Correlates of colorectal cancer screening compliance and stage of adoption among siblings of individuals with early onset colorectal cancer.

Concepts from the health belief, transtheoretical, and dual process models were used to examine how siblings of individuals diagnosed with colorectal cancer (CRC) before age 56 made decisions about CRC screening. Siblings (N=504) were assessed for CRC screening practices and intentions, pros, cons, processes-of-change, perceived risk of CRC, perceived severity of CRC, preventability of CRC, cancer-related distress, and sibling relationship closeness. Physician and family recommendation and knowledge were also assessed. Fifty-seven percent of participants (n=287) were compliant with CRC screening. Logistic regression indicated that perceived pros and cons, perceived risk, commitment to screening, health care avoidance, and sibling closeness were associated with screening compliance. Physician and family recommendation were also strong correlates. A similar set of factors was associated with stage of adoption of CRC screening. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Couples' Support-Related Communication, Psychological Distress, and Relationship Satisfaction Among Women With Early Stage Breast Cancer.

This study examined associations between couple communication about cancer and psychological distress and relationship satisfaction of women diagnosed with early stage breast cancer. One hundred forty-eight couples completed a videotaped discussion of a cancer-related issue and a general issue. Patients completed measures of psychological distress and relationship satisfaction. Videotapes were coded with the Rapid Marital Interaction Coding System (R. E. Heyman & D. Vivian, 1997). Analyses focused on partner responses to patient self-disclosures. During cancer-issue discussions, patients reported less distress when partners responded to disclosures with reciprocal self-disclosure and humor and when partners were less likely to propose solutions. Fewer links between partner responses to patient self-disclosures and distress were found in general-issue discussions. Results suggest partner responses play a role in women's adaptation to breast cancer. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Nuclear power, coal and energy conservation (with a note on the costs of a nuclear moratorium)

A programming model is used to explore some of the options by which the United States may realistically move away from its present heavy dependence on oil and gas to a more diversified energy economy, based on nuclear power and/or coal. The model incorporates both own- and cross-price elasticities. In this way it allows for price-induced interfuel substitution and price-induced energy conservation.Among the supply options considered are: the direct combustion of coal to generate electricity; the conversion of coal to synthetic fuels; the limited petroleum, natural gas, and shale oil resources; nuclear energy from light water reactors and, later, from fast breeder reactors; hydrogen via electrolysis; and such distant future technical options as central station solar power and fusion (aggregated and described only as “advanced technology”).Each of these energy sources is discussed in terms of its own costs and the probable date of its commercial introduction. We then quantify the sensitivity of the benefits from research and development to assumptions with respect to: the discount rate; the future (undiscovered) domestic resource bases of oil, gas and low-cost uranium; and the cost at which large future supplies of coal can be utilized.Under a plausible set of assumptions (the base case), we find that the present value of the benefits from both the fast breeder and coal-based synthetic fuels well exceeds their anticipated research and development costs. In an optimum mix, the combined benefits would be nearly $50 billion (in 1975 dollars) discounted at 10% annually over the 75-year span of our study, and $450 billion at a 5% annual discount rate. Under the same conditions, we also find that if a nuclear moratorium prohibiting the construction of additional plants throughout the country were to come into effect, the direct cost to the United States economy would be approximately $300 billion at a 10% discount rate and $2500 billion at a 5% rate.     

Minimizing Makespan in Batch Machine Scheduling

We study the scheduling of a set of n jobs, each characterized by a release (arrival) time and a processing time, for a batch processing machine capable of running at most B jobs at a time. We obtain an O(n log n)-time algorithm when B is unbounded. When there are only m distinct release times and the inputs are integers, we obtain an O(n(BR_max)^m-1(2/m)^m-3)-time algorithm where R_max is the difference between the maximum and minimum release times. When there are k distinct processing times and m release times, we obtain an O(n log m + k^k+2 B^k+1 m² log m)-time algorithm. We obtain even better algorithms for m=2 and for k=1. These algorithms improve most of the corresponding previous algorithms for the respective special cases and lead to improved approximation schemes for the general problem.     

On the autopersistence functions and the autopersistence graphs of binary autoregressive time series

The classical autocorrelation function may not be an effective and informative means in revealing the dependence features of a binary time series {y_t}. Recently, the autopersistence functions defined as APF⁰(k) = P(y_t+k = 1 | y_t = 0) and APF¹(k) = P(y_t+k = 1 | y_t = 1), k = 1, 2,…, have been proposed as alternatives to the autocorrelation function for binary time series. In this article we consider the theoretical autopersistence functions and their natural sample analogues, the autopersistence graphs, under a binary autoregressive model framework. Some properties of the autopersistence functions and the asymptotic properties of the autopersistence graphs are discussed. The results have potential application in the modelling of binary time series.     

An exact algorithm for vehicle routing and scheduling problem of free pickup and delivery service in flight ticket sales companies based on set-partitioning model

This paper addresses a vehicle routing and scheduling problem arising in Flight Ticket Sales Companies for the service of free pickup and delivery of airline passengers to the airport. The problem is formulated under the framework of Vehicle Routing Problem with Time Windows (VRPTW), with the objective of minimizing the total operational costs, i.e. fixed start-up costs and variable traveling costs. A 0?C1 mixed integer programming model is presented, in which service quality is factored in constraints by introducing passenger satisfaction degree functions that limit time deviations between actual and desired delivery times. The problem addressed in this paper has two distinctive characteristics??small vehicle capacities and tight delivery time windows. An exact algorithm based on the set-partitioning model, concerning both characteristics, is developed. In the first phase of the algorithm the entire candidate set of best feasible routes is generated, and then the optimal solution is obtained by solving the set-partitioning model in the second phase. Finally, we use four actual instances to illustrate application of the proposed algorithm. Moreover, the proposed algorithm is applied to a random instance containing more orders to verify the general effectiveness of the proposed algorithm even if the number of passengers increases in future.     

Application of Equity Sensitivity Theory to Problem-Solving Approaches in Construction Dispute Negotiation

This study applies equity sensitivity theory to investigate how the sensitivity of negotiators to perceived equity or inequity varies with their perception of the adoption of problem-solving approaches (PSAs) in negotiation in the construction industry. Drawing upon this theory, we identify three classes of negotiators: benevolents (known as “givers”), equity sensitives, and entitleds (known as “takers”). Our results suggest that most of the negotiators in our sample are entitleds. The study also provides statistical evidence that the perception of the adoption of PSAs appears to be associated with the degree of equity sensitivity of negotiators. For instance, benevolents demonstrate a significantly stronger preference for the adoption of PSAs and are thus able to obtain a higher level of negotiation satisfaction compared to the other types of negotiators. These findings are particularly relevant to the corporate managers of construction organizations, who may want to consider the inherent equity sensitivity traits of their negotiators before sending them to the negotiating table.     

A Computational Approach to Gene Expression Data Extraction and Analysis

The rapid advancement of DNA microarray technology has revolutionalized genetic research in bioscience. Due to the enormous amount of gene expression data generated by such technology, computer processing and analysis of such data has become indispensable. In this paper, we present a computational framework for the extraction, analysis and visualization of gene expression data from microarray experiments. A novel, fully automated, spot segmentation algorithm for DNA microarray images, which makes use of adaptive thresholding, morphological processing and statistical intensity modeling, is proposed to: (i) segment the blocks of spots, (ii) generate the grid structure, and (iii) to segment the spot within each subregion. For data analysis, we propose a binary hierarchical clustering (BHC) framework for the clustering of gene expression data. The BHC algorithm involves two major steps. Firstly, the fuzzy C-means algorithm and the average linkage hierarchical clustering algorithm are used to split the data into two classes. Secondly, the Fisher linear discriminant analysis is applied to the two classes to assess whether the split is acceptable. The BHC algorithm is applied to the sub-classes recursively and ends when all clusters cannot be split any further. BHC does not require the number of clusters to be known in advance. It does not place any assumption about the number of samples in each cluster or the class distribution. The hierarchical framework naturally leads to a tree structure representation for effective visualization of gene expressions.     

Bid markup selection models by use of multiple criteria

Multiple attribute decision modeling is proposed for determining the most preferred bid markup in a competitive bidding situation. In this note, a previously proposed model is extended by introducing two new bidding criteria, called the conditional positive profit and the expected positive profit ratios, respectively. Three two-criteria decision models and a single criteria decision models using the newly introduced criteria are proposed to determine the bidder's most preferred markup level. The simple additive weighting method and the weighting product method are used to solve these models. Two numerical examples are used to illustrate the different rankings that are obtained when different models and solution methods are used. The results demonstrate that the bidder's preference over the set of bidding criteria has a significant effect on the selection of the bid markup