GAMMA: Revisiting Template-based Automated Program Repair via Mask Prediction

Automated program repair (APR) aims to fix software bugs without human intervention and template-based APR has been widely investigated with promising results. However, it is challenging for template-based APR to select the appropriate donor code, which is an important repair ingredient for generating candidate patches. Inappropriate donor code may cause plausible but incorrect patch generation even with correct fix patterns, limiting the repair performance. In this paper, we aim to revisit template-based APR, and propose GAMMA, to directly leverage large pre-trained language models for donor code generation. Our main insight is that instead of retrieving donor code in the local buggy file, we can directly predict the correct code tokens based on the context code snippets and repair patterns by a cloze task. Specifically, (1) GAMMA revises a variety of fix templates from state-of-the-art template-based APR techniques (i.e., TBar) and transforms them into mask patterns. (2) GAMMA adopts a pre-trained language model to predict the correct code for masked code as a fill-in-the-blank task. The experimental results demonstrate that GAMMA correctly repairs 82 bugs on Defects4J-v1.2, which achieves 20.59\% (14 bugs) and 26.15\% (17 bugs) improvement over the previous state-of-the-art template-based approach TBar and learning-based one Recoder. Furthermore, GAMMA repairs 45 bugs and 22 bugs from the additional Defects4J-v2.0 and QuixBugs, indicating the generalizability of GAMMA in addressing the dataset overfitting issue. We also prove that adopting other pre-trained language models can provide substantial advancement, e.g., CodeBERT-based and ChatGPT-based GAMMA is able to fix 80 and 67 bugs on Defects4J-v1.2, indicating the scalability of GAMMA. Overall, our study highlights the promising future of adopting pre-trained models to generate correct patches on top of fix patterns.Comment: Accepted to 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023

Study on multivariate regression model of indoor and outdoor particulate pollution in severe cold area of China

At present, the widespread existence of haze phenomenon has a serious impact on indoor air quality. Indoor particulate pollution has been paid more and more attention by the society. However, the correlation and diffusion mechanism of indoor and outdoor particulate matter are still controversial. In order to explore the correlation between indoor and outdoor particulate matter of different building types in heating season and non-heating season, the indoor and outdoor particulate concentrations and meteorological parameters of 110 stations in severe cold area of China were monitored by experiments. The analysis shows that indoor and outdoor temperature, humidity, air velocity, wind direction and atmospheric pressure are the main factors affecting indoor and outdoor particulate concentration. And based on these factors, it can model the indoor predicted particulate concentrations by multivariate regression. It also shows a significant difference in the relationship between the concentration of particulate matter and factors of indoor and outdoor particulate matter. Therefore, this study provides a good premise for exploring the health risks and control measures of particulate matter

A Critical Review of Large Language Model on Software Engineering: An Example from ChatGPT and Automated Program Repair

Large Language Models (LLMs) have been gaining increasing attention and demonstrated promising performance across a variety of Software Engineering (SE) tasks, such as Automated Program Repair (APR), code summarization, and code completion. For example, ChatGPT, the latest black-box LLM, has been investigated by numerous recent research studies and has shown impressive performance in various tasks. However, there exists a potential risk of data leakage since these LLMs are usually close-sourced with unknown specific training details, e.g., pre-training datasets. In this paper, we seek to review the bug-fixing capabilities of ChatGPT on a clean APR benchmark with different research objectives. We first introduce {\benchmark}, a new benchmark with buggy and the corresponding fixed programs from competitive programming problems starting from 2023, after the training cutoff point of ChatGPT. The results on {\benchmark} show that ChatGPT is able to fix 109 out of 151 buggy programs using the basic prompt within 35 independent rounds, outperforming state-of-the-art LLMs CodeT5 and PLBART by 27.5\% and 62.4\% prediction accuracy. We also investigate the impact of three types of prompts, i.e., problem description, error feedback, and bug localization, leading to additional 34 fixed bugs. Besides, we provide additional discussion from the interactive nature of ChatGPT to illustrate the capacity of a dialog-based repair workflow with 9 additional fixed bugs. Inspired by the findings, we further pinpoint various challenges and opportunities for advanced SE study equipped with such LLMs (e.g.,~ChatGPT) in the near future. More importantly, our work calls for more research on the reevaluation of the achievements obtained by existing black-box LLMs across various SE tasks, not limited to ChatGPT on APR

Determination of dezocine in rabbit plasma by liquid chromatography-mass spectrometry and its application

A sensitive and selective liquid chromatography-mass spectrometry (LC–MS) method for determination of dezocine in rabbit plasma was developed and validated. After addition of diazepam as internal standard (IS), liquid–liquid extraction (LLE) was used for sample preparation, and chromatography involved Agilent SB-C18 column (2.1 mmx50 mm, 3.5 um) using 0.1 % formic acid in water and acetonitrile as a mobile phase with gradient elution. Detection involved positive ion mode electrospray ionization (ESI), and selective ion monitoring (SIM) mode was used for quantification of target fragment ions m/z 245.8 for dezocine and m/z 284.8 for diazepam (internal standard, IS). The assay was linear over the range of 5–500 ng/mL for dezocine, with a lower limit of quantitation (LLOQ) of 5 ng/mL for dezocine. Intra- and inter-day precisions were less than 13 % and the accuracies were in the range of 93.1-105.2 % for dezocine. This developed method was successfully applied for the determination of dezocine in rabbit plasma for pharmacokinetic study.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Curcumin suppresses gastric tumor cell growth via ROS-mediated DNA polymerase γ depletion disrupting cellular bioenergetics

Abstract Background Curcumin, as a pro-apoptotic agent, is extensively studied to inhibit tumor cell growth of various tumor types. Previous work has demonstrated that curcumin inhibits cancer cell growth by targeting multiple signaling transduction and cellular processes. However, the role of curcumin in regulating cellular bioenergetic processes remains largely unknown. Methods Western blotting and qRT-PCR were performed to analyze the protein and mRNA level of indicated molecules, respectively. RTCA, CCK-8 assay, nude mice xenograft assay, and in vivo bioluminescence imaging were used to visualize the effects of curcmin on gastric cancer cell growth in vitro and in vivo. Seahorse bioenergetics analyzer was used to investigate the alteration of oxygen consumption and aerobic glycolysis rate. Results Curcumin significantly inhibited gastric tumor cell growth, proliferation and colony formation. We further investigated the role of curcumin in regulating cellular redox homeostasis and demonstrated that curcumin initiated severe cellular apoptosis via disrupting mitochondrial homeostasis, thereby enhancing cellular oxidative stress in gastric cancer cells. Furthermore, curcumin dramatically decreased mtDNA content and DNA polymerase γ (POLG) which contributed to reduced mitochondrial oxygen consumption and aerobic glycolysis. We found that curcumin induced POLG depletion via ROS generation, and POLG knockdown also reduced oxidative phosphorylation (OXPHOS) activity and cellular glycolytic rate which was partially rescued by ROS scavenger NAC, indiating POLG plays an important role in the treatment of gastric cancer. Data in the nude mice model verified that curcumin treatment significantly attenuated tumor growth in vivo. Finally, POLG was up-regulated in human gastric cancer tissues and primary gastric cancer cell growth was notably suppressed due to POLG deficiency. Conclusions Together, our data suggest a novel mechanism by which curcumin inhibited gastric tumor growth through excessive ROS generation, resulting in depletion of POLG and mtDNA, and the subsequent disruption of cellular bioenergetics

SRSF3 and HNRNPH1 Regulate Radiation-Induced Alternative Splicing of Protein Arginine Methyltransferase 5 in Hepatocellular Carcinoma

Protein arginine methyltransferase 5 (PRMT5) is an epigenetic regulator which has been proven to be a potential target for cancer therapy. We observed that PRMT5 underwent alternative splicing (AS) and generated a spliced isoform PRMT5-ISO5 in hepatocellular carcinoma (HCC) patients after radiotherapy. However, the regulatory mechanism and the clinical implications of IR-induced PRMT5 AS are unclear. This work revealed that serine and arginine rich splicing factor 3 (SRSF3) silencing increased PRMT5-ISO5 level, whereas heterogeneous nuclear ribonucleoprotein H 1 (HNRNPH1) silencing reduced it. Then, we found that SRSF3 and HNRNPH1 competitively combined with PRMT5 pre-mRNA located at the region around the 3′- splicing site on intron 2 and the alternative 3′- splicing site on exon 4. IR-induced SRSF3 downregulation led to an elevated level of PRMT5-ISO5, and exogenous expression of PRMT5-ISO5 enhanced cell radiosensitivity. Finally, we confirmed in vivo that IR induced the increased level of PRMT5-ISO5 which in turn enhanced tumor killing and regression, and liver-specific Prmt5 depletion reduced hepatic steatosis and delayed tumor progression of spontaneous HCC. In conclusion, our data uncover the competitive antagonistic interaction of SRSF3 and HNRNPH1 in regulating PRMT5 splicing induced by IR, providing potentially effective radiotherapy by modulating PRMT5 splicing against HCC

Long-term efficacy and stability of miniscrew-assisted rapid palatal expansion in mid to late adolescents and adults: a systematic review and meta-analysis

Abstract Background The purpose of this study is to investigate the long-term efficacy and stability of Miniscrew-assisted Rapid Palatal Expansion (MARPE), including its primary outcomes, namely the nasomaxillary complex transverse skeletal and dental expansion, and related secondary outcomes. Methods Electronic databases and manual literature searches, up to October 31, 2022, were performed. The eligibility criteria were the following: studies on patients with transverse maxillary deficiency treated with MARPE in adults and adolescents over 13.5 years of age. Results Ultimately, twelve articles were included in the analysis, one prospective and eleven retrospective observational studies. Five studies showed a moderate risk of bias, while the remaining seven studies were at a serious risk of bias. The GRADE quality of evidence was very low. MARPE is an effective treatment modality for transverse maxillary deficiency (mean success rate: 93.87%). Patients showed increased mean in the skeletal and dental transverse expansion. The basal bone composition, mean alveolar bone and mean dental expansion accounted for 48.85, 7.52, and 43.63% of the total expansion, respectively. There was a certain degree of skeletal and dental relapse over time. MARPE could also cause dental, alveolar, and periodontal side effects, and have an impact on other craniofacial bones, upper airway, and facial soft tissue. Conclusions MARPE is an effective treatment for transverse maxillary deficiency, with a high success rate and a certain degree of skeletal and dental relapse over time

Study on microwave sterilization technology of humidifier in central air conditioning system

© 2019 The issue of fungal microbial contamination in central air conditioning systems is one of the main problems of biological pollution in building environment. In this study, through the basic experimental study of microwave sterilization under ideal conditions, considering the sterilization effect and energy consumption, the preliminary reference range of microwave sterilization effective temperature is 50°C–59 °C. Through the research of microwave sterilization experimental platform of humidifier in central air conditioning system, it is found that microwave sterilization has a slight influence on the air supply parameters of air conditioning system, and it can be considered under the operating conditions of air conditioning system with low accuracy of air supply parameters. The microwave radiation power of 1000 W and 900 W can quickly reach the effective sterilization temperature in 5 min, and the sterilization rate can reach 100%. The heating effect of the shielded parts is also very good. Considering the sterilization effect and energy saving, the microwave power of humidifier in central air conditioning system is ideal at 900 W for 5 min. Finally, the CST (a 3D electromagnetic field simulator) software was used to simulate and verify the power absorbed by the components, and the uniformity of microwave sterilization was also forecasted