FoxQ1 Overexpression Influences Poor Prognosis in Non-Small Cell Lung Cancer, Associates with the Phenomenon of EMT

BACKGROUND: We determined the expression of forkhead box Q1 (FoxQ1), E-cadherin (E-cad), Mucin 1 (MUC1), vimentin (VIM) and S100 calcium binding protein A4 (S100A4), all epithelial-mesenchymal transition (EMT) indicator proteins in non-small cell lung cancer (NSCLC) tissue samples. We also investigated the relationship between these five proteins expression and other clinicopathologic factors in NSCLC. Finally, we assessed the potential value of these markers as prognostic indicators of survival in NSCLC's patients. METHODS: Quantitative real-time PCR and immunohistochemistry were used to characterize the expression of the FoxQ1 mRNA and protein in NSCLC. Expression of transcripts and translated products for the other four EMT indicator proteins was assessed by immunohistochemistry in the same clinical NSCLC samples. RESULTS: FoxQ1 mRNA and protein were up-regulated in NSCLC compared with normal tissues (P = 0.015 and P<0.001, respectively). Expression of FoxQ1 in adenocarcinoma was higher than in squamous cell carcinoma (P = 0.005), and high expression of FoxQ1 correlated with loss of E-cad expression (P = 0.012), and anomalous positivity of VIM (P = 0.024) and S100A4 (P = 0.004). Additional survival analysis showed that high expression of FoxQ1 (P = 0.047) and E-cad (P = 0.021) were independent prognostic factors. CONCLUSION: FoxQ1 maybe plays a specific role in the EMT of NSCLC, and could be used as a prognostic factor for NSCLC

Relative Voltage Control of the Wind Farms Based on the Local Reactive Power Regulation

The fast and coordinated voltage control of distributed nodes inside a large scale wind farm is a stringent issue. To achieve the reactive power compensation without a dedicated upper communication system, this paper proposes a relative control strategy based on the local reactive power regulation. This method can realize the voltage coordination of the key equipment and feeder line nodes, on the basis of the relative voltage observations. Firstly, the stability analysis of a certain wind farm with pre-known parameters and structure is studied under the wind power fluctuations. Secondly, the optimal capacity configurations of the reactive power compensators are discussed, with multiple nodes inside the wind farms. Simulation results of a specific wind farm in North Hebei, China, validate the effectiveness of the proposed control, which is equipped with fast and stable voltage dynamic responses, as well as local reactive power compensations without remote communication

GDSA: A Grid-based Distributed Simulation Architecture

This paper focuses on architecture suitable for largescale simulation system. Based on the scenario of large-scale internet simulation, the grid technology is introduced and a new architecture, GDSA is proposed. GDSA, a full grid-based architecture mainly focuses on four pending problems in distributed system: scalability, communications, management mechanism and QoS insurance computing environment. The Advantages of grid in scalability and uniform communication will be used to improve system&apos;s scalability and communication method. Management system will be built according to Meta-service mechanism. Contractual Computing Mechanism (CCM), a special mechanism added in GDSA, will provide QoS insurance for users. Three-layer QoS model, which is the core of CCM, will take charge of QoS problems in different levels. At the end, a prototype is designed and the experiment results based on this platform show that GDSA is a promising system to overcome the pending problems in distributed simulation. 1

Equilibrium Joining Strategies of Delay-Sensitive Customers in a Queueing System with Service Quality Feedback

In some queueing systems, customers are frequently asked for giving a service quality feedback for their service at their service completion instants. Based on this phenomenon, in this paper, we model this type of queueing systems as clearing queues with service quality feedback and system maintenance. Once the system receives an unsatisfied (negative) feedback from customers (i.e., a customer is unsatisfied with the service), the system undergoes an adjustment procedure, and at the same time, all the present customers are forced to leave the system. By considering the waiting cost and reward, we discuss the joining behavior of customers and, respectively, derive the corresponding equilibrium joining strategies and social optimal strategies under different levels of information (the observable and the unobservable cases). Finally, some numerical examples are provided to show the effect of several system parameters on the equilibrium and optimal balking strategies

Qualitative and Quantitative Integrated Modeling for Stochastic Simulation and Optimization

The simulation and optimization of an actual physics system are usually constructed based on the stochastic models, which have both qualitative and quantitative characteristics inherently. Most modeling specifications and frameworks find it difficult to describe the qualitative model directly. In order to deal with the expert knowledge, uncertain reasoning, and other qualitative information, a qualitative and quantitative combined modeling specification was proposed based on a hierarchical model structure framework. The new modeling approach is based on a hierarchical model structure which includes the meta-meta model, the meta-model and the high-level model. A description logic system is defined for formal definition and verification of the new modeling specification. A stochastic defense simulation was developed to illustrate how to model the system and optimize the result. The result shows that the proposed method can describe the complex system more comprehensively, and the survival probability of the target is higher by introducing qualitative models into quantitative simulation

DR-CIML: Few-shot Object Detection via Base Data Resampling and Cross-iteration Metric Learning

Aiming at the problems of difficult data collection and labor-intensive manual annotation, few-shot object detection (FSOD) has gained wide attention. Although current transfer-learning-based detection methods outperform meta-learning-based methods, their data organization fails to fully utilize the diversity of the source domain data. In view of this, Data Resampling (DR) organization is proposed to fine-tune the network, which can be employed as a component of any model and dataset without additional inference overhead. In addition, in order to improve the generalization of the model, a Cross-Iteration Metric-Learning (CIML) branch is embedded in the few-shot object detector, thus actively improving intra-category feature propinquity and inter-category feature discrimination. Our generic DR-CIML approach obtained competitive scores in extensive comparative experiments. The nAP50 performance on PASCAL VOC improved by up to 6.3 points, and the bAP50 performance reached 81.0, surpassing the base stage model (80.8) for the first time. The nAP75 performance on MS COCO improved by up to 1.6 points