基于实例分割和显著性计算的人工视觉多目标优化处理

通过实例分割Swin-Transformer提取分割所有前景对象,融合亮度、大小和位置图像显著性特征,提出模拟人类视觉注意机制的多特征融合注意力层级计算模型,为不同级别的前景物体采用适合的光幻视分辨率和亮度表达,实现不同的刺激编码策略进行层级优化处理。通过人工假体视觉的仿真试验表明,在所提出的多目标层级优化表达策略下,试验被试完成多目标识别的准确率、识别时间表现具有一定的显著提升。利用深度学习实例分割技术,层级化光幻视编码以仿生人类视觉选择性注意,达到增强假体植入者在复杂场景下的多物体感知,为视觉假体图像信息编码和优化处理研究的发展与应用提供参考。     

右心室间隔部起搏的生物力学效应及其对血流动力学和血脑肽的影响

目的　比较右心室间隔部与右心室心尖部起搏对血流动力学及血脑钠肽的影响。方法　48例病窦综合征及20例完全性房室传导阻滞患者，共68例，均植入DDD型起搏器，按心室导线固定部位不同随机分为右心室间隔部起搏(RVS)组和右心室心尖部起搏(RVA)组，对比观察两组安置起搏器前后心电图QRS波宽度和形态，血流动力学参数（包括左室射血分数(LVEF)、心脏指数(CI)、每搏量(SV)差异）和血脑钠肽(BNP)的变化；两组病窦综合征患者于术后3个月时再行程控优化，继续观察程控优化前后血流动力学参数和血BNP的变化。结果　RVA组起搏心电图Ⅱ导联QRS间期显著长于RVS组(P<0.05)。术前两组LVEF、CI、SV和血BNP水平均差异无统计学意义。术后3个月时RVA组LVEF、CI、SV较RVS组均有显著降低（均P<0.05）；BNP则较RVS组有显著升高(P<0.01)。RVA组病窦综合征患者程控优化前后相比，LVEF、CI、SV有显著增加（均P<0.05），BNP有显著降低(P<0.01)，优化后与术前相比，BNP仍有显著升高(P<0. 05)。RVS组病窦综合征患者程控优化前后相比，LVEF、CI、SV差异无统计学意义(P>0.05)，但BNP有显著降低(P<005)，优化后与术前相比，BNP无显著性差异(P>0.05)。结论　RVA起搏扰乱了双心室电同步，恶化了血流动力学和心功能，RVS起搏尽可能地维持了双心室激动顺序和双心室收缩同步性，对血流动力学影响较小，RVS起搏比RVA起搏更为接近生理性起搏。     

高压静电成囊法工艺参数的优化

比较气流式与高压静电场制备微囊的方法,证明后者制得的微囊较前者的有更好的均匀性和更小的粒径,并对工艺参数进行优化:电压4～5kV、推进速度50～70mm/h,液面距20～25mm.     

抗HSV1单克隆抗体-阿糖胞苷偶联物制备条件的分步优化

目的:建立高效液相凝胶过滤色谱法测定偶联物的偶联率、中间产物的生成量;通过制备条件分步优化实验来提高偶联率.方法:制备条件从投料比、pH、温度、反应时间等方面来逐项优化反应条件以期能提高偶联率;检测方法采用高效液相凝胶过滤色谱法,以0.02 mol·L-1 pH 6.8磷酸盐缓冲溶液为流动相,流速为0.5 mL·min-1,检测波长为280 nm.结果:通过建立高效液相凝胶过滤色谱法来指导优化实验,摸索得到新的投料比和pH,使偶联率从10.19%提高到13.48%.结论:本实验建立的高效液相凝胶过滤色谱法简便、快速、灵敏、准确,对优化实验有指导意义,使偶联率得到了提高.     

Polymeric nanoencapsulation of zaleplon into PLGA nanoparticles for enhanced pharmacokinetics and pharmacological activity

Zaleplon (ZP) is a sedative and hypnotic drug used for the treatment of insomnia. Despite its potent anticonvulsant activity, ZP is not commonly used for the treatment of convulsion since ZP is characterized by its low oral bioavailability as a result of poor solubility and extensive liver metabolism. The following study aimed to formulate specifically controlled release nano‐vehicles for oral and parenteral delivery of ZP to enhance its oral bioavailability and biological activity. A modified single emulsification–solvent evaporation method of sonication force was adopted to optimize the inclusion of ZP into biodegradable nanoparticles (NPs) using poly (dl‐lactic‐co‐glycolic acid) (PLGA). The impacts of various formulation variables on the physicochemical characteristics of the ZP‐PLGA‐NPs and drug release profiles were investigated. Pharmacokinetics and pharmacological activity of ZP‐PLGA‐NPs were studied using experimental animals and were compared with generic ZP tablets. Assessment of gamma‐aminobutyric acid (GABA) level in plasma after oral administration was conducted using enzyme‐linked immunosorbent assay. The maximal electroshock‐induced seizures model evaluated anticonvulsant activity after the parenteral administration of ZP‐loaded NPs. The prepared ZP‐PLGA NPs were negatively charged spherical particles with an average size of 120–300 nm. Optimized ZP‐PLGA NPs showed higher plasma GABA levels, longer sedative, hypnotic effects, and a 3.42‐fold augmentation in oral drug bioavailability in comparison to ZP‐marketed products. Moreover, parenteral administration of ZP‐NPs showed higher anticonvulsant activity compared to free drug. Oral administration of ZP‐PLGA NPs achieved a significant improvement in the drug bioavailability, and parenteral administration showed a pronounced anticonvulsant activity.     

战区军队医院卫生资源优化整合探讨

本文结合军区医院实际,指出军区医院优化整合是完成编制调整的客观要求。是提高资源利用效能的实际需要,也是增强综合保障能力的重要举措。优化整合的基本原则：一是坚持需求牵引。突出重点;二是坚持区域规划。合理布局;三是坚持保留骨干,优势互补。优化整合的主要做法是：确保战区医疗中枢配置;建立区域医疗救治中心;建立医学信息情报中心;建立医学实验研究中心;综合利用医院疗养院资源;同地区资源配置优势互补。同时优化整合应重点把握四个统一：军委决策与利益调整相统一、资源优化配置与合理利用相统一、医院发展能力与保障效能相统一及创新保障模式与管理机制相统一。     

论军队疗养院联勤与优化整合

实行优化整合是军队疗养院联勤的基本要求。疗养院的优化整合包括人力资源整合、设施整合和开发整合三个方面。本文从不同层面对以军兵种特点分区疗养、以疗养对象分区疗养和以功能区块分区疗养进行了对比分析,重点探讨了优化整合应把握的几个问题：①要整体规划、宏观决策;②要体现功能要求和自身特点;③要把握使命任务,适应市场需求;④优化整合是一个动态开放和创新发展的概念。     

Identification of the optimal switching for range-optimal atmospheric flight trajectories

The optimal switching structure associated with long-flight-time, range-optimal trajectories for a high-performance atmospheric flight vehicle is determined. The optimal solution, obtained from Pontryagin's minimum principle, consists of six arcs in total. Four arcs are riding the active dynamic pressure limit, one with singular control setting. Identification of the optimal switching structure was achieved with the direct optimization technique TODI (trajectory optimization via differential inclusion). Implemented in a low-order discretization scheme based on the trapezoidal rule, this code has only modest smoothness requirements and is well suited for problems with discontinuous control jumps at a priori unknown switching times. © 1997 John Wiley & Sons, Ltd.     

Intelligent Generation Method of Innovative Structures Based on Topology Optimization and Deep Learning

Computer-aided design has been widely used in structural calculation and analysis, but there are still challenges in generating innovative structures intelligently. Aiming at this issue, a new method was proposed to realize the intelligent generation of innovative structures based on topology optimization and deep learning. Firstly, a large number of structural models obtained from topology optimization under different optimization parameters were extracted to produce the training set images, and the training set labels were defined as the corresponding load cases. Then, the boundary equilibrium generative adversarial networks (BEGAN) deep learning algorithm was applied to generate numerous innovative structures. Finally, the generated structures were evaluated by a series of evaluation indexes, including innovation, aesthetics, machinability, and mechanical performance. Combined with two engineering cases, the application process of the above method is described here in detail. Furthermore, the 3D reconstruction and additive manufacturing techniques were applied to manufacture the structural models. The research results showed that the proposed approach of structural generation based on topology optimization and deep learning is feasible, and can not only generate innovative structures but also optimize the material consumption and mechanical performance further.