Interferon gamma protects against hepatic tumor growth in rats by increasing Kupffer cell tumoricidal activity

An increasing number of hepatic resections are being performed as potentially curative surgery for malignant liver neoplasms. Hepatectomy and subsequent liver regeneration produce a local environment that enhances growth of microscopic residual tumor. To determine if pretreatment with murine interferon gamma (IFN-gamma) can protect against such enhanced tumor growth, Buffalo rats were randomized to receive a 3-day treatment of IFN-gamma (50,000 U/qD intraperitoneally) or saline. Groups then underwent intrasplenic injection of 10(6) Morris hepatoma cells, followed 1 hour later by sham (control) or partial hepatectomy (PH) of 70%. PH significantly enhanced tumor growth within the liver (control, 8 +/- 3 nodules per liver; PH, 73 +/- 12 nodules per liver; P < .001). This enhancement was attenuated by prior administration of IFN-gamma IFN-gamma/PH, 16 +/- 3; P < .001 vs. PH). Growth factor release and liver regeneration were not affected significantly by pretreatment with IFN-gamma. The effect of IFN-gamma on tumor growth is associated with a significant enhancement of Kupffer cell (KC)-mediated tumoricidal activity (percentage of specific lysis, 55 +/- 10% control, 78 +/- 11% IFN-gamma, P < .01) but not lymphocyte-mediated tumoricidal activity. Because microscopic residual disease may be present after hepatectomies for cancer, IFN-gamma may be useful agent in retarding growth of residual tumors.     

Reliability of A Tree Network

This paper presents a mathematical model for computing the reliability of a system with redundant components in a tree configuration. This model is quite general and can be applied to any system representable by the appropriate tree. A typical example is cited. A computer program that computes reliability of a system with a tree configuration up to n stages is also presented in the Appendix.     

Optimal discrete-time control system with cost for observation

The problem of how to select the total number and the spacings of the observations optimally when a constant cost is incurred for each observation taken is discussed. Approximate expressions for the criterion function with a fixed number of observations are obtained and are used to determine the optimal total number of observations. For a class of multidimensional systems with a dominant eigenvalue, the problem is shown to reduce to that for scalar systems. Detailed discussion is then carded out for scalar systems including some sensitivity study.     

Strained n-Channel Transistors With Silicon Source and Drain Regions and Embedded Silicon/Germanium as Strain-Transfer Structure

We report the demonstration of 55 nm gate length strained n-channel field-effect transistors (n-FETs) having an embedded Si_1-xGe_x structure that is beneath the Si channel region and which acts as a strain-transfer structure (STS). The Si_1-xGe_x STS has lattice interactions with both the silicon source and drain regions and with the overlying Si channel region. This effectively results in a transfer of lateral tensile strain to the Si channel region for electron mobility enhancement. The mechanism of strain transfer is explained. Significant drive current I_on enhancement of 18% at a fixed off-state leakage I_off of 100 nA/mum is achieved, which is attributed to the strain-induced mobility enhancement. Furthermore, continuous downsizing of transistors leads to higher I_on enhancement in the strained n-FETs, which is consistent with the increasing transconductance G_m improvement when the gate length is reduced.     

Advances and Challenges with Data Broadcasting in Wireless Mesh Networks

Wireless mesh networks have become a promising means to provide low-cost broadband access. Many WMN applications require broadcasting data (IPTV etc.) over the WMN. This article studies how efficient data broadcast, measured in terms of broadcast latency, can be realized by exploiting two features of WMNs: the use of multiple transmission rates at the link layer and the use of multiple radio interfaces on each node. We demonstrate that by exploiting these features, broadcast latency can be reduced severalfold compared to the current default practice in wireless LANs of using the lowest transmission rate for broadcast traffic. We also discuss two important insights we have gained from our investigation. First, we find that when multiple radio interfaces are used, a channel assignment algorithm designed for unicast traffic may often perform poorly for broadcast flows. Second, we find that the efficiency of a transmission rate for reducing broadcast latency can be reasonably predicted by the product of the transmission rate and its coverage area.     

The Principles of Eliminating Pulsating Torque in Current Source Inverter Induction Motor Systems

The problem of reducing the pulsating torque in current source inverter induction motor systems is investigated. Two typical approaches presented in recent publications are analyzed by making clear 1) the correlation among the current harmonics and the torque harmonics, and 2) the conceptual contradiction existing between these two approaches. By synthesizing the analyzed results, fundamental principles for treating the current harmonics and torque harmonics are established. In addition, the method for evaluating the degree of torque ripple is described, along with a proposed criterion for torque ripple content. By applying this criterion to these two approaches, objective estimates of degree of torque pulsations, which were unfeasible so far, are now made possible.     

Residual models and stochastic realization in state-space identification

This paper presents theory and algorithms for validation in system identification of state-space models from finite input-output sequences in a subspace model identification framework. Our formulation includes the problem of rank-deficient residual covariance matrices, a case which is encountered in applications with mixed stochastic-deterministic input-output properties as well as for cases where outputs are linearly dependent. Similar to the case of prediction-error identification, it is shown that the resulting model can be decomposed into an input-output model and a stochastic innovations model. Using the Riccati equation, we have designed a procedure to provide a reduced-order stochastic model that is minimal with respect to system order as well as the number of stochastic inputs thereby avoiding several problems appearing in standard application of stochastic realization to the model validation problem.