Analysis of Research Papers on the Use of English Movies in Chinese Senior High School English Teaching in the Past Three Years

Much attention has been paid to using English movies in senior high school English teaching in China since the release of 2017 edition of Senior High School English Curriculum Standards that lists English Movie Appreciation as an optional compulsory course. Senior high school teachers have conducted substantial research over the past three years regarding the practical application of English movies in their teaching, yet there has been a lack of thorough and systematic of analysis of the large number of relevant papers published, which, more or less, limits the understanding and further advancements of this study area. This paper attempts, in light of the emerging systematic review methodology, to present an overview of the research papers spanning the period 2019 to 2022 on the use of English movies in Chinese senior high school from the four perspectives: language ability, cultural awareness, thinking quality, and learning ability based on the concept of core literacy of English as an academic discipline in the new curriculum standard. With focus on the discussion of the common problems and corresponding countermeasures that have been sorted out from the works of front-line teachers, the paper also puts forward suggestions and prospects for further studies

AMPose: Alternatively Mixed Global-Local Attention Model for 3D Human Pose Estimation

The graph convolutional networks (GCNs) have been applied to model the physically connected and non-local relations among human joints for 3D human pose estimation (HPE). In addition, the purely Transformer-based models recently show promising results in video-based 3D HPE. However, the single-frame method still needs to model the physically connected relations among joints because the feature representations transformed only by global relations via the Transformer neglect information on the human skeleton. To deal with this problem, we propose a novel method in which the Transformer encoder and GCN blocks are alternately stacked, namely AMPose, to combine the global and physically connected relations among joints towards HPE. In the AMPose, the Transformer encoder is applied to connect each joint with all the other joints, while GCNs are applied to capture information on physically connected relations. The effectiveness of our proposed method is evaluated on the Human3.6M dataset. Our model also shows better generalization ability by testing on the MPI-INF-3DHP dataset. Code can be retrieved at https://github.com/erikervalid/AMPose.Comment: ICASSP 2023 Accepted Pape

USimAgent: Large Language Models for Simulating Search Users

Due to the advantages in the cost-efficiency and reproducibility, user simulation has become a promising solution to the user-centric evaluation of information retrieval systems. Nonetheless, accurately simulating user search behaviors has long been a challenge, because users' actions in search are highly complex and driven by intricate cognitive processes such as learning, reasoning, and planning. Recently, Large Language Models (LLMs) have demonstrated remarked potential in simulating human-level intelligence and have been used in building autonomous agents for various tasks. However, the potential of using LLMs in simulating search behaviors has not yet been fully explored. In this paper, we introduce a LLM-based user search behavior simulator, USimAgent. The proposed simulator can simulate users' querying, clicking, and stopping behaviors during search, and thus, is capable of generating complete search sessions for specific search tasks. Empirical investigation on a real user behavior dataset shows that the proposed simulator outperforms existing methods in query generation and is comparable to traditional methods in predicting user clicks and stopping behaviors. These results not only validate the effectiveness of using LLMs for user simulation but also shed light on the development of a more robust and generic user simulators

Maximum Likelihood Estimation of Model Uncertainty in Predicting Soil Nail Loads Using Default and Modified FHWA Simplified Methods

Accuracy evaluation of the default Federal Highway Administration (FHWA) simplified equation for prediction of maximum soil nail loads under working conditions is presented in this study using the maximum likelihood method and a large amount of measured lower and upper bound nail load data reported in the literature. Accuracy was quantitatively expressed as model bias where model bias is defined as the ratio of measured to predicted nail load. The maximum likelihood estimation was carried out assuming normal and lognormal distributions of bias. Analysis outcomes showed that, based on the collected data, the default FHWA simplified nail load equation is satisfactorily accurate on average and the spread in prediction accuracy expressed as the coefficient of variation of bias is about 30%, regardless of the distribution type. Empirical calibrations were proposed to the default FHWA simplified nail load equation for accuracy improvement. The Bayesian Information Criterion was adopted to perform a comparison of suitability between the competing normal and lognormal statistical models that were intended for description of model bias. Example of reliability-based design of soil nail walls against internal pullout limit state of nails is provided in the end to demonstrate the benefit of performing model calibration and using calibrated model for design of soil nails

A New Approach of Waveform Interpretation Applied in Nondestructive Testing of Defects in Rock Bolts Based on Mode Identification

Due to the characteristics of dispersion of guided waves, the waveforms recorded in ultrasonic nondestructive testing (NDT) of rock bolts are complicated to interpret. With a goal to increase the inspection sensitivity and accuracy in NDT of rock bolts, an approach of waveform interpretation based on wave modes identification is developed. The numerical simulation of full rock bolt and rock bolts with grout defect by Finite Element Method (FEM) is applied to illustrate the approach; it is found that the sensitive and low attenuation wave modes exist. Laboratory tests on full rock bolt and rock bolt with grout loss using NDT are conducted to evaluate the efficacy of the approach of waveform interpretation. In addition to that, a parametric study was conducted on rock bolt models with different sectional defect size. Based on the waveform interpretation, the mode-based reflection coefficient R is proposed to evaluate the sensitivity of wave modes to the defect size of sectional area. It is found that the sensitivity of the wave mode does not change with the defect sectional area, and the amplitude depends on the size of the defect

Association Between the COVID-19 Pandemic and Infant Neurodevelopment:A Comparison Before and During COVID-19

Aim: To investigate the association between the experience of the coronavirus disease 2019 (COVID-19) pandemic and neurodevelopment of 6-month-old and 1-year-old children and explore the differences in the association by birth order. Methods: This comparison study was embedded in the Born in Guangzhou Cohort Study in China. The exposed group included 546 6-month-old and 285 1-year-old children who attended neurodevelopment assessments between March 1 and May 15, 2020, and the non-exposed group included 3,009 6-month-old and 2,214 1-year-old children during the same months from 2015 to 2019. Neurodevelopment at age 6 months and 1 year was assessed by trained clinical staff using the Ages and Stages Questionnaires, third edition (ASQ-3) and the Gesell Developmental Schedules (GDS). Results: The experience of the pandemic in 2020 was associated with a higher risk of delay in the fine motor (adjusted OR: 2.50, 95% CI: 1.25, 4.99; estimated by logistic regression) and communication (adjusted RR [aRR]: 1.13, 95% CI: 1.02, 1.25; estimated by log-binomial regression) domains at age 1 year. The association between the experience of the pandemic and communication delay at age 1 year only existed in first-born children (aRR: 1.15, 95% CI: 1.03, 1.30) but not in later-born children (aRR: 1.02, 95% CI: 0.84, 1.25). No associations were observed in any domain among 6-month-olds. Conclusion: Experiencing the COVID-19 pandemic and related public health strategies might be associated with a higher risk of delay in the development of fine motor and communication in 1-year-old children; the association observed in the communication domain only existed in first-born children

Electroacupuncture Regulates Hippocampal Synaptic Plasticity via miR-134-Mediated LIMK1 Function in Rats with Ischemic Stroke

MircoRNAs (miRs) have been implicated in learning and memory, by regulating LIM domain kinase (LIMK1) to induce synaptic-dendritic plasticity. The study aimed to investigate whether miRNAs/LIMK1 signaling was involved in electroacupuncture- (EA-) mediated synaptic-dendritic plasticity in a rat model of middle cerebral artery occlusion induced cognitive deficit (MICD). Compared to untreatment or non-acupoint-EA treatment, EA at DU20 and DU24 acupoints could shorten escape latency and increase the frequency of crossing platform in Morris water maze test. T2-weighted imaging showed that the MICD rat brain lesions were located in cortex, hippocampus, corpus striatum, and thalamus regions and injured volumes were reduced after EA. Furthermore, we found that the density of dendritic spine and the number of synapses in the hippocampal CA1 pyramidal cells were obviously reduced at Day 14 after MICD. However, synaptic-dendritic loss could be rescued after EA. Moreover, the synaptic-dendritic plasticity was associated with increases of the total LIMK1 and phospho-LIMK1 levels in hippocampal CA1 region, wherein EA decreased the expression of miR-134, negatively regulating LIMK1 to enhance synaptic-dendritic plasticity. Therefore, miR-134-mediated LIMK1 was involved in EA-induced hippocampal synaptic plasticity, which served as a contributor to improving learning and memory during the recovery stage of ischemic stroke

Toroidic phase transitions in a direct-kagome artificial spin ice

Ferrotoroidicity, the fourth form of primary ferroic order, breaks both space and time inversion symmetry. So far, direct observation of ferrotoroidicity in natural materials remains elusive, which impedes the exploration of ferrotoroidic phase transitions. Here, we overcome the limitations of natural materials using an artificial nanomagnet system that can be characterized at the constituent level and at different effective temperatures. We design a nanomagnet array as to realize a direct-kagome spin ice. This artificial spin ice exhibits robust toroidal moments and a quasi-degenerate ground state with two distinct low-temperature toroidal phases: ferrotoroidicity and paratoroidicity. Using magnetic force microscopy and Monte Carlo simulation, we demonstrate a phase transition between ferrotoroidicity and paratoroidicity, along with a crossover to a non-toroidal paramagnetic phase. Our quasi-degenerate artificial spin ice in a direct-kagome structure provides a model system for the investigation of magnetic states and phase transitions that are inaccessible in natural materials

Establishment of fracture blister model and analysis of plasma protein markers in rats

PurposeFracture blister (FB) is a frequent complication in orthopedic surgery. The primary objective of this study was to refine the animal model of FB and to identify plasma protein markers associated with its development and progression.MethodsIn this study, Sprague-Dawley (SD) rats were used as experimental subjects. Various pressures and compression durations were applied to the lower limbs of rats with fractures to compare the differential expression patterns (DEPs) between the pressure-time combination that resulted in the highest incidence of blisters and other groups. Subsequently, we investigated the variations in DEPs expression across different time intervals of the established model.ResultsOur findings indicate that following a lower limb fracture in SD rats, the highest incidence of blister formation was observed under conditions of 450 mmHg pressure and 9 hours of compression (46%, 7/15). In this group, the levels of CD44 and B2M were significantly elevated, while those of Activin R2A were reduced. Furthermore, we investigated the temporal profile of the group with the highest incidence of blister formation and found that CXCL16 and ROBO1 reached peak secretion 48 hours post-injury, followed by a subsequent decline. Additionally, the secretion of IL-2RG and IL-7 continued to increase 48 hours after the injury.Conclusionsthe increase of CD44 and B2M and the decrease of Activin R2A might be the potential influencing factors for the higher incidence of fracture blisters. CXCL16 and ROBO1 reached their peak 48 hours after the end of molding, and IL-2 RG and IL-7 R continued to increase 48 hours after the end of molding, which will provide a new direction for the study of the occurrence and development mechanism of fracture blisters

Magnetic nonreciprocity in a hybrid device of asymmetric artificial spin-ice-superconductors

Controlling the size and distribution of potential barriers within a medium of interacting particles can unveil unique collective behaviors and innovative functionalities. In this study, we introduce a unique superconducting hybrid device using a novel artificial spin ice structure composed of asymmetric nanomagnets. This structure forms a distinctive superconducting pinning potential that steers unconventional motion of superconducting vortices, thereby inducing a magnetic nonreciprocal effect, in contrast to the electric nonreciprocal effect commonly observed in superconducting diodes. Furthermore, the polarity of the magnetic nonreciprocity is in-situ reversible through the tunable magnetic patterns of artificial spin ice. Our findings demonstrate that artificial spin ice not only precisely modulates superconducting characteristics but also opens the door to novel functionalities, offering a groundbreaking paradigm for superconducting electronics