JALAD: Joint Accuracy- and Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution

Recent years have witnessed a rapid growth of deep-network based services and applications. A practical and critical problem thus has emerged: how to effectively deploy the deep neural network models such that they can be executed efficiently. Conventional cloud-based approaches usually run the deep models in data center servers, causing large latency because a significant amount of data has to be transferred from the edge of network to the data center. In this paper, we propose JALAD, a joint accuracy- and latency-aware execution framework, which decouples a deep neural network so that a part of it will run at edge devices and the other part inside the conventional cloud, while only a minimum amount of data has to be transferred between them. Though the idea seems straightforward, we are facing challenges including i) how to find the best partition of a deep structure; ii) how to deploy the component at an edge device that only has limited computation power; and iii) how to minimize the overall execution latency. Our answers to these questions are a set of strategies in JALAD, including 1) A normalization based in-layer data compression strategy by jointly considering compression rate and model accuracy; 2) A latency-aware deep decoupling strategy to minimize the overall execution latency; and 3) An edge-cloud structure adaptation strategy that dynamically changes the decoupling for different network conditions. Experiments demonstrate that our solution can significantly reduce the execution latency: it speeds up the overall inference execution with a guaranteed model accuracy loss.Comment: conference, copyright transfered to IEE

Twist-Dependent Anisotropic Thermal Conductivity in Homogeneous MoS2_2 Stacks

Thermal transport property of homogeneous twisted molybdenum disulfide (MoS$_2$) is investigated using non-equilibrium molecular dynamics simulations with the state-of-art force fields. The simulation results demonstrate that the cross-plane thermal conductivity strongly depends on the interfacial twist angle, while it has only a minor effect on the in-plane thermal conductivity, exhibiting a highly anisotropic nature. A frequency-decomposed phonon analysis showed that both the cross-plane and in-plane thermal conductivity of MoS$_2$ are dominated by the low-frequency phonons below 15 THz. As the interfacial twist angle increases, these low-frequency phonons significantly attenuate the phonon transport across the interface, leading to impeded cross-plane thermal transport. However, the in-plane phonon transport is almost unaffected, which allows for maintaining high in-plane thermal conductivity. Additionally, our study revealed the strong size dependence for both cross-plane and in-plane thermal conductivities due to the low-frequency phonons of MoS$_2$. The maximum in-plane to cross-plane thermal anisotropy ratio is estimated as 400 for twisted MoS$_2$ from our simulation, which is in the same order of magnitude as recent experimental results (~900). Our study highlights the potential of twist engineering as a tool for tailoring the thermal transport properties of layered materials.Comment: 25 pages, 5 figures and with S

Predictability of extreme daily returns and Preference for lottery-like stocks in an emerging market

This study investigates the presence of the MAX effect – stocks with extreme daily (positive) return in the current month perform poorly in the following month – in the Pakistani stock market (PSX). Similar to the US, Europe, and Chinese stock markets, we find a negative effect of MAX on risk-adjusted returns. Furthermore, we find that the MAX effect persists even if we extend the holding period to three- and six-month. Our results are robust for both portfolio-level and firm-level cross-sectional analyses and across subperiods, size groups, and alternative factor definitions and models. Interestingly, contrary to findings reported elsewhere, we find that the MAX effect in Pakistan exists only when the overall economy is in an expansion state. A battery of tests suggests that triviality in MAX effect during economic contraction in Pakistan is driven by the more negative subsequent performance of low-MAX stocks (short-leg), whereas, in other markets, more negative subsequent performance of high-MAX stocks (long-leg) is evident during economic downturns. Our potential explanation is partially supported by the theoretical model of Palfrey & Wang, who find that demand for speculative stocks (i.e. lottery-like stocks) is higher during ‘good’ economic news (expansion) than ‘bad’ economic news (contraction)

The Influence of Deleterious Mutations on Adaptation in Asexual Populations

We study the dynamics of adaptation in asexual populations that undergo both beneficial and deleterious mutations. In particular, how the deleterious mutations affect the fixation of beneficial mutations was investigated. Using extensive Monte Carlo simulations, we find that in the “strong-selection weak mutation (SSWM)” regime or in the “clonal interference (CI)” regime, deleterious mutations rarely influence the distribution of “selection coefficients of the fixed mutations (SCFM)”; while in the “multiple mutations” regime, the accumulation of deleterious mutations would lead to a decrease in fitness significantly. We conclude that the effects of deleterious mutations on adaptation depend largely on the supply of beneficial mutations. And interestingly, the lowest adaptation rate occurs for a moderate value of selection coefficient of deleterious mutations

Dual blockage of STAT3 and ERK1/2 eliminates radioresistant GBM cells.

Radiotherapy (RT) is the major modality for control of glioblastoma multiforme (GBM), the most aggressive brain tumor in adults with poor prognosis and low patient survival rate. To improve the RT efficacy on GBM, the mechanism causing tumor adaptive radioresistance which leads to the failure of tumor control and lethal progression needs to be further elucidated. Here, we conducted a comparative analysis of RT-treated recurrent tumors versus primary counterparts in GBM patients, RT-treated orthotopic GBM tumors xenografts versus untreated tumors and radioresistant GBM cells versus wild type cells. The results reveal that activation of STAT3, a well-defined redox-sensitive transcriptional factor, is causally linked with GBM adaptive radioresistance. Database analysis also agrees with the worse prognosis in GBM patients due to the STAT3 expression-associated low RT responsiveness. However, although the radioresistant GBM cells can be resensitized by inhibition of STAT3, a fraction of radioresistant cells can still survive the RT combined with STAT3 inhibition or CRISPR/Cas9-mediated STAT3 knockout. A complementally enhanced activation of ERK1/2 by STAT3 inhibition is identified responsible for the survival of the remaining resistant tumor cells. Dual inhibition of ERK1/2 and STAT3 remarkably eliminates resistant GBM cells and inhibits tumor regrowth. These findings demonstrate a previously unknown feature ofSTAT3-mediated ERK1/2 regulation and an effective combination of two targets in resensitizing GBM to RT