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Bone morphogenetic protein 4 (BMP4) is crucial for the development of the inner ear, but the mechanism of how BMP4 affects this process remains unknown. The focus of this research was to determine whether BMP4 can regulate the survival of cochlear sensory epithelial cells through inhibitor of differentiation 1 (Id1) and the epidermal growth factor receptor (EGFR). In this study, we first investigated the effects of BMP4, noggin, and dominant negative BMPR1B (dnBMPR1B) on the proliferation and survival of cochlear sensory epithelial cells. Subsequently, we investigated the influences of BMP4, noggin, and dnBMPR1B on the expression of Id1 and EGFR. We found that BMP4 had a negative effect on cell survival and on Id1 and EGFR expression in vitro, whereas noggin and dnBMPR1B treatment had positive effects. Knockdown of the Id1 gene with short interfering RNA (siRNA) reduced the expression of EGFR and cell proliferation. These data suggest that BMP4 may regulate survival through the Id1/EGFR pathway during development of the rat inner ear.

This study investigates the main climatological features of extreme precipitation (TCER) induced by tropical cyclones (TCs) affecting Guangxi (GX), South China using multiple datasets and a 99th percentile threshold during 1981–2020, with an emphasis on the rainfall diversities of different high-impact TC groups and their associated mechanisms. Results show that there are large regional differences and a seasonal imbalance in the climatological features of TCER in GX. In summer (fall), TCs with TCER events primarily move northward or eastward (northwestward or westward), namely, S-NWTCs and S-ETCs (F-WTCs and F-NWTCs). The rainfall centers exhibit asymmetrical features with S-NWTCs and F-NWTCs located in the northeast quadrant, but S-ETCs and F-WTCs in the southwest and northeast quadrants, respectively. Comparisons of atmospheric circulations and environmental factors indicate that the intense rainfall of F-WTCs is mainly attributed to the trough–TC interaction, which is accompanied by stronger upper-level westerly jet and cold air intrusion, thus increasing baroclinic energy and uplifting for the strongest rainfall among these four groups. This interaction is absent for other groups due to a greater South Asian high and western North Pacific subtropical high. Instead, the increased rainfall in S-NWTCs and F-NWTCs can mainly be attributed to the stronger low-level southwesterly jet, which, in combination with low-level warm advection and convergence induced by land–sea friction, promotes the release of latent heat through moisture condensation. S-ETCs differ from S-NWTCs and F-NWTCs in that moisture convergence is weaker due to the much-weakened TC circulation.

The traditional linear statistical forecast method is often used to address the large inter-annual variation and nonlinear characteristics of summer drought and flood trends in Guangxi, but the forecast accuracy is low. In this study, the inter-annual increment of the average precipitation in August was used to forecast drought and flood trends. By calculating the correlation factor between the forecast and the previous 500 hPa monthly average height field, 81 preliminary forecast factors of the early monthly average circulation field were obtained. First, the random forest algorithm was employed to calculate and rank the importance of the 81 prediction factors and predictors, and the six most important characteristic variable factors were selected as the input of the prediction model of a deep learning long short-term memory (LSTM) network. Second, an attention mechanism was used to provide different attention values to the input variables of the model. Third, a prediction model for the inter-annual increment of average summer precipitation in Guangxi based on random forest and attention mechanism LSTM network (RF-LSTM-Attention) was established. When this prediction model was adopted to predict the average summer precipitation of the eight-year return sample in Guangxi (June–August) from 2013 to 2020, the average absolute percentage error of the model was 9.49%. The relative error percentage in eight years was greater than 30% (30.74%) in only one year (2014) and greater than 15% (19.65%) in another year (2013). The relative error of prediction in the six other years, especially in the years with maximum and minimum precipitation in the eight-year return sample, did not exceed 15%. The study further compared the prediction results of the same eight-year return sample of the prediction model with the LSTM model without the attention mechanism (the introduction factors of the model were the same). Results showed that the average absolute percentage prediction error was 10.88%, the relative error percentage in the same eight-year sample exceeded 30% (43.18%) only in 2014, and the prediction error was greater than that of the RF-LSTM-Attention model. Furthermore, the eight-year return sample forecast error of the forecast model was compared with the forecast results of the linear stepwise regression forecast model (5, 6, and 7 predictor variables were selected). The RF-LSTM-Attention model was approximately doubled and showed better forecast accuracy in qualitative and quantitative forecasting of the average summer precipitation in Guangxi.

The southern Tibetan Plateau (TP) is snow covered during cold season but exhibits faster snow melting in early summer. Using in situ observations and improved satellite-derived data, the present study indicates that the snow depth (SD) over the southern TP exhibits distinction characteristics between late spring (i.e., P1: April 16th–May 15th) and early summer (i.e., P2: May 16th–June 14th). In terms of climate states, the snow melting rate over the southern TP in P2 is faster than that in P1. The acceleration of snow melting during P2 is mainly found over high elevation areas caused by the increase of local air temperature. Diagnoses of the thermodynamic equation further demonstrate that the warming over the southern TP during the two periods is mainly attributed to the meridional temperature advection and diabatic heating in situ. On the interannual time scale, the SD over the southern TP is closely related to diabatic heating over South Asia. During P1, the diabatic cooling from the southern Bay of Bengal eastward to the western South China Sea suppresses convection over the Bay of Bengal and southern TP and has resulted in an upper-level anomalous cyclone and cold temperature anomalies from the surface to 200 hPa over the southern TP, favoring the above-normal SD over the southern TP. On the other hand, SD over the southern TP in P2 is closely related to diabatic cooling over the northern Indochina Peninsula and diabatic heating over the southern China. But we could not prove that these diabatic heating anomalies can affect the SD over the southern TP by modulating local surface air temperature. This may be limited by the quality of the data and the simulation capability of the simple model.

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Light-transmitting concrete prepared by the combination of light-transmitting materials and concrete matrix is a new building material with functions of energy saving and consumption reduction. In this paper, the current research status of scholars in this field at home and abroad is integrated and explored, so as to carry out the analysis of the interfacial bonding performance between the light-transmitting material and the concrete matrix of light-transmitting concrete. This paper selects acrylic as the light-transmitting material, silicate cement mortar, alkali magnesium sulfate cement mortar, ordinary mortar with cork particles, ordinary mortar with expansion agents, ordinary mortar with basalt fibers, and self-compacting cement mortar as the matrix materials, and tests the interfacial bonding performance of different substrates of light-transmitting concrete made by them. Through the interfacial bonding performance test and compressive strength test, the results of the study showed that the interfacial bonding between the concrete matrix and acrylic with the addition of basalt fibers was superior.