Detection of crowdedness in bus compartments based on ResNet algorithm and video images

Multimedia Tools and Applications - The crowding in bus is an important factor affecting passenger satisfaction and bus dispatching level. However, how to use video images to detect crowding...     

柔性纤维结构超级电容器研究进展

为了提高电源器件与人体高曲率表面的适配性，电源器件突破平板结构的限制，衍生出了柔性纤维结构。柔性纤维超级电容器具有高功率密度、超长循环寿命和柔性舒适等特点有望成为最具前景的柔性可穿戴电源之一。因此，本文主要介绍了碳材料、过渡金属氧化物以及复合材料三种功能材料对柔性纤维超级电容器结构和性能的影响。每种材料凭借自身独特的性质在柔性纤维超级电容器器件中发挥着重要作用，并助力可穿戴电源器件的发展。     

Changes in the content and antioxidative activity of β-carotene and its metabolite vitamin A during gastrointestinal digestion and absorption and optimisation of HPLC-based detection

The β-Carotene (BC), an important precursor of vitamin A (VA), possesses antioxidant activity but is fat-soluble and has low bioavailability. In previous in-vitro assays evaluating antioxidant and 2,2′-azobis(2-amidinopropane) dihydrochloride (AAPH) free radical scavenging, both BC and VA showed a strong ability to scavenge radicals and protected cells from oxidative stress. Here, we used artificially simulated gastrointestinal digestion and Caco-2 cell absorption models to evaluate the bioavailability of the BC during gastrointestinal digestion and absorption using high-performance liquid chromatography (HPLC) analysis. We observed high absorptive and transfer rates of BC and detected retinol metabolites (Vitamin A). Therefore, BC can be detected in the acidic gastrointestinal environment using HPLC. Optimised method provided better separation of BC and VA in the column, improving the accuracy of the test results.     

Theoretical investigation of intrinsic point defects and the oxygen migration behavior in rare earth hafnates

In this work, the composition-dependent point defect types and formation energies of RE₂Hf₂O₇ (RE = La, Ce, Pr, Nd, Pm, Sm, Eu and Gd) as well as the oxygen diffusion behavior are systematically investigated by first-principles calculations. The possible defect reactions and dominant defect complexes under stoichiometric and non-stoichiometric conditions are revealed. It is found that O Frenkel pairs are the predominant defect in stoichiometric pyrochlore hafnates. Hf-RE cation anti-site defects, accompanied by RE vacancies and/or oxygen interstitials, are stable in the non-stoichiometric case of HfO₂ excess. On the other hand, RE-Hf anti-site defects together with oxygen vacancies and/or RE interstitials are preferable in the case of RE₂O₃ excess. The energy barriers for the migration along the V_O48f - V_O48f pathway of pyrochlore hafnates were calculated to be between 0.81 eV and 0.89 eV. Based on these results, a defect engineering strategy is proposed and the pyrochlore hafnates investigated here are predicted to exhibit potential oxygen ionic conductivity.     

Facial-sketch Synthesis: A New Challenge

Machine Intelligence Research - This paper aims to conduct a comprehensive study on facial-sketch synthesis (FSS). However, due to the high cost of obtaining hand-drawn sketch datasets, there is a...     

新媒体环境下智慧化阅读推广研究——以重庆第二师范学院为例

开展智慧化阅读推广,紧跟时代步伐,有效提升读者多重阅读体验和满意度,增强智慧化阅读推广的价值,促进智慧化阅读推广服务的有效化、规范化、科学化、常态化、长期化发展,已成为当前阅读推广研究中一个重要的切入点。文章基于智慧化阅读研究,结合"新媒体"高新技术环境,提出智慧化阅读推广的内容分析、具体实施、环境构建、推广评估与效果、推广改进等几个方面组成的以读者为中心的核心服务体系。本文分析了智慧化阅读基本方面,以我校图书馆实际运用推广效果,智慧化阅读存在的优、劣势及相应的对策。     

西藏燕麦主要种植区灌溉定额空间分布及影响因素

燕麦为西藏自治区典型牧草之一,由于种植区地域辽阔,灌溉试验结果受限,西藏燕麦主要种植区的灌溉定额尚不明确。本文在西藏燕麦主要种植区内选取28个典型站点进行资料收集,遵循农业气候相似原则进行区域划分,基于水量平衡法揭示了西藏燕麦主要种植区灌溉定额的空间分布特征,并根据统计学原理分析了其影响因素。研究表明:燕麦主要种植区的灌溉定额呈由西藏中部至东部呈现先递增后递减的趋势,50%水文年下的燕麦灌溉定额在56~265 mm之间变化。降雨量是影响研究区内燕麦灌溉定额的主要因素(R²为0.515),ET₀次之(R²为0.152);其它气象因素中,日照时数对研究区燕麦灌溉定额影响较大(R²为0.462),且呈正相关关系;相对湿度对燕麦灌溉定额影响较小。西藏燕麦主要种植区的灌溉定额及其空间分布可为西藏自治区灌溉用水管理提供支撑。     

基于形态特征提取的急性下壁心肌梗死BiLSTM网络辅助诊断算法

急性下壁心肌梗死是一种病发急、进展快、致死率高的心脏疾病,该文提出一种新颖的基于形态特征提取的BiLSTM神经网络分类的急性下壁心肌梗死辅助诊断算法,可大幅度提高医生对急性下壁心肌梗死疾病的诊断效率并有助于及时确诊.算法包括:对胸痛中心数据库心拍信号进行降噪及心拍分割;根据临床心内科医学诊断指南提取了12导联波形距离特征和分导联波形幅值特征;依据提取的特征搭建LSTM与BiLSTM神经网络进行心拍的分类识别;使用PTB公开数据库和胸痛中心数据库多临床中心进行交叉验证.实验结果表明,加入胸痛中心真实临床数据后,基于形态特征提取BiLSTM神经网络的急性下壁心肌梗死辅助诊断算法准确率达到99.72％,精度达到99.53％,灵敏度达到100.00％,同时F1-Score达到99.76.该算法比其他现有算法准确率提高至少1％,该项研究具有非常重要的临床应用价值.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。