On the Re-Solving Heuristic for (Binary) Contextual Bandits with Knapsacks

In the problem of (binary) contextual bandits with knapsacks (CBwK), the agent receives an i.i.d. context in each of the $T$ rounds and chooses an action, resulting in a random reward and a random consumption of resources that are related to an i.i.d. external factor. The agent's goal is to maximize the accumulated reward under the initial resource constraints. In this work, we combine the re-solving heuristic, which proved successful in revenue management, with distribution estimation techniques to solve this problem. We consider two different information feedback models, with full and partial information, which vary in the difficulty of getting a sample of the external factor. Under both information feedback settings, we achieve two-way results: (1) For general problems, we show that our algorithm gets an $\widetilde O(T^{\alpha_u} + T^{\alpha_v} + T^{1/2})$ regret against the fluid benchmark. Here, $\alpha_u$ and $\alpha_v$ reflect the complexity of the context and external factor distributions, respectively. This result is comparable to existing results. (2) When the fluid problem is linear programming with a unique and non-degenerate optimal solution, our algorithm leads to an $\widetilde O(1)$ regret. To the best of our knowledge, this is the first $\widetilde O(1)$ regret result in the CBwK problem regardless of information feedback models. We further use numerical experiments to verify our results.Comment: 43 pages, 2 figures, 1 tabl

Study on array laterolog response simulation and mud-filtrate invasion correction

It is a complicated task to evaluate the reservoirs influenced by mud-filtrate invasion. This paper presents the numerical simulation results of array laterolog response and the approach for mud-filtrate invasion correction. Based on the differential equations and boundary conditions of the steady current field in the rock medium, the finite element method (FEM) is applied to solve the Laplace equation, then computing the potential value at each node and calculating the apparent resistivity of six measuring modes of array laterolog. Based on the numerical results, the array laterolog response is affected by many parameters including borehole radius, mud-filtrate resistivity, mud-filtrate invasion radius and invaded area resistivity. Correction charts for borehole and mud-filtrate invasion were made to quickly and accurately obtain the mud-filtrate invasion depth and the true resistivity of the uninvaded formation, which can be used to qualitatively estimate the oiliness and permeability characteristics of the formation.Cited as: Zhao, P., Qin, R., Pan, H., Ostadhassan, M., Wu, Y. Study on array laterolog response simulation and mud-filtrate invasion correction. Advances in Geo-Energy Research, 2019, 3(2): 175-186, doi: 10.26804/ager.2019.02.0

Study on array laterolog response simulation and mud-filtrate invasion correction

It is a complicated task to evaluate the reservoirs influenced by mud-filtrate invasion. This paper presents the numerical simulation results of array laterolog response and the approach for mud-filtrate invasion correction. Based on the differential equations and boundary conditions of the steady current field in the rock medium, the finite element method (FEM) is applied to solve the Laplace equation, then computing the potential value at each node and calculating the apparent resistivity of six measuring modes of array laterolog. Based on the numerical results, the array laterolog response is affected by many parameters including borehole radius, mud-filtrate resistivity, mud-filtrate invasion radius and invaded area resistivity. Correction charts for borehole and mud-filtrate invasion were made to quickly and accurately obtain the mud-filtrate invasion depth and the true resistivity of the uninvaded formation, which can be used to qualitatively estimate the oiliness and permeability characteristics of the formation

Dynamic Budget Throttling in Repeated Second-Price Auctions

Throttling is one of the most popular budget control methods in today's online advertising markets. When a budget-constrained advertiser employs throttling, she can choose whether or not to participate in an auction after the advertising platform recommends a bid. This paper focuses on the dynamic budget throttling process in repeated second-price auctions from a theoretical view. An essential feature of the underlying problem is that the advertiser does not know the distribution of the highest competing bid upon entering the market. To model the difficulty of eliminating such uncertainty, we consider two different information structures. The advertiser could obtain the highest competing bid in each round with full-information feedback. Meanwhile, with partial information feedback, the advertiser could only have access to the highest competing bid in the auctions she participates in. We propose the OGD-CB algorithm, which involves simultaneous distribution learning and revenue optimization. In both settings, we demonstrate that this algorithm guarantees an $O(\sqrt{T\log T})$ regret with probability $1 - O(1/T)$ relative to the fluid adaptive throttling benchmark. By proving a lower bound of $\Omega(\sqrt{T})$ on the minimal regret for even the hindsight optimum, we establish the near optimality of our algorithm. Finally, we compare the fluid optimum of throttling to that of pacing, another widely adopted budget control method. The numerical relationship of these benchmarks sheds new light on the understanding of different online algorithms for revenue maximization under budget constraints.Comment: 29 pages, 1 tabl

Acetaldehyde released by Lactobacillus plantarum enhances accumulation of pyranoanthocyanins in wine during malolactic fermentation

This study investigated the evolution of acetaldehyde and pyranoanthocyanins in wine during malolactic fermentation, and further evaluated the correlation between acetaldehyde and pyranoanthocyanins. Cabernet Gernischt wine after alcoholic fermentation was inoculated with four lactic acid bacteria strains. Malolactic fermentation kinetics and wine characteristics were compared. Results showed these strains exhibited different kinetics on wine malolactic fermentation. Wine with Lactobacillus plantarum had lower reducing sugar, total acid, and yellowness. Lactobacillus plantarum elevated the level of acetaldehyde in wine model medium and wine during malolactic fermentation. Malolactic fermentation using Lactobacillus plantarum significantly increased the concentration of pyranoanthocyanins, whereas O. oeni strain reduced the level of pyranoanthocyanins in wine. Polymerized anthocyanins percentage in wine was significantly enhanced after fermentation with Lactobacillus plantarum. Principal component analysis indicated that the characteristics of these strains inoculated wines after malolactic fermentation were segregated. The findings from this study could provide useful information on the wine color improvement through malolactic fermentation with suitable lactic acid bacteria strains

A novel approach for Lithium-ion battery thermal management with streamline shape mini channel cooling plates

The mini-channel cooling plate has been widely used in the Lithium-ion battery thermal management for electric vehicles. The technology development of high efficiency and good temperature uniformity cooling plate can promote the application of electric vehicles by improving the lifespan of the battery. In this study, streamline concept, which is commonly used for the external design of car, aerospace and submarine system to improve the system performance, has been introduced to design and optimise the performance of inner mini channel cooling plate. The flow resistance was proved to be minimised when the streamline shape design was adopted. Moreover, the results have proven the novel designed mini channel cooling plate can keep the heat exchange ability within the acceptable level. The maximum improvement of the heat exchanger efficiency with streamline shape design could be as high as 44.52%. Results indicated the temperature uniformity could also be effectively improved. The streamline shape mini channel cooling plate could be a promising solution for Lithium-ion battery thermal management

Royal Jelly Alleviates Cognitive Deficits and β-Amyloid Accumulation in APP/PS1 Mouse Model Via Activation of the cAMP/PKA/CREB/BDNF Pathway and Inhibition of Neuronal Apoptosis

Alzheimer’s disease (AD) is characterized clinically by progressive cognitive decline and pathologically by the accumulation of amyloid-β (Aβ) in the brain. Royal jelly (RJ), a secretion of honeybee hypopharyngeal and mandibular glands, has previously been shown to have anti-aging and neuromodulatory activities. In this study, we discovered that 3 months of RJ treatment substantially ameliorated behavioral deficits of APP/PS1 mice in the Morris Water Maze (MWM) test and step-down passive avoidance test. Our data also showed that RJ significantly diminished amyloid plaque pathology in APP/PS1 mice. Furthermore, RJ alleviated c-Jun N-terminal kinase (JNK) phosphorylation-induced neuronal apoptosis by suppressing oxidative stress. Importantly, hippocampal cyclic adenosine monophosphate (cAMP), p-PKA, p-CREB and BDNF levels were significantly increased in the APP/PS1 mice after RJ treatment, indicating that the cAMP/PKA/CREB/BDNF pathway might be related to the ameliorative effect of RJ on cognitive decline. Collectively, these results provide a scientific basis for using RJ as a functional food for targeting AD pathology