Stochastic programming for nurse assignment

We present a brief overview of four phases of nurse planning. For the last phase, which assigns nurses to patients, a stochastic integer programming model is developed. A Benders’ decomposition approach is proposed to solve this problem, and a greedy algorithm is employed to solve the recourse subproblem. To improve the efficiency of the algorithm, we introduce sets of valid inequalities to strengthen a relaxed master problem. Computational results are provided based upon data from Baylor Regional Medical Center in Grapevine, Texas. Finally, areas of future research are discussed.     

Design and fabrication of non-superparamagnetic high moment magnetic nanoparticles for bioapplications

We present a new type of magnetic nanoparticles for bioapplications. Multilayered nanodisks consisting of two magnetic layers separated by a non-magnetic layer with two capping layers were designed and fabricated. Two key magnetic requirements for bioapplications, a high saturation magnetic moment and a near-zero remanence, were achieved through the magnetostatic interlayer coupling between two magnetic layers. Capping layers provide functionalization sites for biomolecule attachment. A pillar-template-based synthesis method was employed for fabrication. Nanodisks with a diameter of 70 nm and a thickness of 60 nm were produced in large quantity. The magnetic characterization shows that each nanodisk possesses a magnetic moment equivalent to 100 10-nm Co nanoparticles and a near-zero remanent moment.