ALBERT

Description: BACKGROUND: Recent studies have shown that microRNAs (miRNA) have prognostic values in cancers. This meta-analysis seeks to summarize the global predicting role of miR-155 for survival in patients with a variety of carcinomas.METHODS: Eligible studies were identified through multiple search strategies. Data were extracted from studies investigating the relationship between miR-155 expression and survival in cancer patients. Combined hazard ratios (HRs) of miR-155 for outcome were analyzed.RESULTS: A total of 16 studies dealing with various carcinomas were included for this meta-analysis. For overall survival, higher miR-155 expression could significantly predict worse outcome with the pooled HR of 2.057 (95% CI: 1.392–3.039). For relapse or progress-free survival, elevated miR-155 was also a significant predictor, with a combined HR of 1.918 (95% CI: 1.311–2.806,). In addition, subgroup analysis showed that higher expression of miR-155 had the trends to predict worse outcome in lung cancer. However, the HRs did not reach the statistical significance.CONCLUSION: Our findings suggest that miR-155 detection has a prognostic value in cancer patients. Regularly measuring miR-155 expression may be useful in clinical practice.

Description: The comprehensive understanding of the variation law of soil thermal conductivity is the prerequisite of design and construction of engineering applications in permafrost regions. Compared with the unfrozen soil, the specimen preparation and experimental procedures of frozen soil thermal conductivity testing are more complex and challengeable. In this work, considering for essentially multiphase and porous structural characteristic information reflection of unfrozen soil thermal conductivity, prediction models of frozen soil thermal conductivity using nonlinear regression and Support Vector Regression (SVR) methods have been developed. Thermal conductivity of multiple types of soil samples which are sampled from the Qinghai-Tibet Engineering Corridor (QTEC) are tested by the transient plane source (TPS) method. Correlations of thermal conductivity between unfrozen and frozen soil has been analyzed and recognized. Based on the measurement data of unfrozen soil thermal conductivity, the prediction models of frozen soil thermal conductivity for 7 typical soils in the QTEC are proposed. To further facilitate engineering applications, the prediction models of two soil categories (coarse and fine-grained soil) have also been proposed. The results demonstrate that, compared with nonideal prediction accuracy of using water content and dry density as the fitting parameter, the ternary fitting model has a higher thermal conductivity prediction accuracy for 7 types of frozen soils (more than 98% of the soil specimens’ relative error are within 20%). The SVR model can further improve the frozen soil thermal conductivity prediction accuracy and more than 98% of the soil specimens’ relative error are within 15%. For coarse and fine-grained soil categories, the above two models still have reliable prediction accuracy and determine coefficient (R2) ranges from 0.8 to 0.91, which validates the applicability for small sample soils. This study provides feasible prediction models for frozen soil thermal conductivity and guidelines of the thermal design and freeze-thaw damage prevention for engineering structures in cold regions.

Description: Background. Insulin receptor substrate 1 (IRS-1) is an important molecule of the insulin signal transduction pathway and has been associated with the occurrence and development of many tumors, including hepatocellular carcinoma (HCC). Our study was designed to determine the expression and significance of IRS-1 in human HCC. Methods. Two hundred and forty specimens were drawn from 140 patients, including 100 HCC tissues and 100 paracancerous (PC) tissues from 100 HCC patients, 20 liver cirrhosis (LC) tissues from 20 LC patients, and 20 chronic hepatitis (CH) tissues from 20 CH patients. Baseline and pathological characteristics were included, and the expression of IRS-1 was examined by immunohistochemical (IHC) staining. Binary logistic regression model calculation was used for multivariate analysis. Results. The total positive rates of IRS-1 expression were 41.0%, 17.0%, 15.0%, and 10.0% in HCC, PC, LC and CH tissues, respectively. IRS-1-positive signals were brown in color and located in the nucleus and cytoplasm. Compared with PC, LC, and CH tissues, a significantly increased expression was observed in human HCC tissues (P

Description: Finding fastest driving routes is significant for the intelligent transportation system. While predicting the online traffic conditions of road segments entails a variety of challenges, it contributes much to travel time prediction accuracy. In this paper, we propose O-Sense, an innovative online-traffic-prediction based route finding mechanism, which organically utilizes large scale taxi GPS traces and environmental information. O-Sense firstly exploits a deep learning approach to process spatial and temporal taxi GPS traces shown in dynamic patterns. Meanwhile, we model the traffic flow state for a given road segment using a linear-chain conditional random field (CRF), a technique that well forecasts the temporal transformation if provided with further supplementary environmental resources. O-Sense then fuses previously obtained outputs with a dynamic weighted classifier and generates a better traffic condition vector for each road segment at different prediction time. Finally, we perform online route computing to find the fastest path connecting consecutive road segments in the route based on the vectors. Experimental results show that O-Sense can estimate the travel time for driving routes more accurately.

Description: In dynamic systems, some nonlinearities generate special connection problems of non-Z2 symmetric homoclinic and heteroclinic orbits. Such orbits are important for analyzing problems of global bifurcation and chaos. In this paper, a general analytical method, based on the undetermined Padé approximation method, is proposed to construct non-Z2 symmetric homoclinic and heteroclinic orbits which are affected by nonlinearity factors. Geometric and symmetrical characteristics of non-Z2 heteroclinic orbits are analyzed in detail. An undetermined frequency coefficient and a corresponding new analytic expression are introduced to improve the accuracy of the orbit trajectory. The proposed method shows high precision results for the Nagumo system (one single orbit); general types of non-Z2 symmetric nonlinear quintic systems (orbit with one cusp); and Z2 symmetric system with high-order nonlinear terms (orbit with two cusps). Finally, numerical simulations are used to verify the techniques and demonstrate the enhanced efficiency and precision of the proposed method.

Description: This paper is concerned with the periodic switched control of a linear dual-rate sampled-data system. The state variables of the continuous-time plant are sampled by two types of sensors. The ratio of two sampling rates is assumed to be a rational number. Depending on whether the sampled-data of state variables at two sampling rates is available simultaneously or separately, a periodic switched controller is constructed. Applying an input delay approach, the closed-loop system is modeled as a switched system with subsystems having different input delays. Some delay-dependent criteria for the performance of the switched system and the existence of the switched controller are derived by employing a Lyapunov-Krasovskii functional that includes information about two sampling periods. The dual-rate sampled-data control of a vehicle dynamic system is given to show that the proposed method is effective and it can achieve a better control performance than the single-rate design method.

Description: The profile recovery is an important work in X-ray pulsar-based navigation. It is a key step for the analysis on the pulsar signal’s characteristic and the computing of time of arrival (TOA). This paper makes an argument for an algorithm based on the tracking-differentiator (TD) to recover the profile from the low Signal-to-Noise Ratio (SNR) signals. In the method, a TD filter with cascade structure is designed which has very low phase delay and amplitude distortion. In the simulation experiment, two typical pulsars (PSR B0531+21 and PSR B1937+21) are used to verify the algorithm’s performance. The simulation results show that the method satisfies the application requirements in the aspects of SNR and profile fidelity. By processing the data collected by the Rossi X-Ray Timing Explorer (RXTE) satellite in space, similar results can also be achieved.

Description: Improving the ability to track abruptly changing states and resolving the degeneracy are two difficult problems to particle filter applied to fault prognosis. In this paper, a novel strong tracking fault prognosis algorithm is proposed to settle the above problems. In the proposed algorithm, the artificial immunity algorithm is first introduced to resolve the degeneracy problem, and then the strong tracking filter is introduced to enhance the ability to track abruptly changing states. The particles are updated by strong tracking filter, and better particles are selected by utilizing the artificial immune algorithm to estimate states. As a result, the degeneracy problem is resolved and the accuracy of the proposed fault prognosis algorithm is improved accordingly. The feasibility and validity of the proposed algorithm are demonstrated by the simulation results of the standard validation model and the DTS200 system.

Description: Study on the vulnerability and robustness of urban public transit networks (PTNs) has great implications for PTNs planning and emergency management, particularly considering passengers’ dynamic behaviors. We made a complex weighted network analysis based on passenger flow for Beijing’s bus stop network and multimodal transit network coupled with bus and urban rail systems. The analysis shows that there are small-world or scale-free properties in these two networks, which make them display different robustness under link or node failures. With consideration of the dynamic flow redistribution, we propose a model based on coupled map lattices to analyze the cascading failures of these two weighted networks. We find that the dynamic flow redistribution can significantly improve the tolerance of small-world or scale-free PTN against random faults. Because of the coupling of bus and rail systems, the multimodal network with scale-free topology and flow distribution structures displays an increasing tolerance even against intentional attack; however, its cascade is also much more intense once the failure is triggered. We find some thresholds of topological and flow coupling strength in the spreading process, which can be exploited to develop strategies to control cascade failures.

Description: This paper investigates the stochastic finite-time stabilization and ℋ∞ control problem for one family of linear discrete-time systems over networks with packet loss, parametric uncertainties, and time-varying norm-bounded disturbance. Firstly, the dynamic model description studied is given, which, if the packet dropout is assumed to be a discrete-time homogenous Markov process, the class of discrete-time linear systems with packet loss can be regarded as Markovian jump systems. Based on Lyapunov function approach, sufficient conditions are established for the resulting closed-loop discrete-time system with Markovian jumps to be stochastic ℋ∞ finite-time boundedness and then state feedback controllers are designed to guarantee stochastic ℋ∞ finite-time stabilization of the class of stochastic systems. The stochastic ℋ∞ finite-time boundedness criteria can be tackled in the form of linear matrix inequalities with a fixed parameter. As an auxiliary result, we also give sufficient conditions on the robust stochastic stabilization of the class of linear systems with packet loss. Finally, simulation examples are presented to illustrate the validity of the developed scheme.