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In recent years, the influence of global tropical cyclones (TCs) has a tendency to expand towards the polar direction, and the proportion of high-intensity TCs has also increased greatly. The Northwest Pacific is a high incidence area of TCs, the northward shift of landfalling TCs in China and the increase of high-intensity TCs will lead to an increased risk of storm surge in the East China Sea (ECS). However, due to the lack of long-term observations in the ECS, previous studies have focused on the analysis of individual TC, and the response mechanism of storm surge to long-term trends of TCs is not clear. Based on the long-term observations of TCs from 1949 to 2022 and the numerical experiments of storm surge, the trend of landfalling TCs in China and the response characteristics of storm surge in the ECS were studied in this paper. The observations showed that the probability of TCs entering ECS became greater in the latter 37 years compared with the former 37 years. The average intensity of landfalling TCs (maximum wind speed) increased by 36% to 30 m/s, and the average speed of landfalling TCs increased by 100% to 8 m/s. The model results showed that the intensity of the storm surge is closely related to the intensity and translation speed of TCs. Under the condition of the same translation speed of TCs, the storm surge enhanced with the intensity of TCs. For the TCs with high intensity (strong typhoon and super typhoon), the intensity of the storm surge continues to increase as the translation speed of the TCs increases. However, for the TCs with low or medium intensity (severe tropical storms and typhoons), the intensity of the storm surge reaches a peak with the increase of the translation speed of TCs. The intensity of the storm surge is determined by both the wind speed and the duration of strong wind. The TCs with faster translation speed can produce a stronger wind field but shorter duration of strong wind. Therefore, the intensity of the storm surge decreases when the translation speed of TCs exceeds the threshold value.

This work investigates a new semi-online scheduling problem with lookahead. We focus on job scheduling on two identical parallel machines, where deterministic online algorithms only know the information of k initial jobs (i.e., the initial-lookahead information), while the following jobs still arrive one-by-one in an over-list fashion. We consider makespan minimization as the objective. The study aims at revealing the value of knowing k initial jobs, which are used to improve the competitive performance of those online algorithms without such initial-lookahead information. We provide the following findings: (1) For the scenario where the k initial jobs are all the largest jobs with length Δ , we prove that the classical LIST algorithm is optimal with competitive ratio (k + 3) / (k + 2) ; (2) For the scenario where the total length of these k   (> 1) jobs is at least Δ , we show that any online algorithm has a competitive ratio at least 3/2, implying that the initial-lookahead knowledge is powerless since there exists a 3/2-competitive online algorithm without such information; (3) For the scenario where the total length of these k   (> α) jobs is at least α Δ (α ≥ 2), we propose an online algorithm, named as LPT-LIST, with competitive ratio of (α + 2) / (α + 1) , implying that the initial-lookahead information indeed helps to improve the competitiveness of those online algorithms lacking such information. [ABSTRACT FROM AUTHOR]

Upwelling is a widespread phenomenon in the ocean and plays key roles in the marine environment, marine fishery and air–sea carbon exchange. In coastal regions, the upwelling is usually modulated by tides and complex topography, but the dynamical mechanism is still unclear and yet to be quantified. In this study, a three-dimensional (3D) regional ocean model is used to investigate tide-induced upwelling and its mechanisms quantitatively in the mouth of a semi-closed bay, the Bohai Strait, which is a tide-dominated coastal region. The results show that the upwelling mainly occurs near the tidal front in the north of the Laotieshan Channel and the southern region of the front, with the most active upwelling existing off promontories and small islands. Numerical sensitivity experiments indicate that the upwelling in the study area is mainly caused by tides, accounting for approximately 86% of the total. The 3D balance of the vertical component of the vorticity based on the model results quantifies the dynamic processes of the upwelling and reveals that tides induce the upwelling through tidal mixing and nonlinear effects. In the tidal front zone, the upwelling is mainly caused by baroclinic processes related to tidal mixing. Off promontories and small islands, we first reveal that the upwelling is driven by both the tidal mixing and nonlinear effect related to centrifugal force rather than just one of the two mechanisms, and the latter plays a dominant role in producing the upwelling. The strong nonlinear effect is attributed to the periodic movement of barotropic tidal currents rather than the mean flow. [ABSTRACT FROM AUTHOR]

This work investigates an unrelated parallel machine scheduling problem in the shared manufacturing environment. Based on practical production complexity, five job and machine-related factors, including job splitting, setup time, learning effect, processing cost and machine eligibility constraint, are integrated into the considered problem. Parallel machines with uniform speed but non-identical processing capabilities are shared on a sharing service platform, and jobs with different types can only be processed by the machines with matching eligibilities. The platform pays an amount of processing cost for using any machine to process the jobs. To balance the processing cost paid and the satisfaction of customers, we aim to minimize the weighted sum of total processing cost and total completion time of jobs in the considered problem. We establish a mixed integer linear programming model, and provide a lower bound by relaxing the machine eligibility constraint. The CPLEX solver is employed to generate optimal solutions for small-scale instances. For large-scale instances, we propose an efficient heuristic algorithm. Experimental results demonstrate that for various instance settings, the proposed algorithm can always produce near optimal solutions. We further present several managerial insights for the shared manufacturing platform. [ABSTRACT FROM AUTHOR]