Virtual machine(VM)consolidation aims to run VMs on the least number of physical machines(PMs).The optimal consolidation significantly reduces energy consumption(EC),quality of service(QoS)in applications,and resource...Virtual machine(VM)consolidation aims to run VMs on the least number of physical machines(PMs).The optimal consolidation significantly reduces energy consumption(EC),quality of service(QoS)in applications,and resource utilization.This paper proposes a prediction-basedmulti-objective VMconsolidation approach to search for the best mapping between VMs and PMs with good timeliness and practical value.We use a hybrid model based on Auto-Regressive Integrated Moving Average(ARIMA)and Support Vector Regression(SVR)(HPAS)as a prediction model and consolidate VMs to PMs based on prediction results by HPAS,aiming at minimizing the total EC,performance degradation(PD),migration cost(MC)and resource wastage(RW)simultaneously.Experimental results usingMicrosoft Azure trace show the proposed approach has better prediction accuracy and overcomes the multi-objective consolidation approach without prediction(i.e.,Non-dominated sorting genetic algorithm 2,Nsga2)and the renowned Overload Host Detection(OHD)approaches without prediction,such as Linear Regression(LR),Median Absolute Deviation(MAD)and Inter-Quartile Range(IQR).展开更多
Although VEGF-B was discovered as a VEGF-A homolog a long time ago,the angiogenic effect of VEGF-B remains poorly understood with limited and diverse findings from different groups.Notwithstanding,drugs that inhibit V...Although VEGF-B was discovered as a VEGF-A homolog a long time ago,the angiogenic effect of VEGF-B remains poorly understood with limited and diverse findings from different groups.Notwithstanding,drugs that inhibit VEGF-B together with other VEGF family members are being used to treat patients with various neovascular diseases.It is therefore critical to have a better understanding of the angiogenic effect of VEGF-B and the underlying mechanisms.Using comprehensive in vitro and in vivo methods and models,we reveal here for the first time an unexpected and surprising function of VEGF-B as an endogenous inhibitor of angiogenesis by inhibiting the FGF2/FGFR1 pathway when the latter is abundantly expressed.Mechanistically,we unveil that VEGF-B binds to FGFR1,induces FGFR1/VEGFR1 complex formation,and suppresses FGF2-induced Erk activation,and inhibits FGF2-driven angiogenesis and tumor growth.Our work uncovers a previously unrecognized novel function of VEGF-B in tethering the FGF2/FGFR1 pathway.Given the anti-angiogenic nature of VEGF-B under conditions of high FGF2/FGFR1 levels,caution is warranted when modulating VEGF-B activity to treat neovascular diseases.展开更多
基金funded by Science and Technology Department of Shaanxi Province,Grant Numbers:2019GY-020 and 2024JC-YBQN-0730.
文摘Virtual machine(VM)consolidation aims to run VMs on the least number of physical machines(PMs).The optimal consolidation significantly reduces energy consumption(EC),quality of service(QoS)in applications,and resource utilization.This paper proposes a prediction-basedmulti-objective VMconsolidation approach to search for the best mapping between VMs and PMs with good timeliness and practical value.We use a hybrid model based on Auto-Regressive Integrated Moving Average(ARIMA)and Support Vector Regression(SVR)(HPAS)as a prediction model and consolidate VMs to PMs based on prediction results by HPAS,aiming at minimizing the total EC,performance degradation(PD),migration cost(MC)and resource wastage(RW)simultaneously.Experimental results usingMicrosoft Azure trace show the proposed approach has better prediction accuracy and overcomes the multi-objective consolidation approach without prediction(i.e.,Non-dominated sorting genetic algorithm 2,Nsga2)and the renowned Overload Host Detection(OHD)approaches without prediction,such as Linear Regression(LR),Median Absolute Deviation(MAD)and Inter-Quartile Range(IQR).
基金This study is supported by the State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,and Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science,Guangzhou 510060,P.R.Chinathe National Natural Science Foundation of China(82150710555 and 82220108016 to X.Li,81970823 to Jin Yao and 81830013 to J.O.)+4 种基金a Key Research and Development Plan of Shandong Province(2016GSF201100)the Fundamental Research Funds for the Central Universities(19ykpy151)the long-term structural Methusalem funding by the Flemish Government,Belgiumthe Deutsche Forschungsge-meinschaft(Project No.:394046768-SFB1366)the DZHK partner site Mannheim/Heidelberg to H.F.L.,an ERA PerMed 2020 JTC grant“PROGRESS”.
文摘Although VEGF-B was discovered as a VEGF-A homolog a long time ago,the angiogenic effect of VEGF-B remains poorly understood with limited and diverse findings from different groups.Notwithstanding,drugs that inhibit VEGF-B together with other VEGF family members are being used to treat patients with various neovascular diseases.It is therefore critical to have a better understanding of the angiogenic effect of VEGF-B and the underlying mechanisms.Using comprehensive in vitro and in vivo methods and models,we reveal here for the first time an unexpected and surprising function of VEGF-B as an endogenous inhibitor of angiogenesis by inhibiting the FGF2/FGFR1 pathway when the latter is abundantly expressed.Mechanistically,we unveil that VEGF-B binds to FGFR1,induces FGFR1/VEGFR1 complex formation,and suppresses FGF2-induced Erk activation,and inhibits FGF2-driven angiogenesis and tumor growth.Our work uncovers a previously unrecognized novel function of VEGF-B in tethering the FGF2/FGFR1 pathway.Given the anti-angiogenic nature of VEGF-B under conditions of high FGF2/FGFR1 levels,caution is warranted when modulating VEGF-B activity to treat neovascular diseases.
