A lightweight cell switching and traffic offloading scheme for energy optimization in ultra-dense heterogeneous networks

One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in a tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network, but most of the proposed methods are computationally demanding, which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that THESIS significantly reduces the energy consumption of the UDHN and can reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity.     

PSO-LSSVM对LIBS定量分析精度的提高

针对土壤定量分析受基体效应影响大，LIBS定量分析精度不佳等问题，采用粒子群算法对LSSVM进行优化，提高模型的精确度。选取Pb Ⅰ 405.78 nm和Cr Ⅰ 425.44 nm作为分析谱线进行分析。采集十二个不同浓度样品的特征光谱，每个浓度样品在不同点采集20组数据，将其中17组数据设为训练集，3组数据设为预测集，用LSSVM和PSO-LSSVM两种方法建立定标模型。对比两种模型的拟合相关系数（R2）、训练集均方根误差（RMSEC）和预测集均方根误差(RMSEP)。由于自吸收效应的影响，随着浓度的增加，预测值逐渐低于实际值，LSSVM定标模型的拟合程度较低，无法达到实验要求，模型性能有待提高。利用粒子群算法对LSSVM的模型参数惩罚系数和核函数参数进行优化，得到最佳的参数组合，Pb元素为(8 096.8, 138.865 7)，Cr元素为(4 908.6, 393.563 5)，用最佳的参数组合构建LSSVM的定标模型。相比于LSSVM，PSO-LSSVM定标模型的精确度更高，Pb和Cr元素的R2提高到了0.982 8和0.985 0，拟合效果明显提升。Pb和Cr元素的训练集均方根误差由0.026 0 Wt%和0.027 2 Wt%下降到0.022 4 Wt%和0.019 1 Wt%，预测集均方根误差由0.101 8 Wt%和0.078 8 Wt% 下降到0.045 8 Wt%和0.042 0 Wt%，模型的稳定性进一步提高。说明PSO-LSSVM算法能够更好地降低土壤基体效应和自吸收效应带来的影响，提高分析结果的精确度与稳定性。     

Imposing accurate wall boundary conditions in corrective‐matrix‐based moving particle semi‐implicit method for free surface flow

Corrective matrix that is derived to restore consistency of discretization schemes can significantly enhance accuracy for the inside particles in the Moving Particle Semi‐implicit method. In this situation, the error due to free surface and wall boundaries becomes dominant. Based on the recent study on Neumann boundary condition (Matsunaga et al, CMAME, 2020), the corrective matrix schemes in MPS are generalized to straightforwardly and accurately impose Neumann boundary condition. However, the new schemes can still easily trigger instability at free surface because of the biased error caused by the incomplete/biased neighbor support. Therefore, the existing stable schemes based on virtual particles and conservative gradient models are applied to free surface and nearby particles to produce a stable transitional layer at free surface. The new corrective matrix schemes are only applied to the particles under the stable transitional layer for improving the wall boundary conditions. Three numerical examples of free surface flows demonstrate that the proposed method can help to reduce the pressure/velocity fluctuations and hence enhance accuracy further.     

Deciphering the Structure and Chemical Composition of Drug Nanocarriers: From Bulk Approaches to Individual Nanoparticle Characterization

Drug nanocarriers (NCs) with sizes usually below 200 nm are gaining increasing interest in the treatment of severe diseases such as cancer and infections. Characterization methods to investigate the morphology and physicochemical properties of multifunctional NCs are key in their optimization and in the study of their in vitro and in vivo fate. Whereas a variety of methods has been developed to characterize “bulk” NCs in suspension, the scope of this review is to describe the different approaches for the NC characterization on an individual basis, for which fewer techniques are available. The accent is put on methods devoid of labelling, which could lead to artefacts. For each characterization method, the principles and approaches to analyze the data are presented in an accessible manner. Aspects related to sample preparation to avoid artefacts are indicated, and emphasis is put on examples of applications. NC characterization on an individual basis allows gaining invaluable information in terms of quality control, on: i) NC localization and fate in biological samples; ii) NC morphology and crystallinity; iii) distribution of the NC components (drugs, shells), and iv) quantification of NCs’ chemical composition. The individual characterization approaches are expected to gain increasing interest in the near future.     

全局优化问题的一个新的无参数填充函数

求全局最优化问题的填充函数算法被提出以来，参数的选取和调整一直是制约算法有效性的因素。如何在实际的计算过程中选取合适的参数，直接影响和决定了运算速度和效率。因此，构造不含参数的填充函数就显得极为重要。提出一个新的无参数的填充函数，对其理论性质进行了分析，并给出相应的填充函数算法，数值计算验证了算法的有效性。     

Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

This letter studies the problem of minimizing increasing set functions, equivalently, maximizing decreasing set functions, over the base matroid. This setting has received great interest, since it generalizes several applied problems including actuator and sensor placement problems in control, task allocation problems, video summarization, and many others. We study two greedy heuristics, namely, the forward and reverse greedy. We provide two novel performance guarantees for the approximate solutions obtained by them depending on both submodularity ratio and curvature.     

Solution combustion synthesis,energy and environment: Best parameters for better materials

Solution combustion synthesis (SCS) is a worldwide used methodology for the preparation of inorganic ceramic and composite materials with controlled properties for a wide number of applications, from catalysis to photocatalysis and electrocatalysis, from heavy metal removal to sensoristics and electronics. The high versatility and efficiency of this technique have led to the introduction of many variants, which allowed important optimization to the prepared materials. Moreover, its ecofriendly nature encouraged further studies about the use of sustainable precursors for the preparation of nanomaterials for energy and environment, according to the concept of circular economy. On the other hand, the large variety of expressions to define SCS and the often-contradictory definitions of the SCS parameters witnessed a scarce consciousness of the potentiality of this methodology. In this review article, the most important findings about SCS and the selection criteria for its main parameters are critically reviewed, in order to give useful guidelines to those scientists who want to use this methodology for preparing materials with improved or new functional properties. This review aims as well (i) to bring more clarity in the SCS terminology (ii) to increase the awareness of the SCS as a convenient tool for the synthesis of materials and (iii) to propose a new perspective in the SCS, with special attention to the use of ecofriendly procedures. Part of the review is also dedicated to precautions and limitations of this powerful methodology.     

Decision diagrams for solving traveling salesman problems with pickup and delivery in real time

The Traveling Salesman Problem with Pickup and Delivery seeks a minimum cost path with pickups preceding deliveries. It is important in on-demand last-mile logistics, such as ride sharing and meal delivery. We examine the use of low-width Decision Diagrams in a branch-and-bound with and without Assignment Problem inference duals as a primal heuristic for finding good solutions within strict time budgets. We show these diagrams can be more effective than similarly structured hybrid Constraint Programming techniques for real-time decision making.     

Optimal time delays in a class of reaction-diffusion equations

ABSTRACT

A class of semilinear parabolic reaction diffusion equations with multiple time delays is considered. These time delays and corresponding weights are to be optimized such that the associated solution of the delay equation is the best approximation of a desired state function. The differentiability of the mapping is proved that associates the solution of the delay equation to the vector of weights and delays. Based on an adjoint calculus, first-order necessary optimality conditions are derived. Numerical test examples show the applicability of the concept of optimizing time delays.