Containing Misinformation Spread: A Collaborative Resource Allocation Strategy for Knowledge Popularization and Expert Education

With the prevalence of online social networks, the potential threat of misinformation has greatly enhanced. Therefore, it is significant to study how to effectively control the spread of misinformation. Publishing the truth to the public is the most effective approach to controlling the spread of misinformation. Knowledge popularization and expert education are two complementary ways to achieve that. It has been proven that if these two ways can be combined to speed up the release of the truth, the impact caused by the spread of misinformation will be dramatically reduced. However, how to reasonably allocate resources to these two ways so as to achieve a better result at a lower cost is still an open challenge. This paper provides a theoretical guidance for designing an effective collaborative resource allocation strategy. First, a novel individual-level misinformation spread model is proposed. It well characterizes the collaborative effect of the two truth-publishing ways on the containment of misinformation spread. On this basis, the expected cost of an arbitrary collaborative strategy is evaluated. Second, an optimal control problem is formulated to find effective strategies, with the expected cost as the performance index function and with the misinformation spread model as the constraint. Third, in order to solve the optimal control problem, an optimality system that specifies the necessary conditions of an optimal solution is derived. By solving the optimality system, a candidate optimal solution can be obtained. Finally, the effectiveness of the obtained candidate optimal solution is verified by a series of numerical experiments.

Determination of optimal post-warranty variable maintenance period for repairable second-hand product based on mean residual life

Due to the increased transactions of second-hand products in the market, the optimization of maintenance strategy for the second-hand product has become very important issue to attract a great attention from many researchers of late. This paper proposes a new post-warranty strategy with a variable self-maintenance period for the second-hand product, assuming that the product is replaced by another one on the first failure following a fixed length of post-warranty self-maintenance period. During the non-renewing warranty period, the product is subject to preventive maintenance periodically at a prorated cost while only minimal repair is implemented at each failure by the dealer. The main goal of this study is to determine an optimal length of post-warranty self-maintenance period which minimizes the expected cost rate per unit time during the product’s life cycle from the user’s perspective. This approach considers not only the periodic preventive maintenance during the warranty period, but also the remaining life distribution of the product after the warranty expires, which is the significant difference of this work from many existing maintenance policies. For this purpose, we formulate the expected length of life cycle and evaluate the expected total cost incurred during the life cycle of the second-had product which is purchased at the age of [Formula: see text] The existence of the optimal self-maintenance period is proved analytically under mild conditions and the proposed maintenance model is compared with an existing model with regard to the expected cost rate. Finally, assuming that the life distribution of the product follows a Weibull distribution, the effect of relevant parameters on the optimal self-maintenance period is analyzed numerically.

Adjustable Coins

In this paper we consider a scenario where there are several algorithms for solving a given problem. Each algorithm is associated with a probability of success and a cost, and there is also a penalty for failing to solve the problem. The user may run one algorithm at a time for the specified cost, or give up and pay the penalty. The probability of success may be implied by randomization in the algorithm, or by assuming a probability distribution on the input space, which lead to different variants of the problem. The goal is to minimize the expected cost of the process under the assumption that the algorithms are independent. We study several variants of this problem, and present possible solution strategies and a hardness result.

Cost-Effectiveness of Hypochlorous Acid Preserved Wound Cleanser versus Saline Irrigation in Conjunction with Ultrasonic Debridement for Complex Wounds

Objective: Low-frequency ultrasound debridement with irrigation is an effective method of wound bed preparation. A recent clinical study compared hypochlorous acid preserved wound cleanser (HAPWOC) to saline and found HAPWOC to be a more effective adjunct to low frequency ultrasound debridement. However, HAPWOC has an added cost. The primary objective of this study was to assess the cost-effectiveness of HAPWOC as an irrigation modality with low-frequency ultrasound debridement for the treatment of severely complex wounds that were destined to be closed primarily via a flap. The secondary objective of this study was to estimate the number needed to treat (NNT) to avoid a wound-related complication and its expected cost per NNT. Methods: A patient-level Monte-Carlo simulation model was used to conduct a cost-effectiveness analysis from the US health system perspective. All clinical data were obtained from a prospective clinical trial. Cost data were obtained from the publicly available data sources in 2021 US dollars. The effect measure was the avoidance of wound-related complications at 14-days post-debridement. The primary outcome was the incremental cost-effectiveness ratio (ICER), a measure of the additional cost per benefit. The secondary outcomes were the NNT and expected cost per NNT to avoid one complication (complementary to the ICER in assessing cost-effectiveness). Deterministic and probabilistic sensitivity analyses (PSA) were performed to gauge the robustness and reliability of the results. Results: The ICER for HAPWOC versus saline irrigation was US$90.85 per wound complication avoided. The expected incremental cost per patient in the study and effect was US$49.97 with 55% relative reduction in wound-related complications at day 14 post debridement procedure. The NNT and cost per NNT were 2 and US$99.94, respectively. Sensitivity analyses demonstrated that these results were robust to variation in model parameters. Conclusion: HAPWOC was a cost-effective strategy for the treatment of complex wounds during ultrasonic debridement. For every two patients treated with HAPWOC, one complication was avoided.

1110 The Cost of Fixing a Fractured Mandible: A Waste Reduction Project

Introduction Fractured mandibles are a frequent injury seen in the hospital and are commonly caused by interpersonal violence and accidental injury. The need to reduce expenditure in the NHS and redirect funds to where it is most needed is an important topic in recent times. The cost of open reduction internal fixation (ORIF) of mandible fractures can vary by the choice of equipment and technique used. Therefore, this waste reduction project aimed to identify any variation in treatment and minimise this. Method A data collection exercise was performed of isolated mandibular fractures which required surgical intervention. Operation notes were examined from April 2018 to March 2019, with 99 cases found. Information was collected about the number and type of drill bits, plates and screws that were used in the surgery. The expected cost for plating different mandibular fractures including simple, comminuted and multiple fractures was calculated which was compared to the actual average cost by type of injury and operating surgeon. Results The most common injury seen was Parasymphysis fractures, with the average ORIF cost across all surgeons being £239.07. The expected cost to fix this fracture was calculated at £237.95, or £325.31 if intra-operative intermaxillary fixation is used. It was demonstrated that the cost across all injuries was within the expected range and therefore no improvement could be made. Conclusions By limiting the available equipment, stocking the most cost-effective options, and teaching surgeons standardised treatments we are able to reduce the cost and waste in the hospital.

Optimal Control Policy for a Two-Phase M/M/1 Unreliable Gated Queue under N-Policy with a Fuzzy Environment

The two-phase service models analyzed by several authors considered only the probabilistic nature of the queue parameters with fixed cost elements. But the queue parameters and cost elements will be in general are of both possibilistic and probabilistic in nature. Analyzing the performance of the queueing systems with fuzzy environment facilitates to investigate for the possibilistic interval estimates to the performance measures of a queueing system rather than point estimates. In this work, it is proposed to construct membership function of the fuzzy cost function to obtain confidence estimates for some performance measures of a controllable two-phase service single server Markovian gated queue with server startups and breakdowns under N-policy in which the queue parameters viz. arrival rate, startup rate, batch service rate, individual service rate, repair rate and cost elements are all defined as fuzzy numbers. Based on Zadeh’s extension principle and the α-cuts, a set of parametric nonlinear programming problems are developed to find the upper and lower bounds of the minimum total expected cost per unit time at the possibility level α. As the analytical solutions of the nonlinear programming problems developed for the proposed model are tedious, considering the system parameters and cost elements as trapezoidal fuzzy numbers, numerical results for the lower and upper bounds of the optimal threshold N* and the minimum total expected cost per unit time are computed using the nonlinear programming solver available in MATLAB.

On continuation-passing transformations and expected cost analysis

We define a continuation-passing style (CPS) translation for a typed λ-calculus with probabilistic choice, unbounded recursion, and a tick operator — for modeling cost. The target language is a (non-probabilistic) λ-calculus, enriched with a type of extended positive reals and a fixpoint operator. We then show that applying the CPS transform of an expression M to the continuation λ v . 0 yields the expected cost of M . We also introduce a formal system for higher-order logic, called EHOL, prove it sound, and show it can derive tight upper bounds on the expected cost of classic examples, including Coupon Collector and Random Walk. Moreover, we relate our translation to Kaminski et al.’s ert-calculus, showing that the latter can be recovered by applying our CPS translation to (a generalization of) the classic embedding of imperative programs into λ-calculus. Finally, we prove that the CPS transform of an expression can also be used to compute pre-expectations and to reason about almost sure termination.

Robust Yellow River Delta Flood Management under Uncertainty

A number of principles for evaluating water resources decisions under deep long-run uncertainty have been proposed in the literature. In this paper, we evaluate the usefulness of three widely recommended principles in the context of delta water and sedimentation management: scenario-based uncertainty definition, robustness rather than optimality as a performance measure, and modeling of adaptability, which is the flexibility to change system design or operations as conditions change in the future. This evaluation takes place in the context of an important real-world problem: flood control in the Yellow River Delta. The results give insight both on the physical function of the river system and on the effect of various approaches to modeling risk attitudes and adaptation on the long-term performance of the system. We find that the optimal decisions found under different scenarios differ significantly, while those resulting from using minimal expected cost and minmax regret metrics are similar. The results also show that adaptive multi-stage optimization has a lower expected cost than a static approach in which decisions over the entire time horizon are specified; more surprisingly, recognizing the ability to adapt means that larger, rather than smaller, first-stage investments become optimal. When faced with deep uncertainty in water resources planning, this case study demonstrates that considering scenarios, robustness, and adaptability can significantly improve decisions.