Approach to the application of ultrasonic technology to measuring physical properties of new building materials

739-746Non-metal ultrasonic testing analyzer could be used to measure the physical properities of new building materials. Taking a new subgrade material named municipal solid waste incineration bottom ash (MSWIBA) as an example, the feasibility that ultrasonic wave velocity was used to measure physical and mechanical properties of MSWIBA was analyzed according to studying the relationship between uniaxial compressive strength (σc), main differential stress peak value (σ1-σ3)max, cohesive force (c), internal friction angle (φ) and ultrasonic wave velocity. The feasibility that the Poisson's ratio computational formula of materials that owns cohesive force was analyzed whether it is suitable for use in MSWIBA. The dynamic elastic mechanics parameters were calculated based on elastic theory. The results show that there is a positive linear correlation relationship between σc, (σ1-σ3)max, c, φ, and ultrasonic wave velocity with the slope changing in a small scope. The Poisson's ratio computational formula of materials that owns cohesive force is suitable for MSWIBA, and the Poisson's ratio is 0.20~0.28 with dry density being 1.5 g/cm3 within 28 days . The dynamic modulus of elasticity (E) and dynamic shear modulus (G) increase with curing age increasing (E, G =Alnθ+B); however, the dynamic Poisson's ratio decreases with curing age increasing

A frequency-domain full waveform inversion method of elastic waves in quantitative defection investigation

857-866Full waveform inversion is a challenging data-fitting procedure based on full wave field modeling to extract quantitative information on elastic properties of subsurface structures. We developed a frequency-domain full-waveform inversion method of elastic waves for stratified media, adopting a quasi-linearization method coupled with a random search algorithm. The inversion process of this method is irrelevant to hypocenter function and can be considered as a kind of combination between the heuristic and non-heuristic inversion methods. To verify our method, we apply it to three numerical two-dimensional models with different intermediate structures (dipping, arched and hollow), and their structures are well revealed. With some pretreatments on response waveforms, such as filtering, normalization and correlation analysis, the full-waveform inversion method is extended to models with damaged area and its feasibility and accuracy verified. Alignment of full waveform inversion method and its cost of computing, several strategies exist to treat this quantitative detecting problem. In Chengdu-Chongqing guest emergency project, the application of full waveform inversion method saves a lot of time. In this method, each section only needs 2 detectors and only need to be hammered twice, while the traditional CT (Computed Tomography) test requires 11 detection filters and at least 11 hammering, and each section has 121 waveform data. In some cases, we can obtain some important priori information through field investigation. The priori information can be used to accelerate the inversion process

INSTRUCTSCORE: Explainable Text Generation Evaluation with Finegrained Feedback

Automatically evaluating the quality of language generation is critical. Although recent learned metrics show high correlation with human judgement, these metrics can not explain their verdict or associate the scores with defects in generated text. To address this limitation, we present InstructScore, an explainable evaluation metric for text generation. By harnessing both explicit human instruction and the implicit knowledge of GPT-4, we fine-tune a text evaluation metric based on LLaMA, producing both a score for generated text and a human readable diagnostic report. We evaluate InstructScore on a variety of generation tasks, including translation, captioning, data-to-text and commonsense generation. Experiments show that our 7B model surpasses all other unsupervised metrics, including those based on 175B GPT-3 and GPT-4. Surprisingly, our InstructScore, even without direct supervision from human-rated data, achieves performance levels on par with state-of-the-art metrics like COMET22, which were fine-tuned on human ratings.Comment: Accepted to EMNLP2023 Main Conferenc

PARP inhibitor maintenance treatment for newly diagnosed ovarian cancer patients: a real-world study from China

PurposeThis study evaluated the efficacy and safety in a real-world population of epithelial ovarian cancer (EOC) treated with poly (ADP-ribose) polymerase inhibitor (PARPi) as first-line maintenance therapy in the largest gynecologic oncology center in Western China.MethodsThis study included patients newly diagnosed EOC who received PARPi as first-line maintenance therapy in West China Second University Hospital from August 1, 2018 to September 31, 2022. The primary endpoints were progression-free survival (PFS) and safety evaluated by Common Terminology Criteria for Adverse Events Version 5.0(CTCAE 5.0). The secondary endpoints were overall survival (OS) and prognostic factors influencing the PFS of patients in real world.ResultsAmong the eligible 164 patients, 104 patients received olaparib and 60 patients received niraparib. 100 patients (61.0%) had mutations in breast cancer susceptibility gene (BRCA). 87 patients (53.0%) received primary debulking surgery (PDS) while 77 patients (47.0%) received interval debulking surgery (IDS). 94 patients (94/164, 57.3%) achieved R0 and 39 patients (23.8%) achieved R1 after PDS/IDS. 112 (68.3%) achieved complete response (CR) after first-line chemotherapy, while 49 (29.9%) achieved partial response (PR). The median follow-up time was 17.0 months (95% CI 15.6-18.4), and the median PFS has not been reached yet. Multivariate analysis demonstrated that BRCA mutations and CR/PR after platinum-based chemotherapy were independent factors associated with prolonged PFS. Hematologic toxicity was the most common grade≥3 AE. There were no incidence of myelodysplastic syndromes/acute myelogenous leukemia (MDS/AML).ConclusionFocusing on PARPi as first-line maintenance therapy for patients with EOC, this study represented the largest single-center real-world study in China to date. Two independent factors were identified to prolong the PFS of patients: BRCA mutated type and CR/PR after primary treatment, which should be further confirmed with long-term follow-up and large sample sizes

Numerical Investigation on Dynamic Response Characteristics and Deformation Mechanism of a Bedded Rock Mass Slope Subject to Earthquake Excitation

In order to systematically reveal the dynamic response characteristics of rock mass slopes subject to seismic excitation, time-domain and frequency-domain analyses are used to investigate the dynamic response of a bedded rock slope from multiple perspectives, using the two-dimensional numerical dynamic analyses. Based on the numerical simulation results, the influence of the weak bedded structural planes on the propagation characteristics of seismic waves in the slope is analyzed. The time-domain analysis suggests that the topographic and geological conditions have an influence on the dynamic response of the slope. The effects of ground motion direction on the dynamic response characteristics of the slope are identified. In addition, according to the frequency-domain analysis, the impacts of slope surface, elevation, and structural plane on the seismic response characteristics of the slope are also clarified. The intrinsic characteristics of the slope are investigated by using Fourier spectral analysis and modal analysis, and the deformation response characteristics of the slope are clarified. The relationship between different natural frequencies of the slope, the predominant frequency of the seismic wave, and the dynamic response characteristics of the slope is discussed. Moreover, the dynamic failure mechanism of the slope is analyzed. This work provides a reference for the seismic analysis of this type of slope

Modeling landslide susceptibility based on convolutional neural network coupling with metaheuristic optimization algorithms

Landslides are one of the most common geological hazards worldwide, especially in Sichuan Province (Southwest China). The current study's main purposes are to explore the potential applications of convolutional neural networks (CNN) hybrid ensemble metaheuristic optimization algorithms, namely beluga whale optimization (BWO) and coati optimization algorithm (COA), for landslide susceptibility mapping in Sichuan Province (China). For this aim, fourteen landslide conditioning factors were compiled in a spatial database. The effectiveness of the conditioning factors in the development of the landslide predictive model was quantified using the linear support vector machine model. The receiver operating characteristic (ROC) curve (AUC), the root mean square error, and six statistical indices were used to test and compare the three resultant models. For the training dataset, the AUC values of the CNN-COA, CNN-BWO and CNN models were 0.946, 0.937 and 0.855, respectively. In terms of the validation dataset, the CNN-COA model exhibited a higher AUC value of 0.919, while the AUC values of the CNN-BWO and CNN models were 0.906 and 0.805, respectively. The results indicate that the CNN-COA model, followed by the CNN-BWO model, and the CNN model, offers the best overall performance for landslide susceptibility analysis

Characteristics and emergency mitigation of the 2018 Laochang landslide in Tianquan County, Sichuan Province, China

Abstract This paper describes a recent landslide event, which occurred at Liucheng village in Tianquan County, Sichuan Province, China, on July 15, 2018. The Laochang landslide described in this research is an outstanding and valuable reference for understanding the characteristics of such kind of landslides that are geologically similar to the landslide. The deformation characteristics of the landslide are investigated based on field investigations, drilled boreholes, and exploratory trenches. The 225 residents of 64 households living on the flat platform were threatened by the landslide. Therefore, to guarantee the safety of human life and property becomes the primary emergency task. The anti-sliding piles were taken to stabilize the landslide and mitigate impacts caused by the landslide. Based on the analysis of the monitoring data, the effectiveness of anti-sliding piles is evaluated. The results indicate that the anti-sliding piles are effective in increasing the stability of the landslide, and this work can provide a reference for similar slope engineering projects

Using Near-real-time Monitoring of Landslide Deformation to Interpret Hydrological Triggers in Jiudian Gorge Reservoir

2182-2190 Near-real-time data with fine temporal resolution have been collected through using GPS from 105 to 130 m, and a Fast Moving Zone can be spatially identified from Main Deformation Zone, and the temporal evolution of the landslide consists of a progression in time with short periods of Fast Movement (FM) and longer periods of slower movement. The failure mode of landslide affected by rainfall is studied based on GPS monitoring data with PFC 2D being used to simulated the failure process of rain-induced landslide. Results indicate that three FMs can be identified from 105 to 130 m, and any rapid continuous drawdown of the reservoir water level from 130 to 105 m will definitely trigger FM. In addition, rapid continuous water rise tends to trigger FM from approximately 115 to 130 m while it will not trigger FMs unless there is a continuous drawdown phase before. Generally, there is a lag time between water level fluctuation and FMs

The influence of reservoir filling on a preexisting bank landslide stability

291-300A new monitoring instrument (automatic GPS) was used to understand the relationship between the stability of landslide and the hydrological triggering factors in the process of reservoir filling. These factors were drawn from a study that reported on the relationship between surface movement and hydrological triggers of a typical reservoir landslide (Yanziping landslide) in Jiudian Gorge Reservoir (JGR). A Fast Moving Zone (FMZ) can be spatially identified from the Main Deformation Zone (MDZ), and the temporal evolution of the landslide consists of a progression in time with short periods of Fast Movement (FM) and longer periods of slower movement. The results indicate that three FMs could be identified, which are triggered by different factors. The continuous rapid water rise will definitely trigger FMs with the rainfall being the secondary role and the longer duration of rapid water rise is not conducive to the stability of landslide in the phase of 70～100 m. Rapid drawdown of reservoir water level also triggers FMs from 100 to 130 m. Besides, there is a lag time of approximately 5 days between FMs and rapid water rise. A most dangerous water level for the landslide movement also can be identified approximately 80 m. The sliding mode was changed by reservoir water storage. Near-real-time monitoring by GPS can provide more reliable and timely data, which is significantly important for disaster prevention and mitigation