Power Allocation with Proportional Fairness in Downlink NOMA System

The non-orthogonal multiple access (NOMA) has been regarded as a candidate radio access technology in the 5th generation (5G) mobile networks. In this paper, the problem of power allocation is considered with proportional fairness for downlink NOMA. Our objective is to maximize the logarithmic throughput of the system, which achieves a good tradeoff between the system throughput and user fairness. The approximate optimal solution of this proposed method can be found by the means of quasi-Newton method. For any number of users K, the numerical results verify the accuracy and convergence of our proposed method. Compared to the exhaustive search method, the computational complexity is significantly reduced when the two methods achieve the same accuracy. Furthermore, we show that as the number of users increases, the number of iterations of our method increases with an approximately linear trend.     

Wirtinger-based multiple integral inequality for stability of time-delay systems

Note that the conservatism of the delay-dependent stability criteria can be reduced by increasing the integral terms in Lyapunov–Krasovskii functional (LKF). This brief revisits the stability problem for a class of linear time-delay systems via multiple integral approach. The novelty of this brief lies in that a Wirtinger-based multiple integral inequality is employed to estimate the derivative of a class of LKF with multiple integral terms. Based on these innovations, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities. Two numerical examples are exploited to demonstrate the effectiveness and superiority of the proposed method.     

罐式集装箱组合排放阀的设计

介绍了罐式集装箱组合排放阀的结构特点和工作原理,阐述了主要部件的设计要求、计算方法和材料选用。     

A comparison of five hybrid metaheuristic algorithms for unrelated parallel-machine scheduling and inbound trucks sequencing in multi-door cross docking systems

The objective of this paper is to develop five hybrid metaheuristic algorithms, including three hybrid ant colony optimization (hACO) variants, and compare their performances in two related applications: unrelated parallel machine scheduling and inbound truck sequencing in a multi-door cross docking system in consideration of sequence dependent setup, and both zero and nonzero release time. The three hACO variants were modified and adapted from the existing literature and they differ mainly in how a solution is coded and decoded, how a pheromone matrix is represented, and the local search methods employed. The other two hybrids are newly constructed hybrid simulated annealing (hSA) algorithms, which are built based on the authors’ knowledge and experience. The evaluation criteria are computational time and the objective function value, i.e., makespan. Based on the results of computational experiments the simulated annealing-tabu search hybrid turns out to be the best if maximal CPU time is used as the stopping criterion and the 2-stage hACO variant is the best if maximal number of evaluations is the stopping criterion. The contributions of this paper are: (i) being the first to carry out a comparative study of hybrid metaheuristics for the two selected applications, (ii) being the first to consider nonzero truck arrival time in multi-door cross docking operations, (iii) identifying which hACO variant is the best among the three, and (iv) investigating the effect of release time on the makespan.     

DG placement in radial distribution network by symbiotic organisms search algorithm for real power loss minimization

Incorporation of distributed generation (DG) in distribution network may reduce the network loss if DG of appropriate size is placed at proper strategic location. The current article presents determination of optimal size and location of DG in radial distribution network (RDN) for the reduction of network loss considering deterministic load demand and DG generation using symbiotic organisms search (SOS) algorithm. SOS algorithm is a meta-heuristic technique, inspired by the symbiotic relationship between different biological species. In this paper, optimal size and location of DG are obtained for two different RDNs (such as, 33-bus and 69-bus distribution networks). The obtained results, using the proposed SOS, are compared to the results offered by some other optimization algorithms like particle swarm optimization, teaching-learning based optimization, cuckoo search, artificial bee colony, gravitational search algorithm and stochastic fractal search. The comparison is done based on minimum loss of the distribution network as well as based on the convergence mobility of the fitness function offered by each of the comparative algorithms for both the networks under consideration. It is established that the proposed SOS algorithm offers better result as compared to other optimization algorithms under consideration. The results are also compared to the existing solution available in the literature.     

Solving partner selection problem in cyber-physical production networks using the HUMANT algorithm

The idea of non-hierarchical production networks consisting of autonomous enterprises has been present in scientific community for more than 20 years. Although some global corporations are using their own production networks across continents, they are not similar to the original idea of non-hierarchical production networks in many aspects. It seems that this idea waited for production systems to acquire proper information and communications technology (ICT) or new industrial platforms, like Industry 4.0. The result is a new type of production network called Cyber-Physical Production Network (CPPN). The CPPN is, from ICT point of view, ready to act as non-hierarchical production networks consisting of autonomous production systems with many automated processes. One of the most important processes of the CPPN is a selection of optimal partners (enterprises) to be part of a new virtual enterprise, created inside production network. An optimisation problem emerges in this process, and it is called Partner Selection Problem (PSP). It is non-polynomial-hard combinatorial problem. Since metaheuristic algorithms are well-proven in solving that kind of problem, a specially designed metaheuristic algorithm derived from ant colony optimisation and named the HUMANT (HUManoid ANT) algorithm is used in this paper. It is multi-objective optimisation algorithm that successfully solves different instances of PSP with two, three, four or more objectives.     

Interactive minimax optimisation for integrated performance analysis and resource planning

Analysing performances for future improvement and resource planning is a key management function. Data Envelopment Analysis (DEA) provides an analytical mean for performance modelling without assuming parametric functions. Multiple Objective Optimisation (MOO) is well-suited for resource planning. This paper reports an investigation in exploring relationships between DEA and MOO models for equivalent efficiency analysis in a MOO process. It is shown that under certain conditions minimax reference point models are identical to input-oriented dual DEA models for performance assessment. The former can thus be used for Hybrid Efficiency and Trade-off Analyses (HETA). In this paper, these conditions are first established and the equivalent models are explored both analytically and graphically to better understand HETA. Further investigation in the equivalence models leads to the modification of efficiency measures and the development of a minimax reference point approach for supporting integrated performance analysis and resource planning, with the Decision Maker’s (DM) preferences taken into account in an interactive fashion. Both numerical and case studies are conducted to demonstrate the proposed approach and its potential applications.     

Structural,Electronic Properties,Hydrogen Bonding Analyses,and Biological Activity of Two Multiple Myeloma Drugs: Lenalidomide and Pomalidomide

In this article, we made a comparative study of two multiple myeloma drugs: lenalidomide and pomalidomide. We calculated and discussed their geometries at DFT/B3LYP method. Intra-molecular hydrogen bonding in these molecules is confirmed and characterized by QTAIM calculations. Electronic parameters along with HOMO-LUMO and MESP surfaces are calculated in order to compare their chemical reactivity. The effect of structure and bonding on electronic properties and biological activities is discussed and it is established that pomalidomide is more biologically active than lenalidomide. The phenyl ring of these molecules show teratogenic effects, making a possibility of finding another new class of drugs.     

A Soluble Epoxide Hydrolase Inhibitor, 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) Urea,Ameliorates Experimental Autoimmune Encephalomyelitis

Polyunsaturated fatty acids (PUFAs) are essential FAs for human health. Cytochrome P450 oxygenates PUFAs to produce anti-inflammatory and pain-resolving epoxy fatty acids (EpFAs) and other oxylipins whose epoxide ring is opened by the soluble epoxide hydrolase (sEH/Ephx2), resulting in the formation of toxic and pro-inflammatory vicinal diols (dihydroxy-FAs). Pharmacological inhibition of sEH is a promising strategy for the treatment of pain, inflammation, cardiovascular diseases, and other conditions. We tested the efficacy of a potent, selective sEH inhibitor, 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU), in an animal model of multiple sclerosis (MS), experimental autoimmune encephalomyelitis (EAE). Prophylactic TPPU treatment significantly ameliorated EAE without affecting circulating white blood cell counts. TPPU accumulated in the spinal cords (SCs), which was correlated with plasma TPPU concentration. Targeted lipidomics in EAE SCs and plasma identified that TPPU blocked production of dihydroxy-FAs efficiently and increased some EpFA species including 12(13)-epoxy-octadecenoic acid (12(13)-EpOME) and 17(18)-epoxy-eicosatrienoic acid (17(18)-EpETE). TPPU did not alter levels of cyclooxygenase (COX-1/2) metabolites, while it increased 12-hydroxyeicosatetraenoic acid (12-HETE) and other 12/15-lipoxygenase metabolites. These analytical results are consistent with sEH inhibitors that reduce neuroinflammation and accelerate anti-inflammatory responses, providing the possibility that sEH inhibitors could be used as a disease modifying therapy, as well as for MS-associated pain relief.