The polymer mat: Arrested rebound of a compressed polymer layer

Compression of an adsorbed polymer layer distorts its relaxed structure. Surface force measurements from different laboratories show that the return to this relaxed structure after the compression is released can be slowed to the scale of tens of minutes and that the recovery time grows rapidly with molecular weight. We argue that the arrested state of the free layer before relaxation can be described as a Guiselin brush structure1, in which the surface excess lies at heights of the order of the layer thickness, unlike an adsorbed layer. This brush structure predicts an exponential falloff of the force at large distance with a decay length that varies as the initial compression distance to the 6/5 power. This exponential falloff is consistent with surface force measurements. We propose a relaxation mechanism that accounts for the increase in relaxation time with chain length.Comment: 24 pages, 5 figre

Multi-instance multi-label learning in the presence of novel class instances

Multi-instance multi-label learning (MIML) is a framework for learning in the presence of label ambiguity. In MIML, experts provide labels for groups of instances (bags), instead of directly providing a label for every instance. When labeling efforts are focused on a set of target classes, instances outside this set will not be appropriately modeled. For example, ornithologists label bird audio recordings with a list of species present. Other additional sound instances, e.g., a rain drop or a moving vehicle sound, are not labeled. The challenge is due to the fact that for a given bag, the presence or absence of novel instances is latent. In this paper, this problem is addressed using a discriminative probabilistic model that accounts for novel instances. We propose an exact and efficient implementation of the maximum likelihood approach to determine the model parameters and consequently learn an instance-level classifier for all classes including the novel class. Experiments on both synthetic and real datasets illustrate the effectiveness of the proposed approach

Demographic, Presentation, and Treatment Factors and Racial Disparities in Ovarian Cancer Hospitalization Outcomes

BACKGROUND: This study examines whether racial disparities in hospitalization outcomes persist between African-American and White women with ovarian cancer after matching on demographic, presentation, and treatment factors. METHODS: Using data from the Nationwide Inpatient Sample database, 5,164 African-American ovarian cancer patients were sequentially matched with White patients on demographic (e.g., age, income), presentation (e.g., stage, comorbidities), and treatment (e.g., surgery, radiation) factors. Racial differences in-hospital length of stay, post-operative complications, and in-hospital mortality were evaluated using conditional logistic regression models. RESULTS: White ovarian cancer patients had relatively higher odds of post-operative complications when matched on demographics (OR 1.35, 95% CI 1.05, 1.74), and presentation (OR 1.28, 95% CI 1.00, 1.65) but not when additionally matched on treatment (OR 1.03, 95% CI 0.78, 1.35). African-American patients had longer in-hospital length of stay (6.96 ± 7.21 days) compared with White patients when matched on demographics (6.37 ± 7.07 days), presentation (6.48 ± 7.16 days), and treatment (6.53 ± 7.59 days). Compared with African-American patients, White patients experienced lower odds of in-hospital mortality when matched on demographics (OR 0.78, 95% CI 0.66, 0.92), but this disparity was no longer significant when additionally matched on presentation (OR 0.88, 95% CI 0.75, 1.04) and treatment (OR 0.95, 95% CI 0.81, 1.12). CONCLUSION: Racial disparities in ovarian cancer hospitalization outcomes persisted after adjusting for demographic and presentation factors; however these differences were eliminated after additionally accounting for treatment factors. More studies are needed to determine the factors driving racial differences in ovarian cancer treatment in otherwise similar patient populations

Fluid and Diffusion Limits for Bike Sharing Systems

Bike sharing systems have rapidly developed around the world, and they are served as a promising strategy to improve urban traffic congestion and to decrease polluting gas emissions. So far performance analysis of bike sharing systems always exists many difficulties and challenges under some more general factors. In this paper, a more general large-scale bike sharing system is discussed by means of heavy traffic approximation of multiclass closed queueing networks with non-exponential factors. Based on this, the fluid scaled equations and the diffusion scaled equations are established by means of the numbers of bikes both at the stations and on the roads, respectively. Furthermore, the scaling processes for the numbers of bikes both at the stations and on the roads are proved to converge in distribution to a semimartingale reflecting Brownian motion (SRBM) in a $N^{2}$-dimensional box, and also the fluid and diffusion limit theorems are obtained. Furthermore, performance analysis of the bike sharing system is provided. Thus the results and methodology of this paper provide new highlight in the study of more general large-scale bike sharing systems.Comment: 34 pages, 1 figure

A theoretical and numerical study of a phase field higher-order active contour model of directed networks.

We address the problem of quasi-automatic extraction of directed networks, which have characteristic geometric features, from images. To include the necessary prior knowledge about these geometric features, we use a phase field higher-order active contour model of directed networks. The model has a large number of unphysical parameters (weights of energy terms), and can favour different geometric structures for different parameter values. To overcome this problem, we perform a stability analysis of a long, straight bar in order to find parameter ranges that favour networks. The resulting constraints necessary to produce stable networks eliminate some parameters, replace others by physical parameters such as network branch width, and place lower and upper bounds on the values of the rest. We validate the theoretical analysis via numerical experiments, and then apply the model to the problem of hydrographic network extraction from multi-spectral VHR satellite images

Application of the cross-entropy method to the buffer allocation problem in a simulation-based environment

The buffer allocation problem (BAP) is a well-known difficult problem in the design of production lines. We present a stochastic algorithm for solving the BAP, based on the cross-entropy method, a new paradigm for stochastic optimization. The algorithm involves the following iterative steps: (a) the generation of buffer allocations according to a certain random mechanism, followed by (b) the modification of this mechanism on the basis of cross-entropy minimization. Through various numerical experiments we demonstrate the efficiency of the proposed algorithm and show that the method can quickly generate (near-)optimal buffer allocations for fairly large production lines

Actuation of Micro-Optomechanical Systems Via Cavity-Enhanced Optical Dipole Forces

We demonstrate a new type of optomechanical system employing a movable, micron-scale waveguide evanescently-coupled to a high-Q optical microresonator. Micron-scale displacements of the waveguide are observed for milliwatt(mW)-level optical input powers. Measurement of the spatial variation of the force on the waveguide indicates that it arises from a cavity-enhanced optical dipole force due to the stored optical field of the resonator. This force is used to realize an all-optical tunable filter operating with sub-mW control power. A theoretical model of the system shows the maximum achievable force to be independent of the intrinsic Q of the optical resonator and to scale inversely with the cavity mode volume, suggesting that such forces may become even more effective as devices approach the nanoscale.Comment: 4 pages, 5 figures. High resolution version available at (http://copilot.caltech.edu/publications/CEODF_hires.pdf). For associated movie, see (http://copilot.caltech.edu/research/optical_forces/index.htm

Tension Dynamics and Linear Viscoelastic Behavior of a Single Semiflexible Polymer Chain

We study the dynamical response of a single semiflexible polymer chain based on the theory developed by Hallatschek et al. for the wormlike-chain model. The linear viscoelastic response under oscillatory forces acting at the two chain ends is derived analytically as a function of the oscillation frequency . We shall show that the real part of the complex compliance in the low frequency limit is consistent with the static result of Marko and Siggia whereas the imaginary part exhibits the power-law dependence +1/2. On the other hand, these compliances decrease as the power law -7/8 for the high frequency limit. These are different from those of the Rouse dynamics. A scaling argument is developed to understand these novel results.Comment: 23 pages, 6 figure