Distinctive field dependence of the longitudinal muon polarization for Mu* in polycrystalline silicon

A distinctive longitudinal magnetic field dependence of the muon polarization for anomalous muonium in polycrystalline semiconductor targets has been predicted. The polarization exhibits a cusp,i.e., a discontinuous jump in the slope from negative to positive. Measurements of the longitudinal polarization for polycrystalline silicon in fields up to 0.5 T, and temperatures 53 and 200 K have been made at LAMPF. A cusp in the field dependence indeed occurs at 0.345 T, in excellent agreement with the prediction. No cusp is observed at 200 K because Mu^* has been thermally ionized.     

Using an Integer Programming Model to Determine the Price of Combination Vaccines for Childhood Immunization

The Recommended Childhood Immunization Schedule has become sufficiently crowded that the prospect of adding additional vaccines to this schedule may not be well received by either health-care providers or parents/guardians. This has encouraged vaccine manufacturers to develop combination vaccines that can permit new vaccines to be added to the schedule without requiring children to be exposed to an unacceptable number of injections during a single clinic visit. This paper develops an integer programming model to assess the economic premium that exists in having combination vaccines available. The results of this study suggest that combination vaccines provide a cost effective alternative to individual vaccines and that further developments and innovations in this area by vaccine manufacturers can provide significant economic and societal benefits.     

Generalized sum graphs

Harary [8] calls a finite, simple graphG asum graph if one can assign to eachv _i V(G) a labelx _i so that{v _i ,v _j }E(G) iffx _i +x _j =x _k for somek. We generalize this notion by replacing x _i +x _j with an arbitrary symmetric polynomialf(x _i ,x _j ). We show that for eachf, not all graphs are f-graphs. Furthermore, we prove that for everyf and every graphG we can transformG into anf-graph via the addition of |E(G)| isolated vertices. This result is nearly best possible in the sense that for allf and for , there is a graphG withn vertices andm edges which, even after the addition ofm-O(n logn) isolated vetices, is not andf-graph.Research supported in part by a U.S.A.-Israel Binational Science Foundation and by a Bergmann Memorial Grant.Research supported in part by the Office of Naval Research contract number N00014-85-K0622.     

Kinetics of epidermal growth factor/receptor binding on cells measured by total internal reflection/fluorescence recovery after photobleaching

Total internal reflection fluorescence (TIRF) microscopy is used to measure the dissociation kinetic rate of fluorescein-labeled epidermal growth factor from its specific receptors on the surface of intact but mildly fixed A431 human epidermoid cells in culture. Prior applications of TIRF microscopy have been limited to nonreceptor binding or to model membrane systems. The evanescent field excites fluorescence selectively at the surface of the cell proximal to the coverslip. Prismless epiillumination TIR is employed to avoid space limitations and is achieved by passing the excitation laser beam through a high (1.4)-aperture objective so that the light is incident at the glass/water interface beyond the critical angle. Long-term focus is maintained by a special feedback system. Of the possible effects that can influence the time course of the postbleach fluorescence recoveries—the EGF/receptor dissociation ratek ₂, the bulk solution diffusion rate of EGF, and the cell surface motion of the receptors—we infer that the dissociation ratek ₂ dominates. Several fitting schemes are compared and indicate the presence of a multiplicity of values fork ₂, ranging from about 0.05 to 0.004 s^–1, with an average value of about 0.012 s^–1. These results compare well with values previously obtained by radiolabel/washing techniques. The significance of the results in terms of kinetic models and the advantages of the TIRF technique for these sorts of measurements are discussed.     

流动系统中鲁米诺电生化学发光(ECL)系统研究初探

本文描述了一个新的鲁米诺电生化学发光流动系统.通过微铂电极流动池,H2O2被还原为OH-以维持鲁米诺化学发光所要求的pH条件.本文对鲁米诺化学发光机理进行了初步探讨,并详细研究了ECL的最佳条件,该系统明显降低了反应噪声,优于混合反应系统,可作为液相色谱间接测定检测器.     

Survival of Virus Particles in Water Droplets: Hydrophobic Forces and Landauer’s Principle

Many small biological objects, such as viruses, survive in a water environment and cannot remain active in dry air without condensation of water vapor. From a physical point of view, these objects belong to the mesoscale, where small thermal fluctuations with the characteristic kinetic energy of k_BT (where k_B is the Boltzmann’s constant and T is the absolute temperature) play a significant role. The self-assembly of viruses, including protein folding and the formation of a protein capsid and lipid bilayer membrane, is controlled by hydrophobic forces (i.e., the repulsing forces between hydrophobic particles and regions of molecules) in a water environment. Hydrophobic forces are entropic, and they are driven by a system’s tendency to attain the maximum disordered state. On the other hand, in information systems, entropic forces are responsible for erasing information, if the energy barrier between two states of a switch is on the order of k_BT, which is referred to as Landauer’s principle. We treated hydrophobic interactions responsible for the self-assembly of viruses as an information-processing mechanism. We further showed a similarity of these submicron-scale processes with the self-assembly in colloidal crystals, droplet clusters, and liquid marbles.     

Multilevel Deep Feature Generation Framework for Automated Detection of Retinal Abnormalities Using OCT Images

Optical coherence tomography (OCT) images coupled with many learning techniques have been developed to diagnose retinal disorders. This work aims to develop a novel framework for extracting deep features from 18 pre-trained convolutional neural networks (CNN) and to attain high performance using OCT images. In this work, we have developed a new framework for automated detection of retinal disorders using transfer learning. This model consists of three phases: deep fused and multilevel feature extraction, using 18 pre-trained networks and tent maximal pooling, feature selection with ReliefF, and classification using the optimized classifier. The novelty of this proposed framework is the feature generation using widely used CNNs and to select the most suitable features for classification. The extracted features using our proposed intelligent feature extractor are fed to iterative ReliefF (IRF) to automatically select the best feature vector. The quadratic support vector machine (QSVM) is utilized as a classifier in this work. We have developed our model using two public OCT image datasets, and they are named database 1 (DB1) and database 2 (DB2). The proposed framework can attain 97.40% and 100% classification accuracies using the two OCT datasets, DB1 and DB2, respectively. These results illustrate the success of our model.     

Complex flows by nanohydrodynamics

The study of complex flows by particle simulations is speeded up over molecular dynamics (MD) by more than two orders of magnitude by employing a stochastic collision dynamics method (DSMC) extended to high density (CBA). As a consequence, a picture generated on a single processor shows the typical features of the Rayleigh–Taylor instability and is in quantitative agreement with the experimentally found long time behaviour.