Knowledge and Beliefs about Cancer in African American Population

Cancer is the second most common cause of death in the United States, taking the lives of one in four Americans each year (American Cancer Society [ACS], 2015). A total of 1,658,370 new cancer cases and 589,430 deaths from cancer were projected to occur in the United States in 2015 (ACS, 2015). In 2013, approximately 176,630 new cancer cases and 64,880 deaths from cancer were projected to occur in African American communities. The majority of diagnoses were cancers of the prostate, lung, colon, rectum, breast, and colorectal region (ACS, 2013). For most cancers, African Americans have the highest death rate, and shortest survival rate, of any racial or ethnic sub-groups (ACS, 2013). Individual perception, knowledge, beliefs, and awareness systems can influence the cancer evaluation process and the ability to fight the disease. The health belief model (HBM) is a conceptual framework used to explain an individual’s behavior based on the individual’s belief or perception. This paper reports on an analysis of a sample of self-identified African American respondents to the Health Information National Trends Survey (HINTS) data HINT4 cycle3, to explore an association of African Americans’ knowledge, beliefs and the processes of cancer information-seeking behavior based on the HBM and demographic information. The results showed that African Americans with a higher level of education were significantly more likely to access common sources of cancer information. Perceived benefits and cues-to-action were significantly associated with the common sources of cancer information sought whereas perceived susceptibility, perceived severity, perceived barrier, and self-efficacy were not. African Americans’ perceptions and beliefs of cancer may be enhanced through health education, mass media campaigns, and a wider availability of health information online

Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview

An increasing number of works in natural language processing have addressed the effect of bias on the predicted outcomes, introducing mitigation techniques that act on different parts of the standard NLP pipeline (data and models). However, these works have been conducted in isolation, without a unifying framework to organize efforts within the field. This leads to repetitive approaches, and puts an undue focus on the effects of bias, rather than on their origins. Research focused on bias symptoms rather than the underlying origins could limit the development of effective countermeasures. In this paper, we propose a unifying conceptualization: the predictive bias framework for NLP. We summarize the NLP literature and propose a general mathematical definition of predictive bias in NLP along with a conceptual framework, differentiating four main origins of biases: label bias, selection bias, model overamplification, and semantic bias. We discuss how past work has countered each bias origin. Our framework serves to guide an introductory overview of predictive bias in NLP, integrating existing work into a single structure and opening avenues for future research.Comment: 9 pages excluding references, 1 figure, 3 pages for appendi

Double crush syndrome: clinical review of an unsolved puzzle

Double crush syndrome (DCS) involves compression of a peripheral nerve at two different segments. Median nerve is most commonly involved with proximal compression at the level of cervical spine and distal compression in the carpal tunnel. Little consensus exists in literature regarding its epidemiology, risk factors, pathophysiology and definitive treatment. The purpose of this article is to summarize our current knowledge about this disease process as well as to touch upon the controversies that have been generated in recent times

Text Extraction from Natural Images of Different Languages Using ISEF Edge Detection

In this paper, we proposed the algorithm text extraction of different images of languages. In computer vision research area, text is very important in images. Here, we use edge based extraction of text using ISEF (infinite symmetrical edge filter). ISEF is optimal edge detector which gives accurate results for text in images. Text extraction involves detection, localization, tracking and enhancement. Large numbers of technique have been proposed for the text extraction. Our aim is to present robust technique for text extraction of different languages images

HLA-DQA1*05 carriage associated with development of anti-drug antibodies to infliximab and adalimumab in patients with Crohn's Disease

Anti-tumor necrosis factor (anti-TNF) therapies are the most widely used biologic drugs for treating immune-mediated diseases, but repeated administration can induce the formation of anti-drug antibodies. The ability to identify patients at increased risk for development of anti-drug antibodies would facilitate selection of therapy and use of preventative strategies.This article is freely available via Open Access. Click on Publisher URL to access the full-text

Erweiterung eines Trajektorienrechners zur Simulation von treibstoffoptimierten 4D-Flugzeugtrajektorien für Hyperschallflugzeuge Extension of a trajectory calculator to simulate fuel-optimized-4D-trajectories for hypersonic airliner

According to a study of the International Civil Aviation Organization (ICAO) from 1985 to 2005, passenger and freight air traffic show both an annual growth rate of more than 6 %. Since global air traffic contributes with a share of approx. 5% of the total anthropogenic radiative forcing (RF) to the global climate change, the fraction of air traffic is significant and will thus most probably further increase in the future. The impact of air traffic on the global climate is not only determined by the quantity of pollutant substances emitted, but also decisively by the locus (longitude, latitude and flight altitude) and time of the emissions. Technological advances, such as the reduction of take-off weight, the improvement of engine technology and the increase in aerodynamic performance, including operational measures and new aircraft design concepts, are thus an aspired goal in aviation. Against this background, the feasibility and accessibility of STRATOFLY-MR3, a Mach 8 waverider fueled with liquid hydrogen to perform high-speed passenger stratospheric flights, is addressed in this bachelor thesis in terms of the H2020 STRATOFLY Project, funded by the European Commission under the Horizon 2020 framework

International Conference on Blockchain Technology

This book presents articles from the International Conference on Blockchain Technology (IC-BCT) 2019, held in Mumbai, India, and highlights recent advances in the field. It brings together researchers and industry practitioners to show case their ideas linked to business case studies, and provides an opportunity for engineers, researchers, startups and professionals in the field of Blockchain technology to further collaboration