Real-time production scheduling of an automated cardline

In this paper, we describe a flow model of an automated-printed circuit card assembly line at the International Business Machines Corporation (IBM) plant at Tucson, Arizona. We use a simulation based on this model as a test bed to discuss the performance of a hierarchical scheduling policy described in [3]. We compare this with other policies for loading parts into a flexible manufacturing system. We demonstrate that the hierarchical strategy is effective in meeting production requirements (both total volume and balance among part types) while limiting average work-in-process (WIP). This is a consequence of the feedback nature of the policy. Hedging (i.e. building up buffer stock) compensates for machine failures, thus resulting in high production percentages. The work-in-process (WIP) is low, as the policy reduces internal queues by respecting the capacity constraints of the system at every instant.     

多类型复发事件间隔时间下可加危险率模型

在许多的生物医学和工程研究中,多类型复发事件的间隔时间数据是很常见的。众所周知,比例危险率模型在一些情况下不能很好拟合生存数据。本文,在多类型复发事件的间隔时间数据下,我们利用可加危险率模型来研究协变量对生存时间的影响程度。我们采用估计方程方法获得回归系数和基准累积危险率函数估计。并且,我们建立了所提估计的渐近分布。     

Modelling large motion events in fMRI studies of patients with epilepsy

EEG-correlated fMRI can provide localisation information on the generators of epileptiform discharges in patients with focal epilepsy. To increase the technique's clinical potential, it is important to consider ways of optimising the yield of each experiment while minimizing the risk of false-positive activation. Head motion can lead to severe image degradation and result in false-positive activation and is usually worse in patients than in healthy subjects. We performed general linear model fMRI data analysis on simultaneous EEG-fMRI data acquired in 34 cases with focal epilepsy. Signal changes associated with large inter-scan motion events (head jerks) were modelled using modified design matrices that include 'scan nulling' regressors. We evaluated the efficacy of this approach by mapping the proportion of the brain for which F-tests across the additional regressors were significant. In 95% of cases, there was a significant effect of motion in 50% of the brain or greater; for the scan nulling effect, the proportion was 36%; this effect was predominantly in the neocortex. We conclude that careful consideration of the motion-related effects in fMRI studies of patients with epilepsy is essential and that the proposed approach can be effective.     

Extreme events and entropy: A multiple quantile utility model

This paper introduces a multiple quantile utility model of Cumulative Prospect Theory in an ambiguous setting. We show a representation theorem in which a prospect is valued by a composite value function. The composite value function is able to represent asymmetric attitude on extreme events and a rational prudence on ordinary events.     

Order-disorder transition in conflicting dynamics leading to rank-frequency generalized beta distributions

The behavior of rank-ordered distributions of phenomena present in a variety of fields such as biology, sociology, linguistics, finance and geophysics has been a matter of intense research. Often power laws have been encountered; however, their validity tends to hold mainly for an intermediate range of rank values. In a recent publication (Martínez-Mekler et al., 2009 [7]), a generalization of the functional form of the beta distribution has been shown to give excellent fits for many systems of very diverse nature, valid for the whole range of rank values, regardless of whether or not a power law behavior has been previously suggested. Here we give some insight on the significance of the two free parameters which appear as exponents in the functional form, by looking into discrete probabilistic branching processes with conflicting dynamics. We analyze a variety of realizations of these so-called expansion-modification models first introduced by Wentian Li (1989) [10]. We focus our attention on an order-disorder transition we encounter as we vary the modification probability p. We characterize this transition by means of the fitting parameters. Our numerical studies show that one of the fitting exponents is related to the presence of long-range correlations exhibited by power spectrum scale invariance, while the other registers the effect of disordering elements leading to a breakdown of these properties. In the absence of long-range correlations, this parameter is sensitive to the occurrence of unlikely events. We also introduce an approximate calculation scheme that relates this dynamics to multinomial multiplicative processes. A better understanding through these models of the meaning of the generalized beta-fitting exponents may contribute to their potential for identifying and characterizing universality classes.     

A conceptual framework for predicting the toxicity of reactive chemicals: modeling soft electrophilicity

Although the literature is replete with QSAR models developed for many toxic effects caused by reversible chemical interactions, the development of QSARs for the toxic effects of reactive chemicals lacks a consistent approach. While limitations exit, an appropriate starting-point for modeling reactive toxicity is the applicability of the general rules of organic chemical reactions and the association of these reactions to cellular targets of importance in toxicology. The identification of plausible “molecular initiating events” based on covalent reactions with nucleophiles in proteins and DNA provides the unifying concept for a framework for reactive toxicity. This paper outlines the proposed framework for reactive toxicity. Empirical measures of the chemical reactivity of xenobiotics with a model nucleophile (thiol) are used to simulate the relative rates at which a reactive chemical is likely to bind irreversibly to cellular targets. These measures of intrinsic reactivity serve as correlates to a variety of toxic effects; what's more they appear to be more appropriate endpoints for QSAR modeling than the toxicity endpoints themselves.     

超长距离分布式光纤振动传感器的并发事件信号重构方法

针对超长距离分布式振动检测传感器在复杂地表振动环境下性能指标下降的问题,提出了借鉴雷达信号处理技术领域脉冲分选技术的振动信号特征分析提取、分选和融合方案,实现了对并发振动随机混合信号的同源振动的信号分选和事件的恢复重构。对两起和四起并发事件进行了现场测试,传感器检测和报警结果准确。为超长距离分布式光纤振动传感器在复杂地表振动环境下的应用提供了可能。     

Locked nucleic acid/DNA chimeric aptamer probe for tumor diagnosis with improved serum stability and extended imaging window in vivo

As promising molecular probes for in vivo tumor imaging, aptamers without modification remain problematic due to insufficient serum stability and unabiding imaging window. To address this problem, a novel locked nucleic acid (LNA)/DNA chimeric aptamer probe was developed through proper LNA incorporation and supplemented 3′-3′-thymidine (3′-3′-T) capping. TD05, a DNA aptamer against lymphoma Ramos cells, being used as the model, a series of modification strategies were designed and optimized with different positions, numbers and combinations. It was revealed that the combined use of LNA and 3′-3′-T had a synergistic effect, and with the increase of LNA substitution in stem region, the serum stability of TD05 was gradually enhanced while its affinity and specificity were perfectly maintained to Ramos cells. Particularly, TD05.6 with 7-base pair-LNA substitution exhibited the significantly elevated detection stability half-life from ∼0.5 h of TD05 to 5–6 h of TD05.6 for target cells in serum. Moreover, a much slower clearance rate in tumor-bearing mice was also observed for TD05.6, thus leading to the greatly extended tumor imaging window from <150 min of TD05 to >600 min of TD05.6. This strategy might be of great potentials to generate more aptamer probes that are stable and nuclease-resistant for tumor diagnosis in real biological systems.     

Efficiency comparison between mean and log-rank tests for recurrent event time data

Recurrent event time data are common in biomedical follow-up studies, in which a study subject may experience repeated occurrences of an event of interest. In this paper, we evaluate two popular nonparametric tests for recurrent event time data in terms of their relative efficiency. One is the log-rank test for classical survival data and the other a more recently developed nonparametric test based on comparing mean recurrent rates. We show analytically that, somewhat surprisingly, the log-rank test that only makes use of time to the first occurrence could be more efficient than the test for mean occurrence rates that makes use of all available recurrence times, provided that subject-to-subject variation of recurrence times is large. Explicit formula are derived for asymptotic relative efficiencies under the frailty model. The findings are demonstrated via extensive simulations. This work was supported by US National Science Foundation (Grant No. DMS-0504269)