Dust-acoustic waves and stability in the permeating dusty plasma: II. Power-law distributions

The dust-acoustic waves and their stability driven by a flowing dusty plasma when it cross through a static (target) dusty plasma (the so-called permeating dusty plasma) are investigated when the components of the dusty plasma obey the power-law q-distributions in nonextensive statistics. The frequency, the growth rate and the stability condition of the dust-acoustic waves are derived under this physical situation, which express the effects of the nonextensivity as well as the flowing dusty plasma velocity on the dust-acoustic waves in this dusty plasma. The numerical results illustrate some new characteristics of the dust-acoustic waves, which are different from those in the permeating dusty plasma when the plasma components are the Maxwellian distribution. In addition, we show that the flowing dusty plasma velocity has a significant effect on the dust-acoustic waves in the permeating dusty plasma with the power-law q-distribution.Comment: 20 pages, 10 figures, 41 reference

Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management

In recent years, cloud computing has been widely used. Cloud computing refers to the centralized computing resources, users through the access to the centralized resources to complete the calculation, the cloud computing center will return the results of the program processing to the user. Cloud computing is not only for individual users, but also for enterprise users. By purchasing a cloud server, users do not have to buy a large number of computers, saving computing costs. According to a report by China Economic News Network, the scale of cloud computing in China has reached 209.1 billion yuan. At present, the more mature cloud service providers in China are Ali Cloud, Baidu Cloud, Huawei Cloud and so on. Therefore, this paper proposes an innovative approach to solve complex problems in cloud computing resource scheduling and management using machine learning optimization techniques. Through in-depth study of challenges such as low resource utilization and unbalanced load in the cloud environment, this study proposes a comprehensive solution, including optimization methods such as deep learning and genetic algorithm, to improve system performance and efficiency, and thus bring new breakthroughs and progress in the field of cloud computing resource management.Rational allocation of resources plays a crucial role in cloud computing. In the resource allocation of cloud computing, the cloud computing center has limited cloud resources, and users arrive in sequence. Each user requests the cloud computing center to use a certain number of cloud resources at a specific time

Dust charging processes in the nonequilibrium dusty plasma with nonextensive power-law distribution

The dust charging processes in the collections of electrons and ions in the nonequilibrium dusty plasma with power-law distributions are investigated on the basic of a new q-distribution function theory in nonextensive statistics. Electrons and ions obey the power-law distributions and are with q-parameters different from each other. We derive the generalized formulae for the dust charging currents in which the nonextensive effects play roles. Further we investigate the dust charging processes taking place in the homogeneous dusty plasma where only the particle velocities are power-law distributions and in the dust cloud plasma where the particle velocities and densities are both power-law distributions. By numerical analyses, we show that the nonextensive power-law distributions of electrons and ions have significant effects on the dust charging processes in the nonequilibrium dusty plasma.Comment: 16 pages, 6 figures, 51 reference

Dust-acoustic waves and stability in the permeating dusty plasma: I. Maxwellian distribution

The dust-acoustic waves and their stability in the permeating dusty plasma with the Maxwellian velocity distribution are investigated. We derive the dust-acoustic wave frequency and instability growth rate in two limiting physical cases that the thermal velocity of the flowing dusty plasma is (a) much larger than, and (b) much smaller than the phase velocity of the waves. We find that the stability of the waves depend strongly on the velocity of the flowing dusty plasma in the permeating dusty plasma. The numerical analyses are made based on the example that a cometary plasma tail is passing through the interplanetary space plasma. We show that, in case (a), the waves are generally unstable for any flowing velocity, but in case (b), the waves become unstable only when the wave number is small and the flowing velocity is large. When the physical conditions are between these two limiting cases, we gain a strong insight into the dependence of the stability criterions on the physical conditions in the permeating dusty plasma.Comment: 16 pages, 4 figures, 35 reference

Secondary electron emissions and dust charging currents in the nonequilibrium dusty plasma with power-law distributions

We study the secondary electron emissions induced by the impact of electrons on dust grains and the resulting dust charging processes in the nonequilibrium dusty plasma with power-law distributions. We derive new expressions of the secondary emitted electron flux and the dust charging currents that are generalized by the power-law q-distributions, where the nonlinear core functions are numerically studied for the nonextensive parameter q. Our numerical analyses show that the power-law q-distribution of the primary electrons has a significant effect on the secondary emitted electron flux as well as the dust charging currents, and this effect depends strongly on the ratio of the electrostatic potential energy of the primary electrons at the dust grain's surface to the thermodynamic energy, implying that a competition in the dusty plasma between these two energies plays a crucial role in this novel effect.Comment: 16 pages, 6 figures, 32 reference

Competitive equilibrium and stable coalition in overlay environments

Overlay networks have been widely deployed upon the Internet to provide improved network services. However, the interaction between overlay and traffic engineering (TE) as well as among co-existing overlays may occur. In this paper, we adopt game theoretic approaches to analyze this hybrid interaction. Firstly, we model a situation of the hybrid interaction as an n+1- player non-cooperative game, where overlays and TE are of equal status, and prove the existence of Nash equilibrium (NE). Secondly, we model another situation of the hybrid interaction as a 1-leadern-follower Stackelberg-Nash game, where TE is the leader and coexisting overlays are followers, and prove that the cost at Stackelberg-Nash equilibrium (SNE) is at least as good as that at NE for TE. Thirdly, we propose a cooperative coalition mechanism based on Shapley value to overcome the inherent inefficiency of NE and SNE, where players can improve their performance and form stable coalitions

LILRB4 represents a promising target for immunotherapy by dual targeting tumor cells and myeloid-derived suppressive cells in multiple myeloma

Multiple myeloma (MM) remains an incurable hematological malignancy. Despite tremendous advances in the treatment, about 10% of patients still have very poor outcomes with median overall survival less than 24 months. Our study aimed to underscore the critical mechanisms pertaining to the rapid disease progression and provide novel therapeutic selection for these ultra-high-risk patients. We utilized single-cell transcriptomic sequencing to dissect the characteristic bone marrow niche of patients with survival of less than two years (EM24). Notably, an enrichment of LILRB4high pre-matured plasma-cell cluster was observed in the patients in EM24 compared to patients with durable remission. This cluster exhibited aggressive proliferation and drug-resistance phenotype. High-level LILRB4 promoted MM clonogenicity and progression. Clinically, high expression of LILRB4 was correlated with poor prognosis in both newly diagnosed MM patients and relapsed/refractory MM patients. The ATAC-seq analysis identified that high chromosomal accessibility caused the elevation of LILRB4 on MM cells. CRISPR-Cas9 deletion of LILRB4 alleviated the growth of MM cells, inhibited the immunosuppressive function of MDSCs, and further rescued T cell dysfunction in MM microenvironment. The more infiltration of myeloid-derived suppressive cells (MDSCs) was observed in EM24 patients as well. Therefore, we innovatively generated a TCR-based chimeric antigen receptor (CAR) T cell, LILRB4-STAR-T. Cytotoxicity experiment demonstrated that LILRB4-STAR-T cells efficaciously eliminated tumor cells and impeded MDSCs function. In conclusion, our study elucidates that LILRB4 is an ideal biomarker and promising immunotherapy target for high-risk MM. LILRB4-STAR-T cell immunotherapy is promising against tumor cells and immunosuppressive tumor microenvironment in MM