Enhanced photoelectric properties of PbSnSe thin films via quick oxygen ion-implantation sensitization

Journal of Materials Science - Although chalcogenide materials continue to generate considerable interest due to great potentials for various optoelectronic devices, annealing for a long time in...     

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...     

Improving gelling properties of myofibrillar proteins incorporating with cellulose micro/nanofibres

The effects of cellulose microfibres (CMFs, Average size: 100 ± 5 μm) and cellulose nanofibres (CNFs, Average size: 60 ± 3 nm) on the properties of myofibrillar protein (MP) gels from duck breast meat were studied. The results demonstrated that CMFs and CNFs were mostly connected to MP by non-covalent bonds, the diffusion and cross-linking of MP molecules was promoted, and a denser and more complete gel network was formed. With the increases of CMFs and CNFs concentration (0–10%), the hardness was increased by 13.15% and 19.78% for CMFs10% and CNFs10% gels, respectively, and the elasticity was increased by 40% and 80%, respectively. At the same concentration (0–10%), the increase in gel hardness, viscoelasticity and immobilised water content was greater in the CNFs-MP group than in the CMFs-MP group. The CNFs-MP group had a tighter gel network, and CNFs had a better potential to improve the gelation performance of MP.     

Polymer electrets and their applications

Polymer electrets have revealed great potential application in electromechanical devices because of the low weight, large quasi-piezoelectric sensitivity, and excellent flexibility. For an electret, a permanent and macroscopic electric field exists on the surface, principally led by a macroscopic electrostatic charge on the surface or a net orientation of polar groups inside the object. Here, progress in the development of polymer electrets is reviewed. After a brief retrospect of the research courses and those typical polymer electrets that are classified into fluorine polymer and nonfluorine polymer, we present a survey on the charging methods, including corona, soft X-ray, contact, thermal and monoenergetic particle beams. The latest representative applications (i.e., power harvesting, sensors, field effect transistors, and biomedicine) based on polymer electrets are also summarized. Finally, we complete this review with a discussion on perspectives and challenges in this field.     

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.     

基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。