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Content and Language Integrated Learning (CLIL) has emerged as a pedagogical approach integrating foreign language learning with subject content. Nevertheless, its foray into the online environment, where courses are commonly delivered in two modes: asynchronous and synchronous, remains unexplored. By integrating synchronous delivery into an asynchronous-only online CLIL course, this study aims to probe how synchronous delivery affects students’ learning performances (learning behaviors and outcomes), and investigate learners’ perspectives on synchronous delivery as affordances for enhancing these performances. The study involved 969 learners and two teachers, with data collected from six sources for triangulation: tracking data from social media chat logs, website learning records, course scores, teachers’ reflective narratives, observation of synchronous learning, and student interviews. The findings unveil the effectiveness of synchronous delivery in promoting learning performances, evident in students’ proactive time management and interactive behaviors, as well as elevated learning outcomes. Three affordances – pedagogical, technological, and social – are offered by synchronous delivery for promoting learning performances. Particularly noteworthy are the social affordances, which significantly enhance learning behaviors and outcomes by fostering efficient interactions, cordial interpersonal relationships, and a learning community. [ABSTRACT FROM AUTHOR]

Special vehicles (SVs) are vehicles which conduct tasks such as the maintenance of urban roads and are typically characterized by travelling at a lower speed at a constant rate of speed within the same lane. In order to reduce the influence of SVs, guidance zone is designed and provides traffic guidance suggestions (TGS) for human‐driven vehicles (HVs) helping drivers for better decision between car‐following (CF) and lane‐changing (LC). To verify the effectiveness of TGS, an improved Dogit‐agent‐based model is established to simulate the captive and not captive choice of CF and LC for different driver types under TGS, and build the rules for mixed traffic flow of SV and HVs. Finally, a numerical simulation with a three‐lane system is conducted to analyze the traffic efficiency through a set of indicators, and the results show that the TGS can reduce the influence of SVs on traffic flow in a specific occupancy rates range, increase the cross‐section traffic volume by about 5%. The TGS also can increase the average speed of HVs in the lane behind SV by about 5% to 30%, and increase traffic density to 200% on the underutilized lane in the raw space in front of the SV. [ABSTRACT FROM AUTHOR]

The rapid expansion of urban rail transit necessitates accurate short-term passenger flow forecasts (STPFF) to optimize operation plans and enhance service quality. However, the existing STPFF methods do not fully consider the effect of built environment on passenger flow. In this regard, a convolutional long short-term memory neural network (CNN-LSTM) model incorporating built environment indicators has been proposed for accurately short-term passenger flow predictions. First, a system of built environment indicators (including 11 indicators), anchored in the 5Ds framework, is introduced to depict the characteristics of the built environments surrounding rail transit stations. Then, the random forest model (RF) is utilized to measure and rank the indicator importance. Finally, using historical passenger flow and key built environment indicators as input variables, a CNN-LSTM model for short-term passenger flow forecast is built. Taking Beijing city, China as an example for empirical research, the results show that CNN-LSTM model considering built environment can improve the accuracy of STPFF. Utilizing the top four key built environment indicators (the ratio of commercial land area, density of point of interest (POI) categories, and bus station density) as input variables can effectively reduce model computational complexity while concurrently enhancing predictive accuracy. The highest forecasting accuracy of the model is achieved at a time granularity of 5 min. This study can effectively support the operation and management of urban rail transit. [ABSTRACT FROM AUTHOR]

The occurrence of accidents in expressway weaving areas is significantly influenced by frequent lane change maneuvers. Acquiring the lane change behavior pattern characteristics of vehicles in this area can provide prior knowledge for autonomous vehicles when performing lane change maneuvers, which helps ensure the safety of autonomous vehicles. This study aims to extract lane change behavior patterns of vehicles in weaving areas, to analyze the distribution differences of patterns across different lane change maneuvers, and to explore risk characteristics during the lane change process. First, a lane-changing sequence segmentation method was designed based on the hierarchical Dirichlet process hidden semi-Markov model (HDP-HSMM) algorithm, taking into account the interaction with surrounding vehicles and risk factors. Second, the Gaussian mixture model latent Dirichlet allocation (GMM-LDA) algorithm was employed to cluster the segments and derive patterns of lane-changing behavior that include risk attributes. The trajectory data from the UCF SST dataset were used to validate the method framework and make an in-depth analysis. The results show that the behavior patterns obtained by this method are able to better describe the operational and risk states of the vehicle. Variations exist in the behavioral patterns of different types of lane change maneuvers throughout the entire process. Spatial distribution disparities exist in the behavior patterns of lane change maneuvers across various sections of weaving areas. The findings of this study provide behavioral characteristics of different types of lane change maneuvers in weaving areas, which might contribute to enhancing the accurate recognition of lane change behaviors by autonomous vehicles. [ABSTRACT FROM AUTHOR]

Objective To investigate the relationship between left atrial strain and microvascular complications in patients with type 2 diabetes mellitus (T2DM). Methods A total of 165 T2DM patients who admitted to in the Department of Endocrinology, the First Affiliated Hospital of Air Force Military Medical University from February to December 2023 were collected. The age, sex, duration of diabetes mellitus, use of rapid-acting insulin, use of long-acting insulin were collected, glycated hemoglobin A1c (HbA1c), total cholesterol (TC), urinary albumin to creatinine ratio (UACR) were detected, left ventricular global longitudinal strain (LVGLS), left atrial storage strain during reservoir phase (LASr), left atrial strain during conduit phase (LAScd), left atrial strain during contraction phase (LASct) were examined by two-dimensional spot tracking echocardiography. According to the number of microvascular complications of T2DM, the patients were divided into simple T2DM group (group A, 54 patients), T2DM with one complication group (group B, 69 patients), and T2DM with 2-3 complications group (group C, 42 patients). One-way analysis of variance was used to compare the baseline information, medication characteristics and biochemical indicators among the three groups. The relationship between left atrial strain parameters and microvascular complications of T2DM was evaluated by Spearman correlation analysis and logistic regression analysis. Results The LASr, LAScd, and LVGLS of patients in group C were lower than those in group A and group B, and the LASr, LAScd, LASct, and LVGLS of patients in group B were lower than those in group A (P<0.05). Spearman correlation analysis showed that the microvascular complications of diabetes mellitus were negatively correlated with left atrial strain parameters LASr (r=-0.381, P<0.001) and LAScd (r=-0.385, P<0.001), but not with LASct (r=-0.151, P>0.05). Logistic regression analysis showed that, after adjusting for age, sex, duration of diabetes mellitus, use of rapid-acting insulin, use of long-acting insulin, HbA1c, TC, UACR, and LVGLS, compared with group A, LASr (OR=0.932, 95%CI 0.871-0.998), LAScd (OR=0.910, 95%CI 0.840-0.987) in group B and LASr (OR=0.886, 95%CI 0.799-0.983) and LAScd (OR=0.823, 95%CI 0.719-0.942) in group C were influencing factors associated with complications (P<0.05). Conclusion The number of microvascular complications in T2DM patients was negatively correlated with left atrial strain parameters LASr and LAScd. [ABSTRACT FROM AUTHOR]

In recent years, terrorist attacks all over the world caused many civilian casualties seriously. Under the knife and axe terrorist attack, there are usually four groups of event-related persons, that is, pedestrians, terrorists, police, and safety guards in the scene. The behavior of them is different, but they are rarely considered together in existing litterateurs, especially the police and safety guards. In this paper, we propose the FFPS (extended floor-field model combined with on-site control actions of police and safety guards) model to study pedestrian evacuation dynamics considering terrorist attack on-site control action differences between police and security guards. The FFPS model consists of three aspects. First, pedestrian evacuation dynamics in terrorist attack environment is modeled. Second, the behavior of terrorists, police and safety guards is studied. Third, the differences of on-site control actions between police and safety guards are studied. We set up the scenario for simulation. The influence of terrorists' number and location, police and security guards' different actions, police entering time, police shooting distance, police and safety guards' spatial position, and police control strategy on evacuation dynamics are analyzed in detail. Those results provide valuable insights to quickly control terrorists, and sharply reduce casualties in terrorist attack environment. [ABSTRACT FROM AUTHOR]

Immune memory has been expanded to group 2 innate lymphoid cells (ILC2s), but the cellular and molecular bases remain incompletely understood. Based on house dust mite (HDM)-induced mice asthma models and human samples, we applied flow cytometry, parabiosis, in vivo imaging and adoptive transplantation to confirm the persistence, migration and function of CD45+lineage–CD90.2+NK1.1–NKp46–ST2–KLRG1+IL-17RB+ memory-like ILC2s (ml-ILC2s). Regulated by CCR9/CCL25 and S1P signaling, ml-ILC2s reside in the lamina propria of small intestines (siLP) in asthma remission, and subsequently move to airway upon re-encountering antigens or alarmins. Furthermore, ml-ILC2s possess properties of longevity, potential of rapid proliferation and producing IL-13, and display transcriptional characteristics with up-regulation of Tox and Tcf-7. ml-ILC2s transplantation restore the asthmatic changes abrogated by Tox and Tcf7 knockdown. Our data identify siLP ml-ILC2s as a memory-like subset, which promotes asthma relapse. Targeting TCF-1 and TOX might be promising for preventing asthma recurrence. TCF1 and TOX have been shown to be important in T memory cell formation. Here the authors show that TCF1 and TOX contribute to the regulation and persistence of memory-like ILC2 cells in mouse asthma models and persons with asthma. [ABSTRACT FROM AUTHOR]

Hg2+ is one of the most toxic heavy metals, posing a serious threat to the human body and the environmental ecosystem. In order to detect Hg2+ rapidly, accurately, and sensitively, a kind of boron, nitrogen, and sulfur co‐doped carbon dots (B,N,S‐CDs) were synthesized by a simple, economical, and direct hydrothermal method. The average size of the prepared B,N,S‐CDs is 2.7 ± 0.7 nm, and the high photoluminescence quantum yield is 67.6%. Furthermore, due to the efficient quenching effect of Hg2+, such B,N,S‐CDs are considered to serve as an efficient fluorescence sensing platform for label‐free and sensitive detection of Hg2+ with a detection limit of 72 nM. The selectivity experiments reveal that the B,N,S‐CDs are selective and specific for Hg2+ even in the presence of other interfering substances. Most importantly, the Hg2+ sensing platform based on B,N,S‐CDs can be successfully applied to the determination of Hg2+ in tap water and real lake water samples. This stable and inexpensive carbon material exhibits excellent sensitivity and selectivity, potentially suitable for Hg2+ monitoring in environmental applications. [ABSTRACT FROM AUTHOR]

Luteolin, a commonly used traditional Chinese medicine, has been utilized for several decades in the treatment of hepatocellular carcinoma (HCC). Previous research has demonstrated its anti‐tumour efficacy, but its underlying mechanism remains unclear. This study aimed to assess the therapeutic effects of luteolin in H22 tumour‐bearing mice. luteolin effectively inhibited the growth of solid tumours in a well‐established mouse model of HCC. High‐throughput sequencing revealed that luteolin treatment could enhance T‐cell activation, cell chemotaxis and cytokine production. In addition, luteolin helped sustain a high ratio of CD8+ T lymphocytes in the spleen, peripheral blood and tumour tissues. The effects of luteolin on the phenotypic and functional changes in tumour‐infiltrating CD8+ T lymphocytes were also investigated. Luteolin restored the cytotoxicity of tumour‐infiltrating CD8+ T lymphocytes in H22 tumour‐bearing mice. The CD8+ T lymphocytes exhibited intensified phenotype activation and increased production of granzyme B, IFN‐γ and TNF‐α in serum. The combined administration of luteolin and the PD‐1 inhibitor enhanced the anti‐tumour effects in H22 tumour‐bearing mice. Luteolin could exert an anti‐tumour immune response by inducing CD8+ T lymphocyte infiltration and enhance the anti‐tumour effects of the PD‐1 inhibitor on H22 tumour‐bearing mice. [ABSTRACT FROM AUTHOR]