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

Sequential fault detection for sealed deep groove ball bearings of in-wheel motor in variable operating conditions

Sealed deep groove ball bearings (SDGBBs) are employed to perform the relevant duties of in-wheel motor. However, the unique construction and complex operating environment of in-wheel motor may aggravate the occurrence of SDGBB faults. Therefore, this study presents a new intelligent diagnosis method for detecting SDGBB faults of in-wheel motor. The method is constructed on the basis of optimal composition of symptom parameters (SPOC) and support vector machines (SVMs). SPOC, as the objects of a follow-on process, is proposed to obtain from symptom parameters (SPs) of multi-direction. Moreover, the optimal hyper-plane of two states is automatically obtained using soft margin SVM and SPOC, and then using multi-SVMs, the system of intelligent diagnosis is built to detect many faults and identify fault types. The experiment results confirmed that the proposed method can excellently perform fault detection and fault-type identification for the SDGBB of in-wheel motor in variable operating conditions

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

A fuzzy diagnosis of multi-fault state based on information fusion from multiple sensors

This paper presents a fuzzy diagnosis for detecting and distinguishing multi-fault state, the method is constructed on the basis of possibility theory and support vector machines (SVMs) with information fusion from multiple sensors. Non-dimensional symptom parameters (NSPs) are defined to reflect the characteristics of vibration information, and principal component analysis (PCA) is used to evaluate and select sensitive NSPs of each sensor. SVMs are employed to fuse vibration information from different sensors into an effective synthetic symptom parameter (SSP) for increasing diagnostic sensitivity, then the possibility function of the SSP is used to construct a fuzzy diagnosis for fault detection and fault-type identification by possibility theory. Practical examples of diagnosis for a roller bearing used in a test bench are given to show that multi-fault states of bearing can be identified precisely by the proposed method

Advances in targeted therapy for acute myeloid leukemia.

Acute myeloid leukemia (AML) is a clonal malignancy characterized by genetic heterogeneity due to recurrent gene mutations. Treatment with cytotoxic chemotherapy has been the standard of care for more than half of a century. Although much progress has been made toward improving treatment related mortality rate in the past few decades, long term overall survival has stagnated. Exciting developments of gene mutation-targeted therapeutic agents are now changing the landscape in AML treatment. New agents offer more clinical options for patients and also confer a more promising outcome. Since Midostaurin, a FLT3 inhibitor, was first approved by US FDA in 2017 as the first gene mutation-targeted therapeutic agent, an array of new gene mutation-targeted agents are now available for AML treatment. In this review, we will summarize the recent advances in gene mutation-targeted therapies for patients with AML

Collaborative HRM, climate for cooperation, and employee intra-organizational social ties in high-technology firms in China: A cross-level analysis

Individual social ties have been an important source of competitive advantages for hightech firms in the knowledge economy. However, the existing cross-level studies have mainly investigated the impact of HRM systems on traditional individual attitudinal or behavioral outcomes, and few studies have examined the effect of SHRM on individual social ties. Based on the data collected from 363 knowledge employees working in 64 high-tech firms in China, we examine the cross-level relationships among collaborative HRM practices, climate for cooperation and employee intra-organizational social ties. The hierarchical linear model results show that organizational-level collaborative HRM practices have significant positive effects on the number and strength of individual-level intra-organizational social ties, and the climate for cooperation mediates the positive cross-level relationship between collaborative HRM and individual intra-organizational social ties. This study makes three contributions to the literature. First, with a cross-level model, this study helps us better understand how collaborative HRM acts as an approach to manage individuals’ social capital formation. Second, this study makes contribution to the social network literature by showing how organizational contextual factors (HRM practices and organizational climate) affect employee individual social ties. Third, based on the AMO model, this paper developed a more clear construct and a three-dimension measurement of the collaborative HRM

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

Four-Dimensional Computed Tomography-Based Treatment Planning for Intensity-Modulated Radiation Therapy and Proton Therapy for Distal Esophageal Cancer

Purpose: To compare three-dimensional (3D) and four-dimensional (4D) computed tomography (CT)-based treatment plans for proton therapy or intensity-modulated radiation therapy (IMRT) for esophageal cancer in terms of doses to the lung, heart, and spinal cord and variations in target coverage and normal tissue sparing. Methods and Materials: The IMRT and proton plans for 15 patients with distal esophageal cancer were designed from the 3D average CT scans and then recalculated on 10 4D CT data sets. Dosimetric data were compared for tumor coverage and normal tissue sparing. Results: Compared with IMRT, median lung volumes exposed to 5, 10, and 20 Gy and mean lung dose were reduced by 35.6%, 20.5%, 5.8%, and 5.1 Gy for a two-beam proton plan and by 17.4%, 8.4%, 5%, and 2.9 Gy for a three-beam proton plan. The greater lung sparing in the two-beam proton plan was achieved at the expense of less conformity to the target (conformity index [CI], 1.99) and greater irradiation of the heart (heart-V40, 41.8%) compared with the IMRT plan(CI, 1.55, heart-V40, 35.7%) or the three-beam proton plan (CI, 1.46, heart-V40, 27.7%). Target coverage differed by more than 2% between the 3D and 4D plans for patients with substantial diaphragm motion in the three-beam proton and IMRT plans. The difference in spinal cord maximum dose between 3D and 4D plans could exceed 5 Gy for the proton plans partly owing to variations in stomach gas filling. Conclusions: Proton therapy provided significantly better sparing of lung than did IMRT. Diaphragm motion and stomach gas-filling must be considered in evaluating target coverage and cord doses. © 2008 Elsevier Inc. All rights reserved