Dirac Coupled-channel Analyses of Polarized Proton Scatterings to the 2+^+ Gamma Vibrational Band in 24^{24}Mg and 26^{26}Mg

Dirac coupled channel calculations are performed phenomenologically for the high-lying excited states that belong to the 2$^+$ gamma vibrational band at the 800-MeV polarized proton inelastic scatterings from the s-d shell nuclei, $^{24}$Mg and $^{26}$Mg. Optical potential model is used and scalar and time-like vector potentials are considered as direct potentials. First-order vibrational collective models are used to obtain the transition optical potentials in order to accommodate the high-lying excited vibrational collective states. The complicated Dirac coupled channel equations are solved phenomenologically to reproduce the differential cross section and analyzing power data by varying the optical potential and deformation parameters. It is found that the relativistic Dirac coupled channel calculation could describe the high-lying excited states of the 2$^+$ gamma vibrational band at the 800-MeV polarized proton inelastic scatterings from s-d shell nuclei $^{24}$Mg and $^{26}$Mg reasonably well, showing better agreement with the experimental data compared to the results obtained from the nonrelativistic calculations. Calculated deformation parameters for the excited states are analyzed and compared with those of nonrelativistic calculations.Comment: 13pages, 6 figures. arXiv admin note: text overlap with arXiv:1501.00650, arXiv:1407.5441, arXiv:1511.0172

Identification of Hessian matrix in distributed gradient-based multi-agent coordination control systems

Multi-agent coordination control usually involves a potential function that encodes information of a global control task, while the control input for individual agents is often designed by a gradient-based control law. The property of Hessian matrix associated with a potential function plays an important role in the stability analysis of equilibrium points in gradient-based coordination control systems. Therefore, the identification of Hessian matrix in gradient-based multi-agent coordination systems becomes a key step in multi-agent equilibrium analysis. However, very often the identification of Hessian matrix via the entry-wise calculation is a very tedious task and can easily introduce calculation errors. In this paper we present some general and fast approaches for the identification of Hessian matrix based on matrix differentials and calculus rules, which can easily derive a compact form of Hessian matrix for multi-agent coordination systems. We also present several examples on Hessian identification for certain typical potential functions involving edge-tension distance functions and triangular-area functions, and illustrate their applications in the context of distributed coordination and formation control

Punishment and Welfare: Paternal Incarceration and Families’ Receipt of Public Assistance

The US criminal justice and welfare systems together form important government interventions into the lives of the poor. This paper considers how imprisonment is related to welfare receipt for offenders and their families. Using longitudinal data from the Fragile Families and Child Wellbeing study, it investigates how recent paternal incarceration is associated with families' receipt of TANF, food stamps, and Medicaid/SCHIP. Results robust to multiple tests find that incarceration does not increase the likelihood of TANF receipt but significantly increases food stamps and Medicaid/SCHIP receipt. Further, the effect of incarceration on welfare receipt is larger than the recent loss of father's employment. The findings suggest that an unexpected consequence of mass imprisonment is the expansion of government regulation through welfare provision for offender's families.Fragile Families and Child Wellbeing study, imprisonment, welfare, criminal justice, welfare system, food stamps, Medicaid/SCHIP, incarceration

Daytime Locations in Spatial Mismatch: Job Accessibility and Employment at Reentry From Prison.

Individuals recently released from prison confront many barriers to employment. One potential obstacle is spatial mismatch-the concentration of low-skilled, nonwhite job-seekers within central cities and the prevalence of relevant job opportunities in outlying areas. Prior research has found mixed results about the importance of residential place for reentry outcomes. In this article, we propose that residential location matters for finding work, but this largely static measure does not capture the range of geographic contexts that individuals inhabit throughout the day. We combine novel, real-time GPS information on daytime locations and self-reported employment collected from smartphones with sophisticated measures of job accessibility to test the relative importance of spatial mismatch based on residence and daytime locations. Our findings suggest that the ability of low-skilled, poor, and urban individuals to compensate for their residential deficits by traveling to job-rich areas is an overlooked and salient consideration in spatial mismatch perspectives