Coordinated Container Migration and Base Station Handover in Mobile Edge Computing

Offloading computationally intensive tasks from mobile users (MUs) to a virtualized environment such as containers on a nearby edge server, can significantly reduce processing time and hence end-to-end (E2E) delay. However, when users are mobile, such containers need to be migrated to other edge servers located closer to the MUs to keep the E2E delay low. Meanwhile, the mobility of MUs necessitates handover among base stations in order to keep the wireless connections between MUs and base stations uninterrupted. In this paper, we address the joint problem of container migration and base-station handover by proposing a coordinated migration-handover mechanism, with the objective of achieving low E2E delay and minimizing service interruption. The mechanism determines the optimal destinations and time for migration and handover in a coordinated manner, along with a delta checkpoint technique that we propose. We implement a testbed edge computing system with our proposed coordinated migration-handover mechanism, and evaluate the performance using real-world applications implemented with Docker container (an industry-standard). The results demonstrate that our mechanism achieves 30%-40% lower service downtime and 13%-22% lower E2E delay as compared to other mechanisms. Our work is instrumental in offering smooth user experience in mobile edge computing.Comment: 6 pages. Accepted for presentation at the IEEE Global Communications Conference (Globecom), Taipei, Taiwan, Dec. 202

Elastic and thermodynamic properties of the major clinker phases of Portland cement: Insights from first principles calculations

Portland based cement is one of the most popular materials used in the civil and construction applications. Reliable computational methods to provide an insight into the underlying mechanics of the major phases of this material are of great interest for cement design. The present work investigated the performance of density functional theory (DFT) calculations using the PBE-D2 method to predict the mechanical, thermodynamic properties of four major phases namely Alite C3S, Belite C2S, tricalcium aluminate C3A and tetracalcium aluminoferrite C4AF. The calculated elastic properties were in a good agreement with available experimental data. In addition, a deeper insight into the electron density of state, spin-polarization, atomic charge, as well as free energy and entropy properties were also presented. Further development is necessary to improve the established DFT models for predicting the mechanical properties of the ferrite phase of Portland clinker.publishedVersio

Optimizing Boiler Efficiency by Data Mining Teciques: A Case Study

In a fertilizer plant, the steam boiler is the most important component. In order to keep the plant operating in the effective mode, the boiler efficiency must be observed continuously by several operators. When the trend of the boiler efficiency is going down, they may adjust the controlling parameters of the boiler to increase its efficiency. Since manual operation usually leads to unex-pectedly mistakes and hurts the efficiency of the system, we build an information system that plays the role of the operators in observing the boiler and adjusting the controlling parameters to stabilize the boiler efficiency. In this paper, we first introduce the architecture of the information system. We then present how to apply K-means and Fuzzy C-means algorithms to derive a knowledge base from the historical operational data of the boiler. Next, recurrent fuzzy neural network is employed to build a boiler simulator for evaluating which tuple of input values is the best optimal and then automatically adjusting controlling inputs of the boiler by the optimal val-ues. In order to prove the effectiveness of our system, we deployed it at Phu My Fertilizer Plant equipped with MARCHI boiler having capacity of 76-84 ton/h. We found that our system have improved the boiler efficiency about 0.28-1.12% in average and brought benefit about 57.000 USD/year to the Phu My Fertilizer Plant

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202

The QCD heavy-quark potential to order v^2: one loop matching conditions

The one-loop QCD heavy quark potential is computed to order v^2 in the color singlet and octet channels. Several errors in the previous literature are corrected. To be consistent with the velocity power counting, the full dependence on |p' + p|/|p' - p| is kept. The matching conditions for the NRQCD one-loop potential are computed by comparing the QCD calculation with that in the effective theory. The graphs in the effective theory are also compared to terms from the hard, soft, potential, and ultrasoft regimes in the threshold expansion. The issue of off-shell versus on-shell matching and gauge dependence is discussed in detail for the 1/(m k) term in the potential. Matching on-shell gives a 1/(m k) potential that is gauge independent and does not vanish for QED.Comment: 28 pages, References added and minor changes to section III, results unchange

Hexa Histidine–Tagged Recombinant Human Cytoglobin Deactivates Hepatic Stellate Cells and Inhibits Liver Fibrosis by Scavenging Reactive Oxygen Species

BACKGROUND & AIMS: Anti-fibrotic therapy remains an unmet medical need in human chronic liver disease. We report the anti-fibrotic properties of cytoglobin (CYGB), a respiratory protein expressed in hepatic stellate cells (HSCs), the main cell type involved in liver fibrosis. APPROACH & RESULTS: Cygb-deficient mice which had bile duct ligation (BDL)-induced liver cholestasis or choline-deficient L-amino acid-defined (CDAA) diet-induced steatohepatitis significantly exacerbated liver damage, fibrosis and reactive oxygen species (ROS) formation. All these manifestations were attenuated in Cygb-overexpressing mice. We produced 6His-tagged recombinant human CYGB (His-CYGB), traced its bio-distribution and assessed its function in HSCs or in mice with advanced liver cirrhosis using thioacetamide (TAA) or 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC). In cultured HSCs, extracellular His-CYGB was endocytosed and accumulated in endosomes via clathrin-mediated pathway. His-CYGB significantly impeded ROS formation spontaneously or in the presence of ROS inducers in HSCs, thus leading to the attenuation of collagen type I alpha 1 production and alpha-smooth muscle actin expression. Replacement the iron centre of the heme group with cobalt nullified the effect of His-CYGB. In addition, His-CYGB induced interferon-β secretion by HSCs which partly contributed to its anti-fibrotic function. Momelotinib incompletely reversed the effect of His-CYGB. Intravenously injected His-CYGB markedly suppressed liver inflammation, fibrosis and oxidative cell damage in TAA- or DDC-administered mice without adverse effects. RNA-seq analysis revealed the downregulation of inflammation and fibrosis-related genes and the upregulation of antioxidant genes in both cell culture and liver tissues. The injected His-CYGB predominantly localised to HSCs but not to macrophages, suggesting specific targeting effects. His-CYGB exhibited no toxicity in humanised liver chimeric PXB mice. CONCLUSIONS: His-CYGB could have anti-fibrotic clinical applications for human chronic liver diseases

Research Trends in Evidence-Based Medicine: A Joinpoint Regression Analysis of More than 50 Years of Publication Data

Background Evidence-based medicine (EBM) has developed as the dominant paradigm of assessment of evidence that is used in clinical practice. Since its development, EBM has been applied to integrate the best available research into diagnosis and treatment with the purpose of improving patient care. In the EBM era, a hierarchy of evidence has been proposed, including various types of research methods, such as meta-analysis (MA), systematic review (SRV), randomized controlled trial (RCT), case report (CR), practice guideline (PGL), and so on. Although there are numerous studies examining the impact and importance of specific cases of EBM in clinical practice, there is a lack of research quantitatively measuring publication trends in the growth and development of EBM. Therefore, a bibliometric analysis was constructed to determine the scientific productivity of EBM research over decades. Methods NCBI PubMed database was used to search, retrieve and classify publications according to research method and year of publication. Joinpoint regression analysis was undertaken to analyze trends in research productivity and the prevalence of individual research methods. Findings Analysis indicates that MA and SRV, which are classified as the highest ranking of evidence in the EBM, accounted for a relatively small but auspicious number of publications. For most research methods, the annual percent change (APC) indicates a consistent increase in publication frequency. MA, SRV and RCT show the highest rate of publication growth in the past twenty years. Only controlled clinical trials (CCT) shows a non-significant reduction in publications over the past ten years. Conclusions Higher quality research methods, such as MA, SRV and RCT, are showing continuous publication growth, which suggests an acknowledgement of the value of these methods. This study provides the first quantitative assessment of research method publication trends in EBM