MMF3: Neural Code Summarization Based on Multi-Modal Fine-Grained Feature Fusion

Background: Code summarization automatically generates the corresponding natural language descriptions according to the input code. Comprehensiveness of code representation is critical to code summarization task. However, most existing approaches typically use coarse-grained fusion methods to integrate multi-modal features. They generally represent different modalities of a piece of code, such as an Abstract Syntax Tree (AST) and a token sequence, as two embeddings and then fuse the two ones at the AST/code levels. Such a coarse integration makes it difficult to learn the correlations between fine-grained code elements across modalities effectively. Aims: This study intends to improve the model's prediction performance for high-quality code summarization by accurately aligning and fully fusing semantic and syntactic structure information of source code at node/token levels. Method: This paper proposes a Multi-Modal Fine-grained Feature Fusion approach (MMF3) for neural code summarization. We introduce a novel fine-grained fusion method, which allows fine-grained fusion of multiple code modalities at the token and node levels. Specifically, we use this method to fuse information from both token and AST modalities and apply the fused features to code summarization. Results: We conduct experiments on one Java and one Python datasets, and evaluate generated summaries using four metrics. The results show that: 1) the performance of our model outperforms the current state-of-the-art models, and 2) the ablation experiments show that our proposed fine-grained fusion method can effectively improve the accuracy of generated summaries. Conclusion: MMF3 can mine the relationships between crossmodal elements and perform accurate fine-grained element-level alignment fusion accordingly. As a result, more clues can be provided to improve the accuracy of the generated code summaries.Comment: 12 pages, 5 figure

ERK5 Contributes to VEGF Alteration in Diabetic Retinopathy

Diabetic retinopathy is one of the most common causes of blindness in North America. Several signaling mechanisms are activated secondary to hyperglycemia in diabetes, leading to activation of vasoactive factors. We investigated a novel pathway, namely extracellular signal regulated kinase 5 (ERK5) mediated signaling, in modulating glucose-induced vascular endothelial growth factor (VEGF) expression. Human microvascular endothelial cells (HMVEC) were exposed to glucose. In parallel, retinal tissues from streptozotocin-induced diabetic rats were examined after 4 months of follow-up. In HMVECs, glucose caused initial activation followed by deactivation of ERK5 and its downstream mediators myocyte enhancing factor 2C (MEF2C) and Kruppel-like factor 2 (KLF2) mRNA expression. ERK5 inactivation further led to augmented VEGF mRNA expression. Furthermore, siRNA mediated ERK5 gene knockdown suppressed MEF2C and KLF2 expression and increased VEGF expression and angiogenesis. On the other hand, constitutively active MEK5, an activator of ERK5, increased ERK5 activation and ERK5 and KLF2 mRNA expression and attenuated basal- and glucose-induced VEGF mRNA expression. In the retina of diabetic rats, depletion of ERK5, KLF2 and upregulation of VEGF mRNA were demonstrated. These results indicated that ERK5 depletion contributes to glucose induced increased VEGF production and angiogenesis. Hence, ERK5 may be a putative therapeutic target to modulate VEGF expression in diabetic retinopathy

INVESTIGATION ON THE CURRENT SITUATION AND COUNTERMEASURES OF EXTRACURRICULAR READING FOR PRIMARY SCHOOL STUDENTS: A CASE STUDY OF ZHEJIANG, CHINA

Based on a survey of 697 students in primary schools of Hangzhou, Ningbo, and Jiaxing in Zhejiang Province, this paper found that: (1) 25% of parents support their children to read reference books and regular parent-child reading, but most of the parents are afraid it may negatively influence school curriculum so they limit or against extracurricular reading and do not carry out the parent-child reading; only 27% of teachers often assign extracurricular reading tasks, most rarely or never, parents and schools currently pay little attention to extracurricular reading. (2) Eighty one percent of children spent 2 hours or more on homework or reviewing lessons every day, 88% of them watched about 1 hour of TV every day, and 68% of them played video games for about 1 hour. Except eating, sleeping and commuting, they have an average of 4-5 hours of free time outside school, so more than 50% of primary school students spend less than 0.5 hour reading Chinese books every day. (3) Nearly 80% of children read 2-5 Chinese books every month and spend around ￥500 on books every year; in addition, more than 60% of the respondents read paper books, and the reading of extracurricular English books is close to zero, which caused their limited reading volume, narrow scope of knowledge, restricted international vision, and inadequate reading habits. The situation extracurricular reading is not ideal, which may seriously affect the future academic and career development. To improve the unfavorable situation, this paper put forward the following suggestions: (1) all levels of government should allocate fund to establish and improve bookshelves in school classroom and community library, promote "home - school - community cooperation reading plan", let the children at school can have more 0.5-1 hours of reading at noon, and can approach in the community library for reading on weekend and holidays; (2) distribute free books to low-income families and advocate encouraging parents to spend half an hour reading with their children; (3) the school attaches great importance to the extracurricular reading education, organize pupils in class after school every afternoon 1 hour or so of intensive reading, storytelling and drama class PK activities such as English, both can effectively improve the student's reading interest, also solved the question which is many parents unable to pick up their kids during work at 3:30 p.m.; (4) promote digital reading, reduce the cost of reading, and correctly understand the impact of digital reading on eyesight.  Article visualizations

A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices

Radio frequency fingerprint (RFF) identification is a potentially effective technique to address the authentication security of Internet of Things (IoT) devices. Since the complex working environment and limited resources of IoT devices, noise is non-negligible in RFF identification of IoT devices. It is a challenge to suppress the noise without damaging the RFF information. In this paper, we propose a robust RFF identification scheme, which consists of a frequency point selection (FPS) based denoising algorithm, and a convolutional neural network (CNN) classifier. The FPS algorithm performs denoising by filtering out all the frequency components that are independent of the RFF. The CNN is designed with a dynamically decreasing learning rate to accelerate learning and obtain optimal identification performance. Experiments were conducted with 54 ZigBee devices to evaluate the performance of the proposed scheme under three different RFF identification scenarios. The results show that the FPS algorithm brings the highest accuracy improvement of about 25% when the training signal-to-noise ratio (SNR) is hybrid and the test SNR is 0 dB

The role of disturbed small-world networks in patients with white matter lesions and cognitive impairment revealed by resting state function magnetic resonance images (rs-fMRI)

Background: Leukoaraiosis is characterized by white matter lesions (WMLs) on magnetic resonance imaging (MRI) and is associated with cognitive impairment. The small-world network is viewed as the optimal brain network with maximal efficiency in information processing. Patients with cognitive impairment are thought to have disrupted small-world networks. In this study, we compared the small-world network attributes between controls (study participants without memory complaints) and patients with WMLs with cognitive impairment. Material/Methods: All study participants were prescreened using MRI and neuropsychological tests. Patients with WMLs were further divided into 2 groups according to the result of Montreal Cognitive Assessment (MoCA), i.e., WMLs with non-dementia vascular cognitive impairment (WMLs-VCIND) and WMLs with vascular dementia (WMLs-VaD). Resting-state functional MRI data were collected and applied with graph theoretical analysis to compare small-world properties between the 3 groups. Results: We found that the overall functional connectivity strength was lowest in the WMLs-VaD patients but highest in the normal control study participants. Patients in both the WMLs-VCIND and the WMLs-VaD groups had decreased small-world properties compared with the group of normal control study participants. Moreover, the small-world properties significantly correlated with MoCA scores. Conclusions: These findings suggest potential constructive reorganization of brain networks secondary to WMLs, and provides novel insights into the role of small-world properties in cognitive dysfunction in WMLs