W e analyze a decentralized supply chain with a single risk-averse retailer and multiple risk-averse suppliers under a Conditional Value at Risk objective. We define coordinating contracts and show that the supply chain is coordinated only when the least risk-averse agent bears the entire risk and the lowest-cost supplier handles all production. However, due to competition, not all coordinating contracts are stable. Thus, we introduce the notion of contract core, which reflects the agents' "bargaining power" and restricts the set of coordinating contracts to a subset which is "credible." We also study the concept of contract equilibrium, which helps to characterize contracts that are immune to opportunistic renegotiation. We show that, the concept of contract core imposes conditions on the share of profit among different agents, while the concept of contract equilibrium provide conditions on how the payment changes with the order quantity.

There are three critical elements in visible light positioning (VLP) system: Positioning accuracy, real-time ability, and robustness. However, most of the existing VLP studies only focus on the positioning accuracy and only a few studies consider the real-time ability at the same time. While the robustness is usually ignored in the field of VLP, which has a great impact on positioning performance or even leads to the failure of positioning. Therefore, we propose a novel VLP algorithm based on image sensor (as positioning terminal), exploiting optical flow detection and Bayesian forecast. The proposed optical flow method is used for real-time detection, and solves the problem of blur effect caused by the fast relative movement between the LED and positioning terminal, which would result in location failure in the traditional VLP system with pixel intensity detection. While the proposed Bayesian forecast algorithm is used for forecasting the possible location of the LED in the next frame image according to the previous frames as empirical data, which drastically solve the problem of shielded effect caused by the light link between the LED and the positioning terminal is shielded or broken. Finally, the detection location information and the forecast location information are fused by the Kalman filtering. Experimental results show that the positioning accuracy of the proposed algorithm is 0.86 cm, which realizes high positioning accuracy. The computational time of the algorithm process is about 0.162 s, and the proposed algorithm can support indoor positioning for terminal moving at a speed of up to 48 km/h. Both data demonstrate that the proposed algorithm has good real-time performance. Meanwhile, the proposed algorithm has strong robustness, which can handle the blur effect and the shielded effect in the traditional VLP system based on image sensor.

In the paper, we consider the problem of scheduling jobs on parallel identical machines with the late work criterion and a common due date, both offline and online cases. Since the late work criterion has not been studied in the online mode so far, the analysis of the online problem is preceded by the analysis of the offline problem, whose complexity status has not been formally stated in the literature yet. Namely, for the offline mode, we prove that the twomachine problem is binary NP-hard, and the general case is unary NP-hard. In the online mode we assume that jobs arrive in the system one by one, i.e., we consider the online over list model. We give an algorithm with a competitive ratio being a function of the number of machines, and we prove the optimality of this approach for two identical machines.

Abstract:Manufacturer rebates are commonly used as price discount tools for attracting end customers. In this study, we consider a two-stage supply chain with a manufacturer and a retailer, where a single seasonal product faces uncertain and price-sensitive demand. We characterize the impact of a manufacturer rebate on the expected profits of both the manufacturer and the retailer. We show that unless all of the customers claim the rebate, the rebate always benefits the manufacturer. Our results thus imply that "mail-in rebates," where some customers end up not claiming the rebate, particularly when the size of the rebate is relatively small, always benefit the manufacturer. On the other hand, an "instant rebate," such as the one offered in the automotive industry where every customer redeems the rebate on the spot when he/she purchases a car, does not necessarily benefit the manufacturer.

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This paper studies a capacity management problem with upgrading. A firm needs to procure multiple classes of capacities and then allocate the capacities to satisfy multiple classes of customers that arrive over time. A general upgrading rule is considered, i.e., unmet demand can be satisfied using multi-step upgrade. No replenishment is allowed and the firm has to make the allocation decisions without observing future demand. We first characterize the structure of the optimal allocation policy, which consists of parallel allocation and then sequential rationing. Specifically, the firm first uses capacity to satisfy the same-class demand as much as possible, then considers possible upgrading decisions in a sequential manner. We also propose a heuristic based on certainty equivalence control to solve the problem. Numerical analysis shows that the heuristic is fast and delivers close-to-optimal profit for the firm. Finally, we conduct extensive numerical studies to derive insights into the problem. It is found that under the proposed heuristic, the value of using sophisticated multi-step upgrading can be quite significant; however, using simple approximations for the initial capacity leads to negligible profit loss, which suggests that the firm's profit is not sensitive to the initial capacity decision if the optimal upgrading policy is used.

Influenza A virus (IAV) continues to threaten global public health due to drug resistance and the emergence of frequently mutated strains. Thus, it is critical to find new strategies to control IAV infection. Here, we discover one host protein, HDAC6, that can inhibit viral RNA polymerase activity by deacetylating PA and thus suppresses virus RNA replication and transcription. Previously, it was reported that IAV can utilize the HDAC6-dependent aggresome formation mechanism to promote virus uncoating, but HDAC6-mediated deacetylation of α-tubulin inhibits viral protein trafficking at late stages of the virus life cycle. These findings together will contribute to a better understanding of the role of HDAC6 in regulating IAV infection. Understanding the molecular mechanisms of HDAC6 at various periods of viral infection may illuminate novel strategies for developing antiviral drugs.