Multi-Bit Relaying over a Tandem of Channels

We study error exponents for the problem of relaying a message over a tandem of two channels sharing the same transition law, in particular moving beyond the 1-bit setting studied in recent related works. Our main results show that the 1-hop and 2-hop exponents coincide in both of the following settings: (i) the number of messages is fixed, and the channel law satisfies a condition called pairwise reversibility, or (ii) the channel is arbitrary, and a zero-rate limit is taken from above. In addition, we provide various extensions of our results that relax the assumptions of pairwise reversibility and/or the two channels having identical transition laws, and we provide an example for which the 2-hop exponent is strictly below the 1-hop exponent

Maxflow-Based Bounds for Low-Rate Information Propagation over Noisy Networks

We study error exponents for the problem of low-rate communication over a directed graph, where each edge in the graph represents a noisy communication channel, and there is a single source and destination. We derive maxflow-based achievability and converse bounds on the error exponent that match when there are two messages and all channels satisfy a symmetry condition called pairwise reversibility. More generally, we show that the upper and lower bounds match to within a factor of 4. We also show that with three messages there are cases where the maxflow-based error exponent is strictly suboptimal, thus showing that our tightness result cannot be extended beyond two messages without further assumptions

A Novel Model of Conforming Delaunay Triangulation for Sensor Network Configuration

Delaunay refinement is a technique for generating unstructured meshes of triangles for sensor network configuration engineering practice. A new method for solving Delaunay triangulation problem is proposed in this paper, which is called endpoint triangle’s circumcircle model (ETCM). As compared with the original fractional node refinement algorithms, the proposed algorithm can get well refinement stability with least time cost. Simulations are performed under five aspects including refinement stability, the number of additional nodes, time cost, mesh quality after intruding additional nodes, and the aspect ratio improved by single additional node. All experimental results show the advantages of the proposed algorithm as compared with the existing algorithms and confirm the algorithm analysis sufficiently

Max-Quantile Grouped Infinite-Arm Bandits

In this paper, we consider a bandit problem in which there are a number of groups each consisting of infinitely many arms. Whenever a new arm is requested from a given group, its mean reward is drawn from an unknown reservoir distribution (different for each group), and the uncertainty in the arm's mean reward can only be reduced via subsequent pulls of the arm. The goal is to identify the infinite-arm group whose reservoir distribution has the highest $(1-\alpha)$-quantile (e.g., median if $\alpha = \frac{1}{2}$), using as few total arm pulls as possible. We introduce a two-step algorithm that first requests a fixed number of arms from each group and then runs a finite-arm grouped max-quantile bandit algorithm. We characterize both the instance-dependent and worst-case regret, and provide a matching lower bound for the latter, while discussing various strengths, weaknesses, algorithmic improvements, and potential lower bounds associated with our instance-dependent upper bounds

IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning

We propose a novel framework for uncertainty quantification via information bottleneck (IB-UQ) for scientific machine learning tasks, including deep neural network (DNN) regression and neural operator learning (DeepONet). Specifically, we incorporate the bottleneck by a confidence-aware encoder, which encodes inputs into latent representations according to the confidence of the input data belonging to the region where training data is located, and utilize a Gaussian decoder to predict means and variances of outputs conditional on representation variables. Furthermore, we propose a data augmentation based information bottleneck objective which can enhance the quantification quality of the extrapolation uncertainty, and the encoder and decoder can be both trained by minimizing a tractable variational bound of the objective. In comparison to uncertainty quantification (UQ) methods for scientific learning tasks that rely on Bayesian neural networks with Hamiltonian Monte Carlo posterior estimators, the model we propose is computationally efficient, particularly when dealing with large-scale data sets. The effectiveness of the IB-UQ model has been demonstrated through several representative examples, such as regression for discontinuous functions, real-world data set regression, learning nonlinear operators for partial differential equations, and a large-scale climate model. The experimental results indicate that the IB-UQ model can handle noisy data, generate robust predictions, and provide confident uncertainty evaluation for out-of-distribution data.Comment: 27 pages, 22figure

Envy-Free House Allocation with Minimum Subsidy

House allocation refers to the problem where $m$ houses are to be allocated to $n$ agents so that each agent receives one house. Since an envy-free house allocation does not always exist, we consider finding such an allocation in the presence of subsidy. We show that computing an envy-free allocation with minimum subsidy is NP-hard in general, but can be done efficiently if $m$ differs from $n$ by an additive constant or if the agents have identical utilities

Anti-tumor effect of polysaccharides from rhizome of Curculigo orchioides Gaertn on cervical cancer

Purpose: To investigate the anti-tumor effects of polysaccharides from Curculigo orchioides (PDC) on cervical cancer and the possible mechanisms involved.Methods: A Box–Behnken design (BBD) was employed to optimize extraction conditions for PDC. The anti-tumor effect of PDC on cervical cancer was investigated in vivo in mice injected with Hela cells. The parameters measured were tumor volume and weight. In vitro anti-tumor effects of PDC were assessed by measuring expressions of caspase-3, caspase-9 and P53 proteins in Hela cells via ELISA assay. Thymus and spleen indices were calculated for assessment of PDC effect on immune function.Results: The optimum extraction conditions predicted by the response surface methodology (RSM) were: extraction time = 1.58 h, ratio-of-water-to-sample = 30.05 mL/g and extraction number = 1.95. PDC showed significant anti-tumor effect on cervical cancer in mice. It significantly increased thymus and spleen indices in mice; and significantly up-regulated expressions of caspase-3, caspase-9 and P53 proteins in HeLa cells.Conclusion: PDC has significant anti-tumor effect on cervical cancer in vivo and in vitro, most probably through mechanisms involving enhancement on immune function and induction of apoptosis.Keyword: Curculigo orchioides, Polysaccharides, Cervical cancer, HeLa cells, Apoptosi

Two-photon interference with two independent pseudo-thermal sources

The nature of two-photon interference is a subject that has aroused renewed interest in recent years and is still under debate. In this paper we report the first observation of two-photon interference with independent pseudo-thermal sources in which sub-wavelength interference is observed. The phenomenon may be described in terms of the classical statistical distribution of the two sources and their optical transfer functions.Comment: Phys. Rev. A 74, 053807 (2006

Correlated two-photon imaging with true thermal light

We report the first experimental demonstration of two-photon correlated imaging with true thermal light from a hollow cathode lamp. The coherence time of the source is much shorter than that of previous experiments using random scattered light from a laser. A two-pinhole mask was used as object, and the corresponding thin lens equation was well satisfied. Since thermal light sources are easier to obtain and measure than entangled light it is conceivable that they may be used in special imaging applications.Comment: 3 pages, 5 figures, accepted by Optics Letter