Understanding Solidity Event Logging Practices in the Wild

Writing logging messages is a well-established conventional programming practice, and it is of vital importance for a wide variety of software development activities. The logging mechanism in Solidity programming is enabled by the high-level event feature, but up to now there lacks study for understanding Solidity event logging practices in the wild. To fill this gap, we in this paper provide the first quantitative characteristic study of the current Solidity event logging practices using 2,915 popular Solidity projects hosted on GitHub. The study methodically explores the pervasiveness of event logging, the goodness of current event logging practices, and in particular the reasons for event logging code evolution, and delivers 8 original and important findings. The findings notably include the existence of a large percentage of independent event logging code modifications, and the underlying reasons for different categories of independent event logging code modifications are diverse (for instance, bug fixing and gas saving). We additionally give the implications of our findings, and these implications can enlighten developers, researchers, tool builders, and language designers to improve the event logging practices. To illustrate the potential benefits of our study, we develop a proof-of-concept checker on top of one of our findings and the checker effectively detects problematic event logging code that consumes extra gas in 35 popular GitHub projects and 9 project owners have already confirmed the detected issues.Comment: Accepted by 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE'23

Arrhythmia Classifier Based on Ultra-Lightweight Binary Neural Network

Reasonably and effectively monitoring arrhythmias through ECG signals has significant implications for human health. With the development of deep learning, numerous ECG classification algorithms based on deep learning have emerged. However, most existing algorithms trade off high accuracy for complex models, resulting in high storage usage and power consumption. This also inevitably increases the difficulty of implementation on wearable Artificial Intelligence-of-Things (AIoT) devices with limited resources. In this study, we proposed a universally applicable ultra-lightweight binary neural network(BNN) that is capable of 5-class and 17-class arrhythmia classification based on ECG signals. Our BNN achieves 96.90% (full precision 97.09%) and 97.50% (full precision 98.00%) accuracy for 5-class and 17-class classification, respectively, with state-of-the-art storage usage (3.76 KB and 4.45 KB). Compared to other binarization works, our approach excels in supporting two multi-classification modes while achieving the smallest known storage space. Moreover, our model achieves optimal accuracy in 17-class classification and boasts an elegantly simple network architecture. The algorithm we use is optimized specifically for hardware implementation. Our research showcases the potential of lightweight deep learning models in the healthcare industry, specifically in wearable medical devices, which hold great promise for improving patient outcomes and quality of life. Code is available on: https://github.com/xpww/ECG_BNN_NetComment: 6 pages, 3 figure

Privacy-aware secure anonymous communication protocol in CPSS cloud computing

Cloud computing has emerged as a promising paradigm for the Internet of Things (IoT) and Cyber-Physical-Social Systems (CPSS). However, the problem of how to ensure the security of data transmission and data storage in CPSS is a key issue to address. We need to protect the confidentiality and privacy of users’ data and users’ identity during the transmission and storage process in CPSS. In order to avoid users’ personal information leakage from IoT devices during the process of data processing and transmitting, we propose a certificateless encryption scheme, and conduct a security analysis under the assumption of Computational Diffie-Hellman(CDH) Problem. Furthermore, based on the proposed cryptography mechanism, we achieve a novel anonymous communication protocol to protect the identity privacy of communicating units in CPSS. In the new protocol, an anonymous communication link establishment method and an anonymous communication packet encapsulation format are proposed. The Diffie-Hellman key exchange algorithm is used to construct the anonymous keys distribution method in the new link establishment method. And in the new onion routing packet encapsulation format, the session data are firstly separated from the authentication data to decrease the number of cryptography operations. That is, by using the new onion routing packet we greatly reduces the encryption operations and promotes the forwarding efficiency of anonymous messages, implementing the privacy, security and efficiency in anonymous communication in cyber-physical-social systems

Patterns of Cardiac Perfusion Abnormalities After Chemoradiotherapy in Patients with Lung Cancer

Objective:We evaluated the prevalence of myocardial perfusion defects using myocardial perfusion imaging (MPI) after chemoradiation or radiation therapy (CRT/RT) in lung cancer patients and described their patterns in relation to tumor location.Methods:MPI in 44 patients who received RT for lung cancer and 44 control patients were compared. The two groups were comparable in risk factors for coronary artery disease. Data regarding tumor stage and location, interval between CRT/RT and MPI, and mean radiation dose to the heart was collected. The level of radiation delivered to the affected segments of the left ventricle versus the normal segments was compared using the isodose lines on the simulation computed tomography.Results:Considering all tumor locations, 8 patients (18%) demonstrated MPI defects after CRT/RT versus 9 (20%) in the controls. However, 7 of 18 patients (39%) with centrally located tumors in the CRT/RT group versus only 1 of 15 patients (7%) in the control group demonstrated MPI defect (p= 0.04). The defects in the CRT/RT group were in the anterior and septal segments while the defects were in different segments in the controls. The median interval between end of RT and MPI was 12.3 months. The affected segments in the CRT/RT group received a mean radiation dose of 39.6 versus 11.4 Gy (p = 0.003) to the normal segments.Conclusions:CRT/RT to centrally located lung tumors tends to cause anterior/septal MPI defects. Abnormal MPI segments in the CRT/RT group have received significantly higher radiation than normal segments

Evaluation of the systematic error in using 3D dose calculation in scanning beam proton therapy for lung cancer

The objective of this study was to evaluate and understand the systematic error between the planned three-dimensional (3D) dose and the delivered dose to patient in scanning beam proton therapy for lung tumors. Single-field and multi-field optimized scanning beam proton therapy plans were generated for 10 patients with stage II–III lung cancer with a mix of tumor motion and size. 3D doses in CT data sets for different respiratory phases and the time weighted average CT, as well as the four-dimensional (4D) doses were computed for both plans. The 3D and 4D dose differences for the targets and different organs at risk were compared using dose volume histogram (DVH) and voxel-based techniques and correlated with the extent of tumor motion. The gross tumor volume (GTV) dose was maintained in all 3D and 4D doses using the internal GTV override technique. The DVH and voxel-based techniques are highly correlated. The mean dose error and the standard deviation of dose error for all target volumes were both less than 1.5% for all but one patient. However, the point dose difference between the 3D and 4D doses was up to 6% for the GTV and greater than 10% for the clinical and planning target volumes. Changes in the 4D and 3D doses were not correlated with tumor motion. The planning technique (single-field or multi-field optimized) did not affect the observed systematic error

Assessing the causal relationship between genetically determined inflammatory biomarkers and low back pain risk: a bidirectional two-sample Mendelian randomization study

BackgroundObservational studies have suggested an association between inflammatory markers and low back pain (LBP), but the causal relationship between these factors remains uncertain.MethodsWe conducted a bidirectional two-sample Mendelian randomization analysis (MR) study to investigate whether there is a causal relationship between inflammatory markers and low back pain. We obtained genetic data for CRP, along with its upstream inflammatory markers IL-6, IL-8, and IL-10, as well as low back pain from publicly available genome-wide association studies (GWAS). We applied several MR methods, including inverse variance weighting, weighted median, MR-Egger, Wald Ratio, and MR-PRESSO, to test for causal relationships. Sensitivity analyses were also conducted to assess the robustness of the results.ResultsOur analyses utilizing the Inverse Variance Weighted (IVW) method, the MR-Egger method, and the weighted median method indicated that IL-6 may be associated with an increased risk of LBP (Effect Size: -0.009, 95% Confidence Interval: -0.013–0.006, p = 9.16e-08); however, in the reverse direction, there was no significant causal effect of LBP on inflammatory markers.ConclusionOur study used a Mendelian randomization approach and found that elevated IL-6 levels may reduce the risk of LBP

Prognostic value of N-terminal Pro–B-Type natriuretic peptide in patients with intermediate coronary lesions

BackgroundThe optimal treatment strategy for patients with coronary intermediate lesions, defined as diameter stenosis of 50–70%, remains a great challenge for cardiologists. Identification of potential biomarkers predictive of major adverse cardiovascular events (MACEs) risk may assist in risk stratification and clinical decision.MethodsA total of 1,187 patients with intermediate coronary lesions and available N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were enrolled in the current study. A baseline NT-proBNP level was obtained. The primary endpoint was defined as MACEs, the composite endpoint of all-cause death and non-fatal myocardial infarction. A multivariate Cox regression model was used to explore the association between NT-proBNP level and MACE risk.ResultsThe mean age of the study cohort was 59.2 years. A total of 68 patients experienced MACE during a median follow-up of 6.1 years. Restricted cubic spline analysis delineated a linear relationship between the baseline NT-proBNP level and MACE risk. Both univariate and multivariate analyses demonstrated that an increased NT-proBNP level was associated with an increased risk of MACE [adjusted hazard ratio (HR) per doubling: 1.412, 95% confidence interval (CI): 1.022–1.952, p = 0.0365]. This association remains consistent in clinical meaningful subgroups according to age, sex, body mass index (BMI), and diabetes.ConclusionAn increased NT-proBNP level is associated with an increased risk of MACE in patients with intermediate coronary lesions and may serve as the potential biomarker for risk stratification and treatment decision guidance

Genotypes and haplotypes of the VEGF gene and survival in locally advanced non-small cell lung cancer patients treated with chemoradiotherapy

<p>Abstract</p> <p>Background</p> <p>Vascular endothelial growth factor (VEGF) is a major mediator of angiogenesis involving in carcinogenesis, including lung cancer. We hypothesized that <it>VEGF </it>polymorphisms may affect survival outcomes among locally advanced non-small cell lung cancer (LA-NSCLC) patients.</p> <p>Methods</p> <p>We genotyped three potentially functional <it>VEGF </it>variants [-460 T > C (rs833061), -634 G > C (rs2010963), and +936 C > T (rs3025039)] and estimated haplotypes in 124 Caucasian patients with LA-NSCLC treated with definitive radiotherapy. We used Kaplan-Meier log-rank tests, and Cox proportional hazard models to evaluate the association between <it>VEGF </it>variants and overall survival (OS).</p> <p>Results</p> <p>Gender, Karnofsky's performance scores (KPS) and clinical stage seemed to influence the OS. The variant C genotypes were independently associated with significantly improved OS (CT+CC vs. TT: adjusted hazard ratio [HR] = 0.58; 95% confidence interval [CI] = 0.37-0.92, <it>P </it>= 0.022), compared with the <it>VEGF </it>-460 TT genotype.</p> <p>Conclusions</p> <p>Our study suggests that <it>VEGF </it>-460 C genotypes may be associated with a better survival of LA-NSCLC patients after chemoradiotherapy. Large studies are needed to confirm our findings.</p