Buffer Time Research Articles

Robust aircraft maintenance routing with Heterogeneous aircraft maintenance tasks

Robust aircraft maintenance routing problems (RAMRPs) have been extensively studied due to their significance on flight schedule reliability. In the current practice, the traditional huge A-check program is divided into multiple Heterogeneous small maintenance packages (with different maintenance durations and risk levels) and performed differently during the ground time between two connected flights. As the available maintenance time becomes relatively shorter, maintenance becomes a new source of disruption. Thus, the assignment of maintenance packages-to-ground times becomes more critical. Accordingly, this paper proposes a robust strategy to alleviate the disruption due to maintenance risk. The strategy is to provide each package the appropriate amount of buffer time based on the fuzzy risk assessment. Correspondingly, a robustness measure is developed to construct the RAMRP model. As its impact can be better illustrated in large scale problems, we adopt matheuristic approach. We examine 500 disruption scenarios, the results show that the proposed strategy can greatly reduce flight delays (i.e., an 82.7% reduction in the number of delayed flights) while maintaining an acceptable decrease in aircraft utilization (i.e., a 32.42% increase in average unused flying times) compared to those obtained from the traditional model. Additionally, the proposed model is further investigated from the perspectives of aircraft utilization constraints and the risk-averse attitude of airlines. Our study validates its cost-effectiveness for delay risks reduction and highlights the significance of being properly risk-averse in decision making.

A Shear-Stiffening Mouthguard with Excellent Shock Absorption Capability and Remoldability via a Dynamic Dual Network.

Mouthguards are used to reduce injuries and the probability of them to orofacial tissues when impacted during sports. However, the usage of a mouthguard is low due to the discomfort caused by the thickness of the mouthguard. Herein, we have constructed a dynamic dual network to fabricate a shear-stiffening mouthguard with remoldability, which are called remoldable shear-stiffening mouthguards (RSSMs). Based on diboron/oxygen dative bonds, RSSMs show a shear-stiffening effect and excellent shock absorption ability, which can absorb more than 90% of the energy of a blank. Even reducing the thickness to half, RSSMs can reduce approximately 25% of the transmitted force and elongate by about 1.6-fold the buffer time compared to commercial mouthguard materials (Erkoflex and Erkoloc-pro). What is more, owing to the dynamic dual network, RSSMs show good remolding performance with unchanged shear-stiffening behavior and impact resistance, which conforms to the existing vacuum thermoforming mode. In addition, RSSMs exhibit stability in artificial saliva and biocompatibility. In conclusion, this work will broaden the range of mouthguard materials and offer a platform to apply shear-stiffening materials to biomedical applications and soft safeguarding devices.

The impact of delayed fixed-price payment in the decentralised project supply chain

This paper investigates the impact of the non-delayed and delayed fixed-price payment contracts in a two-stage decentralised project supply chain consisting of a supplier with stochastic production and delivery time and a manufacturer with stochastic on-site task processing time. We consider a Stackelberg game where the manufacturer acts as the leader to determine the buffer time with forbidden early delivery while the supplier acts as the follower to determine when to start production. We find that the delayed payment contract can postpone the production start time when the buffer time is constant compared to the non-delayed one. However, this finding does not always hold when the buffer time is a decision variable. Besides, in contrast to our intuition that the supplier prefers the non-delayed payment contract while the manufacturer prefers the delayed one, our result shows that there is no specific dominant contract for either the supplier or the manufacturer. It is also found that the basic centralised model yields a higher probability of on-time delivery, but not necessarily a lower cost, than our proposed decentralised models. Furthermore, not all equilibrium decisions derived from the basic model remain robust in the N ( N > 1 ) suppliers’ model.

IoT-based Smart Pill Reminding System

Background: The concept of pill reminders has been discussed and developed throughout the decade. It varies from cascaded plastic pill boxes to complicated robust dispensers. This proposed smart pill reminding system based on IoT is being designed by considering ease-to-use and cost-effectiveness. Method: A smart pill reminding system is a system that will alert the patient to take their respective pill at the desired time. It will also track the motion of the patient’s hand while taking the pill and will also display the pill count on an LCD Screen. In case a patient forgets/ignores the reminder provided by the system, the system will automatically display the status on the application that will be installed in the relative/caretaker’s phone and through an email on the patient's relative/caretaker’s email address to take subsequent action. The system will monitor the real-time using an RTC module, and as and when the current time matches the medicines time, it will activate its mechanism, and the patient will have a buffer time to take their medicine. In case a patient does take the medicine in the buffer time provided by the system, then one mechanism of the system will be activated. In another case, if a patient does not take the medicine in the stipulated time, further actions will be initiated by the system to benefit the patient. Results: It was tested and found that out of ten times, the system worked accurately nine times, with calculated accuracy as high as 90%. Initially, the Blynk application will display “Welcome Patient” and “You will be updated”. Once the RTC matches the scheduled time to take medicine, the buzzer starts buzzing. If the IR sensor detects the movement of the user’s hand, the LCD will update the pill count, and the pill count is reduced by one. The LCD will also display the message “Medicine Taken”. If the IR sensor does not detect the movement of the user’s hand, the LCD will display the same pill count. The LCD will also display the message “Med1 not Taken”. The Blynk will also be updated and will display the same messages. The green LED shows the status of the consumption of the pill. The email will sent to the caretaker in this case. Conclusion: In this work, all the problems related to the system are overcome in a systematic manner with the help of IoT and basic electronic applications. Thus, the system will help the user take all the prescribed medicines on time and will also update the user’s caretaker via application and email services. This will largely help the working class as well as the senior citizens. Thus, this proposed system can be commercialised as a handy and cost-effective device.

A Proactive-Reactive-Based Approach for Continuous Berth Allocation and Quay Crane Assignment Problems with Hybrid Uncertainty

Port operations have been suffering from hybrid uncertainty, leading to various disruptions in efficiency and tenacity. However, these essential uncertain factors are often considered separately in literature during berth and quay crane assignments, leading to defective, even infeasible schedules. This paper addressed the integrated berth allocation and quay crane assignment problem (BACAP) with stochastic vessel delays under different conditions. A novel approach that combines both proactive and reactive strategies is proposed. First, a mixed-integer programming model is formulated for BACAP with quay crane maintenance activities under the ideal state of no delay. Then, for minor delays, buffer time is added to absorb the uncertainty of the arrival time of vessels. Thus, a robust optimization model for minimizing the total service time of vessels and maximizing the buffer time is developed. Considering that the schedule is infeasible when a vessel is seriously delayed, a reactive model is built to minimize adjustment costs. According to the characteristics of the problem, this article combined local search with the genetic algorithm and proposed an improved genetic algorithm (IGA). Numerical experiments validate the efficiency of the proposed algorithm with CPLEX and Squeaky Wheel Optimization (SWO) in different delay conditions and problem scales. An in-depth analysis presents some management insights on the coefficient setting, uncertainty, and buffer time.

Dynamic H-Bond crosslinking strategy to prepare impact-hardening protective materials with tunable negative Poisson's ratio

Protective materials with a wide range of practical applications should exhibit a high energy absorption efficiency and be smart and stress-responsive. Herein, a novel smart protective material was formed from an impact-hardening polymer (IHP), which comprised a branched structure, and polyurethane (PU) with quadruple H-bonding. Notably, the quadruple H-bonding was used to enhance the interaction between the two microphases, thus regulating the negative Poisson's ratio. The value of the reversible softness–stiffness switching effect of this material (UPy-IHP-PU) achieved more than 5000, five times stronger than that of a previously reported linear IHP-PU. In addition, the impact-protective ability did not weaken. As the impact velocity increased, the impact energy absorption efficiency of UPy-IHP-PU also increased, even exceeded 70 % under the impact velocity of 5 m/s, thus demonstrating the ability to efficiently reduce the impact force and extend the buffer time against the strike via the impact-hardening phenomenon. Moreover, an adjustable scale of microphase separation can regulate the negative Poisson's ratio to enhance the impact-hardening phenomenon. The excellent energy dissipation ability and smart stress- and rate-responsiveness indicate the application potentials of UPy-IHP-PU as a future wearable impact-protective sensor.

Manufacturing cost reduction techniques for automobile crankcase mould inserts

The manufacturing of automobile moulds is itself a challenging job and very tedious task requiring high accuracy of component profiles. The required complicated and complex profiles are generated when the mould inserts are relinquished from several numbers of workstations, which run for a longer process time. As the accuracy needed for the component area is very high and it (insert) has to pass through several bottleneck workstations, the production time and increased buffer time are observed. This chapter focuses on providing economical methods for manufacturing hot die steel inserts. These techniques are implemented on a pressure die-casting insert component. The present solution is derived for manufacturing time reduction and minimisation of the die-casting inserts (moving and fixed die) at every stage. Implementing combined electrodes, assembly machining and cluster plate machining/sparking techniques are critical development advancements in the research. In the combined electrode concept, one electrode is designed in the same area to cover multiple areas that were initially covered by separate individual electrodes. Furthermore, this concept is outstretched by the cluster plate concept. Those electrodes that cannot be covered by a single electrode are machined together to act as a single electrode and later separated while individual sparking. Combined electrode design, assembly machining and cluster machining/sparking of the electrodes reduce the total machining time of the die and the machining centre. Reducing the machine run time will reduce the production cost and increase profit. The results achieved show that the combined electrode design setup shows 75% savings in the combined sparking setup, whereas the cluster plate machining setup shows 35% savings in the tool list generation (from software used) of the net savings. The proposed solution opens up new avenues for similar automobile components by setting benchmarks to decrease the rope length associated with manufacturing and increase profit.

An adaptive agent-based approach for instant delivery order dispatching: Incorporating task buffering and dynamic batching strategies

The volume of instant delivery has witnessed a significant growth in recent years. Given the involvement of numerous heterogeneous stakeholders, instant delivery operations are inherently characterized by dynamics and uncertainties. This study introduces two order dispatching strategies, namely task buffering and dynamic batching, as potential solutions to address these challenges. The task buffering strategy aims to optimize the assignment timing of orders to couriers, thereby mitigating demand uncertainties. On the other hand, the dynamic batching strategy focuses on alleviating delivery pressure by assigning orders to couriers based on their residual capacity and extra delivery distances. To model the instant delivery problem and evaluate the performances of order dispatching strategies, Adaptive Agent-Based Order Dispatching (ABOD) approach is developed, which combines agent-based modelling, deep reinforcement learning, and the Kuhn-Munkres algorithm. The ABOD effectively captures the system's uncertainties and heterogeneity, facilitating stakeholders learning in novel scenarios and enabling adaptive task buffering and dynamic batching decision-makings. The efficacy of the ABOD approach is verified through both synthetic and real-world case studies. Experimental results demonstrate that implementing the ABOD approach can lead to a significant increase in customer satisfaction, up to 275.42%, while simultaneously reducing the delivery distance by 11.38% compared to baseline policies. Additionally, the ABOD approach exhibits the ability to adaptively adjust buffering times to maintain high levels of customer satisfaction across various demand scenarios. As a result, this approach offers valuable support to logistics providers in making informed decisions regarding order dispatching in instant delivery operations.

Addition of organic amendments derived from invasive apple snails alleviated soil acidification, improved soil nitrogen and phosphorus effectiveness, microbial growth and maize yield in South China

Pomacea canaliculata (apple snail) is an invasive agricultural pest posing serious threats to aquatic crop production and wetland ecosystem function in Asia. The shell of P. canaliculata is composed of calcium carbonate (CaCO3), while its soft tissue is protein-rich (carbon (C) and nitrogen (N) sources). Thus, P. canaliculata has the potential to be used as a source of organic soil amendments. Here, we evaluated the effectiveness of snail derivatives (powder, including shells and soft tissues of the snails) as organic soil amendments to improve the productivity of an acidic dryland soil in South China. Snail powder (SP) was incorporated into the soil at application rates of 0–50 g kg−1, followed by planting of maize. Our results showed that SP addition significantly increased soil pH (up to 7.25–7.95), alleviated soil acidification. Moreover, SP addition improved soil N, phosphorus (P) effectiveness, and dissolved organic carbon (DOC) content, increasing biomass of actinobacteria and arbuscular mycorrhizal fungi (AMF) to stimulate microbial growth. Notably, SP addition increased height (up to 42.4 %), biomass (up to 117.6 %) and yield (up to 118.9 %) of maize, with 10 g kg−1 SP optimal for plant productivity. However, the optimal application rate and buffer time for field application of SP warrant further study. Our findings demonstrate the potential of SP resource utilization for acidic soil remediation and the invasive snail P. canaliculata control.

Impact of connected and automated vehicles on the travel time reliability of an urban network

Connected and automated vehicles (CAVs) have the potential to revolutionise the transportation industry, with a plethora of research already revealing considerable gains in safety, travel time and mobility, as well as reduced congestion and pollution. As the number of CAVs on the road grows, rigorous testing for various market penetration rates (MPRs) of CAVS is essential to determine under what conditions the benefits can be realised. For the studies investigating the impact of CAVs on travel time reliability specifically, the MPRs in which the network most thrives have been inconsistent. The majority of the research is concerned with highway networks with only a few travel time reliability studies that focus on urban networks. In this simulation study, the impact of varying MPRs of CAVs on travel time reliability is evaluated in an urban network for different traffic demands. Travel time reliability metrics are assessed, including the standard deviation, buffer time index and misery index. The study demonstrated that from 0% to 100% MPR, the overall weighted average travel time decreased by 28%, and the standard deviation of the weighted average travel time declined by 35%, highlighting the significant increase in travel time reliability. Travel time improvements were visible from the MPR of 10%; however, the reliability metrics highlighted the greatest benefits occurred at higher MPRs. This study presents valuable results about the reliability that CAVs can bring to urban networks during the fleet transition to CAVs.

Proactive berth scheduling with data‐driven buffer time in container terminals

AbstractGlobal shipment volumes have been increasing due to changes in the business environment of e‐commerce and manufacturing. Consequently, container vessels carry more cargo for international trade, increasing uncertainties in terminal management. Terminal operators manage terminals by establishing a proactive schedule that responds to disruptions such as vessel delays, and the introduction of buffer time is a representative proactive strategy. In this study, by analyzing historical delay data with machine learning, we propose data‐driven buffer times to consider the heterogeneous arrival uncertainty of vessels. Thus, we proactive scheduling with data‐driven buffer times according to the desired robustness levels. This is a novel study on berth scheduling that applies data mining approaches to improve operations research techniques. Numerical experiments were conducted on the berth scheduling with time‐invariant quay crane assignment using real‐life data to validate the effectiveness of the proposed method. These experimental results revealed that applying the data‐driven buffer time could effectively reduce the cost incurred at the terminal by balancing baseline and recovery costs. In addition, our proposed methodology ensured the quality of the solution compared with a stochastic method and reduced the computational burden of a stochastic problem by using the data‐driven buffer times obtained prior to the solution construction. Therefore, the proposed method can be introduced into terminal operations to overcome the deficiencies of traditional approaches in terms of academic perspective.

Research on the scheduling method of ground resource under uncertain arrival time

We present a two-stage scheduling approach including proactive and reactive scheduling to solve the ground resource scheduling problem with uncertain arrival time. In the first stage, an integer programming model is constructed to minimize the delay and transfer costs. After solving this model, we obtain a baseline scheduling plan that considers the service arrival time uncertainty. In the second stage, the feasibility of the subsequent benchmark plan is evaluated based on the current state of the services and resources. The reactive scheduling model is enabled when trigger conditions are met. Moreover, an improved adaptive large neighborhood search is designed to solve the proactive scheduling model effectively. Real data from an international airport in South China is used as a test case to compare different scheduling strategies. The results show that it is difficult to handle the uncertainty of the problem with the benchmark plan that simply considered buffer time. Compared with rolling time-domain scheduling, the average transfer cost of the scheduling strategy proposed in this paper increased slightly, but the average service delay cost can be reduced significantly. Algorithm-wise, instances of different scales are designed to verify the effectiveness of the improved adaptive large neighborhood search algorithm. The efficiency of the algorithm scheme is better than that of the Gurobi solver scheme in medium to large-scale problems. Therefore, the forward and reactive strategies can better handle the uncertainty of airport ground protection services as they can simultaneously guide the allocation and utilization of airport ground protection resources.

Optimizing the Growing Dual Credit Requirements for Automobile Manufacturers in China’s Dual Credit Policy

Dual credit policy (DCP) is a market-based mechanism introduced by the Chinese government to promote the new energy vehicle (NEV) industry and improve energy savings in China. To offer sufficient impetus for the NEV industry while providing sufficient transitional buffer time for automobile manufacturers (AMs), the government needs to scientifically design how to gradually increase its dual credit requirement for AMs year by year. To assist the multi-year DCP design, this paper proposes a generalized Nash equilibrium model to predict AMs’ short-term decisions (i.e., vehicle production and credit trading) and long-term decisions (i.e., investment in production capacity expansion and research and development) under any DCP, considering the interactions among AMs’ decisions, vehicle prices, and credit price. Based on the equilibrium model, we then develop a bi-level programming problem to optimize the multi-year DCP. With numerical experiments, we show that implementing the optimal DCP can effectively enhance the market share of NEVs. In the context of the optimal multi-year DCP, the credit requirements set by the government should maintain a relatively low threshold during the initial years, but rise rapidly after that. Such optimal DCP offers AMs sufficient transition time while compelling a quick shift in their developmental strategies.

A generative adversarial network-based framework for network-wide travel time reliability prediction

This paper introduces a generative model named the travel time reliability-generative adversarial network (TTR-GAN) model for predicting network-wide TTR using automatic vehicle identification data. The TTR-GAN model is capable of generating predicted travel time samples, enabling the assessment of network-wide TTR without the need to assume a specific travel time distribution. In the TTR-GAN model, a combination of graph convolutional networks and long short-term memory (LSTM) neural networks is employed within the GAN framework. When training the TTR-GAN model, special attention is given to adjusting the mean and standard deviation of the generated samples, aiming for a closer resemblance to real samples. Experiments conducted on a road network in China demonstrate the predictive capability of the proposed TTR-GAN model, surpassing several benchmark models such as the LSTM neural network, moving average model, and GAN model in terms of statistical, buffer time, and probability distribution measures. By incorporating the mean and standard deviation into the loss function, the TTR-GAN model achieves an 18.2% reduction in Jensen‒Shannon divergence between predicted and real samples. Furthermore, the model's performance in real-world applications is illustrated through a sensitivity test.

Transient Hydrodynamic Characteristics of a High-Speed Axial Flow Water-Jet Pump during Variable Speed Process

To investigate the transient characteristics of high-speed axial flow water-jet pumps during start-up and emergency acceleration as well as to analyze how different accelerations affect the performance of internal flow, the k–ω turbulence model of the SST model and Zwart cavitation model were used to perform unsteady simulation on an impeller rotating at a speed of 1850. The steady-state numerical simulation method was verified by the experimental data, the numerical calculation results were basically consistent with the experimental data, the margin of error was within 5%, and the numerical simulation method was reliable. The results show that there was an obvious transient effect in the process of variable speed, and the thrust reached a stable state later than the speed. The buffer times for start-up times of 1 s, 2 s, and 3 s were 0.0394 s, 0.0375 s, and 0.0282 s, respectively, and the buffer times for the acceleration times of 0.5 s, 1.0 s, and 1.5 s were 0.0330 s, 0.0273 s, and 0.0230 s, respectively. The greater the acceleration, the more serious the flow rate and thrust lag behind the speed, and the greater the impact thrust. Under the same acceleration, the buffer time required in the start-up process was 19.3~22.6% longer than that in the acceleration process. During the change in speed of the high-speed water-jet pump, the vortex core area of the suction surface (SS) first appeared on the side of the shroud at the inlet, increased with the increase in the rotational speed, and developed toward the middle of the impeller. However, after the flow was stabilized, the vortex core region gradually shrank and eventually disappeared. When the rotational speed reached 0.6 times the design speed, cavitation occurred at the leading edge (LE) of the blade, and the cavitation area increased with the increase in the rotational speed. When reaching the same speed, the greater the acceleration, the more serious the cavitation. Under the design speed, that is, 6000 r/min, the cavitation volume fraction of the 1 s start-up process was 7.32%, the 2 s start-up process was 5.84%, the 3 s start-up process was 5.32%, and the 0.5 s acceleration process was 6.86%. The cavitation volume fraction of the 1 s acceleration process was 5.04%, and that of the 1.5 s acceleration process was 4.23%. Under the same acceleration, the cavitation volume fraction of the start-up process was 6.7~25% larger than that of the acceleration process. Compared with the start-up process and acceleration process under the same acceleration, the accelerated process had a smaller region of vortex core, stronger anti-cavitation ability, and more stable flow than the start-up process. During the actual operation process of the water-jet pump, it is advisable to use smaller accelerations and segmented accelerations as much as possible until the design speed is reached. The research findings serve as a foundation for future investigations into the transient characteristics of high-speed water-jet pumps operating under variable speed conditions.

Buffer Management Techniques in Delay Tolerant Networks: A Comprehensive Survey

Abstract: This paper aims to provide a comprehensive study of the underlying buffer management issues and challenges in developing an efficient DTN routing protocol. Our aim is to begin with the discussion of buffer management schemes in DTNs in full generality and then dive in-depth, covering aspects of buffer management. Buffer strategies are used to determine which packets need to be forwarded or dropped. This paper will focus on the variety of buffer management strategies available, providing a comprehensive survey and analysis. We have also conducted an empirical analysis using simulator ONE to analyze the buffering time in various primary routing protocols such as Epidemic, Spary-and-wait (SNW), Prophet, Encounter based Routing (EBR) and Inter-Contact Delay and Location Information based Routing (ICDLIR). For these algorithms, it is also observed how varying the buffer size effect the delivery probability and overhead.

Buffer Times Between Scheduled Events in Resource Assignment Problem: A Conflict-Robust Perspective

Problem definition: In many resource scheduling problems for services with scheduled starting and completion times (e.g., airport gate assignment), a common approach is to maintain appropriate buffer between successive services assigned to a common resource. With a large buffer, the chances of a “crossing” (i.e., a flight arriving later than the succeeding one at the gate) will be significantly reduced. This approach is often preferred over more sophisticated stochastic mixed-integer programming methods that track the arrival of all the flights to infer the number of “conflicts” (i.e., a flight arriving at a time when the assigned gate becomes unavailable). We provide a theoretical explanation, from the perspective of robust optimization for the good performance of the buffering approach in minimizing not only the number of crossings but also the number of conflicts in the operations. Methodology/results: We show that the buffering method inherently minimizes the worst-case number of “conflicts” under both robust and distributionally robust optimization models using down-monotone uncertainty sets. Interestingly, under down-monotone properties, the worst-case number of crossings is identical to the worst-case number of conflicts. Using this equivalence, we demonstrate how feature information from flight and historical delay information can be used to enhance the effectiveness of the buffering method. Managerial implications: The paper provides the first theoretical justification on the use of buffering method to control for the number of conflicts in resource assignment problem. Funding: This work was supported by the 2019 Academic Research Fund Tier 3 of the Ministry of Education-Singapore [Grant MOE-2019-T3-1-010] and the Research Grants Council of Hong Kong SAR, China [Grant PolyU 152240/17E]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0572 .

Buffer Time Optimization in the Function of Timetable Stability

Timetable stability depends on the regularity of trains. Any deviation from the planned timetable leads to its instability. Railway network characteristics determine the capacities of the transport service. Depending on the capacity calculation method, time components are added to the minimum headway to ensure timetable stability. The UIC 405 method is simple and can be used on all railways. The disadvantage is that the calculations are based on average data. According to the method, the minimum headway consists of the time of the average headway interval, additional time and the buffer time. The additional time is precisely defined by the number of APB sections, while the buffer time is in the average value. When creating the timetable, the goal is optimal utilisation of the infrastructure. If the headway is too long, the capacity is not used, and if it is too short, timetable instability will ensue. Instead of averaging, this work calculates a buffer time that depends on the ratio of the travel time of the previous and the following trains. In this way, the headway is optimised and the calculation of the UIC 405 method is improved.

Rational design of polyphosphate kinase dual-substrate channel cavity for efficient production of glutathione by cell free catalysis

ATP is an important cofactor involved in many biocatalytic reactions that require energy input. Polyphosphate kinases (PPK) can provide energy for ATP-consuming reactions due to their cheap and readily available substrate polyphosphate. We selected ChPPK from Cytophaga hutchinsonii for substrate profiling and tolerance analysis. By molecular docking and site-directed mutagenesis, we rationally engineered the dual-substrate channel cavity of polyphosphate kinase to improve the catalytic activity of PPK. Compared with the wild type, the relative enzyme activity of the screened mutant ChPPKK81H-K103V increased by 326.7%. Meanwhile, the double mutation expanded the substrate utilization range and tolerance of ChPPK, and improved its heat and alkali resistance. Subsequently, we coupled the glutathione bifunctional enzyme GshAB and ChPPKK81H-K103V based on this ATP regeneration system, and glutathione was produced by cell-free catalysis upon disruption of cells. This system produced (25.4±1.9) mmol/L glutathione in 6 h upon addition of 5 mmol/L ATP. Compared with the system before mutation, glutathione production was increased by 41.9%. After optimizing the buffer, bacterial mass and feeding time of this system, (45.2±1.8) mmol/L glutathione was produced in 6 h and the conversion rate of the substrate l-cysteine was 90.4%. Increasing the ability of ChPPK enzyme to produce ATP can effectively enhance the conversion rate of substrate and reduce the catalytic cost, achieving high yield, high conversion rate and high economic value for glutathione production by cell-free catalysis. This study provides a green and efficient ATP regeneration system that may further power the ATP-consuming biocatalytic reaction platform.

Semi-Analytical Midcourse Guidance for Coordinated Interception of Multiple Exo-Atmospheric Targets

The simultaneous interception of multiple exo-atmospheric threat targets can leave no buffer time for the targets and greatly reduces targets’ penetration probability. This paper proposes centralized and decentralized two midcourse guidance methods to solve the coordinated interception of multiple exo-atmospheric targets. First, the free-time cooperative interception problem minimizing the total impulses is established, where the nonlinear dynamics of the interceptors and targets, the initial impulse constraints, and the terminal interception constraints are considered. Second, the necessary conditions for the optimal cooperative interception problem are derived and then approximated using higher-order Taylor expansions, which result in a series of analytical nonlinear equations. Then, the semi-analytical centralized guidance mode is designed to achieve simultaneous interception of targets by directly solving the analytical nonlinear equations. To improve computational efficiency, the decentralized cooperative guidance mode is further proposed by using the developed iterative freezing trajectory method, where each interceptor uses information from other interceptors in the previous iteration for prediction and distributed computation. Numerical examples verify the effectiveness and robustness of the proposed two guidance methods. Results show that the computational efficiency of the decentralized guidance mode is more efficient compared with the centralized midcourse guidance mode.