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This paper investigates China’s grain trade potential and the influencing factors with RCEP partner countries by using the stochastic frontier gravity and trade inefficiency models and explores the impact of the RCEP negotiations on grain trade cooperation between China and RCEP partner countries. The research results verify that the institutional distance, economic distance, and tariff level hinder the grain trade efficiency between China and RCEP partner countries, where the tariff level has the smallest resistance. The transportation and communication infrastructure level can significantly improve the grain trade efficiency, but the transportation infrastructure level has a greater stimulative effect. China’s grain trade potential with RCEP partner countries is enormous, and there is evident heterogeneity in the grain trade potential of different countries. The grain trade relations between China and RCEP partner countries have been improved after the RCEP negotiations. However, there are still greater trade potential and expansion space for New Zealand and Laos. Therefore, some policy suggestions are put forward, such as establishing the risk assessment and early warning system, implementing the tariff reduction measures in the agreement, and developing grain trade cooperation according to local conditions, which provides practical guidance for expanding the grain trade scale.

BackgroundHER2-low expression breast cancer (BC) accounts for approximately 45%-55% of all BC cases. The purpose of this study was to investigate the prognostic difference between patients with HER2-low expression and HER2-zero BC.MethodsAn electronic search of Pubmed, Embase, Cochrane Library, and Web of Science databases was performed to screen studies that included prognostic comparisons between HER2-zero and HER2-low expression groups. A total of 14 studies involving 52106 patients were included.ResultsOur results indicated that HER2-low expression was associated with a significant benefit in OS among all patients with early BC (HR, 0.83; 95% CI, 0.78–0.88), patients with hormone-receptor positive BC (HR, 0.83; 95% CI, 0.77–0.89), and patients with TNBC (HR, 0.78; 95% CI, 0.70–0.87). HER2-low expression was associated with a significant benefit in DFS among all patients (HR, 0.81; 95% CI, 0.71–0.93), patients with hormone receptor-positive BC (HR, 0.81; 95% CI, 0.72–0.90), but no significant difference in DFS was found in patients with TNBC (HR, 0.87; 95% CI, 0.65–1.17). HER2-low expression was associated with a significant benefit in RFS among all patients (HR, 0.90; 95% CI, 0.85–0.95), patients with hormone receptor-positive BC (HR, 0.90; 95% CI, 0.84–0.96), but no significant difference in RFS was found in patients with TNBC (HR, 0.80; 95% CI, 0.55–1.16).ConclusionsAmong patients with early-stage BC, patients with HER2-low expression BC had better OS in the overall population, hormone receptor-positive and TNBC subgroups. Besides, favorable DFS and RFS were observed in both the overall population and hormone receptor-positive subgroup.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier (CRD 42022349458).

Through a study of multi-gas mixture datasets, we show that in multi-component spectral analysis, the number of functional or non-functional principal components required to retain the essential information is the same as the number of independent constituents in the mixture set. Due to the mutual in-dependency among different gas molecules, near one-to-one projection from the principal component to the mixture constituent can be established, leading to a significant simplification of spectral quantification. Further, with the knowledge of the molar extinction coefficients of each constituent, a complete principal component set can be extracted from the coefficients directly, and few to none training samples are required for the learning model. Compared to other approaches, the proposed methods provide fast and accurate spectral quantification solutions with a small memory size needed.

BACKGROUND: Tumor mutation burden (TMB) assessed by tumor-related gene panels (CRGP), microsatellite instability (MSI), and mismatch repair (MMR) has been proven to be associated with prognosis, and these factors are prognostic indicators in predicting the benefits of immune checkpoint blockade (ICB) in solid tumors. However, whether the TMB calculated by CRGPs, MSI, and MMR is associated with overall survival (OS) in patients with colorectal cancer (CRC) remains to be explored. METHODS: The prognostic threshold of the panel-TMB was explored by a panel of 645 genes (GP645) from 41 CRC patients in Jiangsu Cancer Hospital (JCH dataset). The results were further validated using 531 CRC patients from The Cancer Genome Atlas (TCGA) database. RESULTS: Mutations of the GP645 genes were distributed on 21 chromosomes. Spearman correlation analysis showed that the panel-TMB was positively correlated with TMB measured by whole-exome sequencing (WES) (wTMB) in the TCGA dataset (R=0.75, P

With the increasing number of software bugs, bug fixing plays an important role in software development and maintenance. To improve the efficiency of bug resolution, developers utilize bug reports to resolve given bugs. Especially, bug triagers usually depend on bugs’ descriptions to suggest priority levels for reported bugs. However, manual priority assignment is a time-consuming and cumbersome task. To resolve this problem, recent studies have proposed many approaches to automatically predict the priority levels for the reported bugs. Unfortunately, these approaches still face two challenges that include words’ nonconsecutive semantics in bug reports and the imbalanced data. In this article, we propose a novel approach that graph convolutional networks (GCN) based on weighted loss function to perform the priority prediction for bug reports. For the first challenge, we build a heterogeneous text graph for bug reports and apply GCN to extract words’ semantics in bug reports. For the second challenge, we construct a weighted loss function in the training phase. We conduct the priority prediction on four open-source projects, including Mozilla, Eclipse, Netbeans, and GNU compiler collection. Experimental results show that our method outperforms two baseline approaches in terms of the F-measure by weighted average of 13.22%.

The vast coastline provides Canada with a flourishing seafood industry including bivalve shellfish production. To sustain a healthy bivalve molluscan shellfish production, the Canadian Shellfish Sanitation Program was established to monitor the health of shellfish harvesting habitats, and fecal coliform bacteria data have been collected at nearly 15,000 marine sample sites across six coastal provinces in Canada since 1979. We applied Functional Principal Component Analysis and subsequent correlation analyses to find annual variation patterns of bacteria levels at sites in each province. The overall magnitude and the seasonality of fecal contamination were modelled by functional principal component one and two, respectively. The amplitude was related to human and warm-blooded animal activities; the seasonality was strongly correlated with river discharge driven by precipitation and snow melt in British Columbia, but such correlation in provinces along the Atlantic coast could not be properly evaluated due to lack of data during winter., Comment: 30 pages, 7 figures, 0 table

This paper investigates the fluctuation characteristics and asymmetry of cross-correlations between economic policy uncertainty (EPU) and agricultural futures prices in China and the US by using the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA). We find that the multifractal cross-correlations exist between EPU and agricultural futures prices, and the cross-correlations are anti-persistent and asymmetric. The anti-persistent cross-correlations in China are all stronger than those in the US. The multifractal degree of cross-correlation between EPU and soybean futures price is lower in China than in the US, while the multifractal degree of cross-correlation between EPU and soybean meal, soybean oil or corn futures price is higher in China than in the US. Moreover, China’s soybean futures price is more susceptible to the upward and downward trends in China’s EPU, while the US soybean meal, soybean oil, and corn futures prices are more susceptible to them in the US EPU.

Objective: To investigate the correlation between estrogen-related receptor a (ERRα) expression level and gastric cancer (GC). Methods: We collected GC and adjacent normal tissues from 50 patients. The parameters of the patients were summarized, and correlation with the expression level of ERRα was calculated. Downregulated ERRα using lentivirus was designed and transfected to SGC-7901 and MGC-803 cells. Cell migration, invasion and wound assays were conducted to determine the correlation between ERRα and capacity for cell migration and invasion. The expression level of the genes involved in epithelial–mesenchymal transition, including E-cadherin, γ-catenin, N-cadherin and vimentin, was determined via real-time or quantitative polymerase chain reaction(qPCR) and Western blot analysis. Results: The expression of ERRα tends to be higher in GC tissues than in adjacent normal tissues. Analyses ofthe expression level of ERRα and patient parameters show that the ERRα level is significantly correlated with TNM staging and patient survival (P

Ralstonia solanacearum is a common plant bacterium, and the improper use of chemicals to control this bacterium is harmful to the environment. Many undeveloped aromatic plants and green plant waste can be used for the preparation of essential oils (EOs). EOs have various biological activities, such as bacteriostatic, insecticidal and anti-oxidation, and are currently in the exploration stage for the control of R. solanacearum. In the present study, the inhibitory activity of ten EOs against R. solanacearum was determined by an antibacterial test. To prolong the duration of antibacterial activity, microcapsules of EOs were prepared by the complex coacervation method, and the optimal preparation conditions were obtained by central composite design method. The results showed that cinnamon EOs had the strongest antibacterial activity. For GIM1.71, GIM1.74, GIM1.76, GMI1000 and RS-5, the EC50 values of cinnamon EOs were 0.055 mg/mL, 0.071 mg/mL, 0.03 mg/mL, 0.067 mg/mL and 0.063 mg/mL, respectively. The preparation condition of cinnamon EOs microcapsules was as follows: the core-wall ratio was 4.35:1, the ratio of chitosan and sodium alginate was 0.15:1, and the calcium chloride concentration was 0.95 wt%. The encapsulation efficiency was 87.32%, and the average particle size of microcapsule was 870.4 μm. The release rate of microcapsule was 44.53% at 100 °C for 6 h and the release of the core materials in microcapsules was in line with Korsmeyer–Peppas release kinetics. Microcapsules placed at room temperature for 7 days still had significant antibacterial activity against five species of R. solanacearum. Due to its good stability and antibacterial activity, cinnamon EOs microcapsules will have great market application prospects as antibacterial agents.

BackgroundCircular RNAs (circRNAs) are a new class of endogenous non-coding RNAs (ncRNAs) widely expressed in eukaryotic cells. Mounting evidence has highlighted circRNAs as critical regulators of various tumours. More importantly, circRNAs have been revealed to recruit and reprogram key components involved in the tumour microenvironment (TME), and mediate various signaling pathways, thus affecting tumourigenesis, angiogenesis, immune response, and metastatic progression.Main body of the abstractIn this review, we briefly introduce the biogenesis, characteristics and classification of circRNAs, and describe various mechanistic models of circRNAs. Further, we provide the first systematic overview of the interplay between circRNAs and cellular/non-cellular counterparts of the TME and highlight the potential of circRNAs as prospective biomarkers or targets in cancer clinics. Finally, we discuss the biological mechanisms through which the circRNAs drive development of resistance, revealing the mystery of circRNAs in drug resistance of tumours.Short conclusionDeep understanding the emerging role of circRNAs and their involvements in the TME may provide potential biomarkers and therapeutic targets for cancer patients. The combined targeting of circRNAs and co-activated components in the TME may achieve higher therapeutic efficiency and become a new mode of tumour therapy in the future.

The fluctuation characteristics of the correlations between China and the US agricultural futures markets have attracted extensive attention from academic circles and government departments. As the main factor that affects the agricultural futures price, the impact of international crude oil futures price on the correlations of the Sino-US agricultural futures markets is also worth discussing. Therefore, this paper adopts the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal detrended partial cross-correlation analysis (MF-DPXA) to explore the fluctuation characteristics of cross-correlations for China and the US agricultural futures markets before and after removing the West Texas Intermediate (WTI) crude oil futures price as well as the impact on the cross-correlations. The results show that the fluctuation characteristics of the cross-correlations and partial cross-correlations between the corresponding varieties of China and the US agricultural futures markets as well as among the varieties within the markets are multifractal. The cross-correlation behaviors and the cross-market risks are all affected to varying degrees by the West Texas Intermediate (WTI) crude oil futures. The West Texas Intermediate (WTI) crude oil futures weaken the cross-market risk of the Sino-US soybean futures, while strengthening the cross-market risk of the Sino-US corn and wheat futures. In addition, the impact of the West Texas Intermediate (WTI) crude oil futures on the cross-market risks among China agricultural futures is greater than those among the US corresponding agricultural futures.

BACKGROUND: To explore the relationship between L3 skeletal muscle index (SMI) and the prognosis of patients with stage IV gastric cancer (GC). METHODS: A total of 27 patients with stage IV GC requiring chemotherapy admitted to our hospital from 1 April 2015 to 20 May 2019 were selected as participants. The Kaplan-Meier method was used to describe the survival time of all participants. By evaluating the L3 plane CT images, the mass index (cm(2)/m(2)) of L3 skeletal muscle (including psoas major, erector spinae, quadratus psoas, transversus abdominis, external oblique abdominis, and internal oblique abdominis) was calculated to study the changes of L3 SMI during treatment and the correlation between L3 SMI and clinical features. The log-rank method was used to analyze the correlativity between the survival time of patients and their general data, L3 SMI, or other indicators. RESULTS: The survival time of 27 patients with stage IV GC was 7.4–49.9 months, with a mean survival time of 19.72 months and a median survival time of 16.17 months. The 1-year survival rate was 77.78%, and the 3-year survival rate was 7.41%. During treatment, L3 SMI continued to decline in 20 of the 27 participants (74.07%). After the first chemotherapy, 17 participants (62.96%) met the criteria of sarcopenia syndrome, and after the fourth chemotherapy, 19 participants (70.37%) met the criteria of sarcopenia syndrome. The L3 SMI was shown to be significantly correlated with body mass index (BMI) and Onodera’s prognostic nutritional index (OPNI) (both P0.05). Log-rank test showed that there was a correlation between L3 SMI and survival time of patients (P

It was found in this study that long intergenic non-protein coding RNA 346 (LINC00346) was an lncRNA aberrantly expressed in gastric cancer (GC) based on multiple Gene Expression Omnibus (GEO) databases of GC cohorts. The LINC00346 gene was recurrently amplified and upregulated in GC, and its expression was positively correlated with poor pathologic stage, large tumor size, and poor prognosis. In addition, the oncogenic transcription factors KLF5 and MYC could bind to the LINC00346 promoter and enhance its expression. Gene Set Enrichment Analysis (GSEA) in the GEO datasets revealed that cell cycle and focal adhesion genes were enriched in patients with high LINC00346 expression. In vitro and in vivo assays of LINC00346 alterations revealed a complex integrated phenotype affecting cell growth, migration and invasion. Strikingly, high-throughput sequencing analysis after LINC00346 alterations highlighted alterations in cell cycle and focal adhesion pathways in GC cells. Mechanistically, argonaute 2 (Ago2) was recruited by LINC00346, which functioned as a molecular sponge for miR-34a-5p by antagonizing its ability to repress CD44, NOTCH1, and AXL protein translation. Taken together, our findings support a model in which the KLF5, MYC/LINC00346/miR-34a-5p cross-talk served as critical effectors in GC tumorigenesis and progression, suggesting a new therapeutic direction in the treatment of GC.

Additional file 2: Figure S1. Analysis of multiple sequences of GH10 xylanases. The selected mutation sites are marked with red diamonds. Figure S2. Specific activity of wild-type XYL10C_∆N and its mutants against beechwood xylan at 40 ºC. Figure S3. Sodium dodecylsulfate-polyacrylamide gel electrophoresis analysis of purified XYL10C_∆N and its mutants. Lanes: M, the standard protein molecular weight markers; A, C, E, and G: XYL10C_∆N, M53S/F54L, N207G, and M53S/F54L/N207G; B, D, F, and H: deglycosylated enzymes. Figure S4. Graph for Lineweaver–Burk regression and equation for the enzymes at 40 °C. A. XYL10C_∆N; B M53S/F54L; C N207G; D M53S/F54L/N207G. Figure S5. Surface structure of A corn stalk, B wheat bran, and C corn cob treated with buffer for 24 h.

Additional file 2: Figure S1. Analysis of multiple sequences of GH10 xylanases. The selected mutation sites are marked with red diamonds. Figure S2. Specific activity of wild-type XYL10C_∆N and its mutants against beechwood xylan at 40 ºC. Figure S3. Sodium dodecylsulfate-polyacrylamide gel electrophoresis analysis of purified XYL10C_∆N and its mutants. Lanes: M, the standard protein molecular weight markers; A, C, E, and G: XYL10C_∆N, M53S/F54L, N207G, and M53S/F54L/N207G; B, D, F, and H: deglycosylated enzymes. Figure S4. Graph for Lineweaver–Burk regression and equation for the enzymes at 40 °C. A. XYL10C_∆N; B M53S/F54L; C N207G; D M53S/F54L/N207G. Figure S5. Surface structure of A corn stalk, B wheat bran, and C corn cob treated with buffer for 24 h.

Additional file 1: Table S1. Primers used in this study.

Real-time traffic video data analysis and processing technology is an important part of intelligent urban transportation, real-time urban traffic planning, reducing urban traffic congestion, has certain application value. Aiming at the problem that network transmission link resources are limited and it is difficult to meet the real-time analysis and processing of massive video data uploading to the cloud. In this paper, we propose MEMTV, a multi-level edge computing model based on big data machine. The model obtains scene semantic information by processing traffic video data at the edge intelligent terminal, and uploads the scene semantic information as textual metadata to the edge server for analysis, while the edge server only does the inference of the model, and the update training of the model is performed in the cloud, which does not affect the edge data processing while ensuring the high reliability of the prediction model. The experimental results show that the MEMTV can effectively process traffic video stream data.

N6-methyladenosine (m6A), the most prevalent RNA internal modification, is present in most eukaryotic species and prokaryotes. Studies have highlighted an intricate network architecture by which m6A epitranscriptome impacts on immune response and function. However, it was only until recently that the mechanisms underlying the involvement of m6A modification in immune system were uncovered. Here, we systematically review the m6A involvement in the regulation of innate and adaptive immune cells. Further, the interplay between m6A modification and anti-inflammatory, anti-viral and anti-tumour immunity is also comprehensively summarized. Finally, we focus on the future prospects of m6A modification in immune modulation. A better understanding of the crosstalk between m6A modification and immune system is of great significance to reveal new pathogenic pathways and to develop promising therapeutic targets of diseases.

Long non-coding RNAs (lncRNAs) are characterized as key layers of the genome in various cancers. TSPEAR-AS2 was highlighted to be a candidate lncRNA potentially involved in gastric cancer (GC) progression. However, the clinical significance and mechanism of TSPEAR-AS2 in GC required clarification. The clinical significance of TSPEAR-AS2 was elucidated through Kaplan-Meier Plotter. The mechanism of TSPEAR-AS2 in GC was clarified in vitro and in vivo using luciferase reporter, chromatin immunoprecipitation, RNA immunoprecipitation assays, and animal models. TSPEAR-AS2 elevation was closely correlated with overall survival of GC patients. A basic transcription element-binding protein 2 (BTEB2)-activated TSPEAR-AS2 model was first explored in this study. TSPEAR-AS2 silencing substantially reduced tumorigenic capacities of GC cells, while TSPEAR-AS2 elevation had the opposite effect. Mechanistically, TSPEAR-AS2 bound with both polycomb repressive complex 2 (PRC2) and argonaute 2 (Ago2). TSPEAR-AS2 knockdown significantly decreased H3K27me3 levels at promoter regions of gap junction protein alpha 1 (GJA1). Ago2 was recruited by TSPEAR-AS2, which was defined to sponge miR-1207-5p, contributing to the repression of claudin 4 (CLDN4) translation. The axis of EZH2/GJA1 and miR-1207-5p/CLDN4 mediated by BTEB2-activated-TSPEAR-AS2 plays an important role in GC progression, suggesting a new therapeutic direction in GC treatment., Graphical Abstract, Ma and colleagues elucidated the clinical significance and mechanism of lncRNA TSPEAR-AS2 in gastric cancer progression. The regulatory axis of EZH2/GJA1 and miR-1207-5p/CLDN4 mediated by BTEB2-activated-TSPEAR-AS2 suggested a new therapeutic direction for patients with gastric cancer.

Background Gastric cancer (GC) is the third leading cause of cancer-related mortality globally. Long noncoding RNAs (lncRNAs) are dysregulated in obvious malignancies including GC and exploring the regulatory mechanisms underlying their expression is an attractive research area. However, these molecular mechanisms require further clarification, especially upstream mechanisms. Methods LncRNA MNX1-AS1 expression in GC tissue samples was investigated via microarray analysis and further determined in a cohort of GC tissues via quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays. Cell proliferation and flow cytometry assays were performed to confirm the roles of MNX1-AS1 in GC proliferation, cell cycle regulation, and apoptosis. The influence of MNX1-AS1 on GC cell migration and invasion was explored with Transwell assays. A xenograft tumour model was established to verify the effects of MNX1-AS1 on in vivo tumourigenesis. The TEAD4-involved upstream regulatory mechanism of MNX1-AS1 was explored through ChIP and luciferase reporter assays. The mechanistic model of MNX1-AS1 in regulating gene expression was further detected by subcellular fractionation, FISH, RIP, ChIP and luciferase reporter assays. Results It was found that MNX1-AS1 displayed obvious upregulation in GC tissue samples and cell lines, and ectopic expression of MNX1-AS1 predicted poor clinical outcomes for patients with GC. Overexpressed MNX1-AS1 expression promoted proliferation, migration and invasion of GC cells markedly, whereas decreased MNX1-AS1 expression elicited the opposite effects. Consistent with the in vitro results, MNX1-AS1 depletion effectively inhibited the growth of xenograft tumour in vivo. Mechanistically, TEAD4 directly bound the promoter region of MNX1-AS1 and stimulated the transcription of MNX1-AS1. Furthermore, MNX1-AS1 can sponge miR-6785-5p to upregulate the expression of BCL2 in GC cells. Meanwhile, MNX1-AS1 suppressed the transcription of BTG2 by recruiting polycomb repressive complex 2 to BTG2 promoter regions. Conclusions Our findings demonstrate that MNX1-AS1 may be able to serve as a prognostic indicator in GC patients and that TEAD4-activatd MNX1-AS1 can promote GC progression through EZH2/BTG2 and miR-6785-5p/BCL2 axes, implicating it as a novel and potent target for the treatment of GC.

Accumulating data indicate that long noncoding RNAs (lncRNAs) serve as important modulators in biological processes and are dysregulated in diverse tumors. The function of FOXD2-AS1 in gastric cancer (GC) progression and related biological mechanisms remain undefined. A comprehensive analysis identified that FOXD2-AS1 enrichment was upregulated markedly in GC and positively correlated with a large tumor size, a later pathologic stage, and a poor prognosis. Gene-set enrichment analysis (GSEA) in GEO datasets uncovered that cell cycle and DNA replication associated genes were enriched in patients with high FOXD2-AS1 expression. Loss of FOXD2-AS1 function inhibited cell growth via inhibiting the cell cycle in GC, whereas upregulation of FOXD2-AS1 expression promoted cancer progression. The enhancer of zeste homolog 2 (EZH2) and lysine (K)-specific demethylase 1A (LSD1) proteins were found to serve as binding partners of FOXD2-AS1 and mediators of FOXD2-AS1 function. Mechanically, FOXD2-AS1 promoted GC tumorigenesis partly through EZH2 and LSD1 mediated EphB3 downregulation. The present results revealed that FOXD2-AS1 acted as a tumor inducer in GC partly through EphB3 inhibition by direct interaction with EZH2 and LSD1, and may prove to be a potential biomarker of carcinogenesis.

Background/Aims: Lung cancer (LC) is a serious disease with high morbidity and mortality. Long noncoding RNAs (lncRNAs) have garnered attention because they participate in diverse human disorders, including cancer. Our study examined the long intergenic noncoding RNA 00707 (LINC00707). The effects of LINC00707 on lung adenocarcinoma (LAD) and molecular mechanisms are unclear. This study is aimed to investigate the role of LINC00707 in the malignant processes of LAD. Methods: Quantitative reverse transcription PCR (qRT-PCR) was used to examine the expression level of LINC00707 in tissues and cell lines. The association of LINC00707 expression and postoperative prognosis was analyzed by the Kaplan-Meier method and log-rank test. Cell proliferation was evaluated in vitro and in vivo. Transwell assays were performed to examine cell migration. Cell cycle and apoptosis was determined by flow -cytometric and western blot analyses. Microarray analysis was conducted to screen for the downstream target gene Cdc42 of LINC00707, which was identified by qRT-PCR, functional analysis, and rescue experiment. Results: The expression level of LINC00707 was clearly upregulated in LAD tissues compared to that in corresponding normal tissues. Its overexpression was related to advanced TNM stage, larger tumor size, lymphatic metastasis, and poor prognosis. Functional assays revealed that LINC00707 knockdown repressed LAD cell proliferation both in vitro and in vivo. This process may involve the inducing of G1 arrest and apoptosis. Moreover, cell migration was impaired after LINC00707 inhibition. Microarray analysis and rescue assays suggested that Cdc42 is an important target gene involved in the carcinogenesis of LINC00707. Conclusions: In summary, LINC00707 is a noncoding oncogene that exerts important regulatory functions in LAD, suggesting its potential as a biomarker in the prognosis and treatment of LAD.

Context: Developers tend to search and reuse code snippets from a large-scale codebase when they want to implement some functions that exist in the previous projects, which can enhance the efficiency of software development. Objective: As the first deep learning-based code search model, DeepCS outperforms prior models such as Sourcere and CodeHow. However, it utilizes two separate LSTM to represent code snippets and natural language descriptions respectively, which ignores semantic relations between code snippets and their descriptions. Consequently, the performance of DeepCS falls into the bottleneck, and thus our objective is to break this bottleneck. Method: We propose a self-attention joint representation learning model, named SAN-CS (Self-Attention Network for Code Search). Comparing with DeepCS, we directly utilize the self-attention network to construct our code search model. By a weighted average operation, self-attention networks can fully capture the contextual information of code snippets and their descriptions. We first utilize two individual self-attention networks to represent code snippets and their descriptions, respectively, and then we utilize the self-attention network to conduct an extra joint representation network for code snippets and their descriptions, which can build semantic relationships between code snippets and their descriptions. Therefore, SAN-CS can break the performance bottleneck of DeepCS. Results: We evaluate SAN-CS on the dataset shared by Gu et al. and choose two baseline models, DeepCS and CARLCS-CNN. Experimental results demonstrate that SAN-CS achieves significantly better performance than DeepCS and CARLCS-CNN. In addition, SAN-CS has better execution efficiency than DeepCS at the training and testing phase. Conclusion: This paper proposes a code search model, SAN-CS. It utilizes the self-attention network to perform the joint attention representations for code snippets and their descriptions, respectively. Experimental results verify the effectiveness and efficiency of SAN-CS.

With the rapid development of economic globalization, the stock markets in China and the US are increasingly linked. The fluctuation features and cross-correlations of the two countries’ markets have attracted extensive attention from market investors and researchers. In this paper, the fractal analysis methods including multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) and coupled detrended cross-correlation analysis (CDCCA) are applied to explore the volatilities of CSI300 and SP500 sector stock indexes as well as the cross-correlations and coupling cross-correlations between the two corresponding sector stock indexes. The results show that the auto-correlations, cross-correlations and coupling cross-correlations have multifractal fluctuation characteristics, and that the cross-correlations are asymmetric. Additionally, the coupling cross-correlation strengths are distinct due to the different influence of long-range correlations and fat-tailed distribution. Further, the co-movement between China and the US sector stock markets is susceptible to external market factors such as major economic events and national policies.

A microwave-assisted and phosphine-mediated Tomita Zipper cyclization of dicyanomethylideneoxindoles and ynones has been developed. Various functionalized spirooxindoles with five-membered carbocyclic ring can be obtained in moderate to good yields with moderate to excellent diastereoselectivities through in situ generation of α-nucleophile (up to 87% yield, >20:1 dr).

Nowadays, bugs have been common in most software systems. For large-scale software projects, developers usually conduct software maintenance tasks by utilizing software artifacts (e.g., bug reports). The severity of bug reports describes the impact of the bugs and determines how quickly it needs to be fixed. Bug triagers often pay close attention to some features such as severity to determine the importance of bug reports and assign them to the correct developers. However, a large number of bug reports submitted every day increase the workload of developers who have to spend more time on fixing bugs. In this paper, we collect question-and-answer pairs from Stack Overflow and use logical regression to predict the severity of bug reports. In detail, we extract all the posts related to bug repositories from Stack Overflow and combine them with bug reports to obtain enhanced versions of bug reports. We achieve severity prediction on three popular open source projects (e,g., Mozilla, Ecplise, and GCC) with Naive Bayesian, k-Nearest Neighbor algorithm (KNN), and Long Short-Term Memory (LSTM). The results of our experiments show that our model is more accurate than the previous studies for predicting the severity. Our approach improves by 23.03%, 21.86%, and 20.59% of the average F-measure for Mozilla, Eclipse, and GCC by comparing with the Naive Bayesian based approach which performs the best among all baseline approaches.

This paper analyzes the energy levels along the even-parity J = 1 and 2 Rydberg series of Sn I by multichannel quantum defect theory. A good agreement between theoretical and experimental energy levels was achieved. Below 59198 cm−1, a total of 85 and 23 new energy levels, respectively, in the J = 1 and J = 2 series, which cannot be measured previously by experiments, are predicted in this work. Based on the calculated admixture coefficients of each channel, interchannel interactions were discussed in detail. The results are helpful to understand the characteristics of configuration interaction among even-parity levels in Sn I.