High Multiplicity Scheduling with Switching Costs for few Products

We study a variant of the single machine capacitated lot-sizing problem with sequence-dependent setup costs and product-dependent inventory costs. We are given a single machine and a set of products associated with a constant demand rate, maximum loading rate and holding costs per time unit. Switching production from one product to another incurs sequencing costs based on the two products. In this work, we show that by considering the high multiplicity setting and switching costs, even trivial cases of the corresponding "normal" counterparts become non-trivial in terms of size and complexity. We present solutions for one and two products.Comment: 10 pages (4 appendix), to be published in Operations Research Proceedings 201

Optimal sequential fingerprinting: Wald vs. Tardos

We study sequential collusion-resistant fingerprinting, where the fingerprinting code is generated in advance but accusations may be made between rounds, and show that in this setting both the dynamic Tardos scheme and schemes building upon Wald's sequential probability ratio test (SPRT) are asymptotically optimal. We further compare these two approaches to sequential fingerprinting, highlighting differences between the two schemes. Based on these differences, we argue that Wald's scheme should in general be preferred over the dynamic Tardos scheme, even though both schemes have their merits. As a side result, we derive an optimal sequential group testing method for the classical model, which can easily be generalized to different group testing models.Comment: 12 pages, 10 figure

How to inform at-risk relatives?:Attitudes of 1379 Dutch patients, relatives, and members of the general population

The uptake of predictive DNA testing in families with a hereditary disease is <50%. Current practice often relies on the proband to inform relatives about the possibility of predictive DNA testing, but not all relatives are informed adequately. To enable informed decision-making concerning predictive DNA testing, the approach used to inform at-risk relatives needs to be optimized. This study investigated the preferences of patients, relatives, and the general population from the Netherlands on how to inform relatives at risk of autosomal dominant diseases. Online surveys were sent to people with autosomal dominant neuro-, onco-, or cardiogenetic diseases and their relatives via patient organizations (n = 379), and to members of the general population via a commercial panel (n = 1,000). Attitudes of the patient and population samples generally corresponded. A majority believed that initially only first-degree relatives should be informed, following the principles of a cascade screening approach. Most participants also thought that probands and healthcare professionals (HCPs) should be involved in informing relatives, and a large proportion believed that HCPs should contact relatives directly in cases where patients are unwilling to inform, both for untreatable and treatable conditions. Participants from the patient sample were of the opinion that HCPs should actively offer support. Our findings show that both patients and HCPs should be involved in informing at-risk relatives of autosomal dominant diseases and suggest that relatives' 'right to know' was considered a dominant issue by the majority of participants. Further research is needed on how to increase proactive support in informing of at-risk relatives

Curcumin as Treatment for Bladder Cancer : A Preclinical Study of Cyclodextrin-Curcumin Complex and BCG as Intravesical Treatment in an Orthotopic Bladder Cancer Rat Model

Objective. To evaluate the antitumor effect of cyclodextrin-curcumin complex (CDC) on human and rat urothelial carcinoma cells in vitro and to evaluate the effect of intravesical instillations of CDC, BCG, and the combination in vivo in the AY-F344 orthotopic bladder cancer rat model. Curcumin has anticarcinogenic activity on urothelial carcinoma and is therefore under investigation for the treatment of non-muscle invasive bladder cancer. Curcumin and BCG share immunomodulating pathways against urothelial carcinoma. Methods. Curcumin was complexed with cyclodextrin to improve solubility. Four human urothelial carcinoma cell lines and the AY-27 rat cell line were exposed to various concentrations of CDC in vitro. For the in vivo experiment, the AY-27 orthotopic bladder cancer F344 rat model was used. Rats were treated with consecutive intravesical instillations of CDC, BCG, the combination of CDC+BCG, or NaCl as control. Results. CDC showed a dose-dependent antiproliferative effect on all human urothelial carcinoma cell lines tested and the rat AY-27 urothelial carcinoma cell line. Moreover, intravesical treatment with CDC and CDC+BCG results in a lower percentage of tumors (60% and 68%, respectively) compared to BCG (75%) or control (85%). This difference with placebo was not statistically significant (p=0.078 and 0.199, respectively). However, tumors present in the placebo and BCG-treated rats were generally of higher stage. Conclusions. Cyclodextrin-curcumin complex showed an antiproliferative effect on human and rat urothelial carcinoma cell lines in vitro. In the aggressive orthotopic bladder cancer rat model, we observed a promising effect of CDC treatment and CDC in combination with BCG.Peer reviewe

Exposure to low-dose radiation and the risk of breast cancer among women with a familial or genetic predisposition:a meta-analysis

Women with familial or genetic aggregation of breast cancer are offered screening outside the population screening programme. However, the possible benefit of mammography screening could be reduced due to the risk of radiation-induced tumours. A systematic search was conducted addressing the question of how low-dose radiation exposure affects breast cancer risk among high-risk women. A systematic search was conducted for articles addressing breast cancer, mammography screening, radiation and high-risk women. Effects of low-dose radiation on breast cancer risk were presented in terms of pooled odds ratios (OR). Of 127 articles found, 7 were selected for the meta-analysis. Pooled OR revealed an increased risk of breast cancer among high-risk women due to low-dose radiation exposure (OR = 1.3, 95% CI: 0.9- 1.8). Exposure before age 20 (OR = 2.0, 95% CI: 1.3-3.1) or a mean of a parts per thousand yen5 exposures (OR = 1.8, 95% CI: 1.1-3.0) was significantly associated with a higher radiation-induced breast cancer risk. Low-dose radiation increases breast cancer risk among high-risk women. When using low-dose radiation among high-risk women, a careful approach is needed, by means of reducing repeated exposure, avoidance of exposure at a younger age and using non-ionising screening techniques

Hereditary Breast-Ovarian Cancer Team of the University Medical Centre Groningen (UMCG):a Report

Female carriers of a germline BRCA1 or BRCA2 mutation have a cumulative lifetime ovarian cancer risk of 39-54 % or 11-23%, respectively [1, 2]. Preventive health strategies for these women include gynaecological screening aiming at early cancer detection and prophylactic salpingo-ophorectomy aiming at cancer risk reduction. However, it is becoming increasingly clear that (bi) annual gynaecological screening by transvaginal ultrasonography and serum CA125 estimation in women at increased risk of ovarian cancer is ineffective in detecting presymptomatic ovarian cancer [4]. In a recent publication a positive predictive value of 17 % and a sensitivity of less than 50 % were found for screening for ovarian cancer in a high-risk population [3]. Preventive bilateral salpingo-oophorectomy (BSO) reduces ovaria

Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization

Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits the geometric features of blueprint images. This is implemented by utilizing a robust windows operation, which is based on the assumption that the objects have "e;C"e; shape in a small area. We make use of multiple window sizes in the windows operation. This not only reduces computation time but also separates effectively thin lines from wide lines. Our method can automatically determine the threshold of images. Experiments show that our method is effective for blueprint images and achieves good results over a wide range of images. Second, the fuzzy set theory, along with probability partition and maximum entropy theory, is explored to compute the threshold based on the histogram of the image. Fuzzy set theory has been widely used in many fields where the ambiguous phenomena exist since it was proposed by Zadeh in 1965. And many thresholding methods have also been developed by using this theory. The concept we are using here is called fuzzy partition. Fuzzy partition means that a histogram is parted into several groups by some fuzzy sets which represent the fuzzy membership of each group because our method is based on histogram of the image . Probability partition is associated with fuzzy partition. The probability distribution of each group is derived from the fuzzy partition. Entropy which originates from thermodynamic theory is introduced into communications theory as a commonly used criteria to measure the information transmitted through a channel. It is adopted by image processing as a measurement of the information contained in the processed images. Thus it is applied in our method as a criterion for selecting the optimal fuzzy sets which partition the histogram. To find the threshold, the histogram of the image is partitioned by fuzzy sets which satisfy a certain entropy restriction. The search for the best possible fuzzy sets becomes an important issue. There is no efficient method for the searching procedure. Therefore, expansion to multiple level thresholding with fuzzy partition becomes extremely time consuming or even impossible. In this thesis, the relationship between a probability partition (PP) and a fuzzy C-partition (FP) is studied. This relationship and the entropy approach are used to derive a thresholding technique to select the optimal fuzzy C-partition. The measure of the selection quality is the entropy function defined by the PP and FP. A necessary condition of the entropy function arriving at a maximum is derived. Based on this condition, an efficient search procedure for two-level thresholding is derived, which makes the search so efficient that extension to multilevel thresholding becomes possible. A novel fuzzy membership function is proposed in three-level thresholding which produces a better result because a new relationship among the fuzzy membership functions is presented. This new relationship gives more flexibility in the search for the optimal fuzzy sets, although it also increases the complication in the search for the fuzzy sets in multi-level thresholding. This complication is solved by a new method called the "e;Onion-Peeling"e; method. Because the relationship between the fuzzy membership functions is so complicated it is impossible to obtain the membership functions all at once. The search procedure is decomposed into several layers of three-level partitions except for the last layer which may be a two-level one. So the big problem is simplified to three-level partitions such that we can obtain the two outmost membership functions without worrying too much about the complicated intersections among the membership functions. The method is further revised for images with a dominant area of background or an object which affects the appearance of the histogram of the image. The histogram is the basis of our method as well as of many other methods. A "e;bad"e; shape of the histogram will result in a bad thresholded image. A quadtree scheme is adopted to decompose the image into homogeneous areas and heterogeneous areas. And a multi-resolution thresholding method based on quadtree and fuzzy partition is then devised to deal with these images. Extension of fuzzy partition methods to color images is also examined. An adaptive thresholding method for color images based on fuzzy partition is proposed which can determine the number of thresholding levels automatically. This thesis concludes that the "e;C"e; shape assumption and varying sizes of windows for windows operation contribute to a better segmentation of the blueprint images. The efficient search procedure for the optimal fuzzy sets in the fuzzy-2 partition of the histogram of the image accelerates the process so much that it enables the extension of it to multilevel thresholding. In three-level fuzzy partition the new relationship presentation among the three fuzzy membership functions makes more sense than the conventional assumption and, as a result, performs better. A novel method, the "e;Onion-Peeling"e; method, is devised for dealing with the complexity at the intersection among the multiple membership functions in the multilevel fuzzy partition. It decomposes the multilevel partition into the fuzzy-3 partitions and the fuzzy-2 partitions by transposing the partition space in the histogram. Thus it is efficient in multilevel thresholding. A multi-resolution method which applies the quadtree scheme to distinguish the heterogeneous areas from the homogeneous areas is designed for the images with large homogeneous areas which usually distorts the histogram of the image. The new histogram based on only the heterogeneous area is adopted for partition and outperforms the old one. While validity checks filter out the fragmented points which are only a small portion of the whole image. Thus it gives good thresholded images for human face images