Generic Go to Go: Dictionary-Passing, Monomorphisation, and Hybrid

Go is a popular statically-typed industrial programming language. To aid the type safe reuse of code, the recent Go release (Go 1.18) published on 15th March 2022 includes bounded parametric polymorphism via generic types. Go 1.18 implements generic types using combination of monomorphisation and call-graph based dictionary-passing called hybrid. This hybrid approach can be viewed as an optimised form of monomorphisation that statically generates specialised methods and types based on possible instantiations. A monolithic dictionary supplements information lost during monomorphisation, and it is structured according to the program's call graph. Unfortunately, the hybrid approach still suffers from code bloat, poor compilation speed, and limited code coverage. In this paper we propose and formalise a new non-specialising call-site based dictionary-passing translation. Our call-site based translation creates individual dictionaries for each type parameter, with dictionary construction occurring in place of instantiation, overcoming the limitations of hybrid. We prove it correct using a novel and general bisimulation up to technique. To better understand how different generics translations approaches work in practice, we benchmark five translators, Go 1.18, two existing monomorphisation translators, our dictionary-passing translator, and erasure translator. Our findings reveal several suggestions for improvements for Go 1.18 -- specifically how to overcome the expressiveness limitations of generic Go, and improve compile time and compiled code size performance of Go 1.18.Comment: Full version of paper submitted to OOPSLA '2

miR-29c-3p represses the angiogenesis of esophageal squamous cell carcinoma by targeting SERPINH1 to regulate the Wnt signaling pathway

ABSTRACT Purpose: Esophageal squamous cell carcinoma (ESCC) is characterized by early metastasis and late diagnosis. miR-29c-3p is confirmed to repress angiogenesis in multiple tumor types. Yet, the functions of miR-29c-3p in the mechanism of ESCC angiogenesis, which were not sufficiently explored previously, were exactly what we investigated here at the molecular level. Methods: The mRNA level of miR-29c-3p and Serpin peptidase inhibitor clade H member 1 (SERPINH1) in ESCC tissues were assessed via bioinformatics analysis. Thereafter, miR-29c-3p and SERPINH1 (HSP47) mRNA level in ESCC cell lines was evaluated via quantitative real-time polymerase chain reaction. The effects of abnormal miR-29c-3p and SERPINH1 expression on ESCC cell viability, proliferation, migration, invasion, and HUVEC angiogenesis were examined via CCK8, colony formation, transwell, and angiogenesis assays, respectively. The protein levels of SERPINH1, vascular endothelial growth factor-A (VEGFA), Wnt-1, ?-catenin, and p-?-catenin were evaluated via Western blot. Expression of VEGFA secreted by ESCC cells was measured via enzyme-linked immunosorbent assay. Treatment with the Wnt activator BML-284 further revealed the way miR-29c-3p mediated the Wnt signaling pathway and its effects on angiogenesis. Results: Herein, we revealed a decrease of miR-29c-3p expression in ESCC tissues and cells, while the overexpressed miR-29c-3p could remarkably suppress ESCC cell progression, as well as HUVEC angiogenesis. Meanwhile, overexpressed miR-29c-3p notably downregulated VEGFA and repressed the Wnt signaling pathway. Treatment with the Wnt activator BML-284 could reverse the inhibition of HUVEC angiogenesis caused by miR-29c-3p. SERPINH1 was a downstream target of miR-29c-3p. SERPINH1 knockdown suppressed the malignant phenotypes of ESCC cells and impeded the Wnt signaling activation, while such suppression was reversed through miR-29c-3p inhibitor. Conclusions: We confirmed the mechanism that miR-29c-3p targeted SERPINH1, thus regulating angiogenesis in ESCC through the Wnt signaling pathway. It improves the understanding of angiogenesis in ESCC and offers new ideas for the research of ESCC treatment strategies in the future

A five-collagen-based risk model in lung adenocarcinoma: prognostic significance and immune landscape

As part of the tumor microenvironment (TME), collagen plays a significant role in cancer fibrosis formation. However, the collagen family expression profile and clinical features in lung adenocarcinoma (LUAD) are poorly understood. The objective of the present work was to investigate the expression pattern of genes from the collagen family in LUAD and to develop a predictive signature based on collagen family. The Cancer Genome Atlas (TCGA) samples were used as the training set, and five additional cohort samples obtained from the Gene Expression Omnibus (GEO) database were used as the validation set. A predictive model based on five collagen genes, including COL1A1, COL4A3, COL5A1, COL11A1, and COL22A1, was created by analyzing samples from the TCGA cohort using LASSO Cox analysis and univariate/multivariable Cox regression. Using Collagen-Risk scores, LUAD patients were then divided into high- and low-risk groups. KM survival analysis showed that collagen signature presented a robust prognostic power. GO and KEGG analyses confirmed that collagen signature was associated with extracellular matrix organization, ECM-receptor interaction, PI3K-Akts and AGE-RAGE signaling activation. High-risk patients exhibited a considerable activation of the p53 pathway and cell cycle, according to GSEA analysis. The Collage-Risk model showed unique features in immune cell infiltration and tumor-associated macrophage (TAM) polarization of the TME. Additionally, we deeply revealed the association of collagen signature with immune checkpoints (ICPs), tumor mutation burden (TMB), and tumor purity. We first constructed a reliable prognostic model based on TME principal component—collagen, which would enable clinicians to treat patients with LUAD more individually

Research on the Consumers' Willingness to Buy Traceable Pork with Different Quality Information: A Case Study of Consumers in Weifang, Shandong Province

The traceability system can effectively reduce the food safety risks, however, it is confronted with various problems during its implementation. In this context, the paper carried out a case study of consumers in Weifang, Shandong Province, and studied their willingness to pay the traceable pork with different quality information. The results indicated that, the consumers show high expectations towards the introduction of traceability system, and they tend to buy the traceable pork only with breeding and slaughter information; their behaviors of purchase are greatly influenced by the following factors: the consumers’ education, age, income, attention on food safety and whether there are pregnant family members, etc.

Analysis of Assistments Online Tutoring System and Accuplacer

There have been many approaches to improve student learning. In this study, we look at the ASSISTments online tutoring system to prove that instant feedback increases content learning. We find that by having a system that provides correctional feedback as well as instant tutoring, students learn the material presented to them, and do so at their own pace. After experimenting in one university, two high schools and one middle school, three of our experiments support the use of an online tutoring system. We compare this system to a stripped down version of ASSISTments to simulate a typical learning situation presented to students which receive packets of work to complete and potentially prepare them for and upcoming exam

Empirical Analysis of the Main Factors Influencing Rice Harvest Losses Based on Sampling Survey Data of 10 Provinces in China

Grain security should be a priority for the Chinese government when managing state affairs. The total rice production needs to remain stable at more than 200 million tons. However, there have been serious rice harvest losses, especially the harvest stage. In this study, the meaning of rice harvest losses was defined based on previous research findings on the definition of grain harvest losses and the realities in China. The current rice harvest losses in different areas in China were analyzed based on sampling survey data from 957 farmers in 10 provinces in China. On this basis, the main factors influencing rice harvest losses and their marginal effects were analyzed using the ordered multinomial logistic model. The survey found that 56.22% of respondents believed that rice harvest losses were 4% or lower in China, though there were differences among the province. The proportion of family rice-farming income, size of production area, level of mechanization, timely harvest, and operational meticulousness had negative effects on rice harvest losses. On the other hand, farmers' experience of employment as migrant workers had a positive effect on rice harvest losses. In addition, bad weather and short handedness during harvest significantly increased rice harvest losses