Logs are imperative in the development and maintenance process of many software systems. They record detailed runtime information that allows developers and support engineers to monitor their systems and dissect anomalous behaviors and errors. The increasing scale and complexity of modern software systems, however, make the volume of logs explodes. In many cases, the traditional way of manual log inspection becomes impractical. Many recent studies, as well as industrial tools, resort to powerful text search and machine learning-based analytics solutions. Due to the unstructured nature of logs, a first crucial step is to parse log messages into structured data for subsequent analysis. In recent years, automated log parsing has been widely studied in both academia and industry, producing a series of log parsers by different techniques. To better understand the characteristics of these log parsers, in this paper, we present a comprehensive evaluation study on automated log parsing and further release the tools and benchmarks for easy reuse. More specifically, we evaluate 13 log parsers on a total of 16 log datasets spanning distributed systems, supercomputers, operating systems, mobile systems, server applications, and standalone software. We report the benchmarking results in terms of accuracy, robustness, and efficiency, which are of practical importance when deploying automated log parsing in production. We also share the success stories and lessons learned in an industrial application at Huawei. We believe that our work could serve as the basis and provide valuable guidance to future research and deployment of automated log parsing.

The formation of large, well-ordered crystals for crystallographic experiments remains a crucial bottleneck to the structural understanding of many important biological systems. To help alleviate this problem in crystallography, we have developed the MicroED method for the collection of electron diffraction data from 3D microcrystals and nanocrystals of radiation-sensitive biological material. In this approach, liquid solutions containing protein microcrystals are deposited on carbon-coated electron microscopy grids and are vitrified by plunging them into liquid ethane. MicroED data are collected for each selected crystal using cryo-electron microscopy, in which the crystal is diffracted using very few electrons as the stage is continuously rotated. This protocol gives advice on how to identify microcrystals by light microscopy or by negative-stain electron microscopy in samples obtained from standard protein crystallization experiments. The protocol also includes information about custom-designed equipment for controlling crystal rotation and software for recording experimental parameters in diffraction image metadata. Identifying microcrystals, preparing samples and setting up the microscope for diffraction data collection take approximately half an hour for each step. Screening microcrystals for quality diffraction takes roughly an hour, and the collection of a single data set is ~10 min in duration. Complete data sets and resulting high-resolution structures can be obtained from a single crystal or by merging data from multiple crystals.

Increasing evidence suggests that homeodomain-leucine zipper I (HD-Zip) I transcription factors play important roles in abiotic stress responses, but no HD-Zip I proteins have been reported in maize. Here, a drought-induced HD-Zip I gene, Zmhdz10, was isolated from maize and characterized for its role in stress responses. Real-time quantitative PCR showed that expression of Zmhdz10 was also induced by salt stress and ABA. Transient expression of Zmhdz10-green fluorescent protein (GFP) fusion proteins in onion cells showed a nuclear localization of Zmhdz10. Yeast hybrid assays demonstrated that Zmhdz10 has transactivation and DNA-binding activity in yeast cells. Overexpression of Zmhdz10 in rice led to enhanced tolerance to drought and salt stresses and increased sensitivity to ABA. Moreover, Zmhdz10 transgenic plants had lower relative electrolyte leakage (REL), lower malondialdehyde (MDA) and increased proline content relative to wild-type plants under stress conditions, which may contribute to enhanced stress tolerance. Zmhdz10 transgenic Arabidopsis plants also exhibited enhanced tolerance to drought and salt stresses that was concomitant with altered expression of stress/ABA-responsive genes, including Δ1-Pyrroline-5-carboxylate synthetase 1 (P5CS1), Responsive to dehydration 22 (RD22), Responsive to dehydration 29B (RD29B) and ABA-insensitive 1 (ABI1). Taken together, these results suggest that Zmhdz10 functions as a transcriptional regulator that can positively regulate drought and salt tolerance in plants through an ABA-dependent signaling pathway.

Reduction of graphene oxide at the nanoscale is an attractive approach to graphene-based electronics. Here we use a platinum-coated atomic force microscope tip to locally catalyse the reduction of insulating graphene oxide in the presence of hydrogen. Nanoribbons with widths ranging from 20 to 80 nm and conductivities of >104 S m−1 are successfully generated, and a field effect transistor is produced. The method involves mild operating conditions, and uses arbitrary substrates, atmospheric pressure and low temperatures (≤115 °C).