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关键词： Bose-Einstein condensation   dipolar Bose gases   rotons   superfluid density  

摘要： Using the Green's function approach, the density-density correlation function and the dielectric function in the random-phase approximation for a quasi-two-dimensional (quasi-2D) dipolar Bose gas are derived. From the pole of the density correlation function, by considering thermally induced roton-like excitations, the excitation spectrum of the system is calculated. It is shown that the position and depth of the roton minimum of the excitation spectrum are tunable by changing the temperature. To show how the position of the roton minimum influences the phenomenon of superfluidity, the superfluid density of the system is obtained and it is shown that the interplay of the thermal rotonization, contact and dipole-dipole interaction (DDI) can affect the superfluid fraction of a quasi-2D Bose gas. It is found that contact, DDI interactions, and thermally induced rotons enhance the fluctuations and reduce the superfluid density. In the absence of DDI and thermally induced rotons, the usual T-3 dependence of superfluid density in 2D is obtained and the correction T-4 term arises from DDI. It is shown that if the roton minimum is close to zero, the thermally induced rotons change the linear temperature dependence of the superfluid fraction, leading to a transition to nontrivial supersolid phase.

关键词： Hardware   Software   Switches   Throughput   Machine learning   Prototypes   Network function virtualization   Network function virtualization   machine learning   software-defined networks   performance management  

摘要： With the move from traditional hardware appliance based network functions to Network Function Virtualization, software development is decoupled from the hardware. However, as a network function is no longer optimized for hardware, beneficial features of networking hardware may not be used any more. Solutions such as SDN or NIC offloading aim to overcome this antipodes by integrating networking hardware into the packet processing pipelines. On the one hand, offloading traffic of network functions to hardware can increase throughput and reduce resource consumption. On the other hand, the number of parallel flows in a network can be very high, exhausting the capacity of the tables of the networking hardware and force the system to fall back to software processing. Fortunately, it is known that a large portion of the flows in the Internet are mice flows, whereas the majority of the traffic is constituted by elephant flows. If the elephant flows can be detected efficiently, the hardware tables can be used more efficiently as a larger share of the traffic can be offloaded. We introduce a machine learning based approach that takes its decision with the first packet of a flow. A fundamentally different approach is using packet sampling for the offloading decision. We are evaluating both approaches in terms of complexity, offloaded share of the traffic and table occupation. The results show that a machine learning based offloading decision is possible with the first packet. The sampling approach only reaches a comparable performance at very high sampling rates.

关键词： Vorticity equation   Stream function   Bounded domain  

摘要： The main purpose of this work is to provide a Hilbertian functional framework for the analysis of the planar incompressible Navier-Stokes (NS) equations either in vorticity or in stream function formulation. The fluid is assumed to occupy a bounded possibly multiply connected domain. The velocity field satisfies either homogeneous (no-slip boundary conditions) or prescribed Dirichlet boundary conditions. We prove that the analysis of the 2D Navier-Stokes equations can be carried out in terms of the so-called nonprimitive variables only (vorticity field and stream function) without resorting to the classical NS theory (stated in primitive variables, i.e. velocity and pressure fields). Both approaches (in primitive and nonprimitive variables) are shown to be equivalent for weak (Leray) and strong (Kato) solutions. Explicit, Bernoulli-like formulas are derived and allow recovering the pressure field from the vorticity fields or the stream function. In the last section, the functional framework described earlier leads to a simplified rephrasing of the vorticity dynamics, as introduced by Maekawa (Adv Differ Equ 18(1-2):101-146, 2013). At this level of regularity, the vorticity equation splits into a coupling between a parabolic and an elliptic equation corresponding respectively to the non-harmonic and harmonic parts of the vorticity equation. By exploiting this structure it is possible to prove new existence and uniqueness results, as well as the exponential decay of the palinstrophy (that is, loosely speaking, the H-1 norm of the vorticity) for large time.

关键词： Load balancing   Big data flow   Classification   Heterogeneous computing   Software definition networks  

摘要： Distributed network architecture of heterogeneous computing faces with such problems as strict performance constraints of network control, unpredictable mapping relationship between computing data algorithms of different mobile terminals and inconsistency between computing algorithms and link control of data networks. In order to solve the above problems, we begin with software definition network architecture and load balancing algorithm for heterogeneous computing, and gradually improve the real-time and reliability of heterogeneous computing. On the one hand, the heterogeneous computing data of fog node and cloud computing system are distributed. The centralized service of software-defined network combines with distributed computing of mobile edge terminal and its subnet. On the other hand, we define the centralized information and distributed scheduler of the network. In addition, we deploy the optimal assignment of data sharing and heterogeneous computing tasks in real time with ellipse-partitioned area as the object. A series of algorithms for classifying and assigning heterogeneous computing data streams in software-defined networks are designed to achieve the optimal balance among load balancing, minimum classification of large data streams, minimum resource occupation and time constraints. Experimental comparison compared and evaluated the Load Balancing with big data stream (LBBS), Load Balancing with Heterogeneous Computing (LBHC) and the proposed LBBHD. Compared with the other two algorithms, the proposed algorithm improves workload skewness, throughput and load balancing error respectively about 2.1%, 1.96%, 2.9%, 2.2%;5.57%. 2.51%.

关键词： lymphoma   non-hodgkin   classification   artificial intelligence   machine learning   flow cytometry  

摘要： The immunophenotype is a key element to classify B-cell Non-Hodgkin Lymphomas (B-NHL);while it is routinely obtained through immunohistochemistry, the use of flow cytometry (FC) could bear several advantages. However, few FC laboratories can rely on a long-standing practical experience, and the literature in support is still limited;as a result, the use of FC is generally restricted to the analysis of lymphomas with bone marrow or peripheral blood involvement. In this work, we applied machine learning to our database of 1465 B-NHL samples from different sources, building four artificial predictive systems which could classify B-NHL in up to nine of the most common clinico-pathological entities. Our best model shows an overall accuracy of 92.68%, a mean sensitivity of 88.54% and a mean specificity of 98.77%. Beyond the clinical applicability, our models demonstrate (i) the strong discriminatory power of MIB1 and Bcl2, whose integration in the predictive model significantly increased the performance of the algorithm;(ii) the potential usefulness of some non-canonical markers in categorizing B-NHL;and (iii) that FC markers should not be described as strictly positive or negative according to fixed thresholds, but they rather correlate with different B-NHL depending on their level of expression.

关键词： aneurysm   flow diverter   subarachnoid   technique   blood flow  

摘要： We report the case of a patient with subarachnoid hemorrhage and three aneurysms arising from the posterior communicating artery (Pcomm)-P1 complex, treated with endovascular coiling and competitive flow diversion. The largest and likely ruptured Pcomm aneurysm was treated with traditional coiling. Two smaller potentially ruptured aneurysms arose from the distal right posterior cerebral artery (PCA) P1 segment. After a failed attempt to treat with conventional flow diversion across the PCA-P1 segment, the P1 aneurysms were successfully treated with competitive flow diversion distal to the PCA-P1 segment from Pcomm to the P2 segment. Over 12 months, competitive flow diversion redirected flow to the right PCA territory via the internal carotid artery-Pcomm-P2, reducing the size of the PCA-P1 segment and obliterating the P1 aneurysms. Competitive flow diversion treatment should be considered for aneurysms occurring at the circle of Willis when traditional methods are not feasible. Herein, we introduce a novel classification for competitive flow diversion treatment.

关键词： Holm-Staley b-family equation   Large time behavior   Infinite propagation speed  

摘要： In this paper, we study the Holm-Staley b-family equation with weakly dissipative term. Firstly, we show the infinite propagation speed that if the initial datum u(0)(x) has a compact support, the corresponding solution u(x, t) does not have a compact x-support any longer in its lifespan. Then, we obtain the large time behavior of the support of momentum density with the initial data compact supported. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Machine learning   Mass flux   Species segregation   Voidage   Cluster   Circulating fluidized bed  

摘要： Machine learning methods were applied to circulating fluidized bed (CFB) riser data. The goals were to (i) provide insights on various fluidization phenomena through determining the relative dominance of the process variables, and (ii) develop a model to provide predictive capability in the absence of firstprinciples understanding that remains elusive. The Random Forest results indicate radial position had the most dominant influence on local mass flux and species segregation, overall mass flux was the most dominant for local particle concentration, while no variable was particularly dominant or negligible for the local clustering characteristics. Furthermore, the Neural Network can be trained to provide good predictive capability, without any mechanistic understanding needed, if a sufficiently large dataset is used for training and if the input variables fully account for all the effects at play. This study underscores the value of machine learning methods in fluidization to advance understanding and provide adequate predictions. (C) 2020 Elsevier Ltd. All rights reserved.

摘要： The existence of debris flows not only destroys the facilities but also seriously threatens human lives, especially in scenic areas. Therefore, the classification and susceptibility analysis of debris flow are particularly important. In this paper, 21 debris flow catchments located in Huangsongyu Township, Pinggu District, Beijing, China, were investigated. Besides field investigation, a geographic information system, a global positioning system and remote-sensing technology were applied to determine the characteristics of debris flows. This article introduced a clustering validity index to determine the clustering number, and the fuzzy C-means algorithm and factor analysis method were combined to classify 21 debris flow catchments in the study area. The results were divided into four types: debris flow closely related to scale-topography-human activity, topography- human activity-matter source, scale-matter source-geology and topography-scale-matter source-human activity. Nine major factors screened from the classification result were selected for susceptibility analysis, using both the efficacy coefficient method and the combination weighting. Susceptibility results showed that the susceptibility levels of 2 debris flow catchments were high, 6 were moderate and 13 were low. The assessment results were consistent with the field investigation. Finally, a comprehensive assessment including classification and susceptibility evaluation of debris flow was obtained, which was useful for risk mitigation and land use planning in the study area and provided a reference for the research on related issues in other areas.