The motion of the freely falling chain tip

The dynamics of the tip of the falling chain is analyzed. Results of laboratory experiments are presented and compared with results of numerical simulations. Time dependences of the velocity and the acceleration of the chain tip for a number of different initial conformations of the chain are determined. A simple analytical model of the system is also considered.Comment: 29 pages, 13 figure

The motion of whips and chains

We study the motion of an inextensible string (a whip) fixed at one point in the absence of gravity, satisfying the equations $$\eta_{tt} = \partial_s(\sigma \eta_s), \qquad \sigma_{ss}-\lvert \eta_{ss}\rvert^2 = -\lvert \eta_{st}\rvert^2, \qquad \lvert \eta_s\rvert^2 \equiv 1$$ with boundary conditions $\eta(t,1)=0$ and $\sigma(t,0)=0$. We prove local existence and uniqueness in the space defined by the weighted Sobolev energy $$\sum_{\ell=0}^m \int_0^1 s^{\ell} \lvert \partial_s^{\ell}\eta_t\rvert^2 \, ds + \int_0^1 s^{\ell+1} \lvert \partial_s^{\ell+1}\eta\rvert^2 \, ds,$$ when $m\ge 3$. In addition we show persistence of smooth solutions as long as the energy for $m=3$ remains bounded. We do this via the method of lines, approximating with a discrete system of coupled pendula (a chain) for which the same estimates hold.Comment: 47 pages, 8 figure

Ariel - Volume 12(13) Number 2

Editor Gary Fishbein Production & Business Manager Rich Davis Layout Editor Lynn Solomon Assistant Layout Editors Bessann Dawson Tonie Kline Becky A. Zuurbier Photography Editor Ben Alma

Management of Bladder Cancer following Solid Organ Transplantation

Objective. Present our experience managing bladder cancer following liver and renal transplantation. Methods. Single institution retrospective review of patients diagnosed with bladder urothelial carcinoma (BUC) following solid organ transplantation between January 1992 and December 2007. Results. Of the 2,925 renal and 2,761 liver transplant recipients reviewed, we identified eleven patients (0.2%) following transplant diagnosed with BUC. Two patients with low grade T1 TCC were managed by TURBT. Three patients with CIS and one patient with T1 low grade BUC were treated by TURBT and adjuvant BCG. All four are alive and free of recurrence at a mean follow-up of 51 ± 22 months. One patient with T1 high grade BUC underwent radical cystectomy and remains disease free with a follow-up of 98 months. Muscle invasive TCC was diagnosed in four patients at a median of 3.6 years following transplantation. Two patients are recurrence free at 24 and 36 months following radical cystectomy. Urinary diversion and palliative XRT were performed in one patient with un-resectable disease. Conclusions. Bladder cancer is uncommon following renal and liver transplantation, but it can be managed successfully with local and/or extirpative therapy. The use of intravesical BCG is possible in select immunosuppressed patients

Development of the Adherence Predictive Index (API) for Medication Taking

The objective for this study was to explore if characteristics of personality type using the Preferred Communication Style Questionnaire, in concert with the demographic characteristics of age, education, and race/ethnicity, are associated with, and help predict, individuals’ medication adherence behavior. Data were collected via an on-line survey, sent to a sample of adults residing in the United States, between April 28 and June 22, 2015. Out of 26,173 responses to the survey, 16,736 reported taking one or more medications and were eligible for inclusion in this study. The development of the Adherence Predictive Index (API) used mean Morisky Medication Adherence Scale (MMAS-8) scores for each of eight personality types as a starting point. API scores were calculated by adding or subtracting specific values to each group’s mean MMAS-8 score based on personality type, age, education and race/ethnicity characteristics which were demonstrated to have significant effects on adherence. The weighting system was informed by linear regression, logistic regression, personality type literature, researcher experience, and previous qualitative and quantitative research. The resultant score was converted to an API score that ranged from 1 to 5 so that it would be feasible for health care providers to understand and use. The findings showed that an Adherence Predictive Index (API) could be developed based upon a relatively small number of questions that focus on personality type and generational, educational, and cultural experiences. It was developed in order to be a component of a comprehensive program that has the goals of (1) identifying and describing specific behavioral strategies individuals are most likely to successfully employ, (2) motivating patients by using their preferred communication style, and (3) predicting each patient’s propensity to adhere. Future research is needed to evaluate the index’s validity, sensitivity, and effectiveness in actual practice compared with other risk indices

Development of the Adherence Predictive Index (API) for Medication Taking

The objective for this study was to explore if characteristics of personality type using the Preferred Communication Style Questionnaire, in concert with the demographic characteristics of age, education, and race/ethnicity, are associated with, and help predict, individuals’ medication adherence behavior. Data were collected via an on-line survey, sent to a sample of adults residing in the United States, between April 28 and June 22, 2015. Out of 26,173 responses to the survey, 16,736 reported taking one or more medications and were eligible for inclusion in this study. The development of the Adherence Predictive Index (API) used mean Morisky Medication Adherence Scale (MMAS-8) scores for each of eight personality types as a starting point. API scores were calculated by adding or subtracting specific values to each group’s mean MMAS-8 score based on personality type, age, education and race/ethnicity characteristics which were demonstrated to have significant effects on adherence. The weighting system was informed by linear regression, logistic regression, personality type literature, researcher experience, and previous qualitative and quantitative research. The resultant score was converted to an API score that ranged from 1 to 5 so that it would be feasible for health care providers to understand and use. The findings showed that an Adherence Predictive Index (API) could be developed based upon a relatively small number of questions that focus on personality type and generational, educational, and cultural experiences. It was developed in order to be a component of a comprehensive program that has the goals of (1) identifying and describing specific behavioral strategies individuals are most likely to successfully employ, (2) motivating patients by using their preferred communication style, and (3) predicting each patient’s propensity to adhere. Future research is needed to evaluate the index’s validity, sensitivity, and effectiveness in actual practice compared with other risk indices.   Type: Original Researc