Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases

Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completing code that requires intensive domain knowledge for example completing the library names. Although there are several works that have confirmed the effectiveness of fine-tuning techniques to adapt language models for code completion in specific domains. They are limited by the need for constant fine-tuning of the model when the project is in constant iteration. To address this limitation, in this paper, we propose $k$NM-LM, a retrieval-augmented language model (R-LM), that integrates domain knowledge into language models without fine-tuning. Different from previous techniques, our approach is able to automatically adapt to different language models and domains. Specifically, it utilizes the in-domain code to build the retrieval-based database decoupled from LM, and then combines it with LM through Bayesian inference to complete the code. The extensive experiments on the completion of intra-project and intra-scenario have confirmed that $k$NM-LM brings about appreciable enhancements when compared to CodeGPT and UnixCoder. A deep analysis of our tool including the responding speed, storage usage, specific type code completion, and API invocation completion has confirmed that $k$NM-LM provides satisfactory performance, which renders it highly appropriate for domain adaptive code completion. Furthermore, our approach operates without the requirement for direct access to the language model's parameters. As a result, it can seamlessly integrate with black-box code completion models, making it easy to integrate our approach as a plugin to further enhance the performance of these models.Comment: Accepted by ASE202

Structural-semantics Guided Program Simplification for Understanding Neural Code Intelligence Models

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The odontoblastic differentiation of dental mesenchymal stem cells: molecular regulation mechanism and related genetic syndromes

Dental mesenchymal stem cells (DMSCs) are multipotent progenitor cells that can differentiate into multiple lineages including odontoblasts, osteoblasts, chondrocytes, neural cells, myocytes, cardiomyocytes, adipocytes, endothelial cells, melanocytes, and hepatocytes. Odontoblastic differentiation of DMSCs is pivotal in dentinogenesis, a delicate and dynamic process regulated at the molecular level by signaling pathways, transcription factors, and posttranscriptional and epigenetic regulation. Mutations or dysregulation of related genes may contribute to genetic diseases with dentin defects caused by impaired odontoblastic differentiation, including tricho-dento-osseous (TDO) syndrome, X-linked hypophosphatemic rickets (XLH), Raine syndrome (RS), hypophosphatasia (HPP), Schimke immuno-osseous dysplasia (SIOD), and Elsahy-Waters syndrome (EWS). Herein, recent progress in the molecular regulation of the odontoblastic differentiation of DMSCs is summarized. In addition, genetic syndromes associated with disorders of odontoblastic differentiation of DMSCs are discussed. An improved understanding of the molecular regulation and related genetic syndromes may help clinicians better understand the etiology and pathogenesis of dentin lesions in systematic diseases and identify novel treatment targets

Language reorganization patterns in global aphasia–evidence from fNIRS

BackgroundExploring the brain reorganization patterns associated with language recovery would promote the treatment of global aphasia. While functional near-infrared spectroscopy (fNIRS) has been widely used in the study of speech and language impairment, its application in the field of global aphasia is still limited.AimsWe aimed to identify cortical activation patterns of patients with global aphasia during naming and repetition tasks.Methods and proceduresWe recruited patients with post-stroke aphasia from the Department of Rehabilitation Medicine at Huashan Hospital. These individuals were diagnosed with global aphasia without cognitive impairments, as assessed by speech-language pathology evaluations. Age- and sex-matched healthy controls were recruited from the greater Shanghai area. During fNIRS measurement, patients and healthy controls completed the picture-naming and phrase repetition task. Cortical activation patterns on each of these language tasks were then compared between groups.Outcomes and resultsA total of nine patients with global aphasia and 14 healthy controls were included in this study. Compared with the healthy subjects, patients with global aphasia showed increased activation in the left Broca's area, middle temporal gyrus (MTG), superior temporal gyrus (STG), and pre-motor and supplementary motor cortex (SMA) (p < 0.05) in the picture-naming task. Furthermore, the latency of the oxyhemoglobin (HbO) concentration in the left supramarginal gyrus (SMG) region had a strong negative correlation with their score of the naming task (p < 0.01). In the phrase repetition task, decreased activation was detected in the left SMA and SMG (p < 0.05) of patients relative to controls.ConclusionThe left SMG plays a critical role in the language function of patients with global aphasia, especially in their abilities to name and repeat. fNIRS is a promising approach to revealing the changes in brain activities in patients with aphasia, and we believe it will contribute to a deeper understanding of the neurological mechanisms and the establishment of a novel treatment approach for global aphasia

Rescheduling Oriented Dependent Tasks Spread Domain Computing

Abstract: To narrow the scope of rescheduling tasks is one of the effective ways to improve the grid dependent tasks rescheduling efficiency. For how to determine the scope which should improve the efficiency of rescheduling problem as far as possible without affecting the application performance, this paper proposed the rescheduling tasks spread domain concept and its method of computation. Beginning with a minimum tasks set to rescheduling, the computing process is oriented by resource share conflict and data transmission dependent of tasks, and limited by the degree of task to optimize the performance of the whole application. Experimentation results show that static scheduling strategy could maintain the performance advantages compare with the dynamic strategy, thus the efficiency of proposed rescheduling tasks spread domain is validated

Rescheduling Oriented Dependent Tasks Spread Domain Computing

To narrow the scope of rescheduling tasks is one of the effective ways to improve the grid dependent tasks rescheduling efficiency. For how to determine the scope which should improve the efficiency of rescheduling problem as far as possible without affecting the application performance, this paper proposed the rescheduling tasks spread domain concept and its method of computation. Beginning with a minimum tasks set to rescheduling, the computing process is oriented by resource share conflict and data transmission dependent of tasks, and limited by the degree of task to optimize the performance of the whole application. Experimentation results show that static scheduling strategy could maintain the performance advantages compare with the dynamic strategy, thus the efficiency of proposed rescheduling tasks spread domain is validated

Correlationship between self-assembly behavior and emulsion stabilization of pea protein-high methoxyl pectin complexes treated with ultrasound at pH 2.0

This study investigated the effects of ultrasound on the self-assembly behavior of pea protein (PP)-high methoxyl pectin (HMP) complexes at pH 2.0 through transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and intrinsic fluorescence analysis. The emulsion stabilization mechanism of PP-HMP treated with ultrasound (PP-HMP-US) was also elucidated. The results indicated that ultrasound increased the emulsifying activity index (EAI) and emulsifying stability index (ESI) of PP-HMP. Moreover, PP-HMP-US-based emulsions formed small, dispersed oil drops, which were stable during storage. PP-HMP- and PP-HMP-US-based emulsions did not demonstrate any creaming. The TEM results revealed that ultrasound can regulate the self-assembly behavior of PP and HMP to form spherical particles with a core–shell structure. This structure possessed low turbidity, a small particle size, and high absolute zeta potential values. The FTIR and intrinsic fluorescence spectra demonstrated that ultrasound increased the α-helix and β-sheet contents and exposed the tryptophan groups to more hydrophilic environments. Ultrasound also promoted the PP-HMP self-assembly through electrostatic interaction and improved its oil–water interfacial behavior, as indicated by the EAI and ESI values of PP-HMP-US-based emulsions. The current results provide a reference for the development of an innovative emulsifier prepared by ultrasound-treated protein–pectin complexes at low pH

Engineering placenta‐like organoids containing endogenous vascular cells from human‐induced pluripotent stem cells

Abstract The placenta is an essential organ that maintains the health of both the fetus and its mother. Understanding the development of human placenta has been hindered by the limitations of existing animal models and monolayer cell cultures. Models that can recapitulate the essential aspects of human placental multicellular components and vasculature are still lacking. Herein, we presented a new strategy to establish placenta‐like organoids with vascular‐like structures from human‐induced pluripotent stem cells in a defined three‐dimensional (3D) culture system. The resulting placenta‐like tissue resembles first‐trimester human placental development in terms of complex placental components and secretory function. The multicellular tissue was characterized by the inclusion of trophoblasts (cytotrophoblasts, syncytiotrophoblasts, extravillous trophoblasts, and other endogenous vascular cells), which were identified by immunofluorescence, flow cytometry analyses, real‐time quantitative reverse transcription polymerase chain reaction and single‐cell RNA‐seq. Moreover, the 3D tissue was able to secrete the placenta‐specific hormone human chorionic gonadotropin β (hCG‐β) and vascular endothelial growth factor A (VEGFA). The tissue responded to the inflammatory factor tumor necrosis factor‐α (TNF‐α) and VEGF receptor inhibitors. This new model system can represent the major features of placental cellular components, and function, which have not been realized in 2D monolayer cultures. The developed tissue system might open new avenues for studying normal early human placental development and its disease states

A New In Situ Coaxial Capacitive Sensor Network for Debris Monitoring of Lubricating Oil

Wear debris monitoring of lubricant oil is an important method to determine the health and failure mode of key components such as bearings and gears in rotatory machines. The permittivity of lubricant oil can be changed when the wear debris enters the oil. Capacitive sensing methods showed potential in monitoring debris in lubricant due to the simple structure and good response. In order to improve the detection sensitivity and reliability, this study proposes a new coaxial capacitive sensor network featured with parallel curved electrodes and non-parallel plane electrodes. As a kind of through-flow sensor, the proposed capacitive sensor network can be in situ integrated into the oil pipeline. The theoretical models of sensing mechanisms were established to figure out the relationship between the two types of capacitive sensors in the sensor network. The intensity distributions of the electric field in the coaxial capacitive sensor network are simulated to verify the theoretical analysis, and the effects of different debris sizes and debris numbers on the capacitance values were also simulated. Finally, the theoretical model and simulation results were experimentally validated to verify the feasibility of the proposed sensor network

The Somatic Mutational Landscape of Mismatch Repair Deficient Prostate Cancer

Prostate cancers with mismatch repair deficiency (MMR-d) have aggressive clinical and histological features, and they are potentially responsive to immunotherapy. However, its rarity prevents the analysis of the underlying biology. Here, we collected the genomic data of 2664 primary prostate tumors and 1409 metastatic prostate tumors from the GENIE and TCGA databases. A total of 69 (2.59%) primary and 60 (4.26%) metastatic MMR-d tumors were identified among these tumors. Single nucleotide variant (SNV) frequencies of 34 candidate genes (including KMT2D (46.4%), ZFHX3 (33.3%), JAK1 (31.9%), and RNF43 (27.5%)) and 16 candidate genes (including KMT2D (33.3%) and JAK1 (28.3%)) were higher in MMR-d primary tumors and MMR-d metastatic tumors, respectively. The tumor mutation burden (TMB) was higher in primary MMR-d tumors. Homozygous deletions of EPCAM and EPAS1 were enriched in MMR-d primary tumors, while EPCAM deletions were enriched in metastatic MMR-d tumors. For genomic rearrangement events, TMPRSS2-ETS fusions were less frequent in primary MMR-d tumors. Our study indicates MMR-d prostate cancers have unique genomic features. These may play an important role in providing therapeutic targets for the treatment of this subset of prostate cancer patients