Accelerated computation of the genetic algorithm for energy-efficient virtual machine placement in data centers

Energy efficiency is a critical issue in the management and operation of cloud data centers, which form the backbone of cloud computing. Virtual machine (VM) placement has a significant impact on energy-efficiency improvement for virtualized data centers. Among various methods to solve the VM-placement problem, the genetic algorithm (GA) has been well accepted for the quality of its solution. However, GA is also computationally demanding, particularly in the computation of its fitness function. This limits its application in large-scale systems or specific scenarios where a fast VM-placement solution of good quality is required. Our analysis in this paper reveals that the execution time of the standard GA is mostly consumed in the computation of its fitness function. Therefore, this paper designs a data structure extended from a previous study to reduce the complexity of the fitness computation from quadratic to linear one with respect to the input size of the VM-placement problem. Incorporating with this data structure, an alternative fitness function is proposed to reduce the number of instructions significantly, further improving the execution-time performance of GA. Experimental studies show that our approach achieves 11 times acceleration of GA computation for energy-efficient VM placement in large-scale data centers with about 1500 physical machines in size

Progressive-fidelity computation of the genetic algorithm for energy-efficient virtual machine placement in cloud data centers

Energy efficiency is a critical issue in the management and operation of data centers, which form the backbone of cloud computing. Virtual machine placement has a significant impact on the energy efficiency of virtualized data centers. Among various methods to solve the virtual-machine placement problem, the genetic algorithm has been well accepted for its quality of solution. However, it is computationally demanding largely due to the complex form of fitness function, limiting its applications in data centers. To enhance the computational efficiency of the genetic algorithm while maintaining its quality of solution, a progressive-fidelity approach is developed in this paper for genetic-algorithm computation. It starts with a low-fidelity genetic algorithm with a simple fitness function. Then, for solution refinement, it switches to a medium-fidelity genetic algorithm with a more complicated fitness function. Finally, it progresses to the fine tuning of solution through a high-fidelity genetic algorithm with the energy consumption of data centers as fitness function. Heuristics are presented for the adaptive switching of genetic-algorithm computation from low fidelity to medium fidelity and finally to high fidelity. Experiments show that compared with the standard genetic algorithm of high fidelity, our progressive-fidelity approach of genetic algorithm computation is 50% faster for large-scale data centers while maintaining similar quality of solution in terms of the energy consumption of data centers

HPLC-based purification and isolation of potent anti-HIV and latency reversing Daphnane Diterpenes from the medicinal plant Gnidia sericocephala (Thymelaeaceae)

Despite the success of combination antiretroviral therapy (cART), HIV persists in low- and middle-income countries (LMIC) due to emerging drug resistance and insufficient drug accessibility. Furthermore, cART does not target latently-infected CD4+ T cells, which represent a major barrier to HIV eradication. The “shock and kill” therapeutic approach aims to reactivate provirus expression in latently-infected cells in the presence of cART and target virus-expressing cells for elimination. An attractive therapeutic prototype in LMICs would therefore be capable of simultaneously inhibiting viral replication and inducing latency reversal. Here we report that Gnidia sericocephala, which is used by traditional health practitioners in South Africa for HIV/AIDS management to supplement cART, contains at least four daphnane-type compounds (yuanhuacine A (1), yuanhuacine as part of a mixture (2), yuanhuajine (3), and gniditrin (4)) that inhibit viral replication and/or reverse HIV latency. For example, 1 and 2 inhibit HIV replication in peripheral blood mononuclear cells (PBMC) by >80% at 0.08 g/mL, while 1 further inhibits a subtype C virus in PBMC with a half-maximal effective concentration (EC50) of 0.03 M without cytotoxicity. Both 1 and 2 also reverse HIV latency in vitro consistent with protein kinase C activation but at 16.7-fold lower concentrations than the control prostratin. Both 1 and 2 also reverse latency in primary CD4+ T cells from cART-suppressed donors with HIV similar to prostratin but at 6.7-fold lower concentrations. These results highlight G. sericocephala and components 1 and 2 as anti-HIV agents for improving cART efficacy and supporting HIV cure efforts in resource-limited regions.SUPPLEMENTARY MATERIAL : TABLE S1: Anti-HIV replication activity of the positive control efavirenz using the in vitro deCIPhR assay: TABLE S2: Anti-HIV replication activity of G. sericocephala root extracts using the in vitro deCIPhR assay: TABLE S3: Cytotoxicity of G. sericocephala root extracts using the in vitro deCIPhR assay; FIGURE S1: 1H NMR data of yuanhuacine A (1), acquired on a Bruker Avance III HD 500 MHz NMR spectrophotometer with Prodigy Probe, the compound dissolved in deuterated chloroform (CDCl3): FIGURE S2: 13C NMR data of yuanhuacine A (1), acquired on a Bruker Avance III HD 500 MHz NMR spectrophotometer with Prodigy Probe, the compound dissolved in deuterated chloroform (CDCl3): FIGURE S3: The DEBT NMR data of yuanhuacine A (1), acquired on a Bruker Avance III HD 500 MHz NMR spectrophotometer with Prodigy Probe, the compound dissolved in deuterated chloroform (CDCl3).Funding was provided by the South African Department of Science and Innovation (DST/CON 0031/2019), Canadian Institutes for Health Research (CIHR PJT-153057) (I.T.) and the New Frontiers in Research Fund—Explorations (NFRFE-2018-01386) (I.T.). This work was also supported through the Sub-Saharan African Network for TB/HIV Research Excellence (SANTHE) (I.T.; N.G.), a DELTAs African Initiative [grant # DEL-15-006]. The DELTA African Initiative is an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Welcome Trust [grant # 107752/Z/15/Z] and the UK government. This work was also supported by grants to L.J.M.: Beyond Antiretroviral Treatment (BEAT)-HIV Delaney Collaboratory Grants UM1AI126620 and UM1AI64570. It was also supported by the Robert I. Jacobs Fund of the Philadelphia Foundation; Penn Center for AIDS Research Grant P30 AI 045880; and the Herbert Kean. The APC was funded by University of Pretoria and Deaprtment of Science and Innovation.https://www.mdpi.com/journal/virusesam2023Chemistr

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use

Acid-sensing ion channels and migraine

Acid-sensing ion channels (ASICs) are ligand-gated ion channels that are activated by extracellular protons (H+), which belong to epithelial sodium channels/degenerin (ENaC/DEG) superfamily. ASICs are widely distributed in central nervous system, peripheral nervous system, digestive system and some tumor tissues. Different ASIC subunits play important roles in various pathophysiological processes such as touch, sour taste, learning and memory, including inflammation, ischemic stroke, pain, learning and memory decline, epilepsy, multiple sclerosis (MS), migraine, irritable bowel syndrome and tumor. Research over the last 2 decades has achieved substantial advances in migraine pathophysiology. It is now largely accepted that inflammatory pathways play a key role and three main events seem to take place: cortical spreading depression (CSD), activation of the trigeminovascular system (i.e. dural nociceptors), peripheral and central sensitization of this pain pathway. However, the exact mechanisms that link these three events to each other and to inflammation have so far remained to be studied. This article takes an overview of newly research advances in structure, distribution and the relationship with migraine of ASICs.  DOI: 10.3969/j.issn.1672-6731.2015.09.01

The prevalence of amphenicol resistance in Escherichia coli isolated from pigs in mainland China from 2000 to 2018: A systematic review and meta-analysis.

BACKGROUND:Amphenicols have been widely used in the pig industry in China, leading to varying degrees of drug resistance. METHODS:The systematic review was performed according to PRISMA (Preferred Reported Items for Systematic Reviews and Meta-Analysis) recommendations on studies investigating the prevalence of amphenicol-resistant Escherichia coli (E. coli) isolated from pig in mainland China from 2000 to 2018, a random-effects model was selected, then followed by meta-analysis. RESULTS:A total of 103 articles were included in the study. The results of the meta-analysis revealed that the pooled summarized prevalence of resistance to chloramphenicol (CAP) was 72.31% (95% confidence interval (95% CI) = 67.12%-77.23%) and to florfenicol (FF) was 58.64% (95% CI = 52.48%-64.67%). During the past 18 years, the resistance rate to CAP remained high initially but then declined rapidly after 2012, whereas the resistance rate to FF plateaued (54.13%-59.60%) from 2000-2018. In different parts of China, the rate of resistance to amphenicols among E. coli isolates was fairly consistent, with the exception of the north and northwest regions. CONCLUSIONS:In 2002, the veterinary use of CAP was prohibited and its resistance levels in E. coli isolated from pigs was initially maintained at a high level but then showed an obvious downward trend in recent years. Resistance to commonly used FF remained at a high but stable level

Learning to See the Hook: Comparing Phishing Training Approaches

Phishing e-mails are a costly problem for organizations that automated phishing detection systems have been unable to stop. Accordingly, most organizations train their members how to detect and safely respond to phishing e-mails. Most phishing training take a rules-based or behavioral approach. Rules-based approaches provide simple heuristics to employees to follow, but have been criticized for their lack of flexibility. Behavioral approaches, including mindfulness-based training, improve attentiveness, but have been criticized for being misapplied. In a multi-study research program, we evaluate phishing training methods to determine which is the most successful for improving phishing detection. We also uncover the mechanisms through which these training programs improve phishing detection and offer a new integrated phishing training method. Our empirical results indicate that an integrated training program that combines mindfulness concepts, and targets specific linguistic identifiers of phishing, provide the greatest improvements to phishing detection rates