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Nowadays cross-docking operations play a significant role in the cold-chain logistics. This paper addresses the cold-chain cross-docking truck scheduling problem where two types of products, i.e. refrigerated and frozen ones, demand separate trucks and storage areas with distinct temperature settings during their storage and transportation. We present a mixed-integer linear programming model with the objective of minimising the total operational costs that consist of inbound truck arrival penalties for violating contracted time windows, product delivery tardiness penalties, inventory costs and outbound truck transportation costs. Due to the strong NP-hardness of the considered problem, we solve it in two phases where the inbound truck arrival schedule and the schedule of outbound truck departure together with product processing are produced, respectively. Four heuristic algorithms are proposed to generate complete solutions of the considered two-stage problem, which are the combinations of two solution frameworks for the first stage and two methods for the second stage. Computational experiments are carried out to verify the effectiveness and efficiency of the proposed heuristic algorithms in terms of the solution quality and running time, respectively. [ABSTRACT FROM AUTHOR]

In many manufacturing and service systems, it is of great importance to generate processing schedules with strong response abilities to unexpected or urgent jobs. In this paper, we investigate the problem of scheduling jobs on two parallel identical machines. The objective is to minimise the maximum difference between any two consecutive completion times of jobs, i.e. to minimise the maximum inter-completion time. The processing of any job cannot be interrupted, and a smaller objective value of the processing schedule implies a faster response to an unexpected job that may arrive at any time point. The problem was introduced by Zheng, Pinedo, Lee, Liu, and Xu [2019. "Towards Robustness of Response Times: Minimising the Maximum Inter-completion Time on Parallel Machines." International Journal of Production Research 57 (1): 182–199]. In this work, we first give a sufficient condition of feasible solutions with respect to the makespan constraint, and reveal several basic properties of any optimal solution. We then prove a theoretical lower bound of the objective value, and propose a O (n 2) time algorithm to compute the lower bound. An efficient heuristic algorithm is further constructed to solve the considered problem. Experimental results show that the proposed algorithm outperforms all the three heuristics introduced in Zheng, Pinedo, Lee, Liu, and Xu 2019. [ABSTRACT FROM AUTHOR]

With the rapid development of worldwide container trade, quay cranes and other resources in container terminals are suffering from increasing workloads. To reduce their failure probabilities, quay cranes usually require preventive maintenance. However, these important activities are often ignored during quay crane planning in literature. This work studies an integrated berth allocation, quay crane assignment and specific quay crane assignment problem where quay crane maintenance is involved, and establishes an integer linear programming with the objective of minimising the total turnaround time. Due to the NP-hardness of the problem, CPLEX only solves instances with up to 18 vessels. For solving larger instances, we propose Left-and-Right Vessel Move (LRVM) algorithm and improved Genetic Algorithm (GA). Experimental results reveal that GA slightly outperforms LRVM with respect to solution quality as the solution of LRVM serves as one of the initial chromosomes of GA. LRVM can output feasible solutions within seconds, even for instances with 50 vessels. We further present a sensitivity analysis of preferred berth segments, and make numerical comparison on algorithm performance for the relevant model without quay crane maintenance. Both the models and proposed heuristics in this work help in dealing with the operational management of container terminal resources in practice. [ABSTRACT FROM AUTHOR]

Motivated by scheduling practices that require a response to unplanned high-priority jobs as soon as possible without preempting any in-processing jobs, this paper considers a deterministic identical parallel machine scheduling problem to achieve robustness with regard to a worst-case response time. To the best of our knowledge, this paper is the first to study the objective of minimising the maximum inter-completion time, i.e. the maximum time difference between any two consecutive completion times of jobs. For this novel scheduling problem, we first show its NP-hardness, and then propose an integer linear programming formulation and three heuristic approaches. Numerical experiments demonstrate the efficiency of our solution methods. [ABSTRACT FROM AUTHOR]

Autophagy has emerged as a key regulator of cell metabolism. Recently, we have demonstrated that autophagy is involved in RNA metabolism by regulating ribosomal RNA (rRNA) synthesis. We found that autophagy-deficient cells display much higher 47S precursor rRNA level, which is caused by the accumulation of SQSTM1/p62 (sequestosome 1) but not other autophagy receptors. Mechanistically, SQSTM1 accumulation potentiates the activation of MTOR (mechanistic target of rapamycin kinase) complex 1 (MTORC1) signaling, which facilitates the assembly of RNA polymerase I pre-initiation complex at ribosomal DNA (rDNA) promoter regions and leads to the activation of rDNA transcription. Finally, we showed that SQSTM1 accumulation is responsible for the increase in protein synthesis, cell growth and cell proliferation in autophagy-deficient cells. Taken together, our findings reveal a regulatory role of autophagy and autophagy receptor SQSTM1 in rRNA synthesis and may provide novel mechanisms for the hyperactivated rDNA transcription in autophagy-related human diseases. Abbreviations: 5-FUrd: 5-fluorouridine; LAP: MAP1LC3/LC3-associated phagocytosis; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MTOR: mechanistic target of rapamycin kinase; PIC: pre-initiation complex; POLR1: RNA polymerase I; POLR1A: RNA polymerase I subunit A; rDNA: ribosomal DNA; RRN3: RRN3 homolog, RNA polymerase I transcription factor; rRNA: ribosomal RNA; SQSTM1/p62: sequestosome 1; TP53INP2: tumor protein p53 inducible nuclear protein 2; UBTF: upstream binding transcription factor. [ABSTRACT FROM AUTHOR]

This paper studies the makespan minimisation scheduling problem in a two-stage hybrid flow shop. The first stage has one machine and the second stage hasmidentical parallel machines. Neither the processing time nor probability distribution of the processing time of each job is uncertain. We propose a robust (min–max regret) scheduling model. To solve the robust scheduling problem, which is NP-hard, we first derive some properties of the worst-case scenario for a given schedule. We then propose both exact and heuristic algorithms to solve this problem. In addition, computational experiments are conducted to evaluate the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we study a new group-buying mechanism originated in China where the new mechanism adopts a fixed group price rather than a dynamic pricing mechanism. We employ a sensitive parameter, reflecting the initial customer’s seeking and communication cost and formulate this new group-buying business as a game model. First, we formulate the basic model as a Stackelberg game where the website is the leader and the seller is the follower. Our result shows that the group-buying mechanism is more efficient when the value ofis smaller, and there is also an upper bound forto adopt group-buying mechanism. Second, we establish three other group-buying game structures by considering different market power between the website and the seller. By comparing the maximum revenues and optimal decisions obtained under different market structures, some interesting and valuable managerial insights are established such that when to adopt a group-buying mechanism or a non-group-buying mechanism and how to make a decision optimally based on adopted mechanism. [ABSTRACT FROM PUBLISHER]

Paclitaxel-induced peripheral neuropathic pain (PIPNP) is a major therapy- and dose-limiting side effect that is extremely laborious to treat. Resveratrol (Res), with a structure name of 3,5,40-trihydroxystilbene, is a kind of natural polyphenolic chemical with plenty of useful characteristics such as anti-inflammatory, and anti-oxidative stress. However, the impact of Res on PIPNP remains unclear. Therefore, the current study intends to examine the analgesic effect of Res on PIPNP. In the present study, the results revealed that Res could effectively prevent the development of paclitaxel-induced PIPNP in a dose-dependent manner when repeated doses of Res were given during PIPNP induction. This prophylactic effect of Res was involved in inhibited paclitaxel-induced up-regulation of TRPV1 instead of TRPA1 in the dorsal root ganglia. Furthermore, the inhibition of TRPV1 up-regulation by Res may be involved in a phosphorylation of ERK mechanism. In summary, we conclude that Res plays an intriguing role in the prevention of PIPNP and thus may work as a therapeutic compound for treating and preventing PIPNP. [ABSTRACT FROM AUTHOR]