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The motion of ions in the complex fluids widely appears in hydrodynamics, geodynamics and geophysics. Setting up suitable mathematical model, performing accurate and efficient numerical simulations are essential to understand the underlying physical principle in these phenomena. In this paper, we present a linear, second-order accurate in time, decoupled and unconditionally energy stable numerical scheme for solving an electrohydrodynamic power-law model with variable electrical conductivity. Based on a logarithm transformation for conductivity and the zero energy contribution property of the nonlinear coupling terms in the model, we derive an equivalent system by introducing a nonlocal auxiliary variable. The two-step backward differentiation scheme and the finite element method are used for the temporal and spatial discretizations, respectively. To decouple the system, the nonlocal splitting technique is employed to yield several linear subsystems, which can be solved very efficiently. Numerical simulations are carried out to demonstrate the second-order convergence in time and the unconditional energy stability. Moreover, the effects of Coulombic force and power-law fluid exponents are numerically investigated. • An electrohydrodynamic model with variable electrical conductivity is found satisfying an energy dissipation law. • The proposed scheme inherits the energy dissipation law at the fully discrete level. • The proposed scheme is a linear, second-order accurate in time and decoupled method. • The proposed scheme can be solved very efficiently with using a nonlocal splitting technique. [ABSTRACT FROM AUTHOR]

Reinforced concrete shear walls in multistory buildings often undergo the combined action of vertical and horizontal loads, with their failure primarily attributed to localized damage of the concrete at the bottom of edge elements, leading to premature loss of wall functionality. To enhance the performance of shear walls, this study explores the optimization of shear wall design from the perspective of the stress path within the wall, introducing a diagonally distributed reinforcements in shear walls (referred to as DDR shear walls). To investigate the seismic performance of DDR shear walls, we consider the effects of axial compression ratio, the inclination angle of distributed reinforcing bars, reinforcing bar spacing, and shear span ratio. We design 27 shear wall models with various parameter combinations and employ ABAQUS finite element analysis software to simulate the seismic performance. The simulation results reveal that the inclined distribution of reinforcing bars significantly enhances the seismic performance of shear walls. To achieve optimal structural performance, the inclination angle of reinforcing bars should be adjusted for different floor levels, with higher floors requiring a greater angle and lower floors a smaller one. Additionally, increasing the reinforcing bar spacing and altering the shear span ratio will have varying degrees of impact on the seismic performance of shear walls, necessitating rational design adjustments based on specific circumstances. Furthermore, the application of DDR shear walls in prefabricated construction can be considered to optimize construction processes. [ABSTRACT FROM AUTHOR]

The stationary Darcy–Brinkman equations in the double-diffusive convection, which model the heat and mass transfer phenomena, are considered in this paper. Based on a suitable contractive operator, the existence and uniqueness of the problem are firstly proved by using the fixed point theorem. The regularities of the weak solution are also derived. Then, the Newton iterative method is studied for solving the nonlinear discrete system generated from the finite element approximation, including the stability and the optimal error estimates regarding the spatial mesh size and the iterative factor. The analysis indicates that the viscosity coefficient has more impact on the numerical algorithm than the thermal conductivity and the mass diffusivity coefficients. Finally, many numerical examples are shown to confirm the correctness of the theoretical prediction. [ABSTRACT FROM AUTHOR]

An active @ passive anti-icing surface coating was successfully prepared using graphene&SiO 2 hybrid structure toward photothermal superhydrophobic performance. The coating consists of polydimethylsiloxane (PDMS) with E51 epoxy resin linked to fumed silica (nano-SiO 2) to provide a multistage rough structure and graphene as the primary photothermal nanoparticle for various surface anti-freeze application. The surface morphology of this photothermal superhydrophobic coating is validated to be as a uniformly rough cauliflower structure with a large number of "air valley". More importantly, the addition of 0.2 g graphene could exhibit the best photothermal effect (2 sun (≈ 200 mW/cm2), stable average temperature of 49.56 °C) along with superhydrophobic effect (162.2°), excellent chemical stability properties. In order to improve the organic-inorganic interfacial bonding and the mechanical durability of photothermal superhydrophobic coatings, using micro-arc oxidation technology to establish the microporous structure on the surface of substrate for exerting interlocking effect, after pushing and pulling under applied load of 300 g for 200 cm, the outstanding wear resistance of the composite coating was verified. Thanks to the interlocking effect, the excellent superhydrophobic properties provided by the construction of the typical Cassie-Baxter model of the surface and the use of multiple layers of graphene increasing the probability of π - π * electron leap, the multi-stage photothermal superhydrophobic composite coating is able to show a long-lasting anti-icing and de-icing effect. [Display omitted] • Composite coating with excellent multi-stage structural superhydrophobicity. • MAO pretreatment to improve the organic-inorganic interlocking effect. • Double barrier provides excellent corrosion resistance. • Superhydrophobic and Graphene Photothermal Dual De-Icing. [ABSTRACT FROM AUTHOR]

The Penalty Decomposition (PD) method is an effective and versatile algorithm for sparse optimization, which has been used in different applications. The PD method may be slow, since it needs to solve many subproblems. The accelerated iteration hard thresholding (AIHT) method is also a powerful method for sparse optimization, but has a main drawback that it requires a prior estimation of the sparsity level. In this paper, an improvement of the penalty decomposition method is proposed for the sparse optimization problem, which embeds the AIHT method into the PD method. The proposed method has the advantages of the PD method and the AIHT method, but avoids their disadvantages. The convergence analysis of the proposed method is given as well. Moreover, computational experiments on a number of test instances demonstrate the effectiveness of the proposed method in accurately generating sparse and redundant representations of one-dimensional random signals and two-dimensional CT images. [ABSTRACT FROM AUTHOR]

The application of bacterial ghosts as vaccines is limited because of their low lysis efficiency and production and the presence of pathogenic islands and/or antibiotic resistance genes within ghost preparations. To overcome these problems, a new lysis plasmid with fusion gene of mutant gene E and staphylococcal nuclease A gene (mE-L-SNA) were constructed and characterized. The new plasmid pBV-mELS could efficiently induce the genetic inactivation of Escherichia coli cultures, accompanied by the intracellular degradation of the genetic material of host cells, devoid of the presence of pathogenic islands and antibiotic resistance genes within ghost preparations. Furthermore, the lysis efficiency of the plasmid pBV-mELS was not affected by bacterial concentration and could reach 99.99995% for E. coli at late-log phase. However, when the 74-bp non-encoding region of the gene mE-L-SNA were deleted or the first T nucleotide of the gene mE-L-SNA were substituted, these resulting genes lost the function of bacteriolysis, which suggested the 74-bp region of the gene mE-L-SNA, especially the first T nucleotide, played a crucial role in enhancement of bacteriolysis. The lysis system with the gene mE-L-SNA had predominance for large-scale production of safety-enhanced bacterial ghosts. The strategy may provide a promising avenue for efficient production of safe bacterial ghost vaccines. [ABSTRACT FROM AUTHOR]

The common objective of very large-scale integration (VLSI) placement problem is to minimize the total wirelength, which is calculated by the total half-perimeter wirelength (HPWL). Since the HPWL is not differentiable, various differentiable wirelength approximation functions have been proposed in analytical placement methods. In this paper, we reformulate the HPWL as an l1 -norm model of the wirelength function, which is exact but nonsmooth. Based on the l1 -norm wirelength model and exact calculation of overlapping areas between cells and bins, a nonsmooth optimization model is proposed for the VLSI global placement problem, and a subgradient method is proposed for solving the nonsmooth optimization problem. Moreover, local convergence of the subgradient method is proved under some suitable conditions. In addition, two enhanced techniques, i.e., an adaptive parameter to control the step size and a cautious strategy for increasing the penalty parameter, are also used in the nonsmooth optimization method. In order to make the placement method scalable, a multilevel framework is adopted. In the clustering stage, the best choice clustering algorithm is modified according to the l1 -norm wirelength model to cluster the cells, and the nonsmooth optimization method is recursively used in the declustering stage. Comparisons of experimental results on the International Symposium on Physical Design (ISPD) 2005 and 2006 benchmarks show that the global placement method is promising. [ABSTRACT FROM PUBLISHER]

By ignoring some cell overlaps, global placement computes the best position for each cell to minimize the wirelength. It is an important stage in very large scale integration (VLSI) physical design, since circuit performance heavily depends on the placement results. In this paper, we propose an augmented Lagrangian method to solve the VLSI global placement problem. In the proposed method, a cautious dynamic density weight strategy is used to balance the wirelength objective and the density constraints, and an adaptive step size is used to obtain a trade-off between runtime and solution quality. The proposed method is tested on the IBM mixed-size benchmarks and the International Symposium on Physical Design 2006 placement contest benchmarks. Experimental results show that our global placement method outperforms the state-of-the-art placement approaches in terms of solution quality on most of the benchmarks. [ABSTRACT FROM AUTHOR]

Outbreaks of fish bacterial diseases have become quite frequent with the intensification of practices in aquaculture. Vaccination has become an increasingly important prevention strategy against infectious agents in farmed fishes. However, only a few licensed fish bacterial vaccines are commercially available worldwide, and the majority of them are conventional inactivated vaccines. The use of bacterial ghosts (BGs) as novel candidate vaccines has attracted increasing attention from researchers. BGs are nonliving empty cell envelopes mainly derived from gram-negative bacteria. Pores in gram-negative bacteria are formed most commonly through the strictly controlled expression of bacteriophage PhiX174 lysis gene E, whereas pores in gram-positive bacteria can be formed through minimally inhibitory gentle chemical protocols. In biological protocols, the temperature-sensitive λ system has been widely used for quick and efficient lysis without the need for any addition of chemical inducers. To produce BGs with enhanced safety, the incorporation of the staphylococcal nuclease A gene, holin-endolysin system, or antimicrobial peptide genes into gene E -mediated lysis cassettes has been applied to improve lysis efficiency. The ghosts of a few fish pathogenic bacteria, such as Edwardsiella spp., Aeromonas spp., Vibrio spp., and Streptococcus spp., have been successfully developed by gene E -mediated lysis, which maintain the original cell morphology but eliminate genetic contents. Although the lysis efficiency of these BGs does not reach 100%, the lyophilized BGs were free of any living cells. These lyophilized BGs not only have high biological safety for fish, but also can induce stronger humoral, cellular and mucosal immune responses compared to conventional inactivated vaccines. Moreover, BGs are easy to produce in large quantities by fermentation without laborious purification procedures and easy to administer through oral or immersion immunization. Therefore, BGs are good fish vaccine candidates and can be engineered to display heterologous antigens or deliver DNA for use as multivalent vaccines against fish pathogen infection. Yet, completely inactivation was not achieved by the gene E -mediated lysis procedure, how to improve the lysis efficiency of BGs is an important problem for BG production. It is believed that the BG system will play an increasingly important role in the prevention and control of fish diseases with further research and continuous biotechnological development. • Bacterial ghosts (BGs) are produced mainly through phage lysis gene E-mediated lysis. • The safety of BGs is enhanced by the combined application of lysis genes and secondary lethal genes. • The ghosts of 14 important fish pathoges have been successfully generated. • The fish BG vaccines are safe and induce stronger immune responses in fish than conventional inactivated vaccines. • BGs are excellent delivery vectors for fish recombinant and DNA vaccines. [ABSTRACT FROM AUTHOR]

Outbreaks of fish bacterial diseases have become quite frequent with the intensification of practices in aquaculture. Vaccination has become an increasingly important prevention strategy against infectious agents in farmed fishes. However, only a few licensed fish bacterial vaccines are commercially available worldwide, and the majority of them are conventional inactivated vaccines. The use of bacterial ghosts (BGs) as novel candidate vaccines has attracted increasing attention from researchers. BGs are nonliving empty cell envelopes mainly derived from gram-negative bacteria. Pores in gram-negative bacteria are formed most commonly through the strictly controlled expression of bacteriophage PhiX174 lysis gene E, whereas pores in gram-positive bacteria can be formed through minimally inhibitory gentle chemical protocols. In biological protocols, the temperature-sensitive λ system has been widely used for quick and efficient lysis without the need for any addition of chemical inducers. To produce BGs with enhanced safety, the incorporation of the staphylococcal nuclease A gene, holin-endolysin system, or antimicrobial peptide genes into gene E -mediated lysis cassettes has been applied to improve lysis efficiency. The ghosts of a few fish pathogenic bacteria, such as Edwardsiella spp., Aeromonas spp., Vibrio spp., and Streptococcus spp., have been successfully developed by gene E -mediated lysis, which maintain the original cell morphology but eliminate genetic contents. Although the lysis efficiency of these BGs does not reach 100%, the lyophilized BGs were free of any living cells. These lyophilized BGs not only have high biological safety for fish, but also can induce stronger humoral, cellular and mucosal immune responses compared to conventional inactivated vaccines. Moreover, BGs are easy to produce in large quantities by fermentation without laborious purification procedures and easy to administer through oral or immersion immunization. Therefore, BGs are good fish vaccine candidates and can be engineered to display heterologous antigens or deliver DNA for use as multivalent vaccines against fish pathogen infection. Yet, completely inactivation was not achieved by the gene E -mediated lysis procedure, how to improve the lysis efficiency of BGs is an important problem for BG production. It is believed that the BG system will play an increasingly important role in the prevention and control of fish diseases with further research and continuous biotechnological development. • Bacterial ghosts (BGs) are produced mainly through phage lysis gene E-mediated lysis. • The safety of BGs is enhanced by the combined application of lysis genes and secondary lethal genes. • The ghosts of 14 important fish pathoges have been successfully generated. • The fish BG vaccines are safe and induce stronger immune responses in fish than conventional inactivated vaccines. • BGs are excellent delivery vectors for fish recombinant and DNA vaccines. [ABSTRACT FROM AUTHOR]

In this article, a new method is proposed for solving a class of structured variational inequalities (SVIs). The proposed method is referred to as the partial inexact proximal alternating direction (piPAD) method. In the method, two subproblems are solved independently. One is handled by an inexact proximal point method and the other is solved directly. This feature is the major difference between the proposed method and some existing alternating direction-like methods. The convergence of the piPAD method is proved. Two examples of the modern convex optimization problem arising from engineering and information sciences, which can be reformulated into the encountered SVIs, are presented to demonstrate the applicability of the piPAD method. Also, some preliminary numerical results are reported to validate the feasibility and efficiency of the piPAD method. [ABSTRACT FROM AUTHOR]

The max-bisection problem consists in partitioning the vertices of a weighted undirected graph into two equally sized subsets so as to maximize the sum of the weights of crossing edges. It is an NP-hard combinatorial optimization problem that arises in many applications. In this paper, we present a memetic algorithm for the max-bisection problem, which integrates a new fast local search procedure, a crossover operator, and a pool updating strategy. These strategies achieve a balance between intensification and diversification. Extensive experiments were performed on a number of benchmark instances with 800 to 10,000 vertices from the literature. The proposed memetic algorithm improved the best known solutions for all benchmark instances tested in this paper. The improvement in terms of cut value over the CirCut by Burer et al. refid="ref34"/ ranging from 0.02 to 4.15 percent, and the average time of our proposed memetic algorithm is much lower than that of CirCut. It shows that the proposed memetic algorithm can find high quality solutions in an acceptable running time. [ABSTRACT FROM AUTHOR]

The very large-scale integrated circuit (VLSI) placement problem is to determine the exact location of each movable circuit element within a given region. It is a crucial process in physical design, since it affects performance, power consumption, routability, and heat distribution of a design. In this paper, we propose a VLSI placement flow to handle the large-scale mixed-size placement problem. The main idea of our placement flow is using a floorplanning algorithm to guide the placement of circuit elements. It consists of four steps: (1) With the multilevel framework, circuit elements are clustered into blocks by recursively partitioning; (2) a floorplanning algorithm is performed on every level of the blocks; (3) the macro cells are shifted by a macro shifting technique to determine their exact locations; (4) with each macro cell location fixed, a standard cell placement algorithm is applied to place the remaining objects. The proposed approach is tested on the IBM mixed-size benchmarks and the modern mixed-size (MMS) placement benchmarks. Experimental results show that our approach outperforms the state-of-the-art placers on the solution quality for most of the benchmarks. [ABSTRACT FROM AUTHOR]

In this paper, we consider the circuit partitioning problem, which is a fundamental problem in computer-aided design of very large-scale-integrated circuits. We formulate the problem as an equivalent constrained integer programming problem by constructing an auxiliary function. A global search method, entitled the dynamic convexized method, is developed for the integer programming problem. We modify the Fiduccia–Mattheyses (FM) algorithm, which is a fundamental partitioning algorithm for the circuit partitioning problem, to minimize the auxiliary function. We show both computationally and theoretically that our method can escape successfully from previous discrete local minimizers by taking increasing values of a parameter. Experimental results on ACM/SIGDA and ISPD98 benchmarks show up to 58% improvements over the well-known FM algorithm in terms of the best cutsize. Furthermore, we integrate the algorithm with the state-of-the-art practical multilevel partitioner MLPart. Experiments on the same set of benchmarks show that the solutions obtained in this way has 3–7% improvements over that of the MLPart. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a method for finding a Nash equilibrium of two-person games with alternating offers. The proposed method is referred to as the inexact proximal alternating direction method. In this method, the idea of alternating direction method simulates alternating offers in the game, while the inexact solutions of subproblems can be matched to the assumptions of incomplete information and bounded individual rationality in practice. The convergence of the proposed method is proved under some suitable conditions. Numerical tests show that the proposed method is competitive to the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Placement is the process of determining the exact locations of circuit elements within a chip. It is a crucial step in very large scale integration (VLSI) physical design, because it affects routability, performance, and power consumption of a design. In this paper, we develop a new analytical placer to solve the VLSI standard cell placement problem. The placer consists of two phases, multilevel global placement (GP) and detailed cell placement (DP). In the stage of GP, during the clustering stage, we use a nonlinear programming technique and a best-choice clustering algorithm to take a global view of the whole netlist and placement information, and then use an iterative local refinement technique during the declustering stage to further distribute the cells and reduce the wirelength. In the stage of DP, we develop a fast legalization algorithm to make the solution by global placement legal and use a cell order polishing to improve the legal solution. The proposed algorithm is tested on the IBM standard cell benchmark circuits and Peko suites. Experimental results show that our placer obtains high-quality results in a reasonable running time. [ABSTRACT FROM AUTHOR]

The max-cut problem is a classical NP-hard problem in graph theory. In this paper, we adopt a local search method, called MCFM, which is a simple modification of the Fiduccia-Mattheyses heuristic method in Fiduccia and Mattheyses (Proc. ACM/IEEE DAC, pp. 175-181, ) for the circuit partitioning problem in very large scale integration of circuits and systems. The method uses much less computational cost than general local search methods. Then, an auxiliary function is presented which has the same global maximizers as the max-cut problem. We show that maximization of the function using MCFM can escape successfully from previously converged discrete local maximizers by taking increasing values of a parameter. An algorithm is proposed for the max-cut problem, by maximizing the auxiliary function using MCFM from random initial solutions. Computational experiments were conducted on three sets of standard test instances from the literature. Experimental results show that the proposed algorithm is effective for the three sets of standard test instances. [ABSTRACT FROM AUTHOR]

Abstract: This paper considers the nonlinearly constrained continuous global minimization problem. Based on the idea of the penalty function method, an auxiliary function, which has approximately the same global minimizers as the original problem, is constructed. An algorithm is developed to minimize the auxiliary function to find an approximate constrained global minimizer of the constrained global minimization problem. The algorithm can escape from the previously converged local minimizers, and can converge to an approximate global minimizer of the problem asymptotically with probability one. Numerical experiments show that it is better than some other well known recent methods for constrained global minimization problems. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the box constrained nonlinear integer programming problem. We present an auxiliary function, which has the same discrete global minimizers as the problem. The minimization of the function using a discrete local search method can escape successfully from previously converged discrete local minimizers by taking increasing values of a parameter. We propose an algorithm to find a global minimizer of the box constrained nonlinear integer programming problem. The algorithm minimizes the auxiliary function from random initial points. We prove that the algorithm can converge asymptotically with probability one. Numerical experiments on a set of test problems show that the algorithm is efficient and robust. [Copyright &y& Elsevier]

We present a new definition of filled function, named globally concavized filled function, for the box constrained continuous global minimization problem. A class of this kind of filled functions are constructed. These functions contain two easily determinable parameters, which are not dependent on the radius of the basin at the current local minimizer to make them be globally concavized filled functions. We design a randomized algorithm to solve the problem basing on these functions and prove that the algorithm can converge asymptotically with probability one to a global minimizer of the problem. Numerical experiments are presented to show the effectiveness and robustness of the algorithm. [ABSTRACT FROM AUTHOR]

Abstract: We show that over unbounded domain no algorithm can be created for the integer programming, nonlinear equations, continuous global optimization and constraint satisfaction problems. [Copyright &y& Elsevier]

Abstract: In this paper we show that the unconstrained continuous global minimization problem cannot be solved by any algorithm, so we consider the box constrained continuous global minimization problem. We present a definition of filled function for the problem. Moreover, a new class of filled functions are constructed, which contains only one parameter. A randomized algorithm is designed to solve the box constrained continuous global minimization problem based on the filled function. Numerical experiments are presented to show the practicability of the algorithm. [Copyright &y& Elsevier]

Abstract: This paper presents a Branch and Bound method for a nonconvex integer quadratic programming problem with a separable objective function over a bounded box. For this problem, a special branch method is constructed, which has a property that if a box has been partitioned into sub-boxes, then at least one sub-box can be deleted. We analyze the complexity of the algorithm, and prove that it is better than that of the complete enumeration method in the worst case if the solution space is large enough. [Copyright &y& Elsevier]

The addition of HPS prior to NaOL prevented the interaction of NaOL with calcite surface while it did not prevent the interaction of NaOL with fluorite surface. Schematic of fluorite/calcite surface with reagents at pH 8. [Display omitted] The effect of hydroxypropyl starch (HPS) on the flotation separation of fluorite from calcite using sodium oleate (NaOl) as a collector was studied. Micro-flotation results of single minerals showed that both fluorite and calcite presented good floatability in the presence of NaOl. However, by adding HPS before NaOl, the calcite flotation recovery was selectively reduced. The flotation of artificially mixed minerals confirmed that an efficient separation of fluorite from calcite could be achieved using the reagents scheme of HPS/NaOl. Zeta potential measurements demonstrated that HPS prevented the NaOl adsorption onto the calcite surface while it did not inhibit the interaction of NaOl with the fluorite surface. Fourier Transform Infrared (FT-IR) analysis was also revealed that the selective adsorption of HPS onto the calcite surface. [ABSTRACT FROM AUTHOR]

The Pd/PANI catalyst, supported on nickel foam, enabled efficient electrocatalytic alkyne semi-hydrogenation. It efficiently converted various alkynes into alkenes with good to excellent yields, using H 2 O or D 2 O as hydrogen sources. With low Pd loading (0.24–0.4 mol%), the Pd/PANI-NF catalyst demonstrated prolonged catalytic stability in both batch and continuous flow electrolysis processes, underscoring its practical potential for electrocatalytic hydrogenation. [Display omitted] • Efficient and active Pd/PANI catalyst with synergistic effect between Pd nanoparticles and PANI on the nickel foam. • Broad substrate range for alkyne semi-hydrogenation and deuteration. • Gram-scale production of alkenes under continuous flow. In this study, we synthesized Pd/PANI catalysts anchored on nickel foam (NF) via a single-step CV electrodeposition process. The resulting Pd 0.3 /PANI-NF materials exhibited outstanding selectivity and activity for electrocatalytic alkyne semi-hydrogenation and deuteration under ambient conditions. Characterization of Pd/PANI and control experiment revealed that the combination of PANI and Pd had a synergistic effect on the catalytic performance of Pd/PANI-NF for alkyne semi-hydrogenation. Optimized conditions in H-cells allowed efficient conversion of various terminal and internal alkynes into their corresponding alkenes with remarkable yields up to 92 % and a Faradaic efficiency of 88 %, even at low Pd loading (0.4 mol%). The Pd 0.3 /PANI-NF showed sustained catalytic activity for gram-scale alkene synthesis through five usage cycles under continuous flow conditions, marked by a high TOF (up to 230 h−1) and combined TONs of 2151, establishing its practical viability for electrocatalytic hydrogenation. [ABSTRACT FROM AUTHOR]

Numerous studies have demonstrated that connected autonomous vehicles and human-driven vehicles are now coexisting throughout a transitional phase. Traffic flow can be improved, the system can be stabilized, and less energy will be used with dedicated lanes for connected autonomous vehicles. Additionally, with few communication resources, no communication delivery is ever perfect, leading to issues with poly-information uncertainty. First, this paper provides a macroscopic model of heterogeneous traffic flow from the perspective of vehicle dynamics employing electronic throttle dynamics and poly-information uncertainty with/without dedicated lanes. Second, the mixed traffic flow linear stability criterion is derived using the linear stability theory. The third portion, which was based on the theoretical analysis, focused on the consequences of dedicated lane configurations on traffic flow as well as a discussion of the effects of various parameters on the stability of mixed traffic flow and energy consumption emissions. Finally, we modeled the Huanshan Road in Jinan, China using the experimental VISSIM platform. The analysis and demonstration of a two-way, four-lane road with or without dedicated lanes. The findings demonstrate that increasing connected autonomous vehicles penetration and dedicated lanes construction can increase traffic capacity, enhance the stability of traffic flow, and lower energy use and additional emissions. It is important to keep in mind that dedicated lanes must be built at an appropriate connected autonomous vehicle penetration rate to boost traffic flow without squandering resources. • A macro model is developed to describe the CAV dedicated lane setups and poly-information uncertainties • The performance of the system is optimized from the smoothness and stability of the traffic flow density wave • The impacts of poly-information uncertainties on the stability and energy consumption of traffic flow system • Trialability of dedicated lanes in a comparative comparison of real-world settings under specific circumstances [ABSTRACT FROM AUTHOR]

Double-weight optical orthogonal codes are variable-weight optical orthogonal codes (OOCs), which have been widely applied in optical networks and systems. Some works have been devoted to optimal n , W , 1 , Q -OOCs with max w : w ∈ W ≤ 6. So far, there is no explicit construction of optimal n , W , 1 , Q -OOCs with W = 5,7 . It is known that heavier-weight codewords have better code performance than lighter-weight codewords. So, in this paper, we use cyclic packing to construct two infinite classes of optimal OOCs with weights set 5,7 explicitly, for any prime p ≡ 3 mod 4 and p ≥ 7. In addition, for 1 ≤ t < p − 1 / 2 , by breaking t blocks of size 7 into 3 of 31 p , 5,7 , 1 , 1 / 2 , 1 / 2 -OOCs and 41 p , 5,7 , 1 , 2 / 3 , 1 / 3 -OOCs, we obtain new infinite classes of optimal 31 p , 3,5,7 , 1 , 7 t / p − 1 + 6 t , p − 1 / 2 p − 1 + 6 t , p − 1 − 2 t / 2 p − 1 + 6 t -OOCs and 41 p , 3,5,7 , 1 , 14 t / 3 p − 1 + 4 t , 2 p − 1 / 3 p − 1 + 4 t , p − 1 − 2 t / 3 p − 1 + 4 t -OOCs, respectively. [ABSTRACT FROM AUTHOR]

Given a set of sensors distributed on the plane and a set of Point of Interests (POIs) on a line segment, a primary task of the mobile wireless sensor network is to schedule covering the POIs by the sensors, such that each POI is monitored by at least one sensor. For balancing the energy consumption, we study the min-max line barrier target coverage (LBTC) problem which aims to minimize the maximum movement of the sensors from their original positions to their final positions at which the coverage is composed. We first proved that when the radius of the sensors are non-uniform integers, even 1-dimensional LBTC (1D-LBTC), a special case of LBTC in which the sensors are distributed on the line segment instead of the plane, is NP -hard. The hardness result is interesting, since the continuous version of LBTC to cover a given line segment instead of the POIs is known polynomial solvable. Then we present an exact algorithm for LBTC with uniform radius and sensors distributed on the plane, via solving the decision version of LBTC. We argue that our algorithm runs in time O (n 2 log n) and produces an optimal solution to LBTC. The time complexity compares favorably to the state-of-art runtime O (n 3 log n) of the continuous version which aims to cover a line barrier instead of the targets. Last but not the least, we carry out numerical experiments to evaluate the practical performance of the algorithms, which demonstrates a practical runtime gain comparing with an optimal algorithm based on integer linear programming. [ABSTRACT FROM AUTHOR]

Mixed-cell-height circuits have become popular in advanced technologies for better power, area, routability, and performance tradeoffs. With technology and region constraints imposed by modern circuit designs, the mixed-cell-height legalization problem has become even more challenging. Additionally, an ideal legalization method should minimize both the average and maximum cell movements to preserve the quality of a given placement as much as possible. In this article, we present an effective and efficient mixed-cell-height legalization algorithm to consider technology and region constraints while minimizing the average and maximum cell movements. We first present a fence region handling technique to unify the fence regions and the default region. To obtain a desired cell assignment, we then propose a movement-aware cell reassignment method by iteratively reassigning cells in locally dense areas to their desired rows. After cell reassignment, a technology-aware legalization is presented to remove cell overlaps while satisfying the technology constraints. Finally, we propose a technology-aware refinement to further reduce the average and maximum cell movements without increasing the technology constraints violations. Compared with the champion of the 2017 CAD Contest at ICCAD and the state-of-the-art work, experimental results based on the 2017 CAD Contest at ICCAD benchmarks show that our algorithm achieves the best average and maximum cell movements and significantly fewer technology constraint violations, in a comparable runtime. The experimental results based on the modified 2015 ISPD Contest benchmarks also demonstrate the effectiveness of our algorithm in minimizing the average and maximum cell movements, compared with state-of-the-art mixed-cell-height legalizers. [ABSTRACT FROM AUTHOR]

Block copolymer directed self-assembly (DSA) is a simple and promising candidate next-generation device fabrication technology, which is low-cost as complement with multi-patterning for contact layer patterning. In this paper, we consider the contact layer mask and template assignment problem of DSA with triple patterning lithography of general layout. To address this problem, first we construct a weighted conflict grouping graph, in which edges with negative weights are introduced, then a discrete relaxation based mask assignment problem is proposed. The integer linear program (ILP) formulation of the discrete relaxation problem is solved for obtaining a lower bound on the optimal value of this problem. In order to improve the lower bound, some valid inequalities are introduced to prune some poor relaxation solutions. At last, the obtained discrete relaxation solution is transformed to a legal solution of the original problem by solving a template assignment problem on the layout graph, which provides an upper bound on the optimal value of the original problem. Experimental results and comparisons show the effectiveness and efficiency of our method. In addition, under the discrete relaxation theory, the quality of our experimental results can be evaluated by the obtained upper and lower bounds. Specifically, the gap between the obtained upper and lower bounds is 0 for most of the sparse benchmarks, and the average gap is 0.4% for dense benchmarks. [ABSTRACT FROM AUTHOR]

In this paper, we consider the triple patterning lithography layout decomposition problem. To address the problem, a discrete relaxation theory is built. For designing a discrete relaxation based decomposition framework, we propose a surface projection method for identifying native conflicts in a layout, and then constructing the conflict graph. Guided by the theory, the conflict graph is reduced to small size subgraphs by vertex removals, which is a discrete relaxation. Furthermore, by ignoring stitch insertions and assigning weights to features, the layout decomposition problem on the small subgraphs is further relaxed to a 0-1 program, which is solved by the Branch-and-Bound method. To obtain a feasible solution of the original problem, legalization methods are introduced to legalize a relaxation solution. At the legalization stage, we prior utilize one-stitch insertion to eliminate conflicts, and use a backtrack coloring algorithm to obtain a better solution. We test our decomposition approach on the ISCAS-85 & 89 benchmarks. Comparisons of experimental results show that our approach finds solutions of some benchmarks better than those by the state-of-the-art decomposers. Especially, according to our discrete relaxation theory, some optimal decompositions are obtained. [ABSTRACT FROM PUBLISHER]

Fogging and proximity effects (FPEs) are two major factors that cause inaccurate exposure and layout pattern distortions in e-beam lithography. In this article, we propose an analytical placement algorithm that considers both FPEs. We formulate the global placement problem as a separable minimization problem with linear constraints, where different objectives can be tackled one by one in an alternating fashion. Then, we propose a novel proximal group alternating direction method of multipliers (ADMM) to solve the separable minimization problem with two subproblems, where the first subproblem (associated with wirelength and density) is solved by the steepest descent method without line search, and the second one (associated with the FPEs) is handled by an analytical scheme. We prove the property of global convergence of the proximal group ADMM method. Finally, the FPEs-aware legalization and detailed placement are employed to legalize and improve the placement result. The experimental results show that our algorithm is effective and efficient for the addressed problem. Our algorithm achieved 5.7% smaller fogging variation, 6.8% lower proximity variation, and 5.4% lower runtime with a minor wirelength overhead compared with the state-of-the-art work. [ABSTRACT FROM AUTHOR]

Mixed-cell-height standard cells are prevailingly used in advanced technologies to achieve better design tradeoffs among timing, power, and routability. As feature size decreases, the placement of cells with multiple threshold voltages may violate the complex minimum-implant-area (MIA) layer rule arising from the limitations of patterning technologies. Existing works consider the mixed-cell-height placement problem only during legalization or handle the MIA constraints during detailed placement. In this article, we address the mixed-cell-height placement problem with MIA constraints in two major stages: 1) post-global placement (Post-GP) and 2) MIA-aware legalization. In the Post-GP stage, we first present a continuous and differentiable cost function to address the Vdd/Vss alignment constraints and add weighted pseudonets to MIA-violation cells dynamically. Then, we propose a proximal optimization method based on the given global placement result to simultaneously consider Vdd/Vss alignment constraints, MIA constraints, cell distribution, cell displacement, and total wirelength. In the MIA-aware legalization stage, we develop a graph-based method to cluster cells of specific threshold voltages and apply a strip-packing-based binary linear programming to reshape cells. Then, we propose a matching-based technique to resolve intrarow MIA violations and reduce filler insertion. Furthermore, we formulate inter-row MIA-aware legalization as a quadratic programming problem, which is efficiently solved by a modulus-based matrix splitting iteration method. Finally, MIA-aware cell allocation and refinement are performed to further improve the result. Experimental results show that without any extra area overhead, our algorithm still can achieve 5.4% shorter final total wirelength than the state-of-the-art work. [ABSTRACT FROM AUTHOR]

Metal fill insertion has become an essential step in reducing dielectric thickness variation and improving pattern uniformity, which is important in mitigating process variations, thereby achieving better manufacturing yield. However, metal fills could induce coupling capacitance, which is not often considered in existing works that typically focus more on pattern density uniformity, incurring significant problems in timing closure. However, it is a great challenge to consider three types of capacitances (i.e., area, fringe, and lateral capacitances) with design rules and density constraints at the fill insertion stage simultaneously. This article presents an efficient timing-aware fill insertion algorithm for minimizing the total capacitance and fill amount, considering the density constraints. First, we present an initial metal fill insertion and design-rule-aware legalization to obtain an initial fill insertion solution quickly. Second, from critical conductors to powers/grounds in a circuit, we divide conductors into different equivalent paths and then construct a capacitance graph to reduce the capacitance of each equivalent path globally. Third, we propose a density-aware coupling capacitance optimization method and a fast Monte Carlo-based fill selection to further reduce the coupling capacitance between any pair of conductors. Finally, we present a density-aware fill deletion method to reduce the fill amount. We evaluate the performance of our algorithm on the benchmarks of the 2018 CAD Contest at ICCAD and its official contest evaluator. Compared with the first-place team of the contest and the state-of-the-artwork, experimental results show that our algorithm achieves the lowest total capacitance and the least fill amount in a comparable runtime. [ABSTRACT FROM AUTHOR]

Decision-making is a very important cognitive process in our daily life. There has been increasing interest in the discriminability of single-trial electroencephalogram (EEG) during decision-making. In this study, we designed a machine learning based framework to explore the discriminability of single-trial EEG corresponding to different decisions. For each subject, the framework split the decision-making trials into two parts, trained a feature model and a classifier on the first part, and evaluated the discriminability on the second part using the feature model and classifier. A proposed algorithm and five existing algorithms were applied to fulfill the feature models, and the algorithm Linear Discriminative Analysis (LDA) was used to implement the classifiers. We recruited 21 subjects to participate in Chicken Game (CG) experiments. The results show that there exists the discriminability of single-trial EEG between the cooperation and aggression decisions during the CG experiments, with the classification accuray of 75% (±6%), and the discriminability is mainly from the EEG information below 40 Hz. The further analysis indicates that the contributions of different brain regions to the discriminability are consistent with the existing knowledge on the cognitive mechanism of decision-making, confirming the reliability of the conclusions. This study exhibits that it is feasible to apply machine learning methods to EEG analysis of decision-making cognitive process. [ABSTRACT FROM AUTHOR]

Abstract: We propose a derivative-free implementation of Dekkers and Aarts’ continuous simulated annealing (SA). Essential in DFSA is the ’random direction’ local technique that we introduce. We study the convergence properties of the resulting algorithm and test its performance on a set of 50 problems. Numerical results are presented which show the robustness of the algorithm. Numerical comparisons with SA, two derivative-free simulated annealing algorithms and three population-based global optimization algorithms show that the derivative-free SA, DFSA, offers a reasonable alternative to some recent global optimization algorithms, especially for problems requiring a ‘direct search’ type algorithm. [Copyright &y& Elsevier]

Abstract: High-density Co3O4 nanowire arrays have been fabricated by a simple, solvent-free synthesis method inside the alumina pores. It has been found that the pore diameter played a key role in the formation of the Co3O4 nanowires. When the same reaction was performed in the narrow pores of the AAO template (<90nm), a mixture of nanoparticles and short nanorods were obtained. The nanorod consists of a lot of obvious grains, which form grain chains. However, continuous and uniform nanowires could be produced when the larger pores of AAO (>120nm) were applied. Selected-area electron diffraction (SAED) patterns revealed that the nanowires were single-crystalline. Electrochemical measurements by an electrochemical workstation indicate that the specific capacitance characteristics of the as-prepared Co3O4 nanowires are much higher than that of Co3O4 particles. [Copyright &y& Elsevier]

Abstract: In this paper, the partner selection problem with a due date constraint in virtual enterprises is proved to be an NP-complete problem. So it cannot have any polynomial time solution algorithm at present. A nonlinear integer programming model for this problem is established. The objective function and a constraint function of the model have monotone properties. Based on the above observations, a Branch & Bound algorithm is constructed to solve the problem. Numerical experiments show that the algorithm is efficient. [Copyright &y& Elsevier]

With the increasing complexity in modern circuit designs, the 6T&6TPPNN circuits have become popular in advanced technologies for better trade-offs among routability, timing, power and performance. The 6TPPNN cells incur great challenges to layout designs, especially the legalization problem due to their complex minimum width (MW) constraints and the fragmentation effect (FE). In this paper, we address the mixed 6T&6TPPNN cell legalization problem considering both MW constraints and FE issues. Given a global placement result, we first align all cells to the correct rows/half-rows that satisfy the VDD/VSS alignment constraints, and then propose a clustering-based MW constraints solving method to eliminate all the MW violations. After that, we formulate the legalization problem with MW constraints as a quadratic programming (QP) problem, which not only satisfies the MW constraints, but also avoid causing excessive dead spaces. Finally, we integrate the FE issues into the formulated MW-aware QP model, and adopt the modulus-based matrix splitting iteration method (MMSIM) to solve the mathematical model effectively and efficiently. Experimental results show that our algorithm can resolve all MW constraints and mitigate the half-row fragmentation effect without any extra area overhead in a reasonable time. • We propose a clustering-based method to eliminate all the minimum width (MW) violations. • We formulate the legalization problem with MW constraints as a quadratic programming problem. • We further integrate the fragmentation effect (FE) issues into the formulated MWaware legalization model. • We adopt the modulus-based matrix splitting iteration method to solve the MW&FE-aware legalization problem effectively. • Experimental results show that our algorithm can resolve all MW constraints and mitigate the FE in reasonable runtime. [ABSTRACT FROM AUTHOR]

As an emerging manufacture technology, block copolymer directed self-assembly (DSA) is promising for via layer fabrication. Meanwhile, redundant via insertion is considered as an essential step for yield improvement. For better reliability and manufacturability, in this paper, we first concurrently consider DSA guiding template cost assignment with multiple redundant via and dummy via insertion. Firstly, by analyzing the structure property of guiding templates, we propose a building-block based solution expression to discard redundant solutions. Then, honoring the compact solution expression, we construct a conflict graph with dummy via insertion, and then formulate the problem to an integer linear programming (ILP). In addition, to optimize the guiding template cost, we incorporate it into the objective of ILP by introducing vertex weight and edge weight in conflict graph. To make a good trade-off between solution quality and runtime, we relax the ILP to an unconstrained nonlinear programming (UNP). Finally, a line search optimization algorithm is proposed to solve the UNP. Experimental results verify the effectiveness of our new solution expression and the efficiency of our proposed algorithm. Specifically, our guiding template cost optimization method can save 18% total guiding template cost. • In this journal version, we first use multiple redundant via insertion technique to further improve the manufacture rate and insertion rate for the DSA guiding template and redundant via insertion problem. In Section 1, we present the role of multiple redundant via insertion by illustrating an example as Figure 4. • In this journal version, we first consider the cost of DSA guiding template. Complex templates with more holes would introduce larger overlays than regular templates with less holes. Considering guiding template cost can reduce overlays. • For the DSA guiding template assignment with multiple redundant via and dummy via insertion (DMRD) problem, we prove its NP complexity in Section 2.3. • In Section 3.2, we add the introduction of our graph reduction technique. • In Section 3.3, we add the introduction and relationship of guiding template cost, building-block cost and template edge weight. • In Section 4.3, we prove the local convergence and analyze the efficiency of our unconstrained nonlinear programming (UNP) solver. • In Section 4.4, we extend our ILP formulation in conference paper to consider guiding template cost, which is a quadratic integer programming (QIP). Furthermore, the QIP also can be solved by our UNP solver. • In Section 5, we add experimental result comparison of our ILP solver with previous works. And we add the comparison of our UNP solver and the ILP solver in TCAD'17 [18] on nine much larger benchmarks in Table 2. In addition, 1 we compare the guiding template cost between our UNP solver with guiding template cost and without guiding template cost in Section 5.3. [ABSTRACT FROM AUTHOR]

Floorplanning is a crucial step in very large scale integration design flow. It provides valuable insights into the hardware decisions and estimates a floorplan with different cost metrics. In this paper, to handle a multi-objective thermal-aware non-slicing floorplanning optimization problem efficiently, an adaptive hybrid memetic algorithm is presented to optimize the area, the total wirelength, the maximum temperature and the average temperature of a chip. In the proposed algorithm, a genetic search algorithm is used as a global search method to explore the search space as much as possible, and a modified simulated annealing search algorithm is used as a local search method to exploit information in the search region. The global exploration and local exploitation are balanced by a death probability strategy. In this strategy, according to the natural mechanisms, each individual in the population is endowed with an actual age and a dynamic survival age. Experimental results on the standard tested benchmarks show that the proposed algorithm is efficient to obtain floorplans, with decreasing the average and the peak temperature. [ABSTRACT FROM AUTHOR]