Improving Program Comprehension Using Neural Machine Translation

Program comprehension is the task of understanding software projects. One effective way to help programmers comprehend code is documentation. However, manual documentation costs a significant amount of time and effort. Therefore, software documents are often incomplete and out of date. Automatic documentation generation is to address the problem of lack of documentation and to improve the quality of documentation.In this dissertation, I summarize my work on improving program comprehension using neural machine translation to generate documents. First, I conduct two user studies about programmers' behavior when they comprehend code before and after they make changes. Specifically, I study how programmers do change impact analysis, which is the task of finding source code that is affected by a change. The studies show that programmers do more change impact analysis before they make changes than after the changes. When programmers need to understand a change in a software repository, a summary of the change is an important component of the comprehension process. My first project of generating documents is to generate short summaries of software changes using neural machine translation. Neural machine translation (NMT) is a type of neural network for translating natural languages. This project demonstrates that NMT can also be used in translating from diff (results of text differencing techniques) to English text. My second project focuses on topic labeling to generate descriptions of key functionalities in software projects. Topic labeling is the task of labeling hidden topics in topic models, which are often used in program comprehension tools and research to find key functionalities. In these tools and research, key functionalities in software projects are assumed to be the hidden topics in topic models. However, the topics are represented by lists of words with probabilities, which are difficult to interpret. Labeling topics is often a manual task. My project uses NMT to translate topics represented by lists of words to English text. The results show that NMT-generated descriptions are more helpful for programmers to understand software projects than the lists of words.</p

Strain-deformation Reconstruction of Carbon Fiber Composite Laminates Based on BP Neural Network

The Carbon Fiber Reinforced Polymer (CFRP) laminate structural components used in the aerospace and military domains require high precision and strong stability. Usually the deformation of these structural components is difficult to be measured directly during operation, but the deformation of the CFRP laminate structure can be reconstructed with strain information. The CFRP laminate structure can be designed to adapt to the requirements of different applications through layering of variable thickness. In this paper, aiming at the discontinuous stiffness and strength of the variable laminations within the CFRP laminate structure, the BP neural network is proposed to be applied to the deformation reconstruction of CFRP laminates. With strain as input and deformation as output, based on a large amount of experimental data, the BP neural network model between strain and deformation is obtained through training. In this paper, CFRP test piecs with equal thickness and variable thickness were designed, and the corresponding strain-deformation reconstruction experimental system was constructed. The strain on the surface of CFRP test piece was measured by the fiber grating sensor, and the deformation of the test piece was measured by the laser displacement sensor. The comparative analysis between the predicted deflection obtained by neural network reconstruction and the actual measured deflection shows that BP neural network can reconstruct the structural deformation of CFRP laminates within certain error range.</div

Data_Sheet_1_Variation of Neonatal Outcomes and Care Practices for Preterm Infants <34 Weeks' Gestation in Different Regions of China: A Cohort Study.docx

Background: To compare outcomes and care practices of preterm infants born at Methods: This cohort study enrolled all infants born at Results: A total of 27,532 infants at Conclusions: We identified marked disparities in outcomes and clinical care practices of preterm infants born at <34 weeks' gestation in different regions of China. Targeted quality improvement efforts are needed to improve the outcomes of premature infants in different regions of China.</p

Table_1_A bibliometric analysis of metastatic breast cancer: two-decade report (2002-2022).docx

BackgroundMBC is a lethal form of breast cancer that arises when cancer cells invade other organs or tissues. The treatment of MBC needs personalized approaches based on the tumor and patient characteristics. The purpose of this paper is to analyze MBC studies from 2002 to 2022 using bibliometrics and to investigate its current situation, main contributors, core journals, highly cited papers, and topic evolution.Materials and methodsWe retrieved data from Web of Science Core Collection (WOSCC). Bibliometric analysis of the included literatures mainly used the following tools: the function of “analyze results” and “citation report” in WoS, Microsoft excel 2021, CiteSpace v.6.1. R6, VOSviewer v.1.6.18, BICOMB v.2.04 and gCLUTO v.1.0.ResultsWe found 12,653 articles on MBC research published in 1, 802 journals by 69, 753 authors from 118 countries. The annual output and citation of MBC articles showed a rising trend over time. The United States was the most influential country in MBC research. The most cited journal in this field was The Journal of Clinical Oncology. And the most cited article was by Slamon DJ. The co-word analysis of keywords divides MBC into six research clusters. The hormone receptor-positive MBC and liquid biopsy of MBC are the frontiers research trends. “CDK4/6 inhibitor” had the highest burst strength.ConclusionOur bibliometric analysis offers a comprehensive overview of MBC research in the past two decades. It shows the current situation, main contributors, core journals, highly cited papers, and topic evolution of this field. Our study can assist researchers and practitioners to comprehend the development and trends of MBC research and to discover potential directions for future research.</p

Image_1_A bibliometric analysis of metastatic breast cancer: two-decade report (2002-2022).pdf

BackgroundMBC is a lethal form of breast cancer that arises when cancer cells invade other organs or tissues. The treatment of MBC needs personalized approaches based on the tumor and patient characteristics. The purpose of this paper is to analyze MBC studies from 2002 to 2022 using bibliometrics and to investigate its current situation, main contributors, core journals, highly cited papers, and topic evolution.Materials and methodsWe retrieved data from Web of Science Core Collection (WOSCC). Bibliometric analysis of the included literatures mainly used the following tools: the function of “analyze results” and “citation report” in WoS, Microsoft excel 2021, CiteSpace v.6.1. R6, VOSviewer v.1.6.18, BICOMB v.2.04 and gCLUTO v.1.0.ResultsWe found 12,653 articles on MBC research published in 1, 802 journals by 69, 753 authors from 118 countries. The annual output and citation of MBC articles showed a rising trend over time. The United States was the most influential country in MBC research. The most cited journal in this field was The Journal of Clinical Oncology. And the most cited article was by Slamon DJ. The co-word analysis of keywords divides MBC into six research clusters. The hormone receptor-positive MBC and liquid biopsy of MBC are the frontiers research trends. “CDK4/6 inhibitor” had the highest burst strength.ConclusionOur bibliometric analysis offers a comprehensive overview of MBC research in the past two decades. It shows the current situation, main contributors, core journals, highly cited papers, and topic evolution of this field. Our study can assist researchers and practitioners to comprehend the development and trends of MBC research and to discover potential directions for future research.</p

Image_2_A bibliometric analysis of metastatic breast cancer: two-decade report (2002-2022).pdf

BackgroundMBC is a lethal form of breast cancer that arises when cancer cells invade other organs or tissues. The treatment of MBC needs personalized approaches based on the tumor and patient characteristics. The purpose of this paper is to analyze MBC studies from 2002 to 2022 using bibliometrics and to investigate its current situation, main contributors, core journals, highly cited papers, and topic evolution.Materials and methodsWe retrieved data from Web of Science Core Collection (WOSCC). Bibliometric analysis of the included literatures mainly used the following tools: the function of “analyze results” and “citation report” in WoS, Microsoft excel 2021, CiteSpace v.6.1. R6, VOSviewer v.1.6.18, BICOMB v.2.04 and gCLUTO v.1.0.ResultsWe found 12,653 articles on MBC research published in 1, 802 journals by 69, 753 authors from 118 countries. The annual output and citation of MBC articles showed a rising trend over time. The United States was the most influential country in MBC research. The most cited journal in this field was The Journal of Clinical Oncology. And the most cited article was by Slamon DJ. The co-word analysis of keywords divides MBC into six research clusters. The hormone receptor-positive MBC and liquid biopsy of MBC are the frontiers research trends. “CDK4/6 inhibitor” had the highest burst strength.ConclusionOur bibliometric analysis offers a comprehensive overview of MBC research in the past two decades. It shows the current situation, main contributors, core journals, highly cited papers, and topic evolution of this field. Our study can assist researchers and practitioners to comprehend the development and trends of MBC research and to discover potential directions for future research.</p

DataSheet_1_A bibliometric analysis of metastatic breast cancer: two-decade report (2002-2022).zip

BackgroundMBC is a lethal form of breast cancer that arises when cancer cells invade other organs or tissues. The treatment of MBC needs personalized approaches based on the tumor and patient characteristics. The purpose of this paper is to analyze MBC studies from 2002 to 2022 using bibliometrics and to investigate its current situation, main contributors, core journals, highly cited papers, and topic evolution.Materials and methodsWe retrieved data from Web of Science Core Collection (WOSCC). Bibliometric analysis of the included literatures mainly used the following tools: the function of “analyze results” and “citation report” in WoS, Microsoft excel 2021, CiteSpace v.6.1. R6, VOSviewer v.1.6.18, BICOMB v.2.04 and gCLUTO v.1.0.ResultsWe found 12,653 articles on MBC research published in 1, 802 journals by 69, 753 authors from 118 countries. The annual output and citation of MBC articles showed a rising trend over time. The United States was the most influential country in MBC research. The most cited journal in this field was The Journal of Clinical Oncology. And the most cited article was by Slamon DJ. The co-word analysis of keywords divides MBC into six research clusters. The hormone receptor-positive MBC and liquid biopsy of MBC are the frontiers research trends. “CDK4/6 inhibitor” had the highest burst strength.ConclusionOur bibliometric analysis offers a comprehensive overview of MBC research in the past two decades. It shows the current situation, main contributors, core journals, highly cited papers, and topic evolution of this field. Our study can assist researchers and practitioners to comprehend the development and trends of MBC research and to discover potential directions for future research.</p

Supplementary document for Magnetically tunable diffractive optical elements based on ion irradiated ultrathin ferromagnetic stacks - 6357390.pdf

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DSDP: A Blind Docking Strategy Accelerated by GPUs

Virtual screening, including molecular docking, plays an essential role in drug discovery. Many traditional and machine-learning-based methods are available to fulfill the docking task. However, the traditional docking methods are normally extensively time-consuming, and their performance in blind docking remains to be improved. Although the runtime of docking based on machine learning is significantly decreased, their accuracy is still limited. In this study, we take advantage of both traditional and machine-learning-based methods and present a method, deep site and docking pose (DSDP), to improve the performance of blind docking. For traditional blind docking, the entire protein is covered by a cube, and the initial positions of ligands are randomly generated in this cube. In contrast, DSDP can predict the binding site of proteins and provide an accurate searching shape and initial positions for further conformational sampling. The sampling task of DSDP makes use of the score function and a similar but modified searching strategy of AutoDock Vina, accelerated by implementation in GPUs. We systematically compare its performance in redocking, blind docking, and virtual screening tasks with state-of-the-art methods, including AutoDock Vina, GNINA, QuickVina, SMINA, and DiffDock. In the blind docking task, DSDP reaches a 29.8% top-1 success rate (root-mean-squared deviation < 2 Å) on an unbiased and challenging test dataset with 1.2 s wall-clock computational time per system. Its performances on the DUD-E dataset and the time-split PDBBind dataset used in EquiBind, TANKBind, and DiffDock are also evaluated, presenting a 57.2 and 41.8% top-1 success rate with 0.8 and 1.0 s per system, respectively

DataSheet_3_The prognostic significance of further axillary dissection for sentinel lymph node micrometastases in female breast cancer: A competing risk analysis using the SEER database.xls

BackgroundSentinel lymph node (SLN) biopsy has been widely recognized as an excellent surgical and staging procedure for early-stage breast cancer, and its development has greatly improved the detection of micrometastases. However, the axillary treatment of micrometastasis has been the subject of much debate.MethodsWe identified 427,131 women diagnosed with breast cancer from 2010 to 2018 in the Surveillance, Epidemiology, and End Results (SEER) database. Patients whose nodal status was micrometastases (pTxN1miM0) were classified into two groups: the SLNB only group and SLNB with complete ALND group, and we used these classifications to carry out propensity-score matching (PSM) analysis. The primary and secondary endpoints were OS and BCSS, respectively. We then implemented the Kaplan-Meier method and Cox proportional hazard model and used Fine and Gray competitive risk regression to identify factors associated with the risk of all-cause mortality.ResultsAfter the PSM, 1,833 pairs were included in total. The SLNB with complete ALND showed no significant difference in OS (HR=1.04, 95% CI: 0.84-1.28, P=0.73) or BCSS (HR= 1.03, 95% CI: 0.79-1.35, P=0.82) compared to the SLNB only group, and axillary treatment was not associated with breast cancer-specific death (BCSD) (HR=1.13, 95% CI: 0.86-1.48, P=0.400) or other cause-specific death (OCSD) (HR=0.98, 95% CI:0.70-1.38, P=0.920). There was no statistically significant difference in the cumulative incidence of BCSD (Grey’s test, P=0.819) or OCSD (Grey’s test, P=0.788) for between the two groups either. For different molecular subtypes, patients in the SLNB only group showed no statistically significant differences from those in the SLNB with complete ALND group with Luminal A (HR=1.00, 95% CI:0.76-1.32, P=0.98) or Luminal B (HR=0.82, 95% CI:0.42-1.62, P=0.55) but similar OS to HER2-enriched (HR=1.58, 95% CI:0.81-3.07, P=0.19) or triple negative breast cancers (HR=1.18, 95% CI:0.76-1.81, P=0.46).ConclusionsOur results suggest that in early breast cancer patients with micrometastasis, complete ALND does not seem to be required and that SLNB suffices to control locoregional and distant disease, with no significant adverse effects on survival compared to complete ALND.</p