理论和实验研究。首先,采用哈特曼模板获得阵列光束,通过模拟追踪光线在气液两相流中的传播过程,研究出射光线与两相流中气泡尺寸、位置等参数之间的关系,其次,建立BP神经网络模型来实现气泡参数的准确反演,仿真结果表明,气泡定位相对误差在7%以内,气泡粒径的相对误差在±4%以内。在此基础上搭建了实验系统,以已知大小的透明颗粒在垂直管道沉降模拟单个气相通过管道的过程,进行了实验研究,结果表明气泡粒径的相对误差可控制在±6%以内。     

High Pressure State Simulation Studies as an Aid to Understanding Diving Problems

Some of the earliest biological system models used to guide the affairs of man were employed to avoid the ``bends' in diving. A brief discussion of decompression sickness, as it can affect tunnel workers, airplane pilots, or divers, is given, along with an analog computer configuration to represent the situation. The configuration itself has proved helpful in aiding engineers to understand some of the mechanisms involved, and the recordings that result seem helpful in supplying to physiologists and divers a feeling for the probable effect of a change in circumstances associated with a proposed dive. The effect of changing a gas mixture or changing the time course of a dive is readily visualized, for example, as are the results of using a continuously variable gas mixture and continuous ascent for minimum decompression time.     

Cross-entropy minimization given fully decomposable subset and aggregate constraints (Corresp.)

The principle of maximum entropy and the principle of minimum cross-entropy (minimum directed divergence, minimum discrimination information) have been applied recently to problems in queuing theory and computer-system performance modeling. These information-theoretic principles estimate probability distributions based on information in the form of known expected values. In the case of queuing theory and computer-system modeling, the known expected values arise from rate balance equations. This correspondence concerns situations in which the system state probabilities decompose into disjoint subsets and in which the known expected values are either expectations conditional on a specific subset or expectations involving aggregate subset probabilities. New properties of minimum cross-entropy distributions are derived and an efficient method of computing these distributions is derived. Computational examples are included. In the case of queuing theory and computer-system modeling, the disjoint subsets correspond to internal device states, and the aggregate probabilities correspond to overall device states. The results here apply when one has both rate balance equations for device equilibrium involving internal device state probabilities, as well as rate balance equations for system equilibrium involving aggregate device state probabilities.     

A passive protected self-healing mesh network architecture andapplications

The self-healing mesh network architecture using digital cross-connect systems (DCSs) is a crucial part of an integrated network restoration system. The conventional DCS self-healing networks using logical channel protection may require a large amount of spare capacity for network components (such as DCSs) and may not restore services fast enough (e.g., within 2 s). The authors propose a passive protected DCS self-healing network (PPDSHN) architecture using a passive protection cross-connect network for network protection. For the PPDSHN architecture, network restoration is performed in the optical domain and is controlled by electronic working DCS systems. Some case studies have suggested that the proposed PPDSHN architecture may restore services within a two-second objective with less equipment cost than the conventional DCS self-healing network architecture in high-demand metropolitan areas for local exchange carrier networks. The proposed PPDSHN architecture may apply to not only the centralized and distributed control DCS network architectures, but also asynchronous, SONET and ATM DCS networks. Transparency of line rates and transmission formats makes the PPDSHN network even more attractive when network evolution is a key concern of network planning     

Effect of HF discharge structure on etch nonuniformity in plasma-chemical reactor

Numeric simulation is used to study the effect of the high-frequency (HF) discharge structure on the process of plasma-chemical etching of silicon in a mixture of CF₄/O₂. The calculations are carried out using a mathematical model of a nonisothermal reactor, in which the gas mixture motion was described with the help of equations of multicomponent hydrodynamics, taking into account the convection-diffusion transport of individual mixture components. In order to determine the characteristics of low-temperature plasma the hydrodynamic model of axial-symmetric HF discharge was used, including the continuity equations for electrons and positive ions, the energy balance equation for electrons, and the Poisson equation for electric potential. The effect of the HF discharge structure on the generation and mass exchange of active particles in a plasma-chemical etching reactor is studied.     

Intraocular Nd:YAG laser surgery: laser-tissue interaction, damagerange, and reduction of collateral effects

The damage mechanisms of intraocular Nd:YAG laser surgery and their respective damage ranges were investigated in vitro using bovine cornea specimens as a model tissue. The main damage mechanisms are plasma formation and expansion, emission of acoustic transients, and cavitation with jet formation. When a sequence of laser pulses is applied, the interaction of the acoustic transients with gas bubbles remaining from preceding laser exposures is also important. To distinguish the effects caused by the different physical mechanisms, laser pulses were aimed directly onto the corneal endothelium, through the cornea, and parallel to the cornea at various distances. Simultaneously, the cavitation bubble size was determined. The damage range of the acoustic transients produced by a 4 mJ laser pulse is several millimeters, when they can interact with small gas bubbles attached to the corneal endothelium     

Specification and analysis of power-managed systems

Dynamic power management encompasses several techniques for reducing energy dissipation in electronic systems by selective slowdown or shutdown of components. We present a theoretical framework for explaining and classifying different approaches to power management. Within this framework, we model power-manageable components, workloads, and controllers as discrete-event systems (DESs). The structure of these DESs is specified in terms of physical states (representing operation modes) and events (triggering state transitions), while system behavior is specified in terms of next-event and next-state functions. In particular, nondeterministic next-event and next-state functions are modeled by conditional probability distributions, according to generalized semi-Markov processes (GSMPs). The modeling framework provides a general denotational model for system specification and a rigorous execution semantics that enables event-driven simulation. We introduce a modeling framework, built on top of MathWork's Simulink, supporting the specification and execution of our model. In particular, we present templates for the Simulink simulator to execute GSMP models, and we describe how to use such templates for specifying, analyzing, and optimizing dynamic power-managed systems. Finally, we demonstrate the expressive power and versatility of the proposed approach by using the modeling framework and the simulator for the analysis of representative real-life case studies, including the Intel Xscale processor architecture, a multitasking real-time system, and a sensor network.     

Quantification of Bubbles Formed in Animals and Man During Decompression

Bubbles that form in the tissues and bloodstreams of animals and humans undergoing a compression/decompression sequence are considered precursors to symptoms of decompression sickness. A prevalent method used to monitor these bubbles is to ensonify the pulmonary artery or inferior vena cava with ultrasound and listen for Doppler shifted signals in the reflected and scattered sound.     

Nonempirical simulation of chemical deposition of silicon nitride films in CVD reactors

This work is devoted to the atomistic simulation of chemical vapor deposition (CVD) of thin silicon nitride films from the mixture of dichlorosilane (DCS) and ammonia in CVD reactors. The earlier developed chemical mechanism is substantially extended by including the reactions of catalytic decomposition of DCS, and a self-consistent atomistic model of a CVD process is developed. An extended chemical mechanism is constructed and analyzed that allows one to adequately describe kinetic processes in a gas phase within the ranges of temperature, pressure, and the DCS: NH₃ ratio of original reactants, that are characteristic of silicon nitride deposition. An effective kinetic model is developed that involves the calculation of the rate constants and the concentrations of the gas mixture components. A thermodynamic analysis of the surface coverage by various chemisorbed groups is carried out, and equilibrium surface concentrations are obtained for the main chemisorbed groups. Practically significant conclusions are made about the character of the deposition process and, in particular, about the role of the extended chemical mechanism.     

Effects of sample geometry and electrode configuration on measured electrical resistivity of skeletal muscle

Over the past 40 years, researchers from a variety of scientific backgrounds have been using Rush's equations to analyze results of their electrophysiological studies. A lack of understanding of the constraints and the domain in which these equations are valid, often results in situations in which it is challenging to evaluate and compare results obtained by different investigators. In this paper, we reanalyzed the conditions for which Rush's equations were derived, and using mathematical modeling, computer simulation and in vitro measurements, we delineated areas of their appropriate application. Our studies showed that both sample geometry and test electrode configuration affect the measured tissue electrical resistivities: 1) The sample can be considered semi-infinite only if its dimensions are > 50 inter-electrode separation distances (IESD), and thickness > 2.5 IESD, 2) smaller sample sizes increase the transversally measured resistivity, 3) semi-infinite samples thinner than 2.5 IESD, and samples tested with needle electrodes demonstrate reduced anisotropy, and 4) when surface-spot electrodes are longitudinally aligned, as the IESD/tissue thickness ratio decreases, the measured resistivity increases. Our conclusion is that in most experimental situations, it is necessary to use modeling techniques to decouple the electrode configuration/sample geometry influence from the measured tissue resistivity.     

A framework for modeling spatial node density in waypoint-based mobility

User mobility is of critical importance when designing mobile networks. In particular, "waypoint" mobility has been widely used as a simple way to describe how humans move. This paper introduces the first modeling framework to model waypoint-based mobility. The proposed framework is simple, yet general enough to model any waypoint-based mobility regimes. It employs first order ordinary differential equations to model the spatial density of participating nodes as a function of (1) the probability of moving between two locations within the geographic region under consideration, and (2) the rate at which nodes leave their current location. We validate our model against real user mobility recorded in GPS traces collected in three different scenarios. Moreover, we show that our modeling framework can be used to analyze the steady-state behavior of spatial node density resulting from a number of synthetic waypoint-based mobility regimes, including the widely used Random Waypoint model. Another contribution of the proposed framework is to show that using the well-known preferential attachment principle to model human mobility exhibits behavior similar to random mobility, where the original spatial node density distribution is not preserved. Finally, as an example application of our framework, we discuss using it to generate steady-state node density distributions to prime mobile network simulations.     

A physiologic model of capillary-tissue exchange for dynamic contrast-enhanced imaging of tumor microcirculation

We present a multiple compartment, mammillary distributed-parameter model for capillary-tissue exchange, which can be implemented with dynamic contrast-enhanced imaging to study kinetic heterogeneity in tumors. The proposed n-compartment model consists of a vascular distributed-parameter compartment in direct exchange with a number (n - 1) of interstitial compartments. It is applied to a prostate tumor case study to illustrate the possible co-existence of two kinetically distinct compartments in the tumor, and the estimation of useful physiological parameters (such as perfusion, mean transit time, fractional volumes, and transfer and rate constants) associated with tissue microcirculation. The present model exhibits the convenient property of a separable impulse residue response function in time domain, which can be used to provide further insights and understanding on the physiological basis of tissue enhancement parameters commonly used for correlation studies with tumor histological diagnosis.     

领域化业务构件的数据模型可执行语义研究和实现

从企业应用角度出发,为实现快速构建企业信息系统以及提高系统可重用性,提出了一种领域化业务构件描述思路。同时为使开发的信息系统实现企业知识的重用和和共享,方便企业数据交换和集成,将可执行语义建模方法应用到业务构件的业务数据模型中,具体实现参考了语义Web的描述框架。     

A two-dimensional nonisothermal finite element simulation of laserdiodes

A fully self-consistent nonisothermal, two-dimensional model of a semiconductor laser device is presented. The model consists of the simultaneous solution of the electrical equations (Poisson's and electron and hole continuity equations), along with the wave equation, photon rate equation, and thermal conduction equation. An analysis is presented for an AlGaAs-GaAs ridge laser diode structure using this model as a representative example. The results agree well with available experimental data. A comparison of the results between isothermal and nonisothermal simulations shows that the nonisothermal case has a higher threshold current and lower quantum efficiency than the idealized isothermal model. The result was found to depend critically on the thermal exchange boundary condition of the simulated device, demonstrating the importance of considering thermal exchange in the design of laser diodes     

利用DCS进行自动化生产

利用DCS控制工厂进行自动化作业,完成对备煤筛焦、炼焦、煤气净化等过程进行实时监测,并对主要的过程变量实现自动控制。在此基础上对产品质量影响很大的净化生产车间建立了稳态参数优化模型,并获得煤气净化的稳态参数优化模型参数。在这个优化模型结果的指导下,使焦化厂的产品质量大幅度的提高。     

A statistical multiscale framework for Poisson inverse problems

This paper describes a statistical multiscale modeling and analysis framework for linear inverse problems involving Poisson data. The framework itself is founded upon a multiscale analysis associated with recursive partitioning of the underlying intensity, a corresponding multiscale factorization of the likelihood (induced by this analysis), and a choice of prior probability distribution made to match this factorization by modeling the “splits” in the underlying partition. The class of priors used here has the interesting feature that the “noninformative” member yields the traditional maximum-likelihood solution; other choices are made to reflect prior belief as to the smoothness of the unknown intensity. Adopting the expectation-maximization (EM) algorithm for use in computing the maximum a posteriori (MAP) estimate corresponding to our model, we find that our model permits remarkably simple, closed-form expressions for the EM update equations. The behavior of our EM algorithm is examined, and it is shown that convergence to the global MAP estimate can be guaranteed. Applications in emission computed tomography and astronomical energy spectral analysis demonstrate the potential of the new approach     

Integrated physics-oriented statistical modeling, simulation, andoptimization [MESFETs]

Physics-based modeling of MESFETs is addressed from the point of view of efficient simulation, accurate behavior prediction and robust parameter extraction. A novel integration of a large-signal physics-based model into the harmonic balance equations for simulation of nonlinear circuits, involving an efficient Newton update, is presented and exploited in a gradient-based FAST (feasible adjoint sensitivity technique) circuit optimization technique. For yield-driven MMIC design a relevant physics-based statistical modeling methodology is presented. Quadratic approximation of responses and gradients suitable for yield optimization is discussed. The authors verify their theoretical contributions and exemplify their computational results using built-in and user-programmable modeling capabilities of the CAE systems OSA90/hope and HarPE. Results of device modeling using a field-theoretic nonlinear device simulator are reported