Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks

Machine learning is gaining growing momentum in various recent models for the dynamic analysis of information flows in data communications networks. These preliminary models often rely on off-the-shelf learning models to predict from historical statistics while disregarding the physics governing the generating behaviors of these flows. This paper instead introduces Flow Neural Network (FlowNN) to improve the feature representation with learned physical bias. This is implemented by an induction layer, working upon the embedding layer, to impose the physics connected data correlations, and a self-supervised learning strategy with stop-gradient to make the learned physics universal. For the short-timescale network prediction tasks, FlowNN achieves 17% - 71% of loss decrease than the state-of-the-art baselines on both synthetic and real-world networking datasets, which shows the strength of this new approach. Code will be made available.Comment: re-organize the presentatio

Approximate Equivalence of the Hybrid Automata with Taylor Theory

Hybrid automaton is a formal model for precisely describing a hybrid system in which the computational processes interact with the physical ones. The reachability analysis of the polynomial hybrid automaton is decidable, which makes the Taylor approximation of a hybrid automaton applicable and valuable. In this paper, we studied the simulation relation among the hybrid automaton and its Taylor approximation, as well as the approximate equivalence relation. We also proved that the Taylor approximation simulates its original hybrid automaton, and similar hybrid automata could be compared quantitatively, for example, the approximate equivalence we proposed in the paper

Automata-Based Analysis of Stage Suspended Boom Systems

A stage suspended boom system is an automatic steeve system orchestrated by the PLC (programmable logic controller). Security and fault-recovering are two important properties. In this paper, we analyze and verify the boom system formally. We adopt the hybrid automaton to model the boom system. The forward reachability is used to verify the properties with the reachable states. We also present a case study to illustrate the feasibility of the proposed verification

Towards Understanding the Capability of Large Language Models on Code Clone Detection: A Survey

Code cloning, the duplication of code fragments, is common in software development. While some reuse aids productivity, excessive cloning hurts maintainability and introduces bugs. Hence, automatic code clone detection is vital. Meanwhile, large language models (LLMs) possess diverse code-related knowledge, making them versatile for various software engineering challenges. However, LLMs' performance in code clone detection is unclear and needs more study for accurate assessment. In this paper, we provide the first comprehensive evaluation of LLMs for clone detection, covering different clone types, languages, and prompts. We find advanced LLMs excel in detecting complex semantic clones, surpassing existing methods. Adding intermediate reasoning steps via chain-of-thought prompts noticeably enhances performance. Additionally, representing code as vector embeddings, especially with text encoders, effectively aids clone detection.Lastly, the ability of LLMs to detect code clones differs among various programming languages. Our study suggests that LLMs have potential for clone detection due to their language capabilities, offering insights for developing robust LLM-based methods to enhance software engineering.Comment: 13 pages, 3 figure

Pharmacologic inhibition of the Menin-MLL interaction blocks progression of MLL leukemia in vivo

Chromosomal translocations affecting mixed lineage leukemia gene (MLL) result in acute leukemias resistant to therapy. The leukemogenic activity of MLL fusion proteins is dependent on their interaction with menin, providing basis for therapeutic intervention. Here we report the development of highly potent and orally bioavailable small-molecule inhibitors of the menin-MLL interaction, MI-463 and MI-503, and show their profound effects in MLL leukemia cells and substantial survival benefit in mouse models of MLL leukemia. Finally, we demonstrate the efficacy of these compounds in primary samples derived from MLL leukemia patients. Overall, we demonstrate that pharmacologic inhibition of the menin-MLL interaction represents an effective treatment for MLL leukemias in vivo and provide advanced molecular scaffold for clinical lead identification

Plant 45S rDNA Clusters Are Fragile Sites and Their Instability Is Associated with Epigenetic Alterations

Our previous study demonstrated that 45S ribosomal DNA (45S rDNA) clusters were chromosome fragile sites expressed spontaneously in Lolium. In this study, fragile phenotypes of 45S rDNA were observed under aphidicolin (APH) incubation in several plant species. Further actinomycin D (ActD) treatment showed that transcriptional stress might interfere with chromatin packaging, resulting in 45S rDNA fragile expression. These data identified 45S rDNA sites as replication-dependent as well as transcription-dependent fragile sites in plants. In the presence of ActD, a dramatic switch to an open chromatin conformation and accumulated incomplete 5′ end of the external transcribed spacer (5′ETS) transcripts were observed, accompanied by decreased DNA methylation, decreased levels of histone H3, and increased histone acetylation and levels of H3K4me2, suggesting that these epigenetic alterations are associated with failure of 45S rDNA condensation. Furthermore, the finding that γ-H2AX was accumulated at 45S rDNA sites following ActD treatment suggested that the DNA damage signaling pathway was associated with the appearance of 45S rDNA fragile phenotypes. Our data provide a link between 45S rDNA transcription and chromatin-packaging defects and open the door for further identifying the molecular mechanism involved

Nectin2 influences cell apoptosis by regulating ANXA2 expression in neuroblastoma

Neuroblastoma (NB) is a pediatric cancer of the peripheral sympathetic nervous system and represents the most frequent solid malignancy in infants. Nectin2 belongs to the immunoglobulin superfamily and has been shown to play a role in tumorigenesis. In the current study, we demonstrate that serum Nectin2 level is increased in NB patients compared with that in healthy controls and Nectin2 level is correlated with neuroblastoma international neuroblastoma staging system (INSS) classification. There is a positive correlation between Nectin2 level and shorter overall survival in NB patients. Knockdown of Nectin2 reduces the migration of SH-SY5Y and SK-N-BE2 cells and induces their apoptosis and cell cycle arrest. RNA-seq analysis demonstrates that Nectin2 knockdown affects the expressions of 258 genes, including 240 that are upregulated and 18 that are downregulated compared with negative controls. qRT-PCR and western blot analysis confirm that ANXA2 expression is decreased in Nectin2-knockdown SH-SY5Y cells, consistent with the RNA-seq results. ANXA2 overexpression rescues the percentage of apoptotic NB cells induced by Nectin2 knockdown and compensates for the impact of Nectin2 knockdown on cleaved caspase3 and bax expressions. In addition, western blot analysis results show that ANXA2 overexpression rescues the effect of Nectin2 knockdown on MMP2 and MMP9 expressions. The current data highlight the importance of Nectin2 in NB progression and the potential of Nectin2 as a novel candidate target for gene therapy

Effects of Simultaneous Application of Double Chelating Agents to Pb-Contaminated Soil on the Phytoremediation Efficiency of Indocalamus decorus Q. H. Dai and the Soil Environment

Recent studies have shown that the combined application of ethylenediaminetetraacetic acid (EDTA) and degradable chelating agents can enhance EDTA’s affinity for heavy metals and reduce its toxicity, but the effect of this combination on the phytoremediation remains largely unknown. This study evaluated and compared the effects of EDTA, nitrilotriacetic acid (NTA), and glutamic acid-N,N-diacetic acid (GLDA) alone (E, N, G treatment), and in combination (EN and EG treatment), on the growth of dwarf bamboo (Indocalamus decorus Q. H. Dai), their phytoremediation efficiency, and the soil environment in Pb-contaminated soil. The results showed that treatment E significantly reduced the biomass, while treatments N and EN were more conducive to the distribution of aerial plant biomass. Except for treatment E, the total Pb accumulation in all treatments increased significantly, with the highest increase in treatment EN. For double chelating agents, the acid-soluble Pb concentrations in rhizosphere and non-rhizosphere soils of treatments EN and EG were lower than those of treatment E, and the soil water-soluble Pb content after 20 days of treatment EN was significantly lower than that of treatment EG. Furthermore, chelating agents generally increased soil-enzyme activity in rhizosphere soil, indicating that chelating agents may promote plant heavy-metal uptake by changing the rhizosphere environment. In conclusion, treatment EN had the highest phytoremediation efficiency and significantly lower environmental risk than treatments E and EG, highlighting its massive potential for application in phytoremediation of Pb-contaminated soil when combined with I. decorus