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MicroRNAs (miRNA) are reported to be a vital regulator of neuropathic pain. Even so, the molecular mechanisms of miRNA function on neuropathic pain development are known little. Our research was designed to investigate the role of miRNA in neuropathic pain development in rat modle set up by chronic sciatic nerve injury (CCI). Increasing miR-150 expression could significantly alleviate neuropathic pain in CCI rats. For farther researching the regulation mechanism of miR-150 on neuropathic pain, we screened AKT3 as a possible target of miR-150 by bioinformatic mechods and predicted a possible target of miR-150 in 3′-untranslated region (UTR) of AKT3 who serves as an oncogene. In rat model, the expression both of AKT3 mRNA and protein were significantly upregulated. The overexpressed miR-150 importantly repressed the level of AKT3 and simultaneously alleviate mechanical and thermal hyperalgesia in rat model. These suppressant impacts of miR-150 on neuropathic pain process can be reversed by the overexpression of AKT3. Considering all above results, our research declared that miR-150 can restrain neuropathic pain process though targeting AKT3 in vivo, suggesting that miR-150 could be the therapeutic target for neuropathic pain therapy by regulating AKT3.

Recently, evolutionary multi-tasking (EMT) has been proposed as a new evolutionary search paradigm that op-timizes multiple problems simultaneously. Due to the knowledge transfer across optimization tasks occurs along the evolutionary search process, EMT has been demonstrated to outperform the traditional single-task evolutionary search algorithms on many complex optimization problems, such as multimodal continuous optimization problems, NP-hard combinatorial optimization problems, and constrained optimization problems. Today, EMT has attracted lots of attentions, and many EMT algorithms have been proposed in the literature. The explicit EMT algorithm (EEMTA) is a recent proposed new EMT algorithm. In contrast to most of existing EMT algorithms, which employ a single population using unified space and common search operators for solving multiple problems, the EEMTA uses multiple populations which possess problem-specific solution representations and search mechanisms for different problems in evolutionary multi-tasking, which thus could lead to enhanced optimization performance. However, the original EEMTA was proposed for solving only two tasks. As knowledge transfer from inappropriate tasks may lead to negative effect on the evolutionary optimization process, additional designs of identifying task pairs for knowledge transfer is necessary in EEMTA for evolutionary multi-tasking with tasks more than two. To the best of our knowledge, there is no research effort has been conducted on this issue. Keeping this in mind, in this paper, we present a preliminary study on the task selection in EEMTA for many-task optimization. As task similarity may lose to capture the usefulness between tasks in evolutionary search, instead of using similarity measures for task selection, here we propose a credit assignment approach for selecting proper task to conduct knowledge transfer in explicit evolutionary many-tasking. The proposed approach is based on the feedbacks from the transferred solutions across tasks, which is adaptively updated along the evolutionary search. To confirm the efficacy of the proposed method, empirical studies on the many-task optimization problem, which consists of 7 commonly used optimization benchmarks, have been presented and discussed.

Tumor necrosis factor superfamily-15 (TNFSF15; VEGI; TL1A) is a negative modulator of angiogenesis for blood vessel homeostasis and is produced by endothelial cells in a mature vasculature. It is known to be downregulated by vascular endothelial growth factor (VEGF), a major regulator of neovascularization but the mechanism of this interaction is unclear. Here we report that VEGF is able to stimulate the production of two microRNAs, miR-20a and miR-31, which directly target the 3'-UTR of TNFSF15. Additionally, we show that two VEGF-stimulated cell growth signals, Erk and Akt, are responsible for promoting the expression of miR-20a and miR-31. Treatment of human umbilical vein endothelial cells (HUVECs) with Akt inhibitor LY294002 results in diminished miR-20a and miR-31 production, while Erk inhibitor U0126 prevented VEGF-stimulated expression of miR-20a but not that of miR-31. Furthermore, inactivation of either Erk or Akt signals restores TNFSF15 gene expression. In an angiogenesis assay, elevated miR-20a or miR-31 levels in HUVECs leads to enhancement of capillary-like tubule formation in vitro, whereas lowered miR-20a and miR-31 levels results in an inhibition. These findings are consistent with the view that miR-20a and miR-31 mediate VEGF-induced downregulation of TNFSF15. Targeting these microRNA molecules may therefore provide an effective approach to inhibit angiogenesis.

This paper describes a proper low cost way to fabricate defects free porous carbon preforms with interconnect pore structure for making reaction formed SiC (RFSC). Taking charcoal , poplar powder, camphene and polymer dispersant together, making slurries by milling under 55 °C for several hours, controlling the content of charcoal and poplar powder, after casting, sublimating and carbonizing, the porous carbon performs with a series density (0.66 g/cm3-0.78 g/cm3) and porosity (62.9 vol.%-68.6 vol.%) were prepared; through the Si infiltrating process under a vacuum condition (~5.0 Pa) at 1500°C for about 0.5 hour, the RFSCs with fine mechanic performance were fabricated, one RFSC sample has the density, Weibull modulus, and the max three points flexural strength is 2.91 g/cm3, 9.5 and 505.0 MPa respectively.

In this paper, high volume fraction SiCp/Al composite was fabricated by pressureless technique with silicon carbide porous preform which fabricated through gel casting process. The effects of solid loading on the rheological properties of SiC slurry were discussed. High solid loading SiC slurry of 65vol% with low viscosity and high stability was fabricated. Also microstructure, flexural strength of the SiC preform and SiCp/Al composite were studied, the results showed gel casting process and pressureless infiltration technique were suitable for fabricating high volume fraction, homogeneous structure and high performance SiCp/Al composite.

The 3D printing ceramic body was prepared by camphene carbon/silicon carbide slurry, which were prepared with camphene, carbon and silicon carbide, dispersant, binder as rawmaterial, according to certain stoichiometric ratio. The effects of the choice of dispersants on the dispersion of the slurry performance were investigated. The amount of dispersant were determined.

CVD SiC material with many excellent physical and chemical properties was used widely in the field of aerospace as reflector materials. In addition, CVD SiC thin film materials because of its compact structure, high purity can also be used as precision optical components of semiconductor industry. But the CVD process is a complex chemical process and the reaction process is very time consuming. Research of chemical vapor deposition for preparing silicon carbide process mechanism is important significance for the expansion of the application of silicon carbide. In this paper, CVD SiC coatings were fabricated by the pyrolysis of methyltrichlorosilane (MTS) in hydrogen at a low pressure. XRD and EDS were used to characterize the component of intermediate. SEM was used to observe the surface morphology and microstructure of coatings. The results indicated that key problem to be solved is to control the growth rate of SiC for high quality deposition coating, while the growth rate is also affected by process parameters. To obtain the materials to meet the use requirements, the need for control of each parameter in the reaction process.

Neuropathic pain is caused by damage or disease happened to somatosensory nerve system. Due to the high prevalence and inefficient clinic intervention, neuropathic pain has brought considerable burden for world health care system. It is urgent to find novel targets for neuropathic pain basic research and clinical management. In this study, we found that miR-22-3p was decreased in Chronic Constriction Injury （CCI）rats and involved in neuropathic pain progression. Furthermore, it was found that ENO1 was a downstream target of miR-22-3p using bioinformatics analysis and luciferase reporter assays. MiR-22-3p downregulation promoted neuropathic pain via regulating inflammation factors expression by targeting ENO1. Then, we explored the upstream regulator of miR-22-3p using Miranda database. It was found that circular RNA ZNF609 sponged miR-22-3p by biotinylated RNA pull-down, AGO2-RIP, and luciferase reporter assays. Collectively, our study revealed that circZNF609 promoted inflammation factors expression to aggravate neuropathic pain progression via miR-22-3p/ENO1 axis in CCI rat models. Our study might provide a new direction for neuropathic pain basic research.

Abelmoschus is an economically and phylogenetically valuable genus in the family Malvaceae. Owing to coexistence of wild and cultivated form and interspecific hybridization, this genus is controversial in systematics and taxonomy and requires detailed investigation. Here, we present whole chloroplast genome sequences and annotation of three important species: A. moschatus, A. manihot and A. sagittifolius, and compared with A. esculentus published previously. These chloroplast genome sequences ranged from 163121 bp to 163453 bp in length and contained 132 genes with 87 protein-coding genes, 37 transfer RNA and 8 ribosomal RNA genes. Comparative analyses revealed that amino acid frequency and codon usage had similarity among four species, while the number of repeat sequences in A. esculentus were much lower than other three species. Six categories of simple sequence repeats (SSRs) were detected, but A. moschatus and A. manihot did not contain hexanucleotide SSRs. Single nucleotide polymorphisms (SNPs) of A/T, T/A and C/T were the largest number type, and the ratio of transition to transversion was from 0.37 to 0.55. Abelmoschus species showed relatively independent inverted-repeats (IR) boundary traits with different boundary genes compared with the other related Malvaceae species. The intergenic spacer regions had more polymorphic than protein-coding regions and intronic regions, and thirty mutational hotpots (≥200 bp) were identified in Abelmoschus, such as start-psbA, atpB-rbcL, petD-exon2-rpoA, clpP-intron1 and clpP-exon2.These mutational hotpots could be used as polymorphic markers to resolve taxonomic discrepancies and biogeographical origin in genus Abelmoschus. Moreover, phylogenetic analysis of 33 Malvaceae species indicated that they were well divided into six subfamilies, and genus Abelmoschus was a well-supported clade within genus Hibiscus.

The present report demonstrates a simple approach for the synthesis of efficient metal-free electrocatalysts of nitrogen- and sulfur-codoped carbon materials (N–S-DPCs) via carbonization of thiazolothiazole based conjugated microporous polymer precursors (XWB-CMP). The precursors are composed of densely populated thiazolothiazole units that uniformly decorate over the micropore surface and can be readily converted into novel N–S-DPCs with a uniform nitorgen/sulfur distribution by template-free pyrolysis. The electrochemical characterization demonstrates that N–S-DPCs obtained at pyrolysis temperature of 1000 °C exhibits a high electrocatalytic activity toward oxygen reduction reaction (ORR), superior durability, good methanol tolerance as compared to the commercial Pt/C catalyst. The present work sheds insights into the effects of heteroatom doping on ORR electrocatalysts.

The FIR digital filter design plays an important role in communication system. This paper proposes an optimal design method based on least squares method for the model of minimum mean square error criteria. This method derives the model's exact solution using least squares, and improves the solution accuracy. Meanwhile, the multi-objective evolutionary is used to optimize the weight value of sampling frequency to get excellent performance in the pass frequency band and stop frequency band. Experiments show the excellent performance of the FIR filter obtained by the proposed method.

Evolutionary Multi-objective optimization (EMO) Algorithms have been successfully applied in many practical problems. However, their performance deteriorated seriously for the problems with many objectives, i.e. many-objective optimization problems (MaOPs). In some practical applications, there exist some redundant objectives in an MaOP. Reducing the number of objectives of the optimization problem is one of the effective ways to solve the MaOPs with redundant objectives. It can improve the search efficiency of EMO algorithms, and reduce the computational cost. In this paper, we propose a new objective reduction algorithm. A criterion based on the number of non-dominated solution paired is presented to measure the conflict degree between objectives. Furthermore, we develop a effective objective reduction algorithm using feature selection technique. We compared the proposed algorithm with the LPCA, NLMVUP-CA and $\delta$-MOSS algorithm in some benchmark problems, and the results show the effectiveness of the proposed algorithm.

Neuropathic pain, resulting from somatosensory nervous system dysfunction, remains a serious public health problem worldwide. microRNAs are involved in the physiological processes of neuropathic pain. However, the biological roles of miR-98 in neuropathic pain development have not been investigated. Therefore, in our current study, we focused on the effects of miR-98 in neuropathic pain. It was shown that miR-98 was significantly downregulated in chronic sciatic nerve injury (CCI) rat models. In addition, high mobility group A2 (HMGA2) was obviously upregulated in CCI rats. Overexpression of miR-98 inhibited neuropathic pain progression, including mechanical and thermal hyperalgesia. By a bioinformatics analysis, HMGA2 was predicted as a direct target of miR-98. The negative correlation between miR-98 and HMGA2 was validated in our present study. Furthermore, overexpression of miR-98 dramatically repressed HMGA2 protein and messenger RNA (mRNA) expression. Neuroinflammation participates in neural-immune interactions, which can contribute to the neuropathic pain development. Meanwhile, we found that inflammatory cytokine (interleukin [IL]-6, IL-1β, and COX-2) protein expression in rats infected with LV-miR-98 was greatly suppressed. Taking these results together, we concluded that miR-98 might depress neuropathic pain development through modulating HMGA2.

This paper addresses a class of optimization problems in which either part of the objective function is differentiable while the rest is nondifferentiable or the objective function is differentiable in only part of the domain. Accordingly, we propose a dual-decomposition-based approach that includes both objective decomposition and domain decomposition. In the former, the original objective function is decomposed into several relatively simple subobjectives to isolate the nondifferentiable part of the objective function, and the problem is consequently formulated as a multiobjective optimization problem (MOP). In the latter decomposition, we decompose the domain into two subdomains, that is, the differentiable and nondifferentiable domains, to isolate the nondifferentiable domain of the nondifferentiable subobjective. Subsequently, the problem can be optimized with different schemes in the different subdomains. We propose a population-based optimization algorithm, called the simulated water-stream algorithm (SWA), for solving this MOP. The SWA is inspired by the natural phenomenon of water streams moving toward a basin, which is analogous to the process of searching for the minimal solutions of an optimization problem. The proposed SWA combines the deterministic search and heuristic search in a single framework. Experiments show that the SWA yields promising results compared with its existing counterparts.

Based on the ideas of minimizing the loss of convergence and diversity of the candidate solution set, this paper proposes a cost value based evolutionary many-objective algorithm with neighbor selection strategy. In this work, the cost value of each solution is the mutual evaluation from other ones in current population. By this way, the proposed algorithm, named MEMO, can easily recognize the dominated and the nondominated solutions and assess the contribution of convergence and diversity of each solution among the candidate solution set. To further enhance the performance of proposed algorithm, a neighbor selection strategy is also suggested in this paper. Simulation experiments on MaF series indicate that the proposed MEMO is superior to IBEA, MOEA/D, NSGA-III and RVEA in terms of effectiveness and robustness.

Emerging evidence has suggested that microRNAs play a critical role in neuropathic pain development. However, the biological role of miRNAs in regulating neuropathic pain remains barely known. In our present study, we found that miR-124-3p was significantly downregulated in rats after chronic sciatic nerve injury (CCI). In addition, it was showed that overexpression of miR-124-3p obviously repressed mechanical allodynia and heat hyperalgesia. Meanwhile, it has been reported that neuroinflammation can contribute a lot to neuropathic pain progression. Here, we found that inflammatory cytokine (IL-6, IL-1β, and TNF-⍺) protein expression in rats after CCI greatly increased and miR-124-3p mimics depressed inflammation cytokine levels. Consistently, miR-124-3p alleviated inflammation production in lipopolysaccharide-incubated spinal microglial cells. Bioinformatics analysis revealed that EZH2 acted as a direct target of miR-124-3p, which participated in the miR-124-3p-modulated effects on neuropathic pain development and neuroinflammation. We observed that miR-124-3p was able to promote neuroinflammation and neuropathic pain through targeting EZH2. The direct correlation between them was validated in our current study using dual-luciferase reporter assays. Subsequently, it was manifested that EZH2 abrogated the inhibitory role of miR-124-3p on neuropathic pain progression in CCI rats. Taken these together, our findings highlighted a novel contribution of miR-124-3p to neuropathic pain and indicated the possibilities for developing novel therapeutic options for neuropathic pain.

MicroRNA are emerging as significant regulators of neuropathic pain progression. In addition, neuroinflammation contributes a lot to neuropathic pain. miR-26a-5p has been identified as an inflammation-associated miRNA in multiple pathological processes. However, little is known about the biological role of miR-26a-5p in neuroinflammation and neuropathic pain development. Therefore, we aimed to investigate the function of miR-26a-5p in neuropathic pain by establishing a rat model using chronic sciatic nerve injury (CCI). A significant decrease of miR-26a-5p expression was observed in the spinal cord tissues form the CCI rats compared to the control group. Moreover, overexpression of miR-26a-5p significantly repressed neuropathic pain and neuroinflammation in CCI rats. MAPK6 was identified as a direct downstream target gene of miR-26a-5p and confirmed by dual-luciferase reporter assays. As displayed, overexpression of miR-26a-5p greatly reduced MAPK6 levels in vitro and in vivo. Meanwhile, MAPK6 expression and miR-26a-5p were oppositely correlated in CCI rats. Furthermore, up-regulation of MAPK6 obviously reversed the suppressive effect of miR-26a-5p on neuroinflammation and neuropathic pain progression. Taken these together, our results implied that miR-26a-5p could act as a negative regulator of neuropathic pain development through targeting MAPK6, which indicated that miR-26a-5p might serve as a potential therapeutic target for neuropathic pain.

For a many-objective optimization problem with redundant objectives, we propose two novel objective reduction algorithms for linearly and, nonlinearly degenerate Pareto fronts. They are called LHA and NLHA respectively. The main idea of the proposed algorithms is to use a hyperplane with non-negative sparse coefficients to roughly approximate the structure of the PF. This approach is quite different from the previous objective reduction algorithms that are based on correlation or dominance structure. Especially in NLHA, in order to reduce the approximation error, we transform a nonlinearly degenerate Pareto front into a nearly linearly degenerate Pareto front via a power transformation. In addition, an objective reduction framework integrating a magnitude adjustment mechanism and a performance metric [Formula: see text] are also proposed here. Finally, to demonstrate the performance of the proposed algorithms, comparative experiments are done with two correlation-based algorithms, LPCA and NLMVUPCA, and with two dominance-structure-based algorithms, PCSEA and greedy [Formula: see text]MOSS, on three benchmark problems: DTLZ5(I,M), MAOP(I,M), and WFG3(I,M). Experimental results show that the proposed algorithms are more effective.

In this paper, a modified FR conjugate gradient method(MFR) is presented for solving unconstrained optimization problems. The sufficient descent property of the MFR method is satisfied without any line search. Moreover, the MFR method reduces to the standard FR method if line search is exact. Under some mild conditions, the theory of global convergence is established. Numerical results are also given to show the efficiency of the MFR method.

Multiobjective evolutionary algorithm based on decomposition has made a great contribution to the field of evolutionary multiobjective optimization problem. The decomposition-based algorithms construct a number of scalar optimization subproblems by using a set of weight vectors, and optimize these subproblems simultaneously to approximate the Pareto front (PF). The weight vectors have a massive influence on the performance of the decomposition-based algorithm, especially for the multiobjective optimization problems (MOP) with a complex PF. To solve this, we propose a parameterless decomposition scheme to adjust the weight vectors automatically. Experiment results indicate that the proposed algorithm can obtain better uniformity solutions for the MOP with complex PF.

The abnormal point has an important significance in terms of theory and application. In order to study dynamical properties of the abnormal point in the high dimensional space, we will give a new concept of strongly descendible map according to the definition of the descendible map. We will study the abnormal point of strongly descendible map by means of properties of interval map and product map and it is respectively given that equivalence conclusion of strongly descendible map with abnormal points and without abnormal points in the n -dimensional monomer. These results further generalize the research of Professor of Xiong and Zhou.

Lymphangiogenesis is essential in embryonic development but is rare in adults. It occurs, however, in many disease conditions including cancers. Vascular endothelial growth factor-C/D (VEGF-C/D) and VEGF receptor-3 (Vegfr3) play a critical role in the regulation of lymphangiogenesis. We investigated how the VEGF-C/Vegfr3 signalling system is regulated by tumour necrosis factor superfamily member 15 (Tnfsf15), an endothelium-derived cytokine. We report here that Tnfsf15, which is known to induce apoptosis in vascular endothelial cells, can promote lymphatic endothelial cell (LEC) growth and migration, stimulate lymphangiogenesis, and facilitate lymphatic circulation. Treatment of mouse LECs with Tnfsf15 results in up-regulation of Vegfr3 expression; this can be inhibited by gene silencing of death domain-containing receptor-3 (DR3; Tnfrsf25), a cell surface receptor for Tnfsf15, with siRNA, or by blocking Tnfsf15-DR3 interaction with a Tnfsf15 neutralizing antibody, 4-3H. Additionally, Tnfsf15/DR3 signalling pathways in LECs include activation of NF-κB. Tnfsf15-overexpressing transgenic mice exhibit a marked enhancement of lymph drainage; this is confirmed by treatment of wild-type mice with intraperitoneal injection of recombinant Tnfsf15. Moreover, systemic treatment of pregnant Tnfsf15 transgenic mice with 4-3H leads to inhibition of embryonic lymphangiogenesis. Our data indicate that Tnfsf15, a cytokine produced largely by endothelial cells, facilitates lymphangiogenesis by up-regulating Vegfr3 gene expression in LECs, contributing to the maintenance of the homeostasis of the circulatory system. This finding also suggests that Tnfsf15 may be of potential value as a therapeutic tool for the treatment of lymphoedema.

This paper considers the minimum-energy control problem for a class of time-varying systems with multiple state and input delays. First, a state transform matrix is presented. By using the transform matrix, a system with multiple state and input delays is converted to a formal equivalent one without delay. Then, the optimal problem of the novel system is solved by using the maximum principle. Analytical expressions of the optimal control law and optimal performance are given by two formulas with respect to the state transform matrix. At last, an algorithm is given to solve the analytical expression of the state transform matrix. Simulation results show that the design algorithm is efficient and easy to implement.

The decomposition-based multi-objective evolutionary algorithm, i.e. MOEA/D-M2M, has shown to be an efficient algorithm to solve unconstrained imbalanced multiobjective optimization problems. However, the use in constrained imbalanced multi-objective optimization problems has not been fully explored. In this paper, we study the factors that impact the constrained imbalanced multi-objective optimization problems. To begin with, a series of constrained imbalanced multi-objective optimization problems are constructed. Then three kinds of representative algorithms, i.e. NSGA-II, MOEA/D and MOEA/D-M2M, combined with the constraint domination principle respectively, are utilized to solve them. The experimental results demonstrate that MOEA/D-M2M works better than the other two compared algorithms on constrained imbalanced multi-objective optimization problems in terms of the reliability and stability of finding a set of well distributed non-domination solutions.

Background Emergence agitation (EA) is a common phenomenon in preschool children during emergence from general anesthesia. This study evaluated the safety and efficacy of dezocine for emergence agitation in preschool children anesthetized with sevoflurane-remifentanil. Methods A total of 100 preschool children, scheduled for elective laparoscopic repair of an inguinal hernia by high ligation of the hernia sac under sevoflurane-remifentanil anesthesia were randomized into two groups: Group C (n = 50) received Ringer’s lactate 10 mL and Group D received Ringer’s lactate 10 mL containing dezocine 0.1 mg/kg, postoperatively. Results Incidence of EA, defined as a score ≥ 3 on Aono’s four point scale or Pediatric Anesthesia Emergence Delirium (PAED) score ≥ 10 in the PACU (10% vs. 76%) and the percentage of patients with severe EA (PAED score ≥ 13) (12% vs. 76%) were significantly lower in Group D compared to Group C (P

Decomposition based evolutionary algorithms have achieved great success in solving many-objective optimization problems. However, the design of proper decomposition vectors is not an easy task, especially in high dimensional objective space. In this paper, we study how to better use these decomposition vectors. We first show that for any given decomposition vector, new dominance relationship and crowding measurement strategy can be well defined. Based on them, we then propose a new evolutionary algorithm for many objective optimization. By this way, the utilization efficiency of decomposition vectors is enhanced and thus the task of weights design is alleviated accordingly. Experiments are conducted to compare the proposed algorithm with four state-of-the-art decomposition based evolutionary algorithms on a set of well-known many-objective test problems with 5 to 10 objectives. The simulation results show that the proposed algorithm can achieve comparable results with fewer decomposition vectors.

The performance of the most existing classical evolutionary multiobjective optimization (EMO) algorithms, especially for Pareto-based EMO algorithms, generally deteriorates over the number of objectives in solving many-objective optimization problems (MaOPs), in which the number of objectives is greater than three. Objective reduction methods that transform an MaOP into the one with few objectives, are a promising way for solving MaOPs. The dominance-based objective reduction methods, e.g. k-EMOSS and \(\delta \)-MOSS, omitting an objective while preserving the dominant structure of the individuals as much as possible, can achieve good performance. However, these algorithms have higher computational complexity. Therefore, this paper presents a novel measure for measuring the capacity of preserving the dominance structure of an objective set, i.e., the redundancy of an objective to an objective set. Subsequently, we propose a fast algorithm to find a minimum set of objectives preserving the dominance structure as much as possible. We compare the proposed algorithm with its counterparts on eleven test instances. Numerical studies show the effectiveness of the proposed algorithm.

The wideband code division multiple access (WCDMA) network planning problem requires to determine the location and the configuration parameters of the base stations (BSs) so as to maximize the capacity and minimize the installation cost. This problem can be formulated as a complex set covering problem. Compared to the classical set covering problems, the coverage area of each BS is unknown in advance. This makes that the selection of each BS location and configuration parameters is determined by the location and configuration parameters of the neighbor BSs. Accordingly, we will conduct a competition and cooperation model based on the re-covered area of the BSs to measure the relationship of the BSs. Then, an efficient genetic operation based on this model is proposed to generate new-quality solutions. Further, four BS configuration parameters, i.e., the antenna height, antenna tilt, sector orientation and pilot signal power, are taken into account as well. Since there are too many combination levels of the configuration parameters, an encoding method based on orthogonal design is presented to reduce the search space. Subsequently, we merge the proposed encoding method and genetic operation into the multiobjective evolutionary algorithm-based decomposition (MOEA/D-M2M) to solve the WCDMA network planning problem. Simulation results show the efficacy of the proposed encoding and genetic operation in comparison with the existing counterpart.

Desirability function is a mathematically simple description of decision maker's preference. A desirability function transforms objective function to a scale-free desirability value, which actually measures the decision maker's satisfaction with the objective value. In this paper, we utilize desirability functions to express decision maker's preference to specific regions with an objective. These desirability functions are integrated into evolutionary multi-objective algorithms to generate a uniformly distributed set of Pareto solutions in desirability space. The corresponding images in objective space of this set of solutions are exactly the decision maker's preferred solutions. The experimental results show the effectiveness of this approach.

There are several studies on hybrid multi-operator recombination methods, while few works have been proposed in the area of combining different fitness assignment in a framework. On the other hand, it is known that fitness assignment has a marked impact on the performance of evolutionary multiobjective optimization algorithm (EMOA). In this paper, a hybrid EMOA is proposed, which divides the population into several smaller subpopulations according to their distribution in the objective space. Each subpopulation is evolved by an individual EMOA, and a hybrid performance measure estimates the performance of these EMOAs. We focus on the fitness assignment and assume that all EMOAs used in the subpopulations adopt the same recombination operator. To evaluate performance of the proposed algorithm, we compare it with MOEA/D-M2M, MOE-A/D, SMS-EMOA and NSGA-II on 16 test instances. Experimental results show that the proposed algorithm performs better than or similar to those compared EMOAs.

Aimed at the applications of technology of camera calibration to 3D reconstruction, the ideal camera model is discussed, especially on the influences and solving methods of lens radial distortion andtangential distortion, and an arithmetic of camera calibration based on OpenCV (open source computer vision library) in Visual C++ environment is given. This arithmetic makes use of the functions of the library effectively, so it has high calibration precision and good robust. It can meet the needs of august reality and othercomputer vision systems.

This paper presents a new multi-objective artificial bee colony algorithm called dMOABC by dividing the whole searching space S into two independent parts S 1 and S 2. In this algorithm, two "basic" colonies are assigned to search potential solutions in regions S 1 and S 2, while the so-called "synthetic" colony explores in S. This multi-colony model could enable the good diversity of the population, and three colonies share information in a special way. A fixed-size external archive is used to store the non-dominated solutions found so far. The diversity over the archived solutions is controlled by utilizing a self-adaptive grid. For basic colonies, neighbor information is used to generate new food sources. For the synthetic colony, besides neighbor information, the global best food source gbest selected from the archive, is also adopted to guide the flying trajectory of both employed and onlooker bees. The scout bees are used to get rid of food sources with poor qualities. The proposed algorithm is evaluated on a set of unconstrained multi-objective test problems taken from CEC09, and is compared with 11 other state-of-the-art multi-objective algorithms by applying Friedman test in terms of four indicators: HV, SPREAD, EPSILON and IGD. It is shown by the test results that our algorithm significantly surpasses its competitors.

This letter suggests an approach for decomposing a multiobjective optimization problem (MOP) into a set of simple multiobjective optimization subproblems. Using this approach, it proposes MOEA/D-M2M, a new version of multiobjective optimization evolutionary algorithm-based decomposition. This proposed algorithm solves these subproblems in a collaborative way. Each subproblem has its own population and receives computational effort at each generation. In such a way, population diversity can be maintained, which is critical for solving some MOPs. Experimental studies have been conducted to compare MOEA/D-M2M with classic MOEA/D and NSGA-II. This letter argues that population diversity is more important than convergence in multiobjective evolutionary algorithms for dealing with some MOPs. It also explains why MOEA/D-M2M performs better.

How to improve the success rate of the industry-university-research cooperation and form a benign circulation, is the primary topic of current research studies, reasonable investment in research and development is an important guarantee for sharing research results between enterprises and scientific research institutes. It applies the dynamic information game to analysize the input relation between the enterprise and the scientific research institute in the process of the industry-university-research cooperation, and demonstrates the effect of the collaborative pattern on the profit reliezation of the both sides.

High thermal conductivity and dense SiC coating were fabricated by chemical vapor deposition (CVD) on surface of different graphite at temperature of 1100°C. The results indicated that the thickness of the coating influences the quality of coating. There was no crack in coating when thickness of the coating is less than 0.3mm. The structure of graphite affected the reaction badly. When the graphite is coarse and porous the reaction is chemical vapor infiltration (CVI) and the interface of coating and substrate isnt obvious. When the graphite is dense and smooth, the coating is covered in surface of graphite, the interface is found between the coating and substrate. Optical microscope and SEM were used to observe the surface and cross-section morphology and microstructure of coatings. It shown coating and substrate had a good combination and the deposited grains mainly showed equiaxed form with the crystallite size of 30 nm at 1100°C.

The chambers of certain coal mine in Shandong such as central substation situate in soft rock which consists of mudstone and fine sandstone, etc. Obvious ground pressure behaviors, large deformation and failure of surrounding rock have serious effect on mine safety production, with the impact of various complicated deep large ground pressure. This paper presents a rational scheme to control the surrounding rock steadily, based on analysis of deformation and failure on large section soft rock chamber, combined with the concept of the" combined supporting technology of long and short anchors" and "the combined supporting technology of three anchors".

PP/PA6/APP/OMMT Nanocomposites were Prepared via One-Step and Two-Step Melt Intercalation. the Flame Retardation, Thermostability, Structure Characters and Hygrothermal Aging Properties of PP/PA6/APP/OMMT Nanocomposites were Studied by UL-94, OI, TG and TEM. the Results Show that Two-Step can Improve the Flame Retardation of PP/PA6/APP/OMMT Nanocomposites; when OMMT Content is 4% or 6%, the Flame Retardation Gets Tofv-0, and the Lois are 32.2% and 32.8% Respectively; OMMT Doesn’t Play an Obvious Role to Hygrothermal Aging of PP/PA6/APP/OMMT Nanocomposites.

This paper studies the problem of underdetermined blind source separation with the nonstrictly sparse condition. Different from current approaches in literature, we propose a new and more effective algorithm to estimate the mixing matrices resulted from noise output data sets. After we introduce a clustering prototype of orthogonal complement space and give an extension of the normal vector clustering prototype, a new method combing the fuzzy clustering and eigenvalue decomposition technique to estimate the mixing matrix is presented in order to deal with the nonstrictly sparse situation. A convergent algorithm for estimating the mixing matrices is established, and numerical simulations are given to demonstrate the effectiveness of the proposed approach.

We investigated the effects of inhibiting heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNP A2/B1) expression on apoptosis, invasion, migration, and the chemotherapy sensitivity of pancreatic cancer cells to gemcitabine, 5-FU, and oxaliplatin chemotherapy using small interfering RNA (siRNA). Chemically synthesized siRNA hnRNP A2/B1 was transfected into the human pancreatic cancer cell lines SW1990 and BxPC-3. The IC(50) of gemcitabine, 5-FU, and oxaliplatin was determined using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. Cell apoptosis and cycle were detected using flow cytometry. The expressions of apoptosis-related genes, p53, Bax, Bcl-2, TRAIL, Survivin, multidrug resistance 1 (MDR1), E-cadherin, and matrix metalloproteinases-2 (MMP-2) were detected using real-time PCR and western blot. Plate colony formation assay, wound scratch assay, invasion, and migration were also examined. Gemcitabine, 5-FU, and oxaliplatin inhibit the proliferation of SW1990 and BxPC-3 cells in a concentration-dependent manner. Inhibition of hnRNP A2/B1 expression significantly reduced the IC(50) of gemcitabine, 5-FU, and oxaliplatin (P

An experiment was conducted to determine how photosynthesis was affected in Zizania latifolia Turcz. plants by infection of the endophytic smut fungus Ustilago esculenta. The results showed that U. esculenta infection induced a decreased plant height, but significantly increased above-ground biomass production as compared to control plants. Infected plants also exhibited higher Pn and chlorophyll content. In U. esculenta mycelia-sporidial infected plants, Pn, Gs and E generally were higher than those in sporidial infected plants. Compared to control plants, infected plants showed a higher light saturation point (LSP), apparent quantum yield (AQY) but a lower light compensation point (LCP). All leaves at different positions in infected plants showed higher Pn than control plants. The highest Pn was observed in the 4th leaf of infected plants, while it was the 3rd leaf in control plants. Infected plants generally showed relatively higher chlorophyll a fluorescence parameters in ΦPSII, ETR and qP than control plants. Maximum carboxylation rate of Rubisco (Vc, max) and maximum rate of RuBP regeneration (Jmax) were also elevated during U. esculenta infection. Our results revealed that promotion of photosynthetic efficiency was therefore probably mainly due to effects on non-stomatal processes by U. esculenta infection.

This paper presents RandomBug, a novel real-time path planning algorithm, for an autonomous mobile agent in completely unknown environment. According to this algorithm, all the planned paths are described and stored in the form of vectors. When the agent moves along the planned paths, it only considers the rotation angle and the movement distance in a single direction. The algorithm combines range sensor data with a safety radius to determine the blocking obstacles and calculate the shorter path by choosing the random intermediate points. When there is obstacle blocking in the current path, the intermediate points will be calculated randomly and the planned path will be regenerated by inserting the selected random intermediate points. Simulation results are given to show the effectiveness of the proposed algorithm.

T coordinate formation control for multiple underactuated AUVs. An optimal performance index is proposed to give attention to both tracking quality and formation constraint. A reference feasible trajectory for the position and orientation based on velocity control is planned so that it is consistent with vehicle dynamics. And the performance index is transformed to the error one. The optimal controller is designed to solve the problem. Using the controller we demonstrate the physical realization of control system at the same time. Simulation results validate that the proposed formation methodology are presented and discussed.

In recent years, many constraint-handling techniques maintaining infeasible individuals in the population have demonstrated their effectiveness for solving constrained optimization problems. Generally, the effective utilization of the potential of the infeasible individuals will improve the performance of the algorithms. This paper proposes an approach based on decomposition for constrained multi-objective optimization problems. By transforming the degree of constraint violation into one objective, a constraint-handling technique is introduced to exploit useful infeasible individuals during the evolution process. Besides, along with the evolution, it puts more emphasis on infeasible individuals with better objective values and smaller constraint violations, since they can provide more importance information for improving the convergence and diversity of the population. The performance of the proposed algorithm is evaluated by using 8 well-known test instances, i.e. CTP-series test instances. And the experimental results indicate that our algorithm is superior to the compared algorithm.

In this paper, we propose a simple but effective objective reduction algorithm (ORA) for many-objective optimization problems (MaOPs). It uses a hyperplane involving sparse non-negative coefficients to roughly approximate the conflicting structure of the Pareto front in the objective space. Then the objectives with non-zero coefficients are considered as essential objectives. In order to verify the performance of proposed algorithm, we compare the proposed algorithm with two correlation-based ORA, i.e., L-PCA and NL-MVU-PCA and a dominance structure-based ORA, i.e., PCSEA on the benchmark problem DTLZ5(I, M). The experimental results show the effectiveness of the proposed algorithm.

This paper proposes two constraint-handling techniques based on multiobjective optimization with biased dynamic weights for constrained optimization problems (COPs). Transforming a COP into an unconstrained biobjective optimization, two popular strategies based on decomposition, i.e. Tchebycheff approach (TEA) and weighted sum approach (WSA) are used in this paper respectively. In order to keep a good balance between convergence and diversity of the population, this paper uses the weights, which are designed with bias and change dynamically as the generation increases, to select different individuals with smaller objective values and lower degree of constraint violations. Furthermore, 13 benchmark test functions are used to investigate the effectiveness of TEA and WSA. Experimental results demonstrate that TEA not only works better than WSA, but also is superior to the compared algorithms, i.e. MDPE, GDE and SR in terms of reliability and stabilization of converging to a global solution.

When optimizing an multiobjective optimization problem, the evolution of population can be regarded as a approximation to the Pareto Front (PF). Motivated by this idea, we propose an adaptive region decomposition framework: MOEA/D-AM2M for the degenerated Many-Objective optimization problem (MaOP), where degenerated MaOP refers to the optimization problem with a degenerated PF in a subspace of the objective space. In this framework, a complex MaOP can be adaptively decomposed into a number of many-objective optimization subproblems, which is realized by the adaptively direction vectors design according to the present population's distribution. A new adaptive weight vectors design method based on this adaptive region decomposition is also proposed for selection in MOEA/D-AM2M. This strategy can timely adjust the regions and weights according to the population's tendency in the evolutionary process, which serves as a remedy for the inefficiency of fixed and evenly distributed weights when solving MaOP with a degenerated PF. Five degenerated MaOPs with disconnected PFs are generated to identify the effectiveness of proposed MOEA/D-AM2M. Contrast experiments are conducted by optimizing those MaOPs using MOEA/D-AM2M, MOEA/D-DE and MOEA/D-M2M. Simulation results have shown that the proposed MOEA/D-AM2M outperforms MOEA/D-DE and MOEA/D-M2M.

An evolutionary multi-objective optimization (EMO) algorithm based on Pareto dominance have made great achievements in dealing with two or three objectives optimization problems. Nevertheless, with the problem objective function of the number increasing, the selection pressure of Pareto dominance based EMO algorithms deteriorates rapidly. In our paper, we propose an evolutionary algorithm based on M2M population decomposition and reference distance to solve many-objective optimization problems, named EAPD-RD. By population decomposition, the population is decomposed into several subpopulation, and each subpopulation corresponds to a subspace represented by a direction vector. Each individual has a projector distance along the direction vector and a reference distance to the direction vector. The proposed algorithm use projector distance to enhance selection pressure of Pareto dominance. A Niching techniques based on reference distance is designed to the maintain the population diversity. Contrast experiments have been conducted by testing DTLZ(1–4) problems with 8, 10 and 15 objectives with proposed algorithm, MOEA/D and GrEA. The results of simulation illustrate that our algorithm outperforms MOEA/D and GrEA under the IGD metric.

Numerical calculations for the damping effect of foam concrete cushioning layer in crossing high-speed railway tunnel were carried out, based on the fluctuation theory using the Newmark implicit integration algorithm and he Lysmer viscous boundary condition. Then the measure's damping effects were evaluated by indicators such as the displacement, acceleration and stress response of the lining structure. Results indicated that foam concrete cushioning layer had good damping effects on the lining structure and showed significant damping effects within the thickness of 5 to 10 cm. In addition, closer to the crossing point, better the damping effects were. These results could make valuable reference for the anti-vibration design in crossing high-speed railway tunnel.