Four simplified gradient elasticity models for the simulation of dispersive wave propagation

Gradient elasticity theories can be used to simulate dispersive wave propagation as it occurs in heterogeneous materials. Compared to the second-order partial differential equations of classical elasticity, in its most general format gradient elasticity also contains fourth-order spatial, temporal as well as mixed spatial temporal derivatives. The inclusion of the various higher-order terms has been motivated through arguments of causality and asymptotic accuracy, but for numerical implementations it is also important that standard discretization tools can be used for the interpolation in space and the integration in time. In this paper, we will formulate four different simplifications of the general gradient elasticity theory. We will study the dispersive properties of the models, their causality according to Einstein and their behavior in simple initial/boundary value problems

Measuring Goal-Concordant Care in Palliative Care Research

Goal-concordant care is a priority outcome for palliative care research, yet the field lacks consensus on optimal methods for measurement. We sought to 1) categorize methods used to measure goal-concordant care, and 2) discuss strengths and limitations of each method using empirical examples from palliative care research. We categorized measurement methods for goal-concordant care. We identified empirical examples of each method to illustrate the strengths, limitations, and applicability of each method to relevant study designs. We defined four methods used to measure goal-concordant care: 1) Patient- or Caregiver-Reported, 2) Caregiver-Reported After Death, 3) Concordance in Longitudinal Data, and 4) Population-Level Indicators. Patient or caregiver-reported goal-concordant care draws on strengths of patient-reported outcomes, and can be captured for multiple aspects of treatment; these methods are subject to recall bias or family-proxy bias. Concordance in longitudinal data is optimal when a treatment preference can be specifically and temporally linked to actual treatment; the method is limited to common life-sustaining treatment choices and validity may be affected by temporal variation between preference and treatment. Population-level indicators allow pragmatic research to include large populations; its primary limitation is the assumption that preferences held by a majority of persons should correspond to patterns of actual treatment in similar populations. Methods used to measure goal-concordant care have distinct strengths and limitations, and methods should be selected based on research question and study design. Existing methods could be improved, yet a future gold standard is unlikely to suit all research designs

Spin decay and quantum parallelism

We study the time evolution of a single spin coupled inhomogeneously to a spin environment. Such a system is realized by a single electron spin bound in a semiconductor nanostructure and interacting with surrounding nuclear spins. We find striking dependencies on the type of the initial state of the nuclear spin system. Simple product states show a profoundly different behavior than randomly correlated states whose time evolution provides an illustrative example of quantum parallelism and entanglement in a decoherence phenomenon.Comment: 6 pages, 4 figures included, version to appear in Phys. Rev.

Mapping the Memorial Anxiety Scale for Prostate Cancer to the SF-6D

Purpose: To create a crosswalk that predicts Short Form 6D (SF-6D) utilities from Memorial Anxiety Scale for Prostate Cancer (MAX-PC) scores. Methods: The data come from prostate cancer patients enrolled in the North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS, N = 1016). Cross-sectional data from 12- to 24-month follow-up were used as estimation and validation datasets, respectively. Participants’ SF-12 scores were used to generate SF-6D utilities in both datasets. Beta regression mixture models were used to evaluate SF-6D utilities as a function of MAX-PC scores, race, education, marital status, income, employment status, having health insurance, year of cancer diagnosis and clinically significant prostate cancer-related anxiety (PCRA) status in the estimation dataset. Models’ predictive accuracies (using mean absolute error [MAE], root mean squared error [RMSE], Akaike information criterion [AIC] and Bayesian information criterion [BIC]) were examined in both datasets. The model with the highest prediction accuracy and the lowest prediction errors was selected as the crosswalk. Results: The crosswalk had modest prediction accuracy (MAE = 0.092, RMSE = 0.114, AIC = − 2708 and BIC = − 2595.6), which are comparable to prediction accuracies of other SF-6D crosswalks in the literature. About 24% and 52% of predictions fell within ± 5% and ± 10% of observed SF-6D, respectively. The observed mean disutility associated with acquiring clinically significant PCRA is 0.168 (standard deviation = 0.179). Conclusion: This study provides a crosswalk that converts MAX-PC scores to SF-6D utilities for economic evaluation of clinically significant PCRA treatment options for prostate cancer survivors

Better detection of Multipartite Bound Entanglement with Three-Setting Bell Inequalities

It was shown in Phys. Rev. Lett., 87, 230402 (2001) that N (N >= 4) qubits described by a certain one parameter family F of bound entangled states violate Mermin-Klyshko inequality for N >= 8. In this paper we prove that the states from the family F violate Bell inequalities derived in Phys. Rev. A, 56, R1682 (1997), in which each observer measures three non-commuting sets of orthogonal projectors, for N >=7. We also derive a simple one parameter family of entanglement witnesses that detect entanglement for all the states belonging to F. It is possible that these new entanglement witnesses could be generated by some Bell inequalities.Comment: Revtex4, 1 figur

Identification of Patient-Reported Outcome Phenotypes Among Oncology Patients With Palliative Care Needs

PURPOSE: Despite evidence-based guidelines recommending early palliative care, it remains unclear how to identify and refer oncology patients, particularly in settings with constrained access to palliative care. We hypothesize that patient-reported outcome (PRO) data can be used to characterize patients with palliative care needs. To determine if PRO data can identify latent phenotypes that characterize indications for specialty palliative care referral. METHODS: We conducted a retrospective study of self-reported symptoms on the Edmonton Symptom Assessment System collected from solid tumor oncology patients (n = 745) referred to outpatient palliative care. Data were collected as part of routine clinical care from October 2012 to March 2018 at eight community and academic sites. We applied latent profile analysis to identify PRO phenotypes and examined the association of phenotypes with clinical and demographic characteristics using multinomial logistic regression. RESULTS: We identified four PRO phenotypes: (1) Low Symptoms (n = 295, 39.6%), (2) Moderate Pain/Fatigue + Mood (n = 180, 24.2%), (3) Moderate Pain/Fatigue + Appetite + Dyspnea (n = 201, 27.0%), and (4) High Symptoms (n = 69, 9.3%). In a secondary analysis of 421 patients, we found that two brief items assessing social and existential needs aligned with higher severity symptom and psychological distress phenotypes. CONCLUSION: Oncology patients referred to outpatient palliative care in a real-world setting can be differentiated into clinically meaningful phenotypes using brief, routinely collected PRO measures. Latent modeling provides a mechanism to use patient-reported data on a population level to identify distinct subgroups of patients with unmet palliative needs

The supersymmetric interpretation of the EGRET excess of diffuse Galactic gamma rays

Recently it was shown that the excess of diffuse Galactic gamma rays above 1 GeV traces the Dark Matter halo, as proven by reconstructing the peculiar shape of the rotation curve of our Galaxy from the gamma ray excess. This can be interpreted as a Dark Matter annihilation signal. In this paper we investigate if this interpretation is consistent with Supersymmetry. It is found that the EGRET excess combined with all electroweak constraints is fully consistent with the minimal mSUGRA model for scalars in the TeV range and gauginos below 500 GeV.Comment: 11 pages, 6 figures, extended version with more figures, as accepted for publication in Phys. Letters

Facility-level characteristics associated with family planning and child immunization services integration in urban areas of Nigeria: a longitudinal analysis

Background: Unmet need for postpartum contraception is high. Integration of family planning with routine child immunization services may help to satisfy unmet need. However, evidence about the determinants and effects of integration has been inconsistent, and more evidence is required to ascertain whether and how to invest in integration. In this study, facility-level family planning and immunization integration index scores are used to: (1) determine whether integration changes over time and (2) identify whether facility-level characteristics, including exposure to the Nigerian Urban Reproductive Health Initiative (NURHI), are associated with integration across facilities in six urban areas of Nigeria. Methods: This study utilizes health facility data collected at baseline (n = 400) and endline (n = 385) for the NURHI impact evaluation. Difference-in-differences models estimate the associations between facility-level characteristics, including exposure to NURHI, and Provider and Facility Integration Index scores. The two outcome measures, Provider and Facility Integration Index scores, reflect attributes that support integrated service delivery. These indexes, which range from 0 (low) to 10 (high), were constructed using principal component analysis. Scores were calculated for each facility. Independent variables are (1) time period, (2) whether the facility received the NURHI intervention, and (3) additional facility-level characteristics. Results: Within intervention facilities, mean Provider Integration Index scores were 6.46 at baseline and 6.79 at endline; mean Facility Integration Index scores were 7.16 (baseline) and 7.36 (endline). Within non-intervention facilities, mean Provider Integration Index scores were 5.01 at baseline and 6.25 at endline; mean Facility Integration Index scores were 5.83 (baseline) and 6.12 (endline). Provider Integration Index scores increased significantly (p = 0.00) among non-intervention facilities. Facility Integration Index scores did not increase significantly in either group. Results identify facility-level characteristics associated with higher levels of integration, including smaller family planning client load, family planning training among providers, and public facility ownership. Exposure to NURHI was not associated with integration index scores. Conclusion: Programs aiming to increase integration of family planning and immunization services should monitor and provide targeted support for the implementation of a well-defined integration strategy that considers the influence of facility characteristics and concurrent initiatives

Development of integration indexes to determine the extent of family planning and child immunization services integration in health facilities in urban areas of Nigeria

Background: Integrating family planning into child immunization services may address unmet need for contraception by offering family planning information and services to postpartum women during routine child immunization visits. However, policies and programs promoting integration are often based on insubstantial or conflicting evidence about its effects on service delivery and health outcomes. While integration models vary, many studies measure integration as binary (a facility is integrated or not) rather than a multidimensional and varying continuum. It is thus challenging to ascertain the determinants and effects of integrated service delivery. This study creates Facility and Provider Integration Indexes, which measure capacity to support integrated family planning and child immunization services and applies them to analyze the extent of integration across 400 health facilities. Methods: This study utilizes cross-sectional health facility (N = 400; 58% hospitals, 42% primary healthcare centers) and healthcare provider (N = 1479) survey data that were collected in six urban areas of Nigeria for the impact evaluation of the Nigerian Urban Reproductive Health Initiative. Principal Component Analysis was used to develop Provider and Facility Integration Indexes that estimate the extent of integration in these health facilities. The Provider Integration Index measures provider skills and practices that support integrated service delivery while the Facility Integration Index measures facility norms that support integrated service delivery. Index scores range from zero (low) to ten (high). Results: Mean Provider Integration Index score is 5.42 (SD 3.10), and mean Facility Integration Index score is 6.22 (SD 2.72). Twenty-three percent of facilities were classified as having low Provider Integration scores, 32% as medium, and 45% as high. Fourteen percent of facilities were classified as having low Facility Integration scores, 38% as medium, and 48% as high. Conclusion: Many facilities in our sample have achieved high levels of integration, while many others have not. Results suggest that using more nuanced measures of integration may (a) more accurately reflect true variation in integration within and across health facilities, (b) enable more precise measurement of the determinants or effects of integration, and (c) provide more tailored, actionable information about how best to improve integration. Overall, results reinforce the importance of utilizing more nuanced measures of facility-level integration