Program Translation via Code Distillation

Software version migration and program translation are an important and costly part of the lifecycle of large codebases. Traditional machine translation relies on parallel corpora for supervised translation, which is not feasible for program translation due to a dearth of aligned data. Recent unsupervised neural machine translation techniques have overcome data limitations by included techniques such as back translation and low level compiler intermediate representations (IR). These methods face significant challenges due to the noise in code snippet alignment and the diversity of IRs respectively. In this paper we propose a novel model called Code Distillation (CoDist) whereby we capture the semantic and structural equivalence of code in a language agnostic intermediate representation. Distilled code serves as a translation pivot for any programming language, leading by construction to parallel corpora which scale to all available source code by simply applying the distillation compiler. We demonstrate that our approach achieves state-of-the-art performance on CodeXGLUE and TransCoder GeeksForGeeks translation benchmarks, with an average absolute increase of 12.7% on the TransCoder GeeksforGeeks translation benchmark compare to TransCoder-ST

SUT: Active Defects Probing for Transcompiler Models

Automatic Program translation has enormous application value and hence has been attracting significant interest from AI researchers. However, we observe that current program translation models still make elementary syntax errors, particularly, when the target language does not have syntax elements in the source language. Metrics like BLUE, CodeBLUE and computation accuracy may not expose these issues. In this paper we introduce a new metrics for programming language translation and these metrics address these basic syntax errors. We develop a novel active defects probing suite called Syntactic Unit Tests (SUT) which includes a highly interpretable evaluation harness for accuracy and test scoring. Experiments have shown that even powerful models like ChatGPT still make mistakes on these basic unit tests. Specifically, compared to previous program translation task evaluation dataset, its pass rate on our unit tests has decreased by 26.15%. Further our evaluation harness reveal syntactic element errors in which these models exhibit deficiencies

Strength and plasticity of amorphous silicon oxycarbide

Amorphous SiOC films were synthesized by magnetron sputtering at room temperature with/without radio frequency (RF) bias and further improved in terms of mechanical properties by ion irradiation. As-deposited SiOC films without RF bias exhibit catastrophic failure at a low stress and strain, which is ascribed to microstructural heterogeneities associated with the formation of voids during deposition, as evidenced by transmission electron microscopy. Ion irradiation unifies microstructure accompanied with eliminating the voids, resulting in a simultaneously increase in strength and plasticity (ultimate strength of 5–7 GPa and the strain to shear instability of over 20%). Homogeneous microstructures are demonstrated to ensure high strength and plasticity of amorphous SiOC, as observed in SiOC that are deposited with RF-bias. Thus, microstructural homogeneous amorphous SiOC exhibits intrinsically high strength and plasticity, making them promising as structural engineering materials. Includes supplementary material

Prism: Revealing Hidden Functional Clusters from Massive Instances in Cloud Systems

Ensuring the reliability of cloud systems is critical for both cloud vendors and customers. Cloud systems often rely on virtualization techniques to create instances of hardware resources, such as virtual machines. However, virtualization hinders the observability of cloud systems, making it challenging to diagnose platform-level issues. To improve system observability, we propose to infer functional clusters of instances, i.e., groups of instances having similar functionalities. We first conduct a pilot study on a large-scale cloud system, i.e., Huawei Cloud, demonstrating that instances having similar functionalities share similar communication and resource usage patterns. Motivated by these findings, we formulate the identification of functional clusters as a clustering problem and propose a non-intrusive solution called Prism. Prism adopts a coarse-to-fine clustering strategy. It first partitions instances into coarse-grained chunks based on communication patterns. Within each chunk, Prism further groups instances with similar resource usage patterns to produce fine-grained functional clusters. Such a design reduces noises in the data and allows Prism to process massive instances efficiently. We evaluate Prism on two datasets collected from the real-world production environment of Huawei Cloud. Our experiments show that Prism achieves a v-measure of ~0.95, surpassing existing state-of-the-art solutions. Additionally, we illustrate the integration of Prism within monitoring systems for enhanced cloud reliability through two real-world use cases.Comment: The paper was accepted by the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023

Prominent Size Effects without a Depolarization Field Observed in Ultrathin Ferroelectric Oxide Membranes

The increasing miniaturization of electronics requires a better understanding of material properties at the nanoscale. Many studies have shown that there is a ferroelectric size limit in oxides, below which the ferroelectricity will be strongly suppressed due to the depolarization field, and whether such a limit still exists in the absence of the depolarization field remains unclear. Here, by applying uniaxial strain, we obtain pure in-plane polarized ferroelectricity in ultrathin SrTiO3 membranes, providing a clean system with high tunability to explore ferroelectric size effects especially the thickness-dependent ferroelectric instability with no depolarization field. Surprisingly, the domain size, ferroelectric transition temperature, and critical strain for room-temperature ferroelectricity all exhibit significant thickness dependence. These results indicate that the stability of ferroelectricity is suppressed (enhanced) by increasing the surface or bulk ratio (strain), which can be explained by considering the thickness-dependent dipole-dipole interactions within the transverse Ising model. Our study provides new insights into ferroelectric size effects and sheds light on the applications of ferroelectric thin films in nanoelectronics

TMK1-mediated auxin signalling regulates differential growth of the apical hook

The plant hormone auxin has crucial roles in almost all aspects of plant growth and development. Concentrations of auxin vary across different tissues, mediating distinct developmental outcomes and contributing to the functional diversity of auxin. However, the mechanisms that underlie these activities are poorly understood. Here we identify an auxin signalling mechanism, which acts in parallel to the canonical auxin pathway based on the transport inhibitor response1 (TIR1) and other auxin receptor F-box (AFB) family proteins (TIR1/AFB receptors)1,2, that translates levels of cellular auxin to mediate differential growth during apical-hook development. This signalling mechanism operates at the concave side of the apical hook, and involves auxin-mediated C-terminal cleavage of transmembrane kinase 1 (TMK1). The cytosolic and nucleus-translocated C terminus of TMK1 specifically interacts with and phosphorylates two non-canonical transcriptional repressors of the auxin or indole-3-acetic acid (Aux/IAA) family (IAA32 and IAA34), thereby regulating ARF transcription factors. In contrast to the degradation of Aux/IAA transcriptional repressors in the canonical pathway, the newly identified mechanism stabilizes the non-canonical IAA32 and IAA34 transcriptional repressors to regulate gene expression and ultimately inhibit growth. The auxin–TMK1 signalling pathway originates at the cell surface, is triggered by high levels of auxin and shares a partially overlapping set of transcription factors with the TIR1/AFB signalling pathway. This allows distinct interpretations of different concentrations of cellular auxin, and thus enables this versatile signalling molecule to mediate complex developmental outcomes

Manipulating Multiple Order Parameters via Oxygen Vacancies: The case of Eu0.5Ba0.5TiO3-{\delta}

Controlling functionalities, such as magnetism or ferroelectricity, by means of oxygen vacancies (VO) is a key issue for the future development of transition metal oxides. Progress in this field is currently addressed through VO variations and their impact on mainly one order parameter. Here we reveal a new mechanism for tuning both magnetism and ferroelectricity simultaneously by using VO. Combined experimental and density-functional theory studies of Eu0.5Ba0.5TiO3-{\delta}, we demonstrate that oxygen vacancies create Ti3+ 3d1 defect states, mediating the ferromagnetic coupling between the localized Eu 4f7 spins, and increase an off-center displacement of Ti ions, enhancing the ferroelectric Curie temperature. The dual function of Ti sites also promises a magnetoelectric coupling in the Eu0.5Ba0.5TiO3-{\delta}.Comment: Accepted by Physical Review B, 201

The role of anti-aquaporin 4 antibody in the conversion of acute brainstem syndrome to neuromyelitis optica

Background: Acute brainstem syndrome (ABS) may herald multiple sclerosis (MS), neuromyelitis optica (NMO), or occur as an isolated syndrome. The aquaporin 4 (AQP4)-specific serum autoantibody, NMO-IgG, is a biomarker for NMO. However, the role of anti-AQP4 antibody in the conversion of ABS to NMO is unclear.Methods: Thirty-one patients with first-event ABS were divided into two groups according to the presence of anti-AQP4 antibodies, their clinical features and outcomes were retrospectively analyzed.Results: Fourteen of 31 patients (45.16 %) were seropositive for NMO-IgG. The 71.43 % of anti-AQP4 (+) ABS patients converted to NMO, while only 11.76 % of anti-AQP4 (-) ABS patients progressed to NMO. Anti-AQP4 (+) ABS patients demonstrated a higher IgG index (0.68 ± 0.43 vs 0.42 ± 0.13, p

Construction of a high-density genetic map for faba bean (Vicia faba L.) and quantitative trait loci mapping of seed-related traits

Faba bean (Vicia faba L.) is a valuable legume crop and data on its seed-related traits is required for yield and quality improvements. However, basic research on faba bean is lagging compared to that of other major crops. In this study, an F2 faba bean population, including 121 plants derived from the cross WY7×TCX7, was genotyped using the Faba_bean_130 K targeted next-generation sequencing genotyping platform. The data were used to construct the first ultra-dense faba bean genetic map consisting of 12,023 single nucleotide polymorphisms markers covering 1,182.65 cM with an average distance of 0.098 cM. The map consisted of 6 linkage groups, which is consistent with the 6 faba bean chromosome pairs. A total of 65 quantitative trait loci (QTL) for seed-related traits were identified (3 for 100-seed weight, 28 for seed shape, 12 for seed coat color, and 22 for nutritional quality). Furthermore, 333 candidate genes that are likely to participate in the regulation of seed-related traits were also identified. Our research findings can provide a basis for future faba bean marker-assisted breeding and be helpful to further modify and improve the reference genome