Analysis of Noisy Evolutionary Optimization When Sampling Fails

In noisy evolutionary optimization, sampling is a common strategy to deal with noise. By the sampling strategy, the fitness of a solution is evaluated multiple times (called \emph{sample size}) independently, and its true fitness is then approximated by the average of these evaluations. Previous studies on sampling are mainly empirical. In this paper, we first investigate the effect of sample size from a theoretical perspective. By analyzing the (1+1)-EA on the noisy LeadingOnes problem, we show that as the sample size increases, the running time can reduce from exponential to polynomial, but then return to exponential. This suggests that a proper sample size is crucial in practice. Then, we investigate what strategies can work when sampling with any fixed sample size fails. By two illustrative examples, we prove that using parent or offspring populations can be better. Finally, we construct an artificial noisy example to show that when using neither sampling nor populations is effective, adaptive sampling (i.e., sampling with an adaptive sample size) can work. This, for the first time, provides a theoretical support for the use of adaptive sampling

TRPV4, TRPC1, and TRPP2 assemble to form a flow-sensitive heteromeric channel

Transient receptor potential (TRP) channels, a superfamily of ion channels, can be divided into 7 subfamilies, including TRPV, TRPC, TRPP, and 4 others. Functional TRP channels are tetrameric complexes consisting of 4 pore-forming subunits. The purpose of this study was to explore the heteromerization of TRP subunits crossing different TRP subfamilies. Two-step coimmunoprecipitation (co-IP) and fluorescence resonance energy transfer (FRET) were used to determine the interaction of the different TRP subunits. Patch-clamp and cytosolic Ca2+ measurements were used to determine the functional role of the ion channels in flow conditions. The analysis demonstrated the formation of a heteromeric TRPV4-C1-P2 complex in primary cultured rat mesenteric artery endothelial cells (MAECs) and HEK293 cells that were cotransfected with TRPV4, TRPC1, and TRPP2. In functional experiments, pore-dead mutants for each of these 3 TRP isoforms nearly abolished the flow-induced cation currents and Ca2+ increase, suggesting that all 3 TRPs contribute to the ion permeation pore of the channels. We identified the first heteromeric TRP channels composed of subunits from 3 different TRP subfamilies. Functionally, this heteromeric TRPV4- C1-P2 channel mediates the flow-induced Ca2+ increase in native vascular endothelial cells.-Du, J., Ma, X., Shen, B., Huang, Y., Birnbaumer, L., Yao, X. TRPV4, TRPC1, and TRPP2 assemble to form a flowsensitive heteromeric channel.Fil: Du, Juan. Chinese University Of Hong Kong; Hong Kong. Anhui Medical University; ChinaFil: Ma, Xin. Chinese University Of Hong Kong; Hong KongFil: Shen, Bing. Chinese University Of Hong Kong; Hong Kong. Anhui Medical University; ChinaFil: Huang, Yu. Chinese University Of Hong Kong; Hong KongFil: Birnbaumer, Lutz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. National Institutes of Health; Estados UnidosFil: Yao, Xiaoqiang. Chinese University Of Hong Kong; Hong Kon

Cheating-Resilient Incentive Scheme for Mobile Crowdsensing Systems

Mobile Crowdsensing is a promising paradigm for ubiquitous sensing, which explores the tremendous data collected by mobile smart devices with prominent spatial-temporal coverage. As a fundamental property of Mobile Crowdsensing Systems, temporally recruited mobile users can provide agile, fine-grained, and economical sensing labors, however their self-interest cannot guarantee the quality of the sensing data, even when there is a fair return. Therefore, a mechanism is required for the system server to recruit well-behaving users for credible sensing, and to stimulate and reward more contributive users based on sensing truth discovery to further increase credible reporting. In this paper, we develop a novel Cheating-Resilient Incentive (CRI) scheme for Mobile Crowdsensing Systems, which achieves credibility-driven user recruitment and payback maximization for honest users with quality data. Via theoretical analysis, we demonstrate the correctness of our design. The performance of our scheme is evaluated based on extensive realworld trace-driven simulations. Our evaluation results show that our scheme is proven to be effective in terms of both guaranteeing sensing accuracy and resisting potential cheating behaviors, as demonstrated in practical scenarios, as well as those that are intentionally harsher

Dynamical properties of the S=12S=\frac{1}{2} random Heisenberg chain

We use numerical techniques to study dynamical properties at finite temperature ($T$) of the Heisenberg spin chain with random exchange couplings, which realizes the random singlet (RS) fixed point in the low-energy limit. Specifically, we study the dynamic spin structure factor $S(q,\omega)$, which can be probed directly by inelastic neutron scattering experiments and, in the limit of small $\omega$, in nuclear magnetic resonance (NMR) experiments through the spin-lattice relaxation rate $1/T_1$. Our work combines three complementary methods: exact diagonalization, matrix-product-state algorithms, and stochastic analytic continuation of quantum Monte Carlo results in imaginary time. Unlike the uniform system, whose low-energy excitations at low $T$ are restricted to $q$ close to $0$ and $\pi$, our study reveals a continuous narrow band of low-energy excitations in $S(q,\omega)$, extending throughout the Brillouin zone. Close to $q=\pi$, the scaling properties of these excitations are well captured by the RS theory, but we also see disagreements with some aspects of the predicted $q$-dependence further away from $q=\pi$. Furthermore we find spin diffusion effects close to $q=0$ that are not contained within the RS theory but give non-negligible contributions to the mean $1/T_1$. To compare with NMR experiments, we consider the distribution of the local $1/T_1$ values, which is broad, approximately described by a stretched exponential. The mean value first decreases with $T$, but starts to increase and diverge below a crossover temperature. Although a similar divergent behavior has been found for the static uniform susceptibility, this divergent behavior of $1/T_1$ has never been seen in experiments. Our results show that the divergence of the mean $1/T_1$ is due to rare events in the disordered chains and is concealed in experiments, where the typical $1/T_1$ value is accessed.Comment: 19 pages, 14 figure

Possible singlet and triplet superconductivity on honeycomb lattice

We study the possible superconducting pairing symmetry mediated by spin and charge fluctuations on the honeycomb lattice using the extended Hubbard model and the random-phase-approximation method. From $2\%$ to $20\%$ doping levels, a spin-singlet $d_{x^{2}-y^{2}}+id_{xy}$-wave is shown to be the leading superconducting pairing symmetry when only the on-site Coulomb interaction $U$ is considered, with the gap function being a mixture of the nearest-neighbor and next-nearest-neighbor pairings. When the offset of the energy level between the two sublattices exceeds a critical value, the most favorable pairing is a spin-triplet $f$-wave which is mainly composed of the next-nearest-neighbor pairing. We show that the next-nearest-neighbor Coulomb interaction $V$ is also in favor of the spin-triplet $f$-wave pairing.Comment: 6 pages, 4 figure