•Efficient simulation estimation of a risk measure using two-stage simulation optimization•Proposed a new revised probability of sign change metric to intelligently guide simulation•Proved ...asymptotical consistency•Outperforms state-of-the-art procedures in financial and healthcare examples
This paper is concerned with the efficient estimation of the risk measure of a system where the estimation requires solving a two-stage simulation optimization problem. The first stage samples risk factors that specify a second stage simulation optimization problem. The second stage solves a simulation optimization problem and outputs the best performance of the system under the realized risk factors, which are then aggregated across all first stage samples to produce an estimate of the risk measure. Applications of such an estimation scheme arise frequently in important industries such as financial, healthcare, logistics, and manufacturing. Because a large number of first stage samples are typically needed, each of which requires solving a computationally expensive simulation optimization problem, the two-stage simulation optimization approach faces a major computational efficiency challenge. In response to this challenge, this paper proposes a sequential simulation budget allocation procedure that determines the allocation of simulation budget based on a score known as revised probability of sign change for each decision under each scenario. The consistency of the proposed procedure is proved and the computational efficiency gain of the proposed is demonstrated using both benchmark test functions and two test cases in the context of financial portfolio risk estimation and healthcare system resilience estimation.
Future wireless networks promise immense increases on data rate and energy efficiency while overcoming the difficulties of charging the wireless stations or devices in the Internet of Things (IoT) ...with the capability of simultaneous wireless information and power transfer (SWIPT). For such networks, jointly optimizing beamforming, power control, and energy harvesting to enhance the communication performance from the base stations (BSs) (or access points (APs)) to the mobile nodes (MNs) served would be a real challenge. In this work, we formulate the joint optimization as a mixed integer nonlinear programming (MINLP) problem, which can be also realized as a complex multiple resource allocation (MRA) optimization problem subject to different allocation constraints. By means of deep reinforcement learning to estimate future rewards of actions based on the reported information from the users served by the networks, we introduce single-layer MRA algorithms based on deep Q-learning (DQN) and deep deterministic policy gradient (DDPG), respectively, as the basis for the downlink wireless transmissions. Moreover, by incorporating the capability of data-driven DQN technique and the strength of noncooperative game theory model, we propose a two-layer iterative approach to resolve the NP-hard MRA problem, which can further improve the communication performance in terms of data rate, energy harvesting, and power consumption. For the two-layer approach, we also introduce a pricing strategy for BSs or APs to determine their power costs on the basis of social utility maximization to control the transmit power. Finally, with the simulated environment based on realistic wireless networks, our numerical results show that the two-layer MRA algorithm proposed can achieve up to 2.3 times higher value than the single-layer counterparts which represent the data-driven deep reinforcement learning-based algorithms extended to resolve the problem, in terms of the utilities designed to reflect the trade-off among the performance metrics considered.
When peanuts germinate, bioactive compounds such as resveratrol (RES), γ-aminobutyric acid (GABA), isoflavones, and polyphenol compounds are generated. Peanut kernels were germinated in the dark for ...two days, and stimuli including soaking liquid, rice koji, high-pressure processing (HPP), and ultrasonic treatment were tested for their ability to activate the defense mechanisms of peanut kernels, thus increasing their bioactive compound content. The results of this study indicate that no RES was detected in ungerminated peanuts, and only 5.58 μg/g of GABA was present, while unstimulated germinated peanuts contained 4.03 µg/g of RES and 258.83 μg/g of GABA. The RES content of the germinated peanuts increased to 13.64 μg/g after soaking in 0.2% phenylalanine solution, whereas a higher GABA content of 651.51 μg/g was observed after the peanuts were soaked in 0.2% glutamate. Soaking peanuts in 5% rice koji produced the highest RES and GABA contents (28.83 µg/g and 506.34 μg/g, respectively). Meanwhile, the RES and GABA contents of HPP-treated germinated peanuts (i.e., treated with HPP at 100 MPa for 10 min) increased to 7.66 μg/g and 497.09 μg/g, respectively, whereas those of ultrasonic-treated germinated peanuts (for 20 min) increased to 13.02 μg/g and 318.71 μg/g, respectively. After soaking peanuts in 0.5% rice koji, followed by HPP treatment at 100 MPa for 10 min, the RES and GABA contents of the germinated peanuts increased to 37.78 μg/g and 1196.98 μg/g, while the RES and GABA contents of the germinated peanuts treated with rice koji followed by ultrasonic treatment for 20 min increased to 46.53 μg/g and 974.52 μg/g, respectively. The flavonoid and polyphenol contents of the germinated peanuts also increased after exposure to various external stimuli, improving their DPPH free radical-scavenging ability and showing the good potential of germinated peanuts as functional products.
Background
For R/M HNSCC, the differences in prognosis and treatment options between distant metastasis (DM) and locoregional recurrence, especially in the DM group, remain unclear.
Methods
From the ...Taiwan Head Neck Society registry database, patients who were diagnosed with R/M HNSCC and received cetuximab‐based frontline therapy were collected for analysis.
Results
Among the enrolled patients, 59.3% (491/827) belonged to the DM group. The DM group had less primary site of oral cavity, less betel nut chewing, higher lactate dehydrogenase (LDH) levels, and higher LDH/albumin ratio compared with the non‐DM group. For the patients with primary site of oral cavity and current smokers, DM coexisted with poorer outcomes. In the DM group, EXTREME‐like regimen was more suitable for older patients, those with elevated LDH, and those with higher LDH/albumin ratio than TPExtreme‐like regimen.
Conclusion
DM coexisted with poorer prognosis in certain groups. LDH‐associated biomarkers may aid treatment options for DM patients.
The quasinormal modes of a massless Dirac field in the de Rham-Gabadadze-Tolley (dRGT) massive gravity theory with asymptotically de Sitter spacetime are investigated using the ...Wentzel-Kramers-Brillouin approximation. The effective potential for the massless Dirac field due to the dRGT black hole is derived. It is found that the shape of the potential depends crucially on the structure of the graviton mass and the behavior of the quasinormal modes is controlled by the graviton mass parameters. Higher potentials give stronger damping of the quasinormal modes. We compare our results to the Schwarzschild-de Sitter case. Our numerical calculations are checked using Padé approximation and found that the quasinormal mode frequencies converge to ones with reasonable accuracy.
This study investigated the coexistence of public and private companies using a complementary model to explore mixed oligopoly strategies. Compared to the traditional theory of mixed oligopoly, the ...main difference of this study is that it revealed that the products produced by both companies are completely complementary. The five findings of the study were as follows: First, under the premise of having one firm classified as a public firm, although it can reach the equilibrium of the maximum solution for social welfare, this causes a loss. Second, more seriously, the private firm would view this as a huge incentive and aggressively pursue to be the price leader, which may result in a greater loss for the public firm. Third, the asymmetry of the model of the complementary mixed oligopoly is of note; that is, when the private firm is in aggressive pursuit to be the price leader, it can elevate its profit margin, but when the public firm is aggressively pursuing be the price leader, this would not result in better profits. Fourth, if the public firm is under budgetary constraints, then the private firm would have no incentive to aggressively pursue being the price leader. Fifth, if the price of the product between the public firm and the private firm is a “strategic substitute,” the coexistence of the public firm and the private firm will be better than total privatization.
The 1,3‐enyne moiety is commonly found in cyclohexanoid natural products produced by endophytic and plant pathogenic fungi. Asperpentyn (1) is a 1,3‐enyne‐containing cyclohexanoid terpenoid isolated ...from Aspergillus and Pestalotiopsis. The genetic basis and biochemical mechanism of 1,3‐enyne biosynthesis in 1, and other natural products containing this motif, has remained enigmatic despite their potential ecological roles. Identified here is the biosynthetic gene cluster and characterization of two crucial enzymes in the biosynthesis of 1. A P450 monooxygenase that has a dual function, to first catalyze dehydrogenation of the prenyl chain to generate a cis‐diene intermediate and then serve as an acetylenase to yield an alkyne moiety, and thus the 1,3‐enyne, was discovered. A UbiA prenyltransferase was also characterized and it is unusual in that it favors transferring a five‐carbon prenyl chain, rather than a polyprenyl chain, to a p‐hydroxybenzoic acid acceptor.
Clusters: Enynes are an important functionality in organic chemistry. Reported here is the identification of the biosynthetic gene cluster and characterization of two crucial enzymes in the biosynthesis of asperpentyn (1). Notably, P450 monooxygenase was discovered to have a dual function, that is, to first catalyze dehydrogenation of the prenyl chain to generate a cis‐diene intermediate, and then serve as an acetylenase to yield an alkyne moiety.
Opioid addiction is a chronic and complex disease characterized by relapse and remission. In the past decade, the opioid epidemic or opioid crisis in the United States has raised public awareness. ...Methadone, buprenorphine, and naloxone have proven their effectiveness in treating addicted individuals, and each of them has different effects on different opioid receptors. Classic and molecular genetic research has provided valuable information and revealed the possible mechanism of individual differences in vulnerability for opioid addiction. The polygenic risk score based on the results of a genome-wide association study (GWAS) may be a promising tool to evaluate the association between phenotypes and genetic markers across the entire genome. A novel gene editing approach, clustered, regularly-interspaced short palindromic repeats (CRISPR), has been widely used in basic research and potentially applied to human therapeutics such as mental illness; many applications against addiction based on CRISPR are currently under research, and some are successful in animal studies. In this article, we summarized the biological mechanisms of opioid addiction and medical treatments, and we reviewed articles about the genetics of opioid addiction, the promising approach to predict the risk of opioid addiction, and a novel gene editing approach. Further research on medical treatments based on individual vulnerability is needed.
In this article, we consider the problem of selecting important nodes in a random network, where the nodes connect to each other randomly with certain transition probabilities. The node importance is ...characterized by the stationary probabilities of the corresponding nodes in a Markov chain defined over the network, as in Google's PageRank. Unlike a deterministic network, the transition probabilities in a random network are unknown but can be estimated by sampling. Under a Bayesian learning framework, we apply the first-order Taylor expansion and normal approximation to provide a computationally efficient posterior approximation of the stationary probabilities. In order to maximize the probability of correct selection, we propose a dynamic sampling procedure, which uses not only posterior means and variances of certain interaction parameters between different nodes, but also the sensitivities of the stationary probabilities with respect to each interaction parameter. Numerical experiment results demonstrate the superiority of the proposed sampling procedure.
Attaining reliable communications traditionally relies on a closed-loop methodology but inevitably incurs a good amount of networking latency thanks to complicated feedback mechanism and signaling ...storm. Such a closed-loop methodology thus shackles the current cellular network with a tradeoff between high reliability and low latency. To completely avoid the latency induced by closed-loop communication, this article aims to study how to jointly employ open-loop communication and multi-cell association in a heterogeneous network (HetNet) so as to achieve ultra-reliable and low-latency communications. We first introduce how mobile users in a HetNet adopt the proposed proactive multi-cell association (PMCA) scheme to form their virtual cell that consists of multiple access points (APs) and then analyze the communication reliability and latency performances. We show that the communication reliability can be significantly improved by the PMCA scheme and maximized by optimizing the densities of the users and the APs. The analyses of the uplink and downlink delays are also accomplished, which show that extremely low latency can be fulfilled in the virtual cell of a single user if the PMCA scheme is adopted and the radio resources of each AP are appropriately allocated.
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