A High-Precision Single Shooting Method for Solving Hypersensitive Optimal Control Problems

Solving hypersensitive optimal control problems is a long-standing challenge for decades in optimization engineering, mainly due to the possible nonexistence of the optimal solution to meet the required error tolerance under double-precision arithmetic and the hypersensitivity of the optimal solution with respect to the initial conditions. In this paper, a new high-precision single shooting method is presented to address the above two difficulties. Multiple-precision arithmetic and Taylor series method are introduced to provide the accurate optimal solution with arbitrary higher significant digits and arbitrary higher integral accuracy, respectively. Besides, a new modified bidirectional single shooting method is developed, which fully utilizes the three-segment structure of the hypersensitive optimal control problems and provides appropriate initial guess that is close to the optimal solutions. Numerical demonstrations in a typical hypersensitive optimal control problem are presented to illustrate the effectiveness of this new method, which indicates that the accurate optimal solution of this challenging problem can be easily solved by this simple single shooting method within several iterations

Robusni algoritam praćenja mjerenjem smjera pomoću strukturiranog potpunog Kalmanovog filtra zasnovanog na metodi najmanjih kvadrata

A nonlinear approach called the robust structured total least squares kalman filter (RSTLS-KF) algorithm is proposed for solving tracking inaccuracy caused by outliers in bearings-only multi-station passive tracking. In that regard, the robust extremal function is introduced to the weighted structured total least squares (WSTLS) location criterion, and then the improved Danish equivalent weight function is built on the basis, which can identify outliers automatically and reduce the weight of the polluted data. Finally, the observation equation is linearized according to the RSTLS location result with the structured total least norm (STLN) solution. Hence location and velocity of the target can be given by the Kalman filter. Simulation results show that tracking performance of the RSTLS-KF is comparable or better than that of conventional algorithms. Furthermore, when outliers appear, the RSTLS-KF is accurate and robust, whereas the conventional algorithms become distort seriously.U ovome radu predložen je nelinearni pristup za rješavanje netočnosti uzrokovanih netipčnim vrijednostima kod praćenja mjerenjem smjera pasivnim senzorima s više stanica. Pristup je zasnovan na robusnom strukturiranom potpunom Kalmanovom filtru zasnovanom na metodi najmanjih kvadrata. Pomoću predložene metode moguće je estimirati položaj i brzinu praćenog objekta. Simulacijski rezultati pokazuju da je učinkovitost predloženog algoritma jednaka ili bolja od konvencionalnih algoritama. Nadalje, u prisustvu netipčnih vrijednosti mjerenja, predloženi algoritam zadržava točnost i robusnost, dok konvencionalni algoritmi pokazuju pogreške u estimaciji

Out of the Box Thinking: Improving Customer Lifetime Value Modelling via Expert Routing and Game Whale Detection

Customer lifetime value (LTV) prediction is essential for mobile game publishers trying to optimize the advertising investment for each user acquisition based on the estimated worth. In mobile games, deploying microtransactions is a simple yet effective monetization strategy, which attracts a tiny group of game whales who splurge on in-game purchases. The presence of such game whales may impede the practicality of existing LTV prediction models, since game whales' purchase behaviours always exhibit varied distribution from general users. Consequently, identifying game whales can open up new opportunities to improve the accuracy of LTV prediction models. However, little attention has been paid to applying game whale detection in LTV prediction, and existing works are mainly specialized for the long-term LTV prediction with the assumption that the high-quality user features are available, which is not applicable in the UA stage. In this paper, we propose ExpLTV, a novel multi-task framework to perform LTV prediction and game whale detection in a unified way. In ExpLTV, we first innovatively design a deep neural network-based game whale detector that can not only infer the intrinsic order in accordance with monetary value, but also precisely identify high spenders (i.e., game whales) and low spenders. Then, by treating the game whale detector as a gating network to decide the different mixture patterns of LTV experts assembling, we can thoroughly leverage the shared information and scenario-specific information (i.e., game whales modelling and low spenders modelling). Finally, instead of separately designing a purchase rate estimator for two tasks, we design a shared estimator that can preserve the inner task relationships. The superiority of ExpLTV is further validated via extensive experiments on three industrial datasets

Transcriptome analysis of Rpl11-deficient zebrafish model of Diamond-Blackfan Anemia

AbstractTo comprehensively reflect the roles of Rpl11 on the transcriptome of zebrafish model of Diamond-Blackfan Anemia (DBA), we performed whole-genome transcriptome sequencing on the Illumina Hi-Seq 2000 sequencing platform. Two different transcriptomes of zebrafish Rpl11-deficient and control Morpholino (Mo) embryos were collected and analyzed. The experimental design and methods, including sample preparation, RNA-Seq data evaluation and treatment, were described in details so that representative high-throughput sequencing data were acquired for assessing the actual impacts of Rpl11 on zebrafish embryos. We provided the accession number GSE51326 for easy access to the database

T-Bet and Eomes Regulate the Balance between the Effector/Central Memory T Cells versus Memory Stem Like T Cells

Memory T cells are composed of effector, central, and memory stem cells. Previous studies have implicated that both T-bet and Eomes are involved in the generation of effector and central memory CD8 T cells. The exact role of these transcription factors in shaping the memory T cell pool is not well understood, particularly with memory stem T cells. Here, we demonstrate that both T-bet or Eomes are required for elimination of established tumors by adoptively transferred CD8 T cells. We also examined the role of T-bet and Eomes in the generation of tumor-specific memory T cell subsets upon adoptive transfer. We showed that combined T-bet and Eomes deficiency resulted in a severe reduction in the number of effector/central memory T cells but an increase in the percentage of CD62LhighCD44low Sca-1+ T cells which were similar to the phenotype of memory stem T cells. Despite preserving large numbers of phenotypic memory stem T cells, the lack of both of T-bet and Eomes resulted in a profound defect in antitumor memory responses, suggesting T-bet and Eomes are crucial for the antitumor function of these memory T cells. Our study establishes that T-bet and Eomes cooperate to promote the phenotype of effector/central memory CD8 T cell versus that of memory stem like T cells. © 2013 Li et al

TIM-3 Expression Characterizes Regulatory T Cells in Tumor Tissues and Is Associated with Lung Cancer Progression

Background: T cell immunoglobulin-3 (TIM-3) has been established as a negative regulatory molecule and plays a critical role in immune tolerance. TIM-3 is upregulated in exhausted CD8 + T cells in both chronic infection and tumor. However, the nature of TIM-3 +CD4 + T cells in the tumor microenvironment is unclear. This study is to characterize TIM-3 expressing lymphocytes within human lung cancer tissues and establish clinical significance of TIM-3 expression in lung cancer progression. Methodology: A total of 51 human lung cancer tissue specimens were obtained from pathologically confirmed and newly diagnosed non-small cell lung cancer (NSCLC) patients. Leukocytes from tumor tissues, distal normal lung tissues, and peripheral blood mononuclear cells (PBMC) were analyzed for TIM-3 surface expression by flow cytometry. TIM-3 expression on tumor-infiltrating lymphocytes (TILs) was correlated with clinicopathological parameters. Conclusions: TIM-3 is highly upregulated on both CD4 + and CD8 + TILs from human lung cancer tissues but negligibly expressed on T cells from patients' peripheral blood. Frequencies of IFN-γ + cells were reduced in TIM-3 +CD8 + TILs compared to TIM-3 -CD8 + TILs. However, the level of TIM-3 expression on CD8 + TILs failed to associate with any clinical pathological parameter. Interestingly, we found that approximately 70% of TIM-3 +CD4 + TILs expressed FOXP3 and about 60% of FOXP3 + TILs were TIM-3 +. Importantly, TIM-3 expression on CD4 + T cells correlated with poor clinicopathological parameters of NSCLC such as nodal metastasis and advanced cancer stages. Our study reveals a new role of TIM-3 as an important immune regulator in the tumor microenvironment via its predominant expression in regulatory T cells. © 2012 Gao et al

Association of Mitochondrial DNA Variations with Lung Cancer Risk in a Han Chinese Population from Southwestern China

Mitochondrial DNA (mtDNA) is particularly susceptible to oxidative damage and mutation due to the high rate of reactive oxygen species (ROS) production and limited DNA-repair capacity in mitochondrial. Previous studies demonstrated that the increased mtDNA copy number for compensation for damage, which was associated with cigarette smoking, has been found to be associated with lung cancer risk among heavy smokers. Given that the common and “non-pathological” mtDNA variations determine differences in oxidative phosphorylation performance and ROS production, an important determinant of lung cancer risk, we hypothesize that the mtDNA variations may play roles in lung cancer risk. To test this hypothesis, we conducted a case-control study to compare the frequencies of mtDNA haplogroups and an 822 bp mtDNA deletion between 422 lung cancer patients and 504 controls. Multivariate logistic regression analysis revealed that haplogroups D and F were related to individual lung cancer resistance (OR = 0.465, 95%CI = 0.329–0.656, p<0.001; and OR = 0.622, 95%CI = 0.425–0.909, p = 0.014, respectively), while haplogroups G and M7 might be risk factors for lung cancer (OR = 3.924, 95%CI = 1.757–6.689, p<0.001; and OR = 2.037, 95%CI = 1.253–3.312, p = 0.004, respectively). Additionally, multivariate logistic regression analysis revealed that cigarette smoking was a risk factor for the 822 bp mtDNA deletion. Furthermore, the increased frequencies of the mtDNA deletion in male cigarette smoking subjects of combined cases and controls with haplogroup D indicated that the haplogroup D might be susceptible to DNA damage from external ROS caused by heavy cigarette smoking

Optimal Design of a New Rotating Magnetic Beacon Structure Based on Halbach Array

At present, the magnetic signals generated by the common artificial magnetic beacons change periodically with sinusoidal law, and there is a multi-value problem in measuring the target orientation by using the phase information of the magnetic signals. According to the characteristics of Halbach array, a kind of artificial magnetic beacon based on Halbach array is studied. This beacon has the characteristics of magnetic signal aggregation, which can avoid the multi-value problem and facilitate the extraction of phase information. Firstly, the array model is established with MATLAB, the magnetization direction of each permanent magnet is adjusted, and particle swarm optimization is used to find the structural parameters with the strongest magnetic field characteristics. Finally, COMSOL physical simulation software is used to verify the usability of the proposed structure

Feedback Robust Cubature Kalman Filter for Target Tracking Using an Angle Sensor

The direction of arrival (DOA) tracking problem based on an angle sensor is an important topic in many fields. In this paper, a nonlinear filter named the feedback M-estimation based robust cubature Kalman filter (FMR-CKF) is proposed to deal with measurement outliers from the angle sensor. The filter designs a new equivalent weight function with the Mahalanobis distance to combine the cubature Kalman filter (CKF) with the M-estimation method. Moreover, by embedding a feedback strategy which consists of a splitting and merging procedure, the proper sub-filter (the standard CKF or the robust CKF) can be chosen in each time index. Hence, the probability of the outliers’ misjudgment can be reduced. Numerical experiments show that the FMR-CKF performs better than the CKF and conventional robust filters in terms of accuracy and robustness with good computational efficiency. Additionally, the filter can be extended to the nonlinear applications using other types of sensors