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The importance of effective teacher-child interactions in preschool classrooms has been well documented; however, very few studies examined the difference between novice and experienced teachers. The aim of this study was to quantitatively compare the characteristics and patterns of teacher-child interactions during preschool picture book reading activities between novice and experienced teachers. Video observation data were collected from nine novice teachers and nine experienced teachers from a Chinese preschool, and were coded using the Flanders Interaction Analysis System. A total of 7,642 codes of experienced teachers and 6,444 codes of novice teachers were obtained. Aside from some commonalities, results indicated that there were several major differences between novice and experienced teachers. The indirect and positive influence on children, and the rate of positive influence to negative influence of experienced teachers were higher than that of novice teachers; the proportion of teacher talk, positive integration grid, steady-state grid, open question, and indirect response of novice teachers were higher than that of experienced teachers. The findings shed light on how novice and experienced teachers interact with their children, and how professional development supports should be delivered differently to novice and experienced teachers.

AIM: To investigate Omicron's impact on clinical presentation of acute primary angle closure (APAC) in China. METHODS: A consecutive case series with historical controls was conducted at Shenzhen Eye Hospital, the largest specialized hospital in Shenzhen, China. Medical records from a two-month period during the Omicron pandemic (December 1, 2022, to January 31, 2023) were compared with records from two control groups (12/2018–1/2019 and 12/2021–1/2022) before pandemic. Patients with APAC were included, and the prevalence of APAC and demographic characteristics in Omicron-infected and non-infected patients were compared. RESULTS: Seventy-one (23.43%) out of 303 patients were diagnosed with APAC in the pandemic cohort, which was 2.98 and 2.61 times higher than that in control cohorts (7.87% in 2019, 8.96% in 2022, P

Wild soybean (Glycine soja), a relative of cultivated soybean, shows high adaptability to adverse environmental conditions. We identified and characterized a wild soybean transcription factor gene, GsWRKY40, that promotes plant salt stress. GsWRKY40 was highly expressed in wild soybean roots and was up-regulated by salt treatment. GsWRKY40 was localized in nucleus and demonstrated DNA-binding activities but without transcriptional activation. Mutation and overexpression of GsWRKY40 altered salt tolerance of Arabidopsis plants. To understand the molecular mechanism of GsWRKY40 in regulating plant salt resistance, we screened a cDNA library and identified a GsWRKY40 interacting protein GsbHLH92 by using yeast two-hybrid approach. The physical interaction of GsWRKY40 and GsbHLH92 was confirmed by co-immunoprecipitation (co-IP), GST pull-down, and bimolecular fluorescence complementation (BiFC) techniques. Intriguingly, co-overexpression of GsWRKY40 and GsbHLH92 resulted in higher salt tolerance and lower ROS levels than overexpression of GsWRKY40 or GsbHLH92 in composite soybean plants, suggesting that GsWRKY40 and GsbHLH92 may synergistically regulate plant salt resistance through inhibiting ROS production. qRT-PCR data indicated that the expression level of GmSPOD1 gene encoding peroxidase was cooperatively regulated by GsWRKY40 and GsbHLH92, which was confirmed by using a dual luciferase report system and yeast one-hybrid experiment. Our study reveals a pathway that GsWRKY40 and GsbHLH92 collaboratively up-regulate plant salt resistance through impeding GmSPOD1 expression and reducing ROS levels, providing a novel perspective on the regulatory mechanisms underlying plant tolerance to abiotic stresses.

Abstract Topological domain structures have drawn great attention as they have potential applications in future electronic devices. As an important concept linking the quantum and classical magnetism, a magnetic Bloch point, predicted in 1960s but not observed directly so far, is a singular point around which magnetization vectors orient to nearly all directions. Here we show polar Bloch points in tensile-strained ultrathin ferroelectric PbTiO3 films, which are alternatively visualized by phase-field simulations and aberration-corrected scanning transmission electron microscopic imaging. The phase-field simulations indicate local steady-state negative capacitance around the Bloch points. The observation of polar Bloch points and their emergent properties consequently implies novel applications in future integrated circuits and low power electronic devices.

Abstract Background The ectopic superior parathyroid in the tracheoesophageal groove and paraesophageal region is rare. Hyperparathyroidism results when these glands become hyperfunctioning. That may necessitate surgical intervention in the form of parathyroidectomy, which requires a transsternal or transthoracic approach due to a deeply seated mediastinal parathyroid gland. Minimally invasive strategies have emerged recently as an alternative approach with less morbidity. Case presentation We present a case of the paraesophageal ectopic parathyroid gland in the superior posterior mediastinum, which was successfully treated with thoracoscopic resection. Conclusion The current imaging tools improve the thoracoscopic management of mediastinal parathyroid glands. Video-assisted thoracoscopic surgery (VATS) can provide access and exposure to ectopic parathyroid adenoma with low morbidity and financial burden.

Levulinic acid, a hydrolysis product of lignocellulose, can be metabolized into important compounds in the field of medicine and pesticides by engineered strains of Saccharomyces cerevisiae. Levulinic acid, as an intermediate product widely found in the conversion process of lignocellulosic biomass, has multiple applications. However, its toxicity to Saccharomyces cerevisiae reduces its conversion efficiency, so screening Saccharomyces cerevisiae genes that can tolerate levulinic acid becomes the key. By creating a whole-genome knockout library and bioinformatics analysis, this study used the phenotypic characteristics of cells as the basis for screening and found the HMX1 gene that is highly sensitive to levulinic acid in the oxidative stress pathway. After knocking out HMX1 and treating with levulinic acid, the omics data of the strain revealed that multiple affected pathways, especially the expression of 14 genes related to the cell wall and membrane system, were significantly downregulated. The levels of acetyl-CoA and riboflavin decreased by 1.02-fold and 1.44-fold, respectively, while the content of pantothenic acid increased. These findings indicate that the cell wall-membrane system, as well as the metabolism of acetyl-CoA and riboflavin, are important in improving the resistance of Saccharomyces cerevisiae to levulinic acid. They provide theoretical support for enhancing the tolerance of microorganisms to levulinic acid, which is significant for optimizing the conversion process of lignocellulosic biomass to levulinic acid.

Abstract Background The use of adjuvant chemotherapy (ACT) in completely resected stage IB NSCLC is still controversial. This study aims to investigate the efficacy of ACT in pathological stage IB non-small cell lung cancer (NSCLC) with high risk factors. Methods Patients with pT2aN0M0 stage IB NSCLC who underwent complete resection from 2013 to 2017 were retrospectively analyzed. Univariate and multivariable logistic regression analysis was used to assess potential independent risk factors associated with poor prognosis. To compare survival between patients who received ACT and those who did not. Results In univariate and multivariate analyses, adenocarcinomas with predominantly micropapillary (MIP) and solid patterns (SOL), poorly differentiated squamous cell carcinoma (SCC), number of lymph nodes dissected less than 16 and tumor size larger than 36 mm were identified as high-risk factors for recurrence. In patients with high risk factors for recurrence, ACT resulted in significantly longer DFS (HR, 0.4689, 95%CI, 1.193–3.818; p = 0.0108) and OS (HR, 0.4696, 95%CI, 0.6578–6.895; p = 0.2073), although OS failed to reach statistically significance. After propensity score matching (PSM), 67 pairs of patients were 1:1 matched in the two groups and all baseline characteristics were well balanced. The results also demonstrated that ACT was associated with improved DFS (HR, 0.4776, 95%CI, 0.9779–4.484; p = 0.0440) while OS was not significantly different (92.5% vs. 91.0%; HR, 0.6167, 95%CI, 0.1688–2.038; p = 0.7458). In patients with low-risk factors for recurrence, DFS (HR, 0.4831, 95%CI, 0.03025-7.715; p = 0.6068) and OS (HR, 0.969, 95%CI, 0.08364-11.21; p = 0.9794) was not significantly different between those who received ACT and those who did not. Conclusion In patients with completely resected stage IB NSCLC, ACT can improve survival in patients with high risk for recurrence. Further large multicenter studies are needed to confirm these findings.

Landslides, prevalent in mountainous areas, are typically triggered by tectonic movements, climatic changes, and human activities. They pose catastrophic risks, especially when occurring near settlements and infrastructure. Therefore, detecting, monitoring, and predicting landslide deformations is essential for geo-risk mitigation. The mainstream of the previous studies have often focused on deterministic models for immediate landslide prediction. However, in most of them, the aspect of prediction uncertainties are not sufficiently addressed. This paper introduces an innovative probabilistic prediction method using a Variational Autoencoder (VAE) combined with Gated Recurrent Unit (GRU) to forecast landslide deformations from a generative standpoint. Our approach consists of two main elements: firstly, training the VAE-GRU model to maximize the variational lower bound on the likelihood of historical precipitation data; secondly, using the learned approximated posterior distribution to predict imminent deformations from a generative angle. To assess the prediction quality, we use four widely-used metrics: Prediction Interval Coverage Probability (PICP), Prediction Interval Normalized Average Width (PINAW), Coverage Width-Based Criterion (CWC), and Prediction Interval Normalized Root Mean Square Width (PINRW). The results demonstrate that our proposed VAE-GRU framework surpasses traditional state-of-the-art (SOTA) probabilistic deformation prediction algorithms in terms of accuracy and reliability.

Engineering Saccharomyces cerevisiae for biodegradation and transformation of industrial toxic substances such as catechol (CA) has received widespread attention, but the low tolerance of S. cerevisiae to CA has limited its development. The exploration and modification of genes or pathways related to CA tolerance in S. cerevisiae is an effective way to further improve the utilization efficiency of CA. This study identified 36 genes associated with CA tolerance in S. cerevisiae through genome-wide identification and bioinformatics analysis and the ERG6 knockout strain (ERG6Δ) is the most sensitive to CA. Based on the omics analysis of ERG6Δ under CA stress, it was found that ERG6 knockout affects pathways such as intrinsic component of membrane and pentose phosphate pathway. In addition, the study revealed that 29 genes related to the cell wall-membrane system were up-regulated by more than twice, NADPH and NADP+ were increased by 2.48 and 4.41 times respectively, and spermidine and spermine were increased by 2.85 and 2.14 times, respectively, in ERG6Δ. Overall, the response of cell wall-membrane system, the accumulation of spermidine and NADPH, as well as the increased levels of metabolites in pentose phosphate pathway are important findings in improving the CA resistance. This study provides a theoretical basis for improving the tolerance of strains to CA and reducing the damage caused by CA to the ecological environment and human health.

Low-light imaging capabilities are in urgent demand in many fields, such as security surveillance, night-time autonomous driving, wilderness rescue, and environmental monitoring. The excellent performance of SPAD devices gives them significant potential for applications in low-light imaging. This article presents a 64 (rows) × 128 (columns) SPAD image sensor designed for low-light imaging. The chip utilizes a three-dimensional stacking architecture and microlens technology, combined with compact gated pixel circuits designed with thick-gate MOS transistors, which further enhance the SPAD’s photosensitivity. The configurable digital control circuit allows for the adjustment of exposure time, enabling the sensor to adapt to different lighting conditions. The chip exhibits very low dark noise levels, with an average DCR of 41.5 cps at 2.4 V excess bias voltage. Additionally, it employs a denoising algorithm specifically developed for the SPAD image sensor, achieving two-dimensional grayscale imaging under 6 × 10−4 lux illumination conditions, demonstrating excellent low-light imaging capabilities. The chip designed in this paper fully leverages the performance advantages of SPAD image sensors and holds promise for applications in various fields requiring low-light imaging capabilities.

In order to research the characteristics of minitype neutron reference radiation field regulated by ISO 8529 series standards, Monte Carlo simulation method was applied to calculate the ratio of room-scattered neutron response to the direct neutron response, neutron fluence and energy spectra in the radiation field. Firstly, the characteristics of the field were investigated from the four physical factors as shielding materials, field sizes, shielding thicknesses and borated polyethylene with different boron contents. Secondly, the response of sphere instrument with different diameters in the field and the influence of instrument on the field were analyzed. The results showed that minitype neutron reference radiation field with a size of 2 m × 2 m × 2 m, a shielding material of 5 % borated polyethylene and a shielding thickness of 10 cm was expected to be used for the calibration of neutron measuring instrument.

With the development of biometric identification technology, finger vein identification has received more and more widespread attention for its security, efficiency, and stability. However, because of the performance of the current standard finger vein image acquisition device and the complex internal organization of the finger, the acquired images are often heavily degraded and have lost their texture characteristics. This makes the topology of the finger veins inconspicuous or even difficult to distinguish, greatly affecting the identification accuracy. Therefore, this paper proposes a finger vein image recovery and enhancement algorithm using atmospheric scattering theory. Firstly, to normalize the local over-bright and over-dark regions of finger vein images within a certain threshold, the Gamma transform method is improved in this paper to correct and measure the gray value of a given image. Then, we reconstruct the image based on atmospheric scattering theory and design a pixel mutation filter to segment the venous and non-venous contact zones. Finally, the degraded finger vein images are recovered and enhanced by global image gray value normalization. Experiments on SDUMLA-HMT and ZJ-UVM datasets show that our proposed method effectively achieves the recovery and enhancement of degraded finger vein images. The image restoration and enhancement algorithm proposed in this paper performs well in finger vein recognition using traditional methods, machine learning, and deep learning. The recognition accuracy of the processed image is improved by more than 10% compared to the original image.

More than 100,000 dams have been built in China and their safety conditions have drawn more attention to the stakeholders due to large socioeconomic effects, such as economic losses and casualties caused by dam incidents. Dam safety assessment was closely related to the safety conditions of various indicators and associated weights. However, traditional methods tended to adopt either the subjective weighting method (SWM) or the objective weighting method (OWM) to assess the weights of indicators, leading to an unreliable assessment of dam safety. To this end, this study proposed the game theory (GT)-based dam safety performance measure (DSPM) method to evaluate the safety level of dams. To assess the weights of all associated indicators of dams, the GT method that was used to capture the advantages of both the SWM and OWM was developed. The weights of each indicator were considered as variables and their values were obtained based on MATLAB. The DSPM that followed the form of the power-exponential function was proposed to assess dam safety. The whole method was exemplified by the five dams and the effectiveness of the proposed method was verified by comparing it with the code-based method (i.e., SL 258-2017). The results showed that the weights of indicators based on the analytic hierarchy process (AHP) method and the CRiteria Importance Through Intercriteria Correlation (CRITIC) method were different. The maximum and minimum percentage differences between the weights based on AHP and CRITIC methods were 107.4% and 3.1%, respectively, revealing that the weights obtained from only one method were unreliable. The proposed GT method was suitable for assessing the weights. Obtained superiority and inferiority rankings (SIRs) based on the GT-based DSPM and the code-based methods were consistent, which showed the effectiveness of the GT-based DSPM method. The code-based method concerning the dam safety levels was too rough to capture the dam performance accurately; the proposed method gave a more detailed classification, which provided important information on wise investments for the stakeholders when enhancing the performance of deficient dams.

The complex structure of Neogene mudstone plays an important role in geological disasters. A close relationship exists between the mechanisms of mudstone landslides and the disintegration characteristics of rocks. Therefore, understanding the disintegration characteristics of Neogene mudstone at different depths is crucial for enhancing engineering safety and assessing landslide stability. This study employed Neogene mudstone from different depths to perform disintegration and plastic limit experiments and revealed the sliding mechanisms of landslides involving Neogene mudstone, providing theoretical support for mitigating mudstone geological disasters. Our results demonstrate that Neogene mudstone from different depths experiences varied stress conditions and pore water pressure due to geological actions, significantly affecting the disintegration characteristics. By ignoring the factors of the slip surface, the slake durability index of mudstone decreases with increasing burial depth, while the plasticity limit index tends to rise. The influence of groundwater, geo-stress, and pore structure on Neogene mudstones at different depths results in overall weak stability and disintegration. Landslide occurrences are likely connected to the mechanical properties of mudstones at the slip surface, where a low slake durability index and higher plasticity index make the mudstones prone to fracturing, breaking, and disintegrating once in contact with water.