Structure of 55Sc and development of the N=34 subshell closure

The low-lying structure of $^{55}$Sc has been investigated using in-beam $\gamma$-ray spectroscopy with the $^{9}$Be($^{56}$Ti,$^{55}$Sc+$\gamma$)$X$ one-proton removal and $^{9}$Be($^{55}$Sc,$^{55}$Sc+$\gamma$)$X$ inelastic-scattering reactions at the RIKEN Radioactive Isotope Beam Factory. Transitions with energies of 572(4), 695(5), 1539(10), 1730(20), 1854(27), 2091(19), 2452(26), and 3241(39) keV are reported, and a level scheme has been constructed using $\gamma\gamma$ coincidence relationships and $\gamma$-ray relative intensities. The results are compared to large-scale shell-model calculations in the $sd$-$pf$ model space, which account for positive-parity states from proton-hole cross-shell excitations, and to it ab initio shell-model calculations from the in-medium similarity renormalization group that includes three-nucleon forces explicitly. The results of proton-removal reaction theory with the eikonal model approach were adopted to aid identification of positive-parity states in the level scheme; experimental counterparts of theoretical $1/2^{+}_{1}$ and $3/2^{+}_{1}$ states are suggested from measured decay patterns. The energy of the first $3/2^{-}$ state, which is sensitive to the neutron shell gap at the Fermi surface, was determined. The result indicates a rapid weakening of the $N=34$ subshell closure in $pf$-shell nuclei at $Z>20$, even when only a single proton occupies the $\pi f_{7/2}$ orbital

A primary care, multi-disciplinary disease management program for opioid-treated patients with chronic non-cancer pain and a high burden of psychiatric comorbidity

BACKGROUND: Chronic non-cancer pain is a common problem that is often accompanied by psychiatric comorbidity and disability. The effectiveness of a multi-disciplinary pain management program was tested in a 3 month before and after trial. METHODS: Providers in an academic general medicine clinic referred patients with chronic non-cancer pain for participation in a program that combined the skills of internists, clinical pharmacists, and a psychiatrist. Patients were either receiving opioids or being considered for opioid therapy. The intervention consisted of structured clinical assessments, monthly follow-up, pain contracts, medication titration, and psychiatric consultation. Pain, mood, and function were assessed at baseline and 3 months using the Brief Pain Inventory (BPI), the Center for Epidemiological Studies-Depression Scale scale (CESD) and the Pain Disability Index (PDI). Patients were monitored for substance misuse. RESULTS: Eighty-five patients were enrolled. Mean age was 51 years, 60% were male, 78% were Caucasian, and 93% were receiving opioids. Baseline average pain was 6.5 on an 11 point scale. The average CESD score was 24.0, and the mean PDI score was 47.0. Sixty-three patients (73%) completed 3 month follow-up. Fifteen withdrew from the program after identification of substance misuse. Among those completing 3 month follow-up, the average pain score improved to 5.5 (p = 0.003). The mean PDI score improved to 39.3 (p < 0.001). Mean CESD score was reduced to 18.0 (p < 0.001), and the proportion of depressed patients fell from 79% to 54% (p = 0.003). Substance misuse was identified in 27 patients (32%). CONCLUSIONS: A primary care disease management program improved pain, depression, and disability scores over three months in a cohort of opioid-treated patients with chronic non-cancer pain. Substance misuse and depression were common, and many patients who had substance misuse identified left the program when they were no longer prescribed opioids. Effective care of patients with chronic pain should include rigorous assessment and treatment of these comorbid disorders and intensive efforts to insure follow up

Bayesian and Markov chain Monte Carlo methods for identifying nonlinear systems in the presence of uncertainty

In this paper, the authors outline the general principles behind an approach to Bayesian system identification and highlight the benefits of adopting a Bayesian framework when attempting to identify models of nonlinear dynamical systems in the presence of uncertainty. It is then described how, through a summary of some key algorithms, many of the potential difficulties associated with a Bayesian approach can be overcome through the use of Markov chain Monte Carlo (MCMC) methods. The paper concludes with a case study, where an MCMC algorithm is used to facilitate the Bayesian system identification of a nonlinear dynamical system from experimentally observed acceleration time histories

Central Pb+Pb Collisions at 158 A GeV/c Studied by Pion-Pion Interferometry

Two-particle correlations have been measured for identified negative pions from central 158 AGeV Pb+Pb collisions and fitted radii of about 7 fm in all dimensions have been obtained. A multi-dimensional study of the radii as a function of kT is presented, including a full correction for the resolution effects of the apparatus. The cross term Rout-long of the standard fit in the Longitudinally CoMoving System (LCMS) and the vl parameter of the generalised Yano-Koonin fit are compatible with 0, suggesting that the source undergoes a boost invariant expansion. The shapes of the correlation functions in Qinv and Qspace have been analyzed in detail. They are not Gaussian but better represented by exponentials. As a consequence, fitting Gaussians to these correlation functions may produce different radii depending on the acceptance of the experimental setup used for the measurement.Comment: 13 pages including 10 figure

Search for Heavy Neutral and Charged Leptons in e+ e- Annihilation at LEP

A search for exotic unstable neutral and charged heavy leptons as well as for stable charged heavy leptons is performed with the L3 detector at LEP. Sequential, vector and mirror natures of heavy leptons are considered. No evidence for their existence is found and lower limits on their masses are set