A Decision Technology System To Advance the Diagnosis and Treatment of Breast Cancer

Geographical variations in cancer rates have been observed for decades. Described spatial patterns and trends have provided clues for generating hypotheses about the etiology of cancer. For breast cancer, investigators have demonstrated that some variation can be explained by differences in the population distribution of known breast cancer risk factors such as menstrual and reproductive variables (Laden, Spiegelman, and Neas, 1997; Robbins, Bescianini, and Kelsey, 1997; Sturgeon, Schairer, and Gail, 1995). However, regional patterns also may reflect the effects of Workshop on Hormones, Hormone Metabolism, Environment, and Breast Cancer (1995): (a) environmental hazards (such as air and water pollution), (b) demographics and the lifestyle of a mobile population, (c) subgroup susceptibility, (d) changes and advances in medical practice and healthcare management, and (e) other factors. To accurately measure breast cancer risk in individuals and population groups, it is necessary to singly and jointly assess the association between such risk and the hypothesized factors. Various statistical models will be needed to determine the potential relationships between breast cancer development and estimated exposures to environmental contamination. To apply the models, data must be assembled from a variety of sources, converted into the statistical models’ parameters, and delivered effectively to researchers and policy makers. A Web-enabled decision technology system can be developed to provide the needed functionality. This chapter will present a conceptual architecture for such a decision technology system. First, there will be a brief overview of a typical geographical analysis. Next, the chapter will present the conceptual Web-based decision technology system and illustrate how the system can assist users in diagnosing and treating breast cancer. The chapter will conclude with an examination of the potential benefits from system use and the implications for breast cancer research and practice

Eelgrass Distribution in the Great Bay Estuary and Piscataqua River for 2017

Eelgrass distribution in Great Bay, Little Bay, and the Piscataqua River Estuary was mapped from aerial photography acquired on August 24, 2017. The total area of eelgrass beds with 10% or greater cover and a polygon area equal to or greater than 100 square meters was 625.9 hectares or 1546.7 acres. Eelgrass polygons were coded for Assessment Zone location and the results reported for each zone. The largest concentration of eelgrass was found in Great Bay with lesser amounts in the vicinity of Portsmouth Harbor. The total area of eelgrass beds with 10% or greater cover and a polygon area equal to or greater than 100 square meters has decreased by 142 acres which is approximately an 8.5% decrease from the previous year

A taxonomy for emergency service station location problem

The emergency service station (ESS) location problem has been widely studied in the literature since 1970s. There has been a growing interest in the subject especially after 1990s. Various models with different objective functions and constraints have been proposed in the academic literature and efficient solution techniques have been developed to provide good solutions in reasonable times. However, there is not any study that systematically classifies different problem types and methodologies to address them. This paper presents a taxonomic framework for the ESS location problem using an operations research perspective. In this framework, we basically consider the type of the emergency, the objective function, constraints, model assumptions, modeling, and solution techniques. We also analyze a variety of papers related to the literature in order to demonstrate the effectiveness of the taxonomy and to get insights for possible research directions

Spiropyran-based reversible, light-modulated sensing with reduced photofatigue

Switchable materials have tremendous potential for application in sensor development that could be applied to many fields. We are focusing on emerging area of wireless sensor networks due to the potential impact of this concept in society. Spiropyran-based sensors are probably the most studied type of photoswitchable sensing devices. They suffer from many issues but photofatigue, insufficient selectivity and lack of sensitivity are probably the most important characteristics that hinder their wider application. Here, we are address these issues and demonstrate that covalent attachment of modified spiropyran into a polymeric film significantly reduces photodegradation. The observed signal loss after 12th cycle of switching between the spiropyran and merocyanine forms is only about 27% compared to the loss of 57% of the initial signal in an equivalent experiment based on non-immobilized spiropyran. This has enabled us to demonstrate at least five reversible cycles of detection of an ion of interest (in our case H+) with minimal signal loss. Furthermore, we demonstrate that the sensitivity can be increased by incorporation of additional binding groups in the parent spiropyran molecule. Using molecular modelling to calculate the relevant bond lengths as a measure of interaction between MC and H+, the calculated increase of H-bond strength is approximately an order of magnitude for a derivative containing a methoxy group incorporated in the o-position of the parent spiropyran in comparison to the equivalent unsubstituted phenol. This theoretical result was found to correspond very well with experimental observation. As a result, we have increased the sensitivity to H+ by approximately one order of magnitude

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM