Prompt-Enhanced Software Vulnerability Detection Using ChatGPT

With the increase in software vulnerabilities that cause significant economic and social losses, automatic vulnerability detection has become essential in software development and maintenance. Recently, large language models (LLMs) like GPT have received considerable attention due to their stunning intelligence, and some studies consider using ChatGPT for vulnerability detection. However, they do not fully consider the characteristics of LLMs, since their designed questions to ChatGPT are simple without a specific prompt design tailored for vulnerability detection. This paper launches a study on the performance of software vulnerability detection using ChatGPT with different prompt designs. Firstly, we complement previous work by applying various improvements to the basic prompt. Moreover, we incorporate structural and sequential auxiliary information to improve the prompt design. Besides, we leverage ChatGPT's ability of memorizing multi-round dialogue to design suitable prompts for vulnerability detection. We conduct extensive experiments on two vulnerability datasets to demonstrate the effectiveness of prompt-enhanced vulnerability detection using ChatGPT. We also analyze the merit and demerit of using ChatGPT for vulnerability detection.Comment: 13 Pages, 4 figure

A semi-analytical method for the dynamic analysis of cylindrical shells with arbitrary boundaries

The dynamic behavior of cylindrical shells with arbitrary boundaries is studied in this paper. Love's shell theory and Hamilton's principle are employed to derive the motion equations for cylindrical shells. A semi-analytical methodology, which incorporates Durbin's inverse Laplace transform, differential quadrature method and Fourier series expansion technique, is proposed to investigate this phenomenon. The use of the differential quadrature method provides a solution in terms of the axial direction whereas the use of Durbin's numerical inversion method generates a solution in the time domain. Comparison of calculated frequency parameters to that derived from the literature illustrates the effectiveness of the method. Specifically, convergence tests indicate that the present approach has a rapid convergence, the time-history response and the Navier's solution are in great agreement. Comparisons between time-history responses derived by two shell theories show that the results fit well with each other when the thickness-radius ratios are small enough. An analysis of the influences of boundaries on the time-history response of cylindrical shells indicates that the peak displacement is closely related to the degrees of freedom of boundaries. The influences of the length-radius ratios and the thickness-radius ratios on the peak displacement are further investigated

Binding of Pseudomonas aeruginosa Apo-Bacterioferritin Associated Ferredoxin to Bacterioferritin B Promotes Heme Mediation of Electron Delivery and Mobilization of Core Mineral Iron†

The bfrB gene from Pseudomonas aeruginosa was cloned and expressed in E. coli. The resultant protein (BfrB), which assembles into a 445.3 kDa complex0020from 24 identical subunits, binds 12 molecules of heme axially coordinated by two Met residues. BfrB, isolated with 5–10 iron atoms per protein molecule, was reconstituted with ferrous ions to prepare samples with a core mineral containing 600 ± 40 ferric ions per BfrB molecule and approximately one phosphate molecule per iron atom. In the presence of sodium dithionite or in the presence of P. aeruginosa ferredoxin NADP reductase (FPR) and NADPH the heme in BfrB remains oxidized and the core iron mineral is mobilized sluggishly. In stark contrast, addition of NADPH to a solution containing BfrB, FPR and the apo-form of P. aeruginosa bacterioferritin associated ferredoxin (apo-Bfd) results in rapid reduction of the heme in BfrB and in the efficient mobilization of the core iron mineral. Results from additional experimentation indicate that Bfd must bind to BfrB to promote heme mediation of electrons from the surface to the core to support the efficient mobilization of ferrous ions from BfrB. In this context, the thus far mysterious role of heme in bacterioferritins has been brought to the front by reconstituting BfrB with its physiological partner, apo-Bfd. These findings are discussed in the context of a model for the utilization of stored iron in which the significant upregulation of the bfd gene under low-iron conditions [Ochsner, U.A., Wilderman, P.J., Vasil, A.I., and Vasil, M.L. (2002) Mol. Microbiol. 45, 1277–1287] ensures sufficient concentrations of apo-Bfd to bind BfrB and unlock the iron stored in its core. Although these findings are in contrast to previous speculations suggesting redox mediation of electron transfer by holo-Bfd, the ability of apo-Bfd to promote iron mobilization is an economical strategy used by the cell because it obviates the need to further deplete cellular iron levels to assemble iron sulfur clusters in Bfd before the iron stored in BfrB can be mobilized and utilized

Identifying microbial signatures for patients with postmenopausal osteoporosis using gut microbiota analyses and feature selection approaches

Osteoporosis (OP) is a metabolic bone disorder characterized by low bone mass and deterioration of micro-architectural bone tissue. The most common type of OP is postmenopausal osteoporosis (PMOP), with fragility fractures becoming a global burden for women. Recently, the gut microbiota has been connected to bone metabolism. The aim of this study was to characterize the gut microbiota signatures in PMOP patients and controls. Fecal samples from 21 PMOP patients and 37 controls were collected and analyzed using amplicon sequencing of the V3-V4 regions of the 16S rRNA gene. The bone mineral density (BMD) measurement and laboratory biochemical test were performed on all participants. Two feature selection algorithms, maximal information coefficient (MIC) and XGBoost, were employed to identify the PMOP-related microbial features. Results showed that the composition of gut microbiota changed in PMOP patients, and microbial abundances were more correlated with total hip BMD/T-score than lumbar spine BMD/T-score. Using the MIC and XGBoost methods, we identified a set of PMOP-related microbes; a logistic regression model revealed that two microbial markers (Fusobacteria and Lactobacillaceae) had significant abilities in disease classification between the PMOP and control groups. Taken together, the findings of this study provide new insights into the etiology of OP/PMOP, as well as modulating gut microbiota as a therapeutic target in the diseases. We also highlight the application of feature selection approaches in biological data mining and data analysis, which may improve the research in medical and life sciences

Epidemiological and virological characteristics of pandemic influenza A (H1N1) 2009 in school outbreaks in China

Background: During the 2009 pandemic influenza H1N1 (2009) virus (pH1N1) outbreak, school students were at an increased risk of infection by the pH1N1 virus. However, the estimation of the attack rate showed significant variability. Methods: Two school outbreaks were investigated in this study. A questionnaire was designed to collect information by interview. Throat samples were collected from all the subjects in this study 6 times and sero samples 3 times to confirm the infection and to determine viral shedding. Data analysis was performed using the software STATA 9.0. Findings: The attack rate of the pH1N1 outbreak was 58.3% for the primary school, and 52.9% for the middle school. The asymptomatic infection rates of the two schools were 35.8% and 37.6% respectively. Peak virus shedding occurred on the day of ARI symptoms onset, followed by a steady decrease over subsequent days (p = 0.026). No difference was found either in viral shedding or HI titer between the symptomatic and the asymptomatic infectious groups. Conclusions: School children were found to be at a high risk of infection by the novel virus. This may be because of a heightened risk of transmission owing to increased mixing at boarding school, or a lack of immunity owing to socioeconomic status. We conclude that asymptomatically infectious cases may play an important role in transmission of the pH1N1 virus

A Robust Technique without Additional Computational Cost in Evolutionary Antenna Optimization

A robustness-enhancing technique without additional computational cost in antenna optimization design is presented. The robustness is implemented by minimizing the variances of the gains, axial ratios and VSWRs over the required frequency band. It is demonstrated that the new technique has two obvious advantages. One is that it can ensure the antenna robustness without the extra computational overhead. The other one is that it is possible to broaden the bandwidth of the antenna. We apply this technique to design a microstrip antenna at 2.4GHz. Experimental results show that, by adopting this new technique, the evolved antenna is more robust than by using two other techniques

Defining Essentiality Score of Protein-Coding Genes and Long Noncoding RNAs

Measuring the essentiality of genes is critically important in biology and medicine. Here we proposed a computational method, GIC (Gene Importance Calculator), which can efficiently predict the essentiality of both protein-coding genes and long noncoding RNAs (lncRNAs) based on only sequence information. For identifying the essentiality of protein-coding genes, GIC outperformed well-established computational scores. In an independent mouse lncRNA dataset, GIC also achieved an exciting performance (AUC = 0.918). In contrast, the traditional computational methods are not applicable to lncRNAs. Moreover, we explored several potential applications of GIC score. Firstly, we revealed a correlation between gene GIC score and research hotspots of genes. Moreover, GIC score can be used to evaluate whether a gene in mouse is representative for its homolog in human by dissecting its cross-species difference. This is critical for basic medicine because many basic medical studies are performed in animal models. Finally, we showed that GIC score can be used to identify candidate genes from a transcriptomics study. GIC is freely available at http://www.cuilab.cn/gic/

Functional characterization of PETIOLULE-LIKE PULVINUS (PLP) gene in abscission zone development in Medicago truncatula and its application to genetic improvement of alfalfa

Alfalfa (Medicago sativa L.) is one of the most important forage crops throughout the world. Maximizing leaf retention during the haymaking process is critical for achieving superior hay quality and maintaining biomass yield. Leaf abscission process affects leaf retention. Previous studies have largely focused on the molecular mechanisms of floral organ, pedicel and seed abscission but scarcely touched on leaf and petiole abscission. This study focuses on leaf and petiole abscission in the model legume Medicago truncatula and its closely related commercial species alfalfa. By analysing the petiolule-like pulvinus (plp) mutant in M. truncatula at phenotypic level (breakstrength and shaking assays), microscopic level (scanning electron microscopy and cross-sectional analyses) and molecular level (expression level and expression pattern analyses), we discovered that the loss of function of PLP leads to an absence of abscission zone (AZ) formation and PLP plays an important role in leaflet and petiole AZ differentiation. Microarray analysis indicated that PLP affects abscission process through modulating genes involved in hormonal homeostasis, cell wall remodelling and degradation. Detailed analyses led us to propose a functional model of PLP in regulating leaflet and petiole abscission. Furthermore, we cloned the PLP gene (MsPLP) from alfalfa and produced RNAi transgenic alfalfa plants to down-regulate the endogenous MsPLP. Down-regulation of MsPLP results in altered pulvinus structure with increased leaflet breakstrength, thus offering a new approach to decrease leaf loss during alfalfa haymaking process

Insight Into the Superlubricity and Self-Assembly of Liquid Crystals

Liquid crystals are promising molecular materials in the application of lubrication. Herein, the microscale solid superlubricity is accomplished by the construction of uniform and ordered self-assembly of several liquid crystals. The self-assembly structures on a highly oriented pyrolytic graphite (HOPG) surface are explicitly revealed by using scanning tunneling microscopy (STM). Meanwhile, the nanotribological performance of the self-assemblies are measured by using atomic force microscopy (AFM), revealing ultralow friction coefficients lower than 0.01. The interaction energies are calculated by density functional theory (DFT) method, indicating the positive correlation between friction coefficients and interaction strength. The effort on the self-assembly and superlubricity of liquid crystals could enhance the understanding of the nanotribological mechanism and benefit the further application of liquid crystals as lubricants