Research on optimization-based design

Research on optimization-based design is discussed. Illustrative examples are given for cases involving continuous optimization with discrete variables and optimization with tolerances. Approximation of computationally expensive and noisy functions, electromechanical actuator/control system design using decomposition and application of knowledge-based systems and optimization for the design of a valve anti-cavitation device are among the topics covered

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Prediction of an undimerized, insulating, antiferromagnetic ground-state in halogen-bridged linear-chain Ni compounds

A parameter-free, mean-field, multi-orbital Hubbard model with nonspherical Coulomb and exchange interactions, implemented around all-electron local-density approximation (LDA) calculations, correctly predicts the band-gap energy, the absence of dimerization, and the antiferromagnetic ground state of halogen-bridged linear-chain Ni compounds. This approach also reproduces the insulating ground state and dimerization in PtX linear-chain compounds in agreement with experiment and previous calculations. Three "ps" figures are included at the end of the RevTex file and compressed using uufiles.Comment: 11 RevTex pages and three ps figures. Paper accepted by PRB Rapid Com

Lagrange Anchor and Characteristic Symmetries of Free Massless Fields

A Poincar\'e covariant Lagrange anchor is found for the non-Lagrangian relativistic wave equations of Bargmann and Wigner describing free massless fields of spin $s>1/2$ in four-dimensional Minkowski space. By making use of this Lagrange anchor, we assign a symmetry to each conservation law and perform the path-integral quantization of the theory

Factors that Influence Providers’ Pain Treatment Decisions

poster abstractMedical and non-medical factors influence providers’ pain treatment decisions. Among these, patient demographic characteristics and substance use have received particular attention. However, few empirical studies have examined the specific factors providers rely on for their pain treatment decisions. This study employed lens model methodology to examine the factors that providers reportedly used, actually used, and would have used (if available) to make pain treatment decisions. We hypothesized that: (1) providers would rate patients’ pain history and description of pain as the most influential factors provided in the clinical vignettes, and (2) providers would rate patients’ substance use history as the most important factor not provided in the vignettes. 100 providers viewed 16 computer-simulated patients; each included a picture with accompanying text describing the patient’s medical condition. After making multi-modal treatment ratings for each patient, providers indicated the factors they used to make treatment decisions and the factors they would have used (if available) to make decisions. Results indicated that most providers reported being influenced by patients’ pain histories (98%) and descriptions (96%), whereas fewer reported using patients' movement (75%) or demographic characteristics (62%). Providers reported that they wanted additional information on patients’ treatment histories (98%), current/average pain (96%), and drug use (94%) to guide their decisions. Exploratory analyses indicated that, compared to providers who were not statistically influenced by patient demographics, a slightly greater proportion of providers who were statistically influenced by patient demographics wanted additional information about patients’ alcohol use to inform their decisions, χ2 (1) = 3.09, p = .08. These results suggest that providers prioritize both objective and subjective information about patients’ pain conditions, as well as patients’ substance use behaviors, when making treatment decisions. These findings have important implications for pain management and may lead to improved patient safety and care

Examining Influential Factors in Providers’ Chronic Pain Treatment Decisions: A Comparison of Physicians and Medical Students

Reports have found that chronic pain management guidelines are unclear and conflicting. Due to this confusion, it is critical to understand factors that influence providers’ treatment decisions for chronic pain. Little is known about which factors providers use to make treatment decisions or whether providers of different training levels endorse using similar factors. The purpose of this study was to examine the factors that providers report using to make their chronic pain treatment decisions. We hypothesized that providers would: (1) prioritize objective factors over subjective factors, (2) be particularly interested in information about patients’ substance use, and (3) endorse using different factors depending on their training level (physicians vs. medical students). Eighty-five providers (35 medical students, 50 physicians) viewed 16 computer-simulated patients; each included a picture with text describing the patients’ condition (i.e., chronic lower back pain, open to any treatment, presence/absence of depression). After making treatment decisions, participants selected from a list the factors they used and would have used (if the information had been available) to make their treatment decisions. Most providers reported being influenced by patients’ pain histories (97.6%) and pain descriptions (95.3%). Providers indicated they would have used information about patients’ previous treatments (97.6%), average pain ratings (96.5%), and current pain (96.5%) had this information been available. Compared to physicians, medical students endorsed more often that they would have used patients’ employment and/or disability status (p<.01), illicit drug use (p=.09), and alcohol use (p=.08) to make treatment decisions. These results indicate that providers rely on objective and subjective information to make pain treatment decisions, and compared to physicians, medical students place a stronger emphasis on patients’ substance abuse and social history when making treatment decisions. Future studies should examine additional provider and patient factors that influence decisions for specific pain treatment options

Access to interpreting services in England: secondary analysis of national data

Background: Overcoming language barriers to health care is a global challenge. There is great linguistic diversity in the major cities in the UK with more than 300 languages, excluding dialects, spoken by children in London alone. However, there is dearth of data on the number of non-English speakers for planning effective interpreting services. The aim was to estimate the number of people requiring language support amongst the minority ethnic communities in England. Methods: Secondary analysis of national representative sample of subjects recruited to the Health Surveys for England 1999 and 2004. Results: 298,432 individuals from the four main minority ethnic communities (Indian, Pakistani, Bangladeshi and Chinese) who may be unable to communicate effectively with a health professional. This represents 2,520,885 general practice consultations per year where interpreting services might be required. Conclusion: Effective interpreting services are required to improve access and health outcomes of non-English speakers and thereby facilitate a reduction in health inequalities

Examining Gender Differences in Pain Treatment Recommendations

poster abstractUnderstanding how pain treatment decisions are made has important clinical implications for healthcare. Research suggests that men and women receive disparate pain care, however, little is known about the specific treatment recommendations that are differentially made for men and women. The purpose of this study was to examine differences between the types of pain treatments recommended for men and women. Undergraduate psychology students from Indiana University-Purdue University Indianapolis (IUPUI) and the University of North Texas (UNT) (n=621) made treatment recommendations for 8 chronic pain patients after reading a vignette describing the patient’s pain and watching a video of each patient completing a pain-inducing task (i.e., transition between sitting and standing). Participants made pain treatment recommendations for each patient using separate 0-100 visual analogue scales (VASs). Dependent samples t-tests indicated that participants were more likely to recommend workplace accommodations (t(620)= -3.05, p= .002, d= 0.17), disability compensation (t(620)= -7.77, p< .001, d= 0.44), and opioid medications (t(620)= -5.16, p< .001, d= 0.29) for men compared to women. Moreover, participants were more likely to recommend psychological therapy (t(620)= 4.59, p< .001, d= 0.26), rest (t(620)= 7.80, p< .001, d= 0.44), and diet/exercise (t(620)= 2.97, p= .003, d= 0.17) for women compared to men. These results are consistent with social psychological theories of gender-based stereotyping and suggest that men’s pain was perceived to be more legitimate, severe, and disabling than was women’s pain. Future studies are needed to examine how these differences affect pain outcomes and whether knowledge of these factors can improve training for future health care providers

Mapping lessons from ants to free flight: An ant-based weather aviodance algorithm in free flight airspace

The continuing growth of air traffic worldwide motivates the need for new approaches to air traffic management that are more flexible both in terms of traffic volume and weather. Free Flight is one such approach seriously considered by the aviation community. However the benefits of Free Flight are severely curtailed in the convective weather season when weather is highly active, leading aircrafts to deviate from their optimal trajectories. This paper investigates the use of ant colony optimization in generating optimal weather avoidance trajectories in Free Flight airspace. The problem is motivated by the need to take full advantage of the airspace capacity in a Free Flight environment, while maintaining safe separation between aircrafts and hazardous weather. The experiments described herein were run on a high fidelity Free Flight air traffic simulation system which allows for a variety of constraints on the computed routes and accurate measurement of environments dynamics. This permits us to estimate the desired behavior of an aircraft, including avoidance of changing hazardous weather patterns, turn and curvature constraints, and the horizontal separation standard and required time of arrival at a pre determined point, and to analyze the performance of our algorithm in various weather scenarios. The proposed Ant Colony Optimization based weather avoidance algorithm was able to find optimum weather free routes every time if they exist. In case of highly complex scenarios the algorithm comes out with the route which requires the aircraft to fly through the weather cells with least disturbances. All the solutions generated were within flight parameters and upon integration with the flight management system of the aircraft in a Free Flight air traffic simulator, successfully negotiated the bad weather

Development and validation of a risk score for chronic kidney disease in HIV infection using prospective cohort data from the D:A:D study.

Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice