CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models

Code generation models based on the pre-training and fine-tuning paradigm have been increasingly attempted by both academia and industry, resulting in well-known industrial models such as Codex, CodeGen, and PanGu-Coder. To evaluate the effectiveness of these models, multiple existing benchmarks are proposed, including only cases of generating a standalone function, i.e., a function that may invoke or access only built-in functions and standard libraries. However, non-standalone functions, which typically are not included in the existing benchmarks, constitute more than 70% of the functions in popular open-source projects, and evaluating models' effectiveness on standalone functions cannot reflect these models' effectiveness on pragmatic code generation scenarios. To help bridge the preceding gap, in this paper, we propose a benchmark named CoderEval, consisting of 230 Python and 230 Java code generation tasks carefully curated from popular real-world open-source projects and a self-contained execution platform to automatically assess the functional correctness of generated code. CoderEval supports code generation tasks from six levels of context dependency, where context refers to code elements such as types, APIs, variables, and consts defined outside the function under generation but within the dependent third-party libraries, current class, file, or project. CoderEval can be used to evaluate the effectiveness of models in generating code beyond only standalone functions. By evaluating three code generation models on CoderEval, we find that the effectiveness of these models in generating standalone functions is substantially higher than that in generating non-standalone functions. Our analysis highlights the current progress and pinpoints future directions to further improve a model's effectiveness by leveraging contextual information for pragmatic code generation

Using high level roadway to control gas emission in a longwall mining face – numerical simulation study

With the increase of coal mining depth, the gas content in coal seams could also become larger and larger, which could suddenly cause an inrush of gas into the longwall mining face. It is very dangerous for miners’ safety in the underground. The U-shaped ventilation pattern of longwall mining face that underground coal mines currently use is not enough to deliver sufficient air quantities to dilute gases in mining faces, which could result in the gas concentration over the required celling limit by government laws. Thus, the mine must stop production. In this paper, the high level roadway (HLR) is designed and the U + HLR new ventilation pattern is proposed to control gas emission in a longwall mining face. Using computational fluid dynamics simulation (CFD) software, the flow field and gas transportation in the mine gob are studied. The optimized ventilation parameters are summarized. It is found that the best vertical distance of the HLR is 35 m over the coal seam and the horizontal distance is 25 m from the air return roadway. It is recommended that the negative suction pressure design of the high level roadway should be ranged from 9000 Pa to 10000 Pa. Based on the study outcomes, the gas emission could be well controlled in mining faces and avoid any gas disaster accidents

Identification of a c-type heme oxygenase and its function during acclimation of cyanobacteria to nitrogen fluctuations

Abstract The mechanisms of acclimating to a nitrogen-fluctuating environment are necessary for the survival of aquatic cyanobacteria in their natural habitats, but our understanding is still far from complete. Here, the synthesis of phycobiliprotein is confirmed to be much earlier than that of photosystem components during recovery from nitrogen chlorosis and an unknown protein Ssr1698 is discovered to be involved in this synthetic process. The unknown protein is further identified as a c-type heme oxygenase (cHO) in tetrapyrrole biosynthetic pathway and catalyzes the opening of heme ring to form biliverdin IXα, which is required for phycobilin production and ensuing phycobiliprotein synthesis. In addition, the cHO-dependent phycobiliprotein is found to be vital for the growth of cyanobacterial cells during chlorosis and regreening through its nitrogen-storage and light-harvesting functions, respectively. Collectively, the cHO expressed preferentially during recovery from nitrogen chlorosis is identified in photosynthetic organisms and the dual function of this enzyme-dependent phycobiliprotein is proposed to be an important mechanism for acclimation of aquatic cyanobacteria to a nitrogen-fluctuating environment

Genome-Wide Association Study of Phenylalanine Derived Glucosinolates in Brassica rapa

Glucosinolates (GSLs) are sulfur-containing bioactive compounds usually present in Brassicaceae plants and are usually responsible for a pungent flavor and reduction of the nutritional values of seeds. Therefore, breeding rapeseed varieties with low GSL levels is an important breeding objective. Most GSLs in Brassica rapa are derived from methionine or tryptophan, but two are derived from phenylalanine, one directly (benzylGSL) and one after a round of chain elongation (phenethylGSL). In the present study, two phenylalanine (Phe)-derived GSLs (benzylGSL and phenethylGSL) were identified and quantified in seeds by liquid chromatography and mass spectrometry (LC-MS) analysis. Levels of benzylGSL were low but differed among investigated low and high GSL genotypes. Levels of phenethylGSL (also known as 2-phenylethylGSL) were high but did not differ among GSL genotypes. Subsequently, a genome-wide association study (GWAS) was conducted using 159 B. rapa accessions to demarcate candidate regions underlying 43 and 59 QTNs associated with benzylGSL and phenethylGSL that were distributed on 10 chromosomes and 9 scaffolds, explaining 0.56% to 70.86% of phenotypic variations, respectively. Furthermore, we find that 15 and 18 known or novel candidate genes were identified for the biosynthesis of benzylGSL and phenethylGSL, including known regulators of GSL biosynthesis, such as BrMYB34, BrMYB51, BrMYB28, BrMYB29 and BrMYB122, and novel regulators or structural genes, such as BrMYB44/BrMYB77 and BrMYB60 for benzylGSL and BrCYP79B2 for phenethylGSL. Finally, we investigate the expression profiles of the biosynthetic genes for two Phe-derived GSLs by transcriptomic analysis. Our findings provide new insight into the complex machinery of Phe-derived GSLs in seeds of B. rapa and help to improve the quality of Brassicaceae plant breeding