Brown University

About: Brown University is a education organization based out in Providence, Rhode Island, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 35778 authors who have published 90896 publications receiving 4471489 citations. The organization is also known as: brown.edu & Brown.

Mechanics of morphological instabilities and surface wrinkling in soft materials: a review

Abstract: Morphological instabilities and surface wrinkling of soft materials such as gels and biological tissues are of growing interest to a number of academic disciplines including soft lithography, metrology, flexible electronics, and biomedical engineering. In this paper, we review some of the recent progresses in experimental and theoretical investigations of instabilities that lead to the emergence and evolution of surface wrinkling, folding and creasing under various geometrical constraints (e.g., thin films, sheets, fibers, particles, tubes, cavities, vesicles and capsules) and loading stimuli (e.g., mechanical forces, growth, atrophy, swelling, shrinkage, van der Waals interactions). Some representative theoretical and numerical approaches aimed at modelling the onset of instabilities as well as the postbuckling evolution involving multiple bifurcations and symmetry-breakings are discussed along with the main characteristics and some possible applications of this rich phenomenon.

A disconfirmation bias in the evaluation of arguments.

Abstract: Two experiments provided evidence for a disconfirmation bias in argument evaluation such that arguments incompatible with prior beliefs are scrutinized longer, subjected to more extensive refutational analyses, and consequently are judged to be weaker than arguments compatible with prior beliefs. The idea that people are unable to evaluate evidence independently of prior beliefs has been documented elsewhere, including in the classic study by C. G. Lord, L. Ross, and M. R. Lepper (1979). The present findings contribute to this literature by specifying the processes by which prior beliefs affect the evaluation of evidence. The authors compare the disconflrmation model to several other models of how prior beliefs influence current judgments and present data that provide support for the disconfirmation model. Results indicate that whether a person's prior belief is accompanied by emotional conviction affects the magnitude and form of the disconfirmation bias. When evaluating an argument, can one assess its strength independently of one's prior belief in the conclusion? A good deal of evidence indicates the answer is an emphatic no (e.g., Batson, 1975; Chapman & Chapman, 1959; Darley & Gross, 1983; Geller & Pitz, 1968; Nisbett & Ross, 1980; Sherif & Hovland, 1961). This phenomenon, which we refer to as the prior belief effect, has important implications. Given two people, or groups, with opposing beliefs about a social, political, or scientific issue, the degree to which they will view relevant evidence as strong will differ. This difference, in turn, may result in a failure of the opposing parties to converge on any kind of meaningful agreement, and, under some circumstances, they may become more extreme in their beliefs. Perhaps the most renowned study documenting the prior belief effect is one conducted by Lord, Ross, and Lepper (1979); this study served as the starting point for our work. Lord et al. were concerned with people's evaluations of arguments about

The Confusion Assessment Method: a systematic review of current usage.

Abstract: Delirium is a common and serious problem affecting older adults, associated with increased mortality, prolonged hospital stays, increased healthcare costs, higher rates of institutionalization, and decreased functional independence (1). High-risk settings for delirium include the hospital, intensive care, emergency, post-operative, institutional, and terminal care settings (2). Delirium increases hospital costs by at least $2,500 per patient, resulting in over $6.9 billion (2004 USD) in hospital costs each year (2). Despite its adverse impact, delirium remains poorly recognized in clinical practice. The Confusion Assessment Method is a delirium instrument published in 1990 (3), which was created to improve the identification of delirium. The Confusion Assessment Method (CAM) includes an instrument and diagnostic algorithm for identification of delirium (3). Originally developed by literature review and expert consensus, the CAM was validated against the reference standard ratings of geropsychiatrists based on Diagnostic and Statistical Manual for Mental Disorders Third Edition Revised (DSM-IIIR) (4) criteria. The CAM was designed to allow non-psychiatric clinicians to diagnose delirium quickly and accurately following brief formal cognitive testing. The CAM instrument assesses the presence, severity, and fluctuation of 9 delirium features: acute onset, inattention, disorganized thinking, altered level of consciousness, disorientation, memory impairment, perceptual disturbances, psychomotor agitation or retardation, and altered sleep-wake cycle. The CAM diagnostic algorithm is based on four cardinal features of delirium: 1) acute onset and fluctuating course, 2) inattention, 3) disorganized thinking, and 4) altered level of consciousness. A diagnosis of delirium according to the CAM requires the presence of features 1, 2, and either 3 or 4. The CAM demonstrated sensitivities from 94–100%, specificities from 90–95%, positive predictive accuracy of 91– 94%, negative predictive accuracy of 90–100%, interrater reliability ranging from .81–1.00; and convergent agreement with other mental status tests including the Mini-Mental State Examination (MMSE) (5). The Confusion Assessment Method (CAM) Training Manual was developed to facilitate its appropriate use . Because of its accuracy, brevity, and ease of use by clinical and lay interviewers, the CAM has become the most widely used standardized delirium instrument for clinical and research purposes over the past 16 years. The purpose of this article is to provide a systematic review of all original English language articles utilizing the CAM to synthesize its psychometric properties, adaptations, published translations, and clinical and research applications. Strengths and limitations of the articles have been highlighted. Ultimately, it is hoped that this summary will provide a comprehensive overview of the current utility of the CAM, and recommendations for its appropriate use.

Low-Fat Dietary Pattern and Risk of Colorectal Cancer: The Women's Health Initiative Randomized Controlled Dietary Modification Trial

Abstract: ContextObservational studies and polyp recurrence trials are not conclusive regarding the effects of a low-fat dietary pattern on risk of colorectal cancer, necessitating a primary prevention trial.ObjectiveTo evaluate the effects of a low-fat eating pattern on risk of colorectal cancer in postmenopausal women.Design, Setting, and ParticipantsThe Women’s Health Initiative Dietary Modification Trial, a randomized controlled trial conducted in 48 835 postmenopausal women aged 50 to 79 years recruited between 1993 and 1998 from 40 clinical centers throughout the United States.InterventionsParticipants were randomly assigned to the dietary modification intervention (n = 19 541; 40%) or the comparison group (n = 29 294; 60%).The intensive behavioral modification program aimed to motivate and support reductions in dietary fat, to increase consumption of vegetables and fruits, and to increase grain servings by using group sessions, self-monitoring techniques, and other tailored and targeted strategies. Women in the comparison group continued their usual eating pattern.Main Outcome MeasureInvasive colorectal cancer incidence.ResultsA total of 480 incident cases of invasive colorectal cancer occurred during a mean follow-up of 8.1 (SD, 1.7) years. Intervention group participants significantly reduced their percentage of energy from fat by 10.7% more than did the comparison group at 1 year, and this difference between groups was mostly maintained (8.1% at year 6). Statistically significant increases in vegetable, fruit, and grain servings were also made. Despite these dietary changes, there was no evidence that the intervention reduced the risk of invasive colorectal cancer during the follow-up period. There were 201 women with invasive colorectal cancer (0.13% per year) in the intervention group and 279 (0.12% per year) in the comparison group (hazard ratio, 1.08; 95% confidence interval, 0.90-1.29). Secondary analyses suggested potential interactions with baseline aspirin use and combined estrogen-progestin use status (P = .01 for each). Colorectal examination rates, although not protocol defined, were comparable between the intervention and comparison groups. Similar results were seen in analyses adjusting for adherence to the intervention.ConclusionIn this study, a low-fat dietary pattern intervention did not reduce the risk of colorectal cancer in postmenopausal women during 8.1 years of follow-up.Clinical Trials RegistrationClinicalTrials.gov Identifier: NCT00000611