Feature analysis of multidisciplinary scientific collaboration patterns based on PNAS

The features of collaboration patterns are often considered to be different from discipline to discipline. Meanwhile, collaborating among disciplines is an obvious feature emerged in modern scientific research, which incubates several interdisciplines. The features of collaborations in and among the disciplines of biological, physical and social sciences are analyzed based on 52,803 papers published in a multidisciplinary journal PNAS during 1999 to 2013. From those data, we found similar transitivity and assortativity of collaboration patterns as well as the identical distribution type of collaborators per author and that of papers per author, namely a mixture of generalized Poisson and power-law distributions. In addition, we found that interdisciplinary research is undertaken by a considerable fraction of authors, not just those with many collaborators or those with many papers. This case study provides a window for understanding aspects of multidisciplinary and interdisciplinary collaboration patterns

Theoretical and experimental study on the dynamic characteristics of an axially moving nested clamped-hinged beam

The present paper is concerned with the transverse vibration properties of an axially moving nested clamped-hinged beam, which can be regarded as a stepped beam. The transverse vibration equation for the axially moving nested clamped-hinged beam is derived by D’Alembert’s principle. The modified Galerkin’s method, which uses the instantaneous modal function of the clamped-hinged stepped beam as a trial function, is used to solve the vibration equation. An axially moving nested clamped-hinged beam model is designed for the vibration test. The theoretical model is updated by calculating the flexural rigidity values of the first segment of the nested beam based on the measured first-order vibration frequencies, which are tested for different lengths in the main beam. The first order decay coefficients are identified by the logarithmic decrement method. Then, the functional relationship between the flexural rigidity and beam length, as well as the decay coefficient and beam length, is established using the polynomial fitting method. The calculated responses of the modified model agree well with the experimental results, which verifies the correctness of the proposed calculation model and indicates the effectiveness of the methods of model updating and damping determination. The theoretical and experimental results demonstrate that the change law of the frequency with the main beam length increasing is a low-high-low-high trend. Further investigations into the non-damping free vibration properties of the nested clamped-hinged beam during extension and retraction of the main beam are performed. It is determined that there is no obvious change of the dynamic response amplitude of the nested structure during different axial moving rates in the main beam. Furthermore, as the length of the main beam increases, the vibration displacement decreases gradually, and the total mechanical energy increases constantly; therefore, the extension movement of the main beam becomes unstable. Moreover, the numerical results indicate that the non-damping free vibration characteristics of the nested clamped-hinged beam during extension and retraction of the main beam are inversely related

Control Input Inference of Mobile Agents under Unknown Objective

Trajectory and control secrecy is an important issue in robotics security. This paper proposes a novel algorithm for the control input inference of a mobile agent without knowing its control objective. Specifically, the algorithm first estimates the target state by applying external perturbations. Then we identify the objective function based on the inverse optimal control, providing the well-posedness proof and the identifiability analysis. Next, we obtain the optimal estimate of the control horizon using binary search. Finally, the agent's control optimization problem is reconstructed and solved to predict its input. Simulation illustrates the efficiency and the performance of the algorithm

A Genetic Algorithm-based BP Neural Network Method for Operational Performance Assessment of ATC Sector

To assess operational performance of air traffic control sector, a multivariate detection index system consisting of 5 variables and 17 indicators is presented, which includes operational trafficability, operational complexity, operational safety, operational efficiency, and air traffic controller workload. An improved comprehensive evaluation method, is designed for the assessment by optimizing initial weights and thresholds of back propagation (BP) neural network using genetic algorithm. By empirical study conducted in one air traffic control sector, 400 sets of sample data are selected and divided into 350 sets for network training and 50 sets for network testing, and the architecture of genetic algorithm-based back propagation (GABP) neural network is established as a three-layer network with 17 nodes in input layer, 5 nodes in hidden layers, and 1 node in output layer. Further testing with both GABP and traditional BP neural network reveals that GABP neural network performs betterthan BP neural work in terms of mean error, mean square error and error probability, indicating that GABP neural network can assess operational performance of air traffic control sector with high accuracy and stable generalization ability. The multivariate detection index system and GABP neural network method in this paper can provide comprehensive, accurate, reliable and practical operational performance assessment of air traffic control sector, which enable the frontline of air traffic service provider to detect and evaluate operational performance of air traffic control sector in real time, and trigger an alarm when necessary.</p

Revisiting Estimation Bias in Policy Gradients for Deep Reinforcement Learning

We revisit the estimation bias in policy gradients for the discounted episodic Markov decision process (MDP) from Deep Reinforcement Learning (DRL) perspective. The objective is formulated theoretically as the expected returns discounted over the time horizon. One of the major policy gradient biases is the state distribution shift: the state distribution used to estimate the gradients differs from the theoretical formulation in that it does not take into account the discount factor. Existing discussion of the influence of this bias was limited to the tabular and softmax cases in the literature. Therefore, in this paper, we extend it to the DRL setting where the policy is parameterized and demonstrate how this bias can lead to suboptimal policies theoretically. We then discuss why the empirically inaccurate implementations with shifted state distribution can still be effective. We show that, despite such state distribution shift, the policy gradient estimation bias can be reduced in the following three ways: 1) a small learning rate; 2) an adaptive-learning-rate-based optimizer; and 3) KL regularization. Specifically, we show that a smaller learning rate, or, an adaptive learning rate, such as that used by Adam and RSMProp optimizers, makes the policy optimization robust to the bias. We further draw connections between optimizers and the optimization regularization to show that both the KL and the reverse KL regularization can significantly rectify this bias. Moreover, we provide extensive experiments on continuous control tasks to support our analysis. Our paper sheds light on how successful PG algorithms optimize policies in the DRL setting, and contributes insights into the practical issues in DRL.Comment: 12 pages, 9 figure

Clinical value of alpha-fetoprotein: alpha-fetoprotein-L3 isoform ratio and des-γ-carboxyprothrombin in early diagnosis of HBV-related hepatocellular carcinoma

Objective To evaluate the value of different combinations of alpha-fetoprotein （AFP）， alpha-fetoprotein-L3 isoform ratio （AFP-L3%） and des-γ-carboxyprothrombin （DCP） for early diagnosis of hepatitis B virus （HBV）-related hepatocellular carcinoma （HCC）. Methods A total of 167 patients were enrolled in this study， including 100 patients with HCC and 67 patients with infection-related liver cirrhosis （LC）. The levels of serum AFP， AFP-L3% and DCP were detected by chemiluminescence enzyme immunoassay. The receiver operating characteristic （ROC） curve was delineated for subsequent analysis. Results The levels of AFP， AFP-L3% and DCP in HCC patients were significantly higher than those in LC patients （all P &lt; 0.05）. There was no significant difference in AFP and AFP-L3% levels between stage 0 and stage A patients in HCC group （both P &gt; 0.05）. DCP levels in stage 0 patients were significantly lower than those in stage A patients in HCC group （P &lt; 0.05）. The sensitivity and specificity of AFP， AFP-L3% and DCP in the diagnosis of early HCC were 51.5%， 92.5%， 28.3%， and 95.5%， 60.0%， 84.7%， respectively. Analysis of the area under the ROC curve （AUC） results showed that the AUC values of AFP， AFP-L3% and DCP for the diagnosis of early HCC were 0.760， 0.619 and 0.749， respectively. The AUC value of combined detection of AFP and DCP was 0.810， which yielded the highest diagnostic efficiency. Conclusion AFP has important diagnostic value in the diagnosis of early HCC. The combination of AFP and DCP can improve the diagnostic efficiency of HBV-related early HCC

Theoretical and experimental study on the dynamic characteristics of an axially moving nested clamped-hinged beam

The present paper is concerned with the transverse vibration properties of an axially moving nested clamped-hinged beam, which can be regarded as a stepped beam. The transverse vibration equation for the axially moving nested clamped-hinged beam is derived by D’Alembert’s principle. The modified Galerkin’s method, which uses the instantaneous modal function of the clamped-hinged stepped beam as a trial function, is used to solve the vibration equation. An axially moving nested clamped-hinged beam model is designed for the vibration test. The theoretical model is updated by calculating the flexural rigidity values of the first segment of the nested beam based on the measured first-order vibration frequencies, which are tested for different lengths in the main beam. The first order decay coefficients are identified by the logarithmic decrement method. Then, the functional relationship between the flexural rigidity and beam length, as well as the decay coefficient and beam length, is established using the polynomial fitting method. The calculated responses of the modified model agree well with the experimental results, which verifies the correctness of the proposed calculation model and indicates the effectiveness of the methods of model updating and damping determination. The theoretical and experimental results demonstrate that the change law of the frequency with the main beam length increasing is a low-high-low-high trend. Further investigations into the non-damping free vibration properties of the nested clamped-hinged beam during extension and retraction of the main beam are performed. It is determined that there is no obvious change of the dynamic response amplitude of the nested structure during different axial moving rates in the main beam. Furthermore, as the length of the main beam increases, the vibration displacement decreases gradually, and the total mechanical energy increases constantly; therefore, the extension movement of the main beam becomes unstable. Moreover, the numerical results indicate that the non-damping free vibration characteristics of the nested clamped-hinged beam during extension and retraction of the main beam are inversely related

Analyses of the Global Multilocus Genotypes of the Human Pathogenic Yeast Candida tropicalis

Candida tropicalis is a globally distributed human pathogenic yeast, especially prevalent in tropical and sub-tropical regions. Over the last several decades, a large number of studies have been published on the genetic diversity and molecular epidemiology of C. tropicalis from different parts of the world. However, the global pattern of genetic variation remains largely unknown. Here we analyzed the published multilocus sequence data at six loci for 876 isolates from 16 countries representing five continents. Our results showed that 280 of the 2677 (10.5%) analyzed nucleotides were polymorphic, resulting in a mean of 82 (a range of 38–150) genotypes per locus and a total of 633 combined diploid sequence types (DSTs). Among these, 93 combined DSTs were shared by 336 strains, including 10 by strains from different continents. Analysis of Molecular Variance (AMOVA) showed that 89% of the observed genetic variations were found within regional and national populations while &lt; 10% was due to among-country separations. Pairwise geographic population analyses showed overall low but statistically significant genetic differentiation between most geographic populations, with the Singaporean and Indian populations being the most distinct from other populations. However, the Mantel test showed no significant correlation between genetic distance and geographic distance among the geographic populations. Consistent with high genetic variation within and limited variations among geographic populations, results from STRUCTURE analyses showed that the 876 isolates could be grouped into 15 genetic clusters, with each cluster having a broad geographic distribution. Together, our results suggest frequent gene flows among certain regional, national, and continental populations of C. tropicalis, resulting in abundant regional and national genetic diversities of this important human fungal pathogen