Improving automatic source code summarization via deep reinforcement learning

© 2018 Association for Computing Machinery. Code summarization provides a high level natural language description of the function performed by code, as it can benefit the software maintenance, code categorization and retrieval. To the best of our knowledge, most state-of-the-art approaches follow an encoder-decoder framework which encodes the code into a hidden space and then decode it into natural language space, suffering from two major drawbacks: a) Their encoders only consider the sequential content of code, ignoring the tree structure which is also critical for the task of code summarization; b) Their decoders are typically trained to predict the next word by maximizing the likelihood of next ground-truth word with previous ground-truth word given. However, it is expected to generate the entire sequence from scratch at test time. This discrepancy can cause an exposure bias issue, making the learnt decoder suboptimal. In this paper, we incorporate an abstract syntax tree structure as well as sequential content of code snippets into a deep reinforcement learning framework (i.e., actor-critic network). The actor network provides the confidence of predicting the next word according to current state. On the other hand, the critic network evaluates the reward value of all possible extensions of the current state and can provide global guidance for explorations. We employ an advantage reward composed of BLEU metric to train both networks. Comprehensive experiments on a real-world dataset show the effectiveness of our proposed model when compared with some state-of-the-art methods

Conditionally reprogrammed primary airway epithelial cells maintain morphology, lineage and disease specific functional characteristics

© 2017 The Author(s). Current limitations to primary cell expansion led us to test whether airway epithelial cells derived from healthy children and those with asthma and cystic fibrosis (CF), co-cultured with an irradiated fibroblast feeder cell in F-medium containing 10 µM ROCK inhibitor could maintain their lineage during expansion and whether this is influenced by underlying disease status. Here, we show that conditionally reprogrammed airway epithelial cells (CRAECs) can be established from both healthy and diseased phenotypes. CRAECs can be expanded, cryopreserved and maintain phenotypes over at least 5 passages. Population doublings of CRAEC cultures were significantly greater than standard cultures, but maintained their lineage characteristics. CRAECs from all phenotypes were also capable of fully differentiating at air-liquid interface (ALI) and maintained disease specific characteristics including; defective CFTR channel function cultures and the inability to repair wounds. Our findings indicate that CRAECs derived from children maintain lineage, phenotypic and importantly disease-specific functional characteristics over a specified passage range

Dynamical Analysis of a Novel Fractional-Order Chaotic System Based on Memcapacitor and Meminductor

In this paper, a chaotic circuit based on a memcapacitor and meminductor is constructed, and its dynamic equation is obtained. Then, the mathematical model is obtained by normalization, and the system is decomposed and summed by an Adomian decomposition method (ADM) algorithm. So as to study the dynamic behavior in detail, not only the equilibrium stability of the system is analyzed, but also the dynamic characteristics are analyzed by means of a Bifurcation diagram and Lyapunov exponents (Les). By analyzing the dynamic behavior of the system, some special phenomena, such as the coexistence of attractor and state transition, are found in the system. In the end, the circuit implementation of the system is implemented on a Digital Signal Processing (DSP) platform. According to the numerical simulation results of the system, it is found that the system has abundant dynamical characteristics

Molecular mechanisms of calcium inducing salt tolerance in rice : Ameliorative interaction between CBL4 and P5CR proteins

The rice plant is sensitive to soil salinity. Calcium (Ca) acts as an ameliorative agent that helps plants induce salt tolerance. This study was carried out with a comparison of the ameliorative effect of calcium on salt-stressed rice seedlings, the determination of the role of salt-responsive protein groups, and the analysis of their genetic expressions in 21-day-old rice seedlings of ten locally cultivable varieties of West Bengal. For this study, 15-day-old seedlings were treated with 200 mM of sodium chloride (NaCl) solutions along with 10 mM of calcium sulfate (CaSO4) treatment. The determination of the relationship between the salt-responsive proteins and the analysis of the gene expression of those corresponding proteins were not carried out earlier on the selected ten locally cultivable rice varieties of West Bengal. The NaCl crystals were visible on the abaxial leaf surface of salt-stressed rice seedlings. The superoxide dismutase activity was increased in rice varieties, and a similar result was also expressed with calcium treatment. The fourier transform infrared spectroscopy-attenuated total reflection spectral result gave strong evidence for the presence of several salt-tolerant proteins and their genetic expression. STRING database results have suggested that the calcium treatment, coupled with the expression of the CBL4 protein, has regulated the P5CR protein of proline biosynthesis for better salt tolerance and osmotic protection. The quantitative real-time polymerase chain reaction and SDS-PAGE gel electrophoresis analysis showed that salt-tolerant varieties, Chinsurah_nona_1, and Jarava had high calcium signaling mechanisms and osmo-protection abilities

Study on the Complex Dynamical Behavior of the Fractional-Order Hopfield Neural Network System and Its Implementation

The complex dynamics analysis of fractional-order neural networks is a cutting-edge topic in the field of neural network research. In this paper, a fractional-order Hopfield neural network (FOHNN) system is proposed, which contains four neurons. Using the Adomian decomposition method, the FOHNN system is solved. The dissipative characteristics of the system are discussed, as well as the equilibrium point is resolved. The characteristics of the dynamics through the phase diagram, the bifurcation diagram, the Lyapunov exponential spectrum, and the Lyapunov dimension of the system are investigated. The circuit of the system was also designed, based on the Multisim simulation platform, and the simulation of the circuit was realized. The simulation results show that the proposed FOHNN system exhibits many interesting phenomena, which provides more basis for the study of complex brain working patterns, and more references for the design, as well as the hardware implementation of the realized fractional-order neural network circuit