Dynamic Response and Safety Control of Newly Poured Secondary Lining Concrete under Large Section Tunnel Blasting-A Case Study of Longnan Tunnel of Ganshen High-speed Railway

The age of newly poured concrete is short, the cementation between aggregates is weak. At this time, the vibration will affect its performance. The secondary lining concrete newly poured in the tunnel is close to the work face and is susceptible to blasting vibration during construction. In order to study the safety threshold of blasting vibration velocity of newly poured secondary lining concrete in tunnels, the finite element model is established in ANSYS with the large-section Longnan tunnel project as an example. The attenuation law of vibration velocity in three directions of secondary lining under blasting load was analyzed by combining field blasting monitoring with numerical simulation, and the reliability of numerical simulation was verified. Through the numerical simulation results, the vibration velocity and von mises stress distribution of the newly poured secondary lining concrete of the tunnel are analyzed; combined with the dynamic tensile strength theory of concrete, the safety threshold of vibration velocity of newly poured secondary lining concrete of tunnel based on numerical calculation is established; through the indoor vibration test, taking the compressive strength and acoustic velocity of concrete as the indexes, the safety threshold of blasting vibration velocity of newly poured secondary lining concrete of tunnel based on shaking table test is obtained. Combined with the results of numerical simulation and vibration test, the safety threshold of blasting vibration velocity of newly poured secondary lining concrete in large-section tunnels is obtained, and the standard in this field is improved

Re-annotation of protein-coding genes in 10 complete genomes of Neisseriaceae family by combining similarity-based and composition-based methods.

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Arginine deiminase pathway is far more important than urease for acid resistance and intracellular survival in Laribacter hongkongensis: a possible result of arc gene cassette duplication

Title in Final Programme: Arginine deiminase pathway is far more important than urease for acid resistance in Laribacter hongkongensis: result of arc gene cassette duplicationPoster Session - Pathogenesis and animal models of bacterial infections: abstract no. P1122INTRODUCTION AND PURPOSE: Laribacter hongkongensis is a Gram-negative, urease-positive bacillus associated with invasive bacteremic infections in liver cirrhosis patients and fish-borne community- acquired gastroenteritis and traveler’s diarrhea (1-2). Its mechanisms of acid resistance are unknown. a complete urease cassette and two adjacent arc gene cassettes (encoding enzymes of ADI pathway) were found in the genome (3). In this study, we investigated the mechanism for resisting acidic environment in vitro, in macrophages and in a mouse model ...published_or_final_versio

Arginine Metabolism in Bacterial Pathogenesis and Cancer Therapy

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Arginine deiminase pathway is far more important than urease for acid resistance and intracellular survival in Laribacter hongkongensis: a possible result of arc gene cassette duplication

BACKGROUND: Laribacter hongkongensis is a Gram-negative, urease-positive bacillus associated with invasive bacteremic infections in liver cirrhosis patients and fish-borne community-acquired gastroenteritis and traveler's diarrhea. Its mechanisms of adaptation to various environmental niches and host defense evasion are largely unknown. During the process of analyzing the L. hongkongensis genome, a complete urease cassette and two adjacent arc gene cassettes were found. We hypothesize that the urease cassette and/or the arc gene cassettes are important for L. hongkongensis to survive in acidic environment and macrophages. In this study, we tested this hypothesis by constructing single, double and triple non-polar deletion mutants of the urease and two arc gene cassettes of L. hongkongensis using the conjugation-mediated gene deletion system and examining their effects in acidic environment in vitro, in macrophages and in a mouse model. RESULTS: HLHK9ureA, HLHK9ureC, HLHK9ureD and HLHK9ureE all exhibited no urease activity. HLHK9arcA1 and HLHK9arcA2 both exhibited arginine deiminase (ADI) activities, but HLHK9arcA1/arcA2 double deletion mutant exhibited no ADI activity. At pH 2 and 3, survival of HLHK9arcA1/arcA2 and HLHK9ureA/arcA1/arcA2 were markedly decreased (p < 0.001) but that of HLHK9ureA was slightly decreased (p < 0.05), compared to wild type L. hongkongensis HLHK9. Survival of HLHK9ureA/arcA1/arcA2 and HLHK9arcA1/arcA2 in macrophages were also markedly decreased (p < 0.001 and p < 0.01 respectively) but that of HLHK9ureA was slightly decreased (p < 0.05), compared to HLHK9, although expression of arcA1, arcA2 and ureA genes were all upregulated. Using a mouse model, HLHK9ureA exhibited similar survival compared to HLHK9 after passing through the murine stomach, but survival of HLHK9arcA1/arcA2 and HLHK9ureA/arcA1/arcA2 were markedly reduced (p < 0.01). CONCLUSIONS: In contrast to other important gastrointestinal tract pathogens, ADI pathway is far more important than urease for acid resistance and intracellular survival in L. hongkongensis. The gene duplication of the arc gene cassettes could be a result of their functional importance in L. hongkongensis.published_or_final_versio

Observation of isoprene hydroxynitrates in the southeastern United States and implications for the fate of NO_x

Isoprene hydroxynitrates (IN) are tracers of the photochemical oxidation of isoprene in high NO_x environments. Production and loss of IN have a significant influence on the NO_x cycle and tropospheric O_3 chemistry. To better understand IN chemistry, a series of photochemical reaction chamber experiments was conducted to determine the IN yield from isoprene photooxidation at high NO concentrations (> 100 ppt). By combining experimental data and calculated isomer distributions, a total IN yield of 9(+4/−3) % was derived. The result was applied in a zero-dimensional model to simulate production and loss of ambient IN observed in a temperate forest atmosphere, during the Southern Oxidant and Aerosol Study (SOAS) field campaign, from 27 May to 11 July 2013. The 9 % yield was consistent with the observed IN/(MVK+MACR) ratios observed during SOAS. By comparing field observations with model simulations, we identified NO as the limiting factor for ambient IN production during SOAS, but vertical mixing at dawn might also contribute (~ 27 %) to IN dynamics. A close examination of isoprene's oxidation products indicates that its oxidation transitioned from a high-NO dominant chemical regime in the morning into a low-NO dominant regime in the afternoon. A significant amount of IN produced in the morning high NO regime could be oxidized in the low NO regime, and a possible reaction scheme was proposed

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation

Large language models (LLMs) frequently hallucinate and produce factual errors, yet our understanding of why they make these errors remains limited. In this study, we delve into the underlying mechanisms of LLM hallucinations from the perspective of inner representations, and discover a salient pattern associated with hallucinations: correct generations tend to have sharper context activations in the hidden states of the in-context tokens, compared to the incorrect ones. Leveraging this insight, we propose an entropy-based metric to quantify the ``sharpness'' among the in-context hidden states and incorporate it into the decoding process to formulate a constrained decoding approach. Experiments on various knowledge-seeking and hallucination benchmarks demonstrate our approach's consistent effectiveness, for example, achieving up to an 8.6 point improvement on TruthfulQA. We believe this study can improve our understanding of hallucinations and serve as a practical solution for hallucination mitigation.Comment: code repo is available at: https://github.com/hkust-nlp/Activation_decoding.gi

DialogRE^C+: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs

Dialogue relation extraction (DRE) that identifies the relations between argument pairs in dialogue text, suffers much from the frequent occurrence of personal pronouns, or entity and speaker coreference. This work introduces a new benchmark dataset DialogRE^C+, introducing coreference resolution into the DRE scenario. With the aid of high-quality coreference knowledge, the reasoning of argument relations is expected to be enhanced. In DialogRE^C+ dataset, we manually annotate total 5,068 coreference chains over 36,369 argument mentions based on the existing DialogRE data, where four different coreference chain types namely speaker chain, person chain, location chain and organization chain are explicitly marked. We further develop 4 coreference-enhanced graph-based DRE models, which learn effective coreference representations for improving the DRE task. We also train a coreference resolution model based on our annotations and evaluate the effect of automatically extracted coreference chains demonstrating the practicality of our dataset and its potential to other domains and tasks.Comment: Accepted by NLPCC 202

Bayesian updating of soil-water character curve parameters based on the monitor data of a large-scale landslide model experiment

It is important to determine the soil-water characteristic curve (SWCC) for analyzing landslide seepage under varying hydrodynamic conditions. However, the SWCC exhibits high uncertainty due to the variability inherent in soil. To this end, a Bayesian updating framework based on the experimental data was developed to investigate the uncertainty of the SWCC parameters in this study. The objectives of this research were to quantify the uncertainty embedded within the SWCC and determine the critical factors affecting an unsaturated soil landslide under hydrodynamic conditions. For this purpose, a large-scale landslide experiment was conducted, and the monitored water content data were collected. Steady-state seepage analysis was carried out using the finite element method (FEM) to simulate the slope behavior during water level change. In the proposed framework, the parameters of the SWCC model were treated as random variables and parameter uncertainties were evaluated using the Bayesian approach based on the Markov chain Monte Carlo (MCMC) method. Observed data from large-scale landslide experiments were used to calculate the posterior information of SWCC parameters. Then, 95% confidence intervals for the model parameters of the SWCC were derived. The results show that the Bayesian updating method is feasible for the monitoring of data of large-scale landslide model experiments. The establishment of an artificial neural network (ANN) surrogate model in the Bayesian updating process can greatly improve the efficiency of Bayesian model updating