Expression Patterns and Gonadotropin Regulation of the TGF-β II Receptor (Bmpr2) during Ovarian Development in the Ricefield Eel Monopterus albus

Bmpr2 plays a central role in the regulation of reproductive development in mammals, but its role during ovarian development in fish is still unclear. To ascertain the function of bmpr2 in ovarian development in the ricefield eel, we isolated and characterized the bmpr2 cDNA sequence; the localization of Bmpr2 protein was determined by immunohistochemical staining; and the expression patterns of bmpr2 in ovarian tissue incubated with FSH and hCG in vitro were analyzed. The full-length bmpr2 cDNA was 3311 bp, with 1061 amino acids encoded. Compared to other tissues, bmpr2 was abundantly expressed in the ovary and highly expressed in the early yolk accumulation (EV) stages of the ovary. In addition, a positive signal for Bmpr2 was detected in the cytoplasm of oocytes in primary growth (PG) and EV stages. In vitro, the expression level of gdf9, the ligand of bmpr2, in the 10 ng/mL FSH treatment group was significantly higher after incubation for 4 h than after incubation for different durations. However, bmpr2 expression in the 10 ng/mL FSH treatment group at 2 h, 4 h and 10 h was significantly lower. Importantly, the expression level of bmpr2 and gdf9 in the 100 IU/mL hCG group had similar changes that were significantly decreased at 4 h and 10 h. In summary, Bmpr2 might play a pivotal role in ovarian growth in the ricefield eel, and these results provide a better understanding of the function of bmpr2 in ovarian development and the basic data for further exploration of the regulatory mechanism of gdf9 in oocyte development.     

Sensing Leakage of Electrolytes from Magnesium Batteries Enabled by Natural AIEgens

The potential for leakage of liquid electrolytes from magnesium (Mg) batteries represents a large hurdle to future application. Despite this, there are no efficient sensing technologies to detect the leakage of liquid electrolytes. Here, we developed a sensor using laccaic acid (L-AIEgen), a naturally occurring aggregation-induced emission luminogen (AIEgens) isolated from the beetle Laccifer lacca. L-AIEgen showed good selectivity and sensitivity for Mg²⁺, a universal component of electrolytes in Mg batteries. Using L-AIEgen, we then produced a smart film (L-AIE-F) that was able to sense leakage of electrolytes from Mg batteries. L-AIE-F showed a strong “turn-on” AIE-active fluorescence at the leakage point of electrolyte from model Mg batteries. To the best of our knowledge, this is the first time that AIE technology has been used to sense the leakage of electrolytes.     

赤泥和钛白废液中提钪的浸出工艺研究

通过对赤泥中物相组成及钪的分布状态分析,提出将赤泥和钛白废液这两种工业废弃物酸碱中和后,再进行钪的提取。试验结果表明,赤泥和钛白废液浸出过程中对钪浸出率影响最大的是液固比,其次为浸出温度,而浸出时间的影响最小。浸出工艺的优化条件为液固比为3∶1,60℃下浸出30min时,浸出体系的过滤性能良好,浸出液中硫酸浓度为1.81 mol/L,其稳定性良好,钪富集浓度为28.4mg/L,钪浸出率为69.75%。     

表面织构形貌参数影响润滑性能的三维CFD分析

为研究在流体润滑条件下,表面微织构形貌参数对润滑性能的影响,建立考虑空化效应的单织构三维计算模型。用CFD方法模拟织构在不同深度、面积密度和表面形状条件下,油膜承载力、摩擦因数和压力分布的变化情况。结果表明:随着织构深度(面积密度)的增加,油膜的承载力先增大后减小,摩擦因数先减小后增大,即织构存在最优的深度和面积密度使得流体动压润滑性能最优;随着上壁面滑移速度的增大,织构的最优深度有减小的趋势,而最优面积密度趋于稳定;设计具有汇流作用的织构表面形状可以提高油膜的承载力,且速度越大,改善润滑的效果越明显。     

自然崩落法诱发井下泥石流降雨临界阈值试验

诱发井下泥石流灾害的降雨阈值是矿山井下泥石流防控重要参数。为获得普朗铜矿诱发井下泥石流的降雨临界阈值,以室内试验为研究方法,开展矿区不同降雨强度工况下诱发井下泥石流的降雨阈值及暴发时间研究。结果表明：当雨强为0.563 mL/min时发生破坏性较大井下泥石流概率较大,当雨强为0.293 mL/min时诱发井下泥石流概率较小,当雨强为0.186 mL/min时则不易形成井下泥石流;降雨强度0.293 mL/min是井下泥石流发生的极限临界状态,是诱发井下泥石流的降雨阈值;降雨强度0.563 mL/min时,3~#、4~#和2~#不同放矿口诱发井下泥石流的暴发时间分别为240、260和220 min;降雨强度0.293 mL/min时,3~#、4~#和2~#放矿口诱发井下泥石流的暴发时间分别为180、200和220 min;最后基于水量总量原理验证了试验确定降雨临界阈值的科学性和合理性。研究成果为普朗铜矿及类似矿山井下泥石流的预防和管控提供重要的科学理论依据。     

蒸汽冷凝水管线频繁腐蚀穿孔问题的研究与解决对策

通过水质分析,查找蒸汽冷凝水管频繁腐蚀穿孔的原因.结果表明,因水质中含有超量的O2及存在CO2,是腐蚀产生的主要原因.同时管材本身及安装过程中的残余应力,对腐蚀起到了促进的作用.最后根据分析结果提出了防腐蚀措施.     

基于ADIS16354的姿态角传感器设计

介绍了ADIS16354器件(陀螺仪和加速度计集成传感器)的基本功能;利用TMS320F2812 DSP搭建了一个硬件平台并通过SPI接口完成对ADIS16354的控制、数据采集和状态查询;结合捷联惯性导航系统姿态解算算法及DSP快速解算的特点实现了载体的俯仰角和倾斜角的测量;编写上位机程序实现对ADIS16354的配置和解算结果的实时显示。在无磁转台上进行了静态和动态条件下的测试,结果表明:该姿态角传感器具有较高的角度稳定度(陀螺漂移率小于0.02°/s)和准确度,抗磁干扰能力强,可广泛用于在工业自动化、导航定位、航空航天等场合。     

基于MPSO-CWLS-SVM的瓦斯涌出量预测

针对瓦斯涌出量受多因素影响,传统的预测方法难以建立准确的数学模型,导致预测精度低这一问题。提出一种经改进的粒子群算法(MPSO)优化的基于柯西分布加权的最小二乘支持向量机(CWLS-SVM)算法来预测非线性动态瓦斯涌出量。柯西分布加权的最小二乘支持向量机根据预测误差的统计特性,确定加权规则参数,以达到赋予训练样本不同权值的目的。并用MPSO算法对CWLS-SVM模型的正则化参数λ和高斯核参数σ寻优。利用无线传感器网络采集到的各项历史数据进行实例分析。结果表明,该算法有效的提高了瓦斯涌出量的预测精度,降低了预测误差,为煤矿瓦斯防治提供理论支持。     

改进的LS-SVM方法在EMD端点效应问题中的应用

经验模态分解能有效处理非平稳、非线性信号,但在多次采用三次样条插值获取信号上、下包络的过程中容易产生影响分解精度的端点问题。为了抑制经验模态分解中存在的端点效应问题,提出了一种基于最小二乘支持向量机和镜像延拓的端点效应抑制方法。该方法采用最小二乘支持向量机对原始信号序列两端分别向左、右各延拓有限个数据点;用镜像延拓对延拓后的信号序列进行对称延拓处理,将其延拓成一个环形信号序列;对这一环形信号序列进行经验模态分解。通过对仿真信号以及真实脑电信号进行实验分析以及与其他延拓方法的对比,结果表明该方法能够有效抑制端点效应问题,并在抑制端点效应问题方面优于传统的支持向量机和最小二乘支持向量机。