Swap Strategy Research Articles

Periodic Scheduling Optimization for Dual-Arm Cluster Tools with Arm Task and Residency Time Constraints via Petri Net Model

In order to improve quality assurance in wafer manufacturing, there are strict process requirements. Besides the well-known residency time constraints (RTCs), a dual-arm cluster tool also requires each robot arm to execute a specific set of tasks. We call such a tool an arm task-constrained dual-arm cluster tool (ATC-DACT). To do this, one of the arms is identified as the dirty one and the other as the clean one. The dirty one can deal with raw wafers, while the clean one can deal with processed wafers. This requirement raises a new problem for scheduling a cluster tool. This paper discusses the scheduling problem of ATC-DACTs with RTCs. Due to the arm task constraints, the proven, effective swap strategy is no longer applicable to ATC-DACTs, making the scheduling problem difficult. To address this problem, we explicitly describe the robot waiting as an event and build a Petri net (PN) model. Then, we propose a hybrid task sequence (HTS) as an operation strategy by combining the swap and backward strategies. Based on the HTS, the necessary and sufficient conditions for schedulability are established; also, a linear programming model is developed. We then develop an algorithm using these results to optimally schedule the system. Industrial case studies demonstrate the application of this method.

High-throughput mutagenesis and screening approach for the identification of drug-resistant mutations in the rifampicin resistance-determining region of mycobacteria

Rifampicin is the most powerful first-line antibiotic for tuberculosis, which is caused by Mycobacterium tuberculosis. Although accumulating evidence from sequencing data of clinical M. tuberculosis isolates suggested that mutations in the rifampicin-resistance-determining region (RRDR) are strongly associated with rifampicin resistance, the comprehensive characterisation of RRDR polymorphisms that confer this resistance remains challenging. By incorporating I-SceI sites for I-SceI-based integrant removal and utilizing an L5 swap strategy, we efficiently replaced the integrated plasmid with alternative alleles, making mass allelic exchange feasible in mycobacteria. Using this method to establish a fitness-related gain-of function screen, we generated a mutant library that included all single-amino-acid mutations in the RRDR, and identified the important positions corresponding to some well-known rifampicin-resistance mutations (Q513, D516, S522, H525, R529, S531). We also detected a novel two-point mutation located in the RRDR confers a fitness advantage to M. smegmatis in the presence or absence of rifampicin. Our method provides a comprehensive insight into the growth phenotypes of RRDR mutants and should facilitate the development of anti-tuberculosis drugs.

An organometallic swap strategy for bottlebrush polymer-protein conjugate synthesis.

Polymer-protein bioconjugation offers a powerful strategy to alter the physical properties of proteins, and various synthetic polymer compositions and architectures have been investigated for this purpose. Nevertheless, conjugation of molecular bottlebrush polymers (BPs) to proteins remains an unsolved challenge due to the large size of BPs and a general lack of methods to transform the chain ends of BPs into functional groups suitable for bioconjugation. Here, we present a strategy to address this challenge in the context of BPs prepared by "graft-through" ring-opening metathesis polymerization (ROMP), one of the most powerful methods for BP synthesis. Quenching ROMP of PEGylated norbornene macromonomers with an activated enyne terminator facilitates the transformation of the BP Ru alkylidene chain ends into Pd oxidative addition complexes (OACs) for facile bioconjugation. This strategy is shown to be effective for the synthesis of two BP-protein conjugates (albumin and ERG), setting the stage for a new class of BP-protein conjugates for future therapeutic and imaging applications.

Non-iterative border-peeling clustering algorithm based on swap strategy

Border-Peeling algorithm is a recently proposed density based clustering algorithm. The method of peeling off border points by continuous iteration and calculating the density influence value by using the Gaussian kernel distance makes the algorithm more complex. At the same time, there is a risk of excessive peeling of small clusters on unbalanced datasets, which leads to a large number of noise misidentification. In order to reduce the time consumption and improve the clustering performance on unbalanced datasets, this paper proposes a non-iterative border-peeling clustering algorithm. First, the potential core points are determined by the centroids of k-nearest neighbor. Secondly, the points with lower local relative density in the core points and the points with higher relative density in the border points are exchanged to complete the distinction between the core points and the border points. Then basic DBSCAN method is used to cluster core points and noise points. Finally, the associations between the border points and the core points are based on the number of reverse nearest neighbors of the border points in the core points. Our method has achieved competitive results on 10 synthetic datasets and 8 UCI real-world datasets.

A SAT Approach to the Initial Mapping Problem in SWAP Gate Insertion for Commuting Gates

Most quantum circuits require SWAP gate insertion to run on quantum hardware with limited qubit connectivity. A promising SWAP gate insertion method for blocks of commuting two-qubit gates is a predetermined swap strategy which applies layers of SWAP gates simultaneously executable on the coupling map. A good initial mapping for the swap strategy reduces the number of required swap gates. However, even when a circuit consists of commuting gates, e.g., as in the Quantum Approximate Optimization Algorithm (QAOA) or trotterized simulations of Ising Hamiltonians, finding a good initial mapping is a hard problem. We present a SAT-based approach to find good initial mappings for circuits with commuting gates transpiled to the hardware with swap strategies. Our method achieves a 65% reduction in gate count for random three-regular graphs with 500 nodes. In addition, we present a heuristic approach that combines the SAT formulation with a clustering algorithm to reduce large problems to a manageable size. This approach reduces the number of swap layers by 25% compared to both a trivial and random initial mapping for a random three-regular graph with 1000 nodes. Good initial mappings will therefore enable the study of quantum algorithms, such as QAOA and Ising Hamiltonian simulation applied to sparse problems, on noisy quantum hardware with several hundreds of qubits.

Dynamic and Pareto-improving swapping of vehicles to enhance integrated and modular mobility services

Efficiency of many mobility services depends on effective matching of service vehicles and customers over time and space. New technologies, such as those related to service integrators and modularized autonomous vehicle platforms (i.e., chassis with built-in power and control systems), further allow pooling of vehicles from traditionally separate service operators to flexibly serve multiple types of customers (e.g., passengers and freight). Dynamic matching systems, if not carefully managed, suffer from the so-called wild goose chase (WGC) phenomenon, which describes an inefficient system equilibrium with a large number of vehicles trapped in unproductive deadheading. This paper proposes a new dynamic vehicle swap strategy that can be used to enhance system efficiency by reducing the expected waiting/deadheading time. This strategy can not only mitigate the WGC and reduce the needed fleet size, but also ensure that the vehicle swap achieves a Pareto improvement for each involved participant. Approximate analytic formulas are derived from a series of differential equations and spatial probability models to estimate the expected system performance in the steady state. This system of nonlinear equations can be solved numerically to yield the equilibrium points and the associated system performance metrics. Agent-based simulations are used to verify the accuracy of the derived formulas, and to demonstrate the effectiveness of the proposed dynamic and Pareto-improving swap strategy in a variety of application contexts (e.g., taxi, service integrator, or pooled modular chassis).

Infrastructure planning for airport microgrid integrated with electric aircraft and parking lot electric vehicles

To achieve net-zero emissions in aviation with defined CO2 mitigation objectives in “Flightpath 2050″, electric aircraft (EA) becomes an attractive technology. Many aircraft prototypes with a fully electrically powered propulsion system for short-haul commuting air transport have been designed in recent years. Planning and designing the ground power systems and associated electric aircraft charging operations are also essential for realising electrified aviation. In this work, a bi-objective infrastructure planning framework for airport microgrid to accommodate parking lot electric vehicles (EVs) and EA is developed, and the impact of V2G on the airport microgrid is assessed as well. The dispatching problem of the airport microgrid is formulated as a heuristic optimisation problem, and the NSGA-II algorithm is adopted to find the Pareto Fronts and optimal solutions. There are two different scheduling strategies for charging EA: plug-in charge and battery swap. The economic and technological assessments for both strategies are conducted and compared. The results show that adopting V2G strategy can indeed improve the airport microgrid economical performance. In general, the EA plug-in charge strategy performs better than the EA battery strategy in terms of resilience, while the EA battery swap strategy can reduce the operation costs of the airport microgrid.

Solution-based tabu search for the capacitated dispersion problem

Given a weighted graph with a capacity associated to each node (element), the capacitated dispersion problem (CDP) consists in selecting a subset of elements satisfying a capacity constraint, in such a way that the minimum distance among them is maximized. The purpose of this work is to tackle this NP-hard problem, by developing an effective and parameter-free heuristic algorithm based on the solution-based tabu search. Specifically, we propose a fast greedy construction heuristic to obtain high-quality initial solutions. To ensure a high search efficiency, our algorithm exploits the combination of three neighborhoods, including a new neighborhood based on the constrained swap strategy, and uses hash functions to identify eligible candidate solutions. Extensive computational experiments on benchmark instances in the literature are performed to demonstrate the high performance of our algorithm and get insights into the influences of the algorithmic components. The application of our algorithm to a realistic location problem further shows the usefulness of our approach for practical problems.

P643 Psoriasis induced by anti-TNF therapy in Inflammatory Bowel Disease: analysis of therapeutic management and evolution of both diseases in a nationwide cohort study

Abstract Background Some patients with Inflammatory Bowel Disease (IBD) who are treated with anti-TNFα therapy develop a drug-induced psoriasis (IP) as an adverse event. There are some therapeutic approaches, being more frequent to change the biologic therapy to ustekinumab, effective and approved for the treatment of both entities. This could be the best option, but available data are lacking and it could increase the risk of IBD relapse. Our aim is to assess the management of anti-TNF IP in IBD, and the subsequent evolution of both diseases in a large nationwide cohort of patients. Methods Retrospective, observational multicenter study from the prospectively maintained Spanish ENEIDA registry. Participants were patients with IBD and anti-TNFα IP. At baseline, psoriasis severity was classified as mild, moderate or severe, and remission was defined as the resolution of skin lesions, clinical response as an improvement without complete resolution, and no response as the absence of improvement. IBD clinical activity was defined based on Harvey-Bradshaw Index and Partial Mayo Score. All items were evaluated when available at baseline and 16, 32 and 54 weeks. Results Anti-TNFα IP was reported in 234 patients (CD: 185, UC: 46, unclassified IBD: 3). SWAP strategy was chosen in 76 patients (32.5%), most of them to ustekinumab (90.8%), 71 (30.3%) patients continued anti-TNF, 49 (20.9%) discontinued it, and in 38 (16.2%) a switch to a second anti-TNF was made. The decision to continue or not anti-TNF was associated to psoriasis severity (p<0.001) and baseline IBD activity (p=0.03). In mild psoriasis, anti-TNF was continued in 56.81% of patients, whereas SWAP and withdrawal of the anti-TNF were the most used in moderate and severe disease (32.3% and 36.5% respectively). SWAP strategy was also the most used in active IBD (46%). During follow-up, CD activity got worse in anti-TNF withdrawal group (p=0.003), without differences in the other groups. Regarding to psoriatic lesions, all strategies showed a significant improvement, with worse results when anti-TNF was continued (remission rate of 58%, p=0.042), and without differences between the other strategies at week 54. In multivariate analysis, male gender was associated with IBD remission (HR 0.233; IC95% 0.061-0.894). Trunk (OR 2.777; IC95% 1.120-6.889), as well as palms and soles location (OR 2.091; IC95% 1.018-4.294), and stopping anti-TNF treatment (OR 3.010; IC95% 1.110-8.159), were independently associated with remission of skin lesions. Conclusion Evaluating IBD activity and psoriasis severity is essential before modifying IBD treatment due to IP. Continuing anti-TNF treatment in mild psoriasis cases, and considering SWAP to ustekinumab in moderate-severe ones, could be a suitable strategy.

Measurement and mitigation of the “wild goose chase” phenomenon in taxi services

This paper examines the so-called wild goose chase phenomenon in taxi systems and proposes a new mitigation strategy based on dynamic vehicle swaps. An analytic queuing network model, including a system of differential equations, is derived to yield approximate formulas for the expected system performance in the steady-state equilibria under the vehicle swap strategy. This model is solved numerically to yield equilibrium points and the expected system performance metrics. To corroborate the theoretical predictions, a new data-processing method based on dynamic programming is proposed to identify and measure multiple distinct equilibrium states from observed data. Agent-based simulations are conducted to generate examples of such data, and to verify the formulas. Numerical results show that (i) the proposed measurement method works well in identifying the distinct equilibria, and (ii) the vehicle swap strategy works quite effectively in mitigating the wild goose chase phenomenon.

Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware

Quantum computers may provide good solutions to combinatorial optimization problems by leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often presented as an algorithm for noisy hardware. However, hardware constraints limit its applicability to problem instances that closely match the connectivity of the qubits. Furthermore, the QAOA must outpace classical solvers. Here, we investigate swap strategies to map dense problems into linear, grid and heavy-hex coupling maps. A line-based swap strategy works best for linear and two-dimensional grid coupling maps. Heavy-hex coupling maps require an adaptation of the line swap strategy. By contrast, three-dimensional grid coupling maps benefit from a different swap strategy. Using known entropic arguments we find that the required gate fidelity for dense problems lies deep below the fault-tolerant threshold. We also provide a methodology to reason about the execution-time of QAOA. Finally, we present a QAOA Qiskit Runtime program and execute the closed-loop optimization on cloud-based quantum computers with transpiler settings optimized for QAOA. This work highlights some obstacles to improve to make QAOA competitive, such as gate fidelity, gate speed, and the large number of shots needed. The Qiskit Runtime program gives us a tool to investigate such issues at scale on noisy superconducting qubit hardware.

An improved iterated greedy algorithm for the energy-efficient blocking hybrid flow shop scheduling problem

• A mathematical model of a blocking hybrid flow shop scheduling problem with energy consumption criteria is proposed. • A simple global perturbation based on a half-swap operator is proposed to further search for the potentially best solution. • A local perturbation strategy based on a swap operator is designed to ensure the convergence of the algorithm. • The proposed algorithm is applied to 140 test instances with different scales and compared with state-of-the-art algorithms and can obtain the best solution to the BHFSP. With the continuous development of national economies, problems of various energy consumption levels and pollution emissions in manufacturing have attracted attention from researchers. Most existing research has focused on reducing economic costs and energy consumption. However, the Hybrid Flow Shop Scheduling Problem with energy-efficient criteria has not yet been well studied, especially with blocking constraints. This paper is the first to present a mathematical model of the blocking hybrid flow shop problem with an energy-efficient criterion and a modified Iterative Greedy algorithm based on a swap strategy designed to optimize the constructed model. In the proposed algorithm, first, a heuristic is adopted to generate the initial solution. Second, a local perturbation strategy based on a swap operator is designed to ensure the convergence of the algorithm. Third, a simple global perturbation strategy based on a half-swap operator is proposed as a means to further search for the potentially best solution with the traditional simulated annealing criterion. The proposed algorithm is applied to 150 test instances at different scales and compared to state-of-the-art algorithms. The experimental results demonstrate that the proposed algorithm outperforms the compared algorithms and can obtain a better solution.

A simple and efficient parallel immersed boundary-lattice Boltzmann method for fully resolved simulations of incompressible settling suspensions

This study presents an efficient and parallel fully resolved direct numerical simulation (FR-DNS) of settling suspensions on multiple CPU cores based on the boundary-thickening direct forcing immersed boundary method (BTDF-IBM) and incompressible lattice Boltzmann method (LBM). The simple BTDF-IBM is used to meet the no-slip and no-penetration conditions on particle boundaries, and the incompressible LBM is used to achieve the capability of large pressure fluctuations in suspensions. In addition, a theoretical force model is used to compensate for the unresolved lubrication force between the two approaching particles. A swap strategy for the streaming step is used to reduce the memory storage of the LBM particle density functions to half. A distribution and communication strategy is proposed to handle the IBM computing and complete the immersed boundary (IB) force of the particles residing in the interface region between adjacent subdomains. The developed BTDF-IBM-LBM solver “PFlows” can simulate large particle-laden flows with more than O(106) particles and with a particle volume fraction of up to 0.4. An almost linear parallel speedup and efficiency of higher than 0.8 are obtained by testing three-dimensional (3D) cases (up to 1.0 billion fluid grids and 0.45 million particles) and two-dimensional (2D) cases (up to 1.2 billion fluid grids and 2.39 million particles). Finally, the framework is applied to three large-scale real simulations involving 50,000 particles settling in 2D and 3D bounded and unbounded domains for qualitative and quantitative validations. The particle settling behaviors and disturbed complex fluid flows in the vertical channel are demonstrated. The Boycott effect in the inclined channel is uncovered by a new mechanism that combines particle sliding at the lower sidewall with fluid convection in the upper region. The hindered settling of particles in the 3D periodic domain, which is affected by the strong particle-fluid hydrodynamic interactions and particle-particle many-body interactions at a high solid volume fraction, are analyzed. The complex behaviors and statistical characteristics of the suspensions are preliminarily revealed and analyzed, which demonstrates the prospective capability of the present framework for FR-DNS of large-scale 2D and 3D suspension flows that are relevant to many industrial applications by IB-LBM.

Land Swap Formula in the Nagorno-Karabakh Crisis Solution: Goble Plan and Lavrov Plan

When we examine the history of Nagorno-Karabakh, we can see that Armenian and Azerbaijani historians have been looking for the truth in the thousand-year history which, in turn, creates a controversial issue. The Nagorno-Karabakh Autonomous Region was established in 1923 and had an official status within Azerbaijan. In order to resolve this conflict, after the dissolution of the USSR, solution proposals were presented under the umbrella of the OSCE Minsk Group. In this study, plans based on land swap and international solution proposals are discussed comparatively. In addition, the land swap strategy that will be implemented within the frame of the ceasefire agreement that took place on November 9, 2020 and that will become a topic for discussion in the future will be evaluated in this study.

Sensory swap: Modelling the impact of swapping discretionary choices for similar tasting core foods on the energy, nutrients and sensory properties of Australian diets

Food choice is strongly driven by the sensory characteristics of foods with sweet, salty and fatty mouthfeel considered highly palatable and rewarding. Attempts to improve diet quality have not addressed sensory characteristics of diets before. This report describes a data modelling exercise that could underpin a dietary strategy to help support consumption of higher quality diets without compromising sensory preferences. This study used the Australian National Nutrition and Physical Activity Survey data (in 9341 adults) and the CSIRO sensory-diet database. A method was developed to find core food swaps which had a similar sensory profile as discretionary foods. This study investigated the impact of such swaps on energy and nutrient intake and the impact of the swaps on servings of food groups. The modelling resulted in a similar sensory profile of core foods to that of discretionary foods with hardness, sweetness and fatty mouthfeel all within 1–3% but the saltiness approached a 4% change. There was a small (3.6%) increase in energy intake. This swap strategy decreased the intake of risk nutrients such as saturated fat and added sugars, but not sodium, while increasing the intake of beneficial nutrients like calcium, zinc and vitamin C. Results also show that there was an increase in the intake of servings of core food groups such as fruits, grains, and dairy products but little change in vegetables. In conclusion, similar sensory swaps are possible and could underpin a diet strategy, that could be further refined through food appropriateness, to improve quality.

The impact of local search strategies on chaotic hybrid firefly particle swarm optimization algorithm in flow-shop scheduling

A flow-shop production environment is a widely used production setting in the industry, especially preferred when the variety of products and processes is limited. The constant development of technology and the increasing competition in the market compel researchers to seek ways to increase efficiency. Therefore, scheduling remains an important area of study for researchers. When the size of the problem increases, particularly in real-life contexts, it becomes almost impossible to work out a feasible solution to scheduling problems through current computer technologies. In such cases, solutions are often developed using heuristic or meta-heuristic methods. However, the performance of these methods may vary according to the problem or the components of the suggested method of solution.This study aimed to investigate the effect of local search strategies on the solution performance of hybrid firefly and particle swarm optimization algorithm, developed using chaotic local search. We used four different solution methods: the triple local search strategy consisting of insertion, swap and inversion, which were used frequently in earlier studies, and the individual use of each of these three strategies. In this study, the average relative difference values calculated using insertion, swap, inversion and triple strategy were found to be 3.03, 1.27, 2.54 and 1.20, respectively. As a result of the analyses carried out to compare the results of the solutions obtained in the flow-shop scheduling problems of Taillard, it was found that better results were obtained using the triple strategy. These findings can be a point of reference for future research.

Failure of first anti-TNF agent in Takayasu's arteritis: to switch or to swap?

Biologic drugs (bDMARD), especially TNF-α-inhibitors (TNFi), are used in refractory Takayasu's arteritis (TAK) patients. Up to 23% of patients are switched to a different bDMARD because of inefficacy. No data are available on which strategy is more efficient after TNFi failure. The aim of our study is to evaluate whether a switch or swap strategy should be preferred in TAK patients failing TNFis. TAK patients treated with a second bDMARD after the failure of the first TNFi were identified from 3 referral centres. Patients were classified as switch if treated with a different TNFi, and swap if treated with a non-TNFi bDMARD. Baseline features were evaluated. Efficacy and safety of the second bDMARD at 6 and 12 months were assessed and a comparison between switch and swap patients was made. Twenty-four TAK patients were identified. Eleven patients (46%) were switched and 13 patients (54%) were swapped (12 to tocilizumab, 1 to ustekinumab). Baseline features of patients in the 2 groups were comparable. At 12 months, the second bDMARD was suspended in 4 switch (36%) and in 5 swap (42%) patients. Second biologic drug survival and relapse-free survival were equivalent between the two groups at 6 and 12 months. A vascular worsening was observed in 4 switch (40%) and 2 swap (25%) patients. Severe infections, myocardial infarction, ischemic stroke or cancer were recorded in no patient. Our retrospective study suggests that in first-line TNFi failure TAK patients both switch and swap strategies can be considered suitable approaches.

Swap Strategy for Urban Resilience: Reviving the Ayamama River Corridor and Ataturk Decommissioned Airport in Istanbul, Turkey

Swap Strategy for Urban Resilience: Reviving the Ayamama River Corridor and Ataturk Decommissioned Airport in Istanbul, Turkey

Zygote morphogenesis but not the establishment of cell polarity in Plasmodium berghei is controlled by the small GTPase, RAB11A.

Plasmodium species are apicomplexan parasites whose zoites are polarized cells with a marked apical organisation where the organelles associated with host cell invasion and colonization reside. Plasmodium gametes mate in the mosquito midgut to form the spherical and presumed apolar zygote that morphs during the following 24 hours into a polarized, elongated and motile zoite form, the ookinete. Endocytosis-mediated protein transport is generally necessary for the establishment and maintenance of polarity in epithelial cells and neurons, and the small GTPase RAB11A is an important regulator of protein transport via recycling endosomes. PbRAB11A is essential in blood stage asexual of Plasmodium. Therefore, a promoter swap strategy was employed to down-regulate PbRAB11A expression in gametocytes and zygotes of the rodent malaria parasite, Plasmodium berghei which demonstrated the essential role of RAB11A in ookinete development. The approach revealed that lack of PbRAB11A had no effect on gamete production and fertility rates however, the zygote to ookinete transition was almost totally inhibited and transmission through the mosquito was prevented. Lack of PbRAB11A did not prevent meiosis and mitosis, nor the establishment of polarity as indicated by the correct formation and positioning of the Inner Membrane Complex (IMC) and apical complex. However, morphological maturation was prevented and parasites remained spherical and immotile and furthermore, they were impaired in the secretion and distribution of microneme cargo. The data are consistent with the previously proposed model of RAB11A endosome mediated delivery of plasma membrane in Toxoplasma gondii if not its role in IMC formation and implicate it in microneme function.

Operating policies in multi-warehouse drone delivery systems

Drones are increasingly used to deliver packages with high efficiency in several areas. We study a multi-warehouse drone delivery system, considering the allocation rule that all warehouses share the drones and the allocation rule that each warehouse owns its drones. Both plug-in charge and battery swap strategies are investigated for battery management. We examine the random and closest drone to warehouse assignment rules, and design a heuristic to improve the drone to warehouse assignment rule. A closed queueing network is built to estimate the maximum throughput capacity and a cost minimisation model is developed for cost analysis. We validate the analytical model by simulation and conduct numerical experiments to analyse the operating polices. The results show that the closest drone to warehouse assignment rule outperforms the random drone to warehouse assignment rule when the number of drones is not large, and our heuristic can improve the throughput capacity by about 13.31%. The battery swap strategy provides a better throughput capacity than the plug-in charge strategy in most cases, while it needs more investment. Moreover, the shared allocation rule gives a larger throughput capacity than the dedicated allocation rule, and it reduces the operating cost by about 30.70%.