Cyclin B1/CDK1-regulated mitochondrial bioenergetics in cell cycle progression and tumor resistance.

A mammalian cell houses two genomes located separately in the nucleus and mitochondria. During evolution, communications and adaptations between these two genomes occur extensively to achieve and sustain homeostasis for cellular functions and regeneration. Mitochondria provide the major cellular energy and contribute to gene regulation in the nucleus, whereas more than 98% of mitochondrial proteins are encoded by the nuclear genome. Such two-way signaling traffic presents an orchestrated dynamic between energy metabolism and consumption in cells. Recent reports have elucidated the way how mitochondrial bioenergetics synchronizes with the energy consumption for cell cycle progression mediated by cyclin B1/CDK1 as the communicator. This review is to recapitulate cyclin B1/CDK1 mediated mitochondrial activities in cell cycle progression and stress response as well as its potential link to reprogram energy metabolism in tumor adaptive resistance. Cyclin B1/CDK1-mediated mitochondrial bioenergetics is applied as an example to show how mitochondria could timely sense the cellular fuel demand and then coordinate ATP output. Such nucleus-mitochondria oscillation may play key roles in the flexible bioenergetics required for tumor cell survival and compromising the efficacy of anti-cancer therapy. Further deciphering the cyclin B1/CDK1-controlled mitochondrial metabolism may invent effect targets to treat resistant cancers

Elastic and non-linear stiffness of graphene: a simple approach

The recent experiment [Science \textbf{321}, 385 (2008)] on the Young's modulus and third-order elastic stiffness of graphene are well explained in a very simple approach, where the graphene is described by a simplified system and the force constant for the non-linear interaction is estimated from the Tersoff-Brenner potential.Comment: 4 pages, 4 figure

Algorithms and Adaptivity Gaps for Stochastic k-TSP

Given a metric $(V,d)$ and a $\textsf{root} \in V$, the classic \textsf{k-TSP} problem is to find a tour originating at the $\textsf{root}$ of minimum length that visits at least $k$ nodes in $V$. In this work, motivated by applications where the input to an optimization problem is uncertain, we study two stochastic versions of \textsf{k-TSP}. In Stoch-Reward $k$-TSP, originally defined by Ene-Nagarajan-Saket [ENS17], each vertex $v$ in the given metric $(V,d)$ contains a stochastic reward $R_v$. The goal is to adaptively find a tour of minimum expected length that collects at least reward $k$; here "adaptively" means our next decision may depend on previous outcomes. Ene et al. give an $O(\log k)$-approximation adaptive algorithm for this problem, and left open if there is an $O(1)$-approximation algorithm. We totally resolve their open question and even give an $O(1)$-approximation \emph{non-adaptive} algorithm for this problem. We also introduce and obtain similar results for the Stoch-Cost $k$-TSP problem. In this problem each vertex $v$ has a stochastic cost $C_v$, and the goal is to visit and select at least $k$ vertices to minimize the expected \emph{sum} of tour length and cost of selected vertices. This problem generalizes the Price of Information framework [Singla18] from deterministic probing costs to metric probing costs. Our techniques are based on two crucial ideas: "repetitions" and "critical scaling". We show using Freedman's and Jogdeo-Samuels' inequalities that for our problems, if we truncate the random variables at an ideal threshold and repeat, then their expected values form a good surrogate. Unfortunately, this ideal threshold is adaptive as it depends on how far we are from achieving our target $k$, so we truncate at various different scales and identify a "critical" scale.Comment: ITCS 202

Dust in the Local Group

How dust absorbs and scatters starlight as a function of wavelength (known as the interstellar extinction curve) is crucial for correcting for the effects of dust extinction in inferring the true luminosity and colors of reddened astrophysical objects. Together with the extinction spectral features, the extinction curve contains important information about the dust size distribution and composition. This review summarizes our current knowledge of the dust extinction of the Milky Way, three Local Group galaxies (i.e., the Small and Large Magellanic Clouds, and M31), and galaxies beyond the Local Group.Comment: 21 pages, 11 figures; invited review article published in "LESSONS FROM THE LOCAL GROUP -- A Conference in Honour of David Block and Bruce Elmegreen" eds. Freeman, K.C., Elmegreen, B.G., Block, D.L. & Woolway, M. (SPRINGER: NEW YORK), pp. 85-10

Chaos for endomorphisms of completely metrizable groups and linear operators on Fr\'echet spaces

Using the techniques in topological dynamics, we give a uniform treatment of Li-Yorke chaos, mean Li-Yorke chaos and distributional chaos for continuous endomorphisms of completely metrizable groups, and characterize three kinds of chaos (resp. extreme chaos) in term of the existence of corresponding semi-irregular points (resp. irregular points). We also apply the results to the chaos theory of continuous linear operators on Fr\'echet spaces, which improve some results in the literature.Comment: 50 page

Establishment of Genetic Hybrid Neurotourism Algorithm

In order to grasp the changing trend of customer churn and improve the prediction accuracy of customer churn, a prediction method of tourism customer churn based on Hybrid Neural Genetics is proposed. The mixed neural genetic algorithm is used to model and predict the customer turnover, estimate the tourism customer value calculation