基于包装功能的时间–温度指示器与食品新鲜度指示器研究进展

目的 从包装功能实现的角度分析研究时间–温度指示器和食品新鲜度指示器的原理、类型与发展趋势，指出开发设计时间–温度指示器和食品新鲜度指示器应完成的包装功能，为有效实现包装交流功能提供研究思路和技术支持。方法 列出现有食品包装功能在物理环境、周围环境和人类环境下的实现矩阵，通过研究时间–温度指示器和食品新鲜度指示器的实现原理和所满足的包装交流功能，探讨这2种技术提高矩阵中分值较低元素的可行性。结果 时间–温度指示器监测食品所经历的时间、温度的完整历程，有助于提高实现矩阵中ComA元素的分值;食品新鲜度指示器提供生理变化或微生物生长引起的食品质量变化的定性或半定量信息，有助于提高实现矩阵中ComH元素的分值。结论 时间–温度指示器和食品新鲜度指示器能够有效提升食品包装的交流功能，保证消费者安全，减少资源浪费，具有广阔的发展前景。     

Effects of red-wine grape pomace on the quality and sensory attributes of beef hamburger patty

This study was conducted to evaluate the effect of red-wine grape pomaces on the quality and sensory attributes of beef hamburger patties. Both phenolic content and antioxidant activity were assessed using Syrah, Merlot and Cabernet Sauvignon pomaces. Following the assessment, hamburger patties were prepared with Merlot pomace at 0%, 2% and 4% for the patty quality and sensory attributes. Grape seeds possessed significantly higher phenolics and antioxidant activities over the seedless pomace (P < 0.05), whereas no significant difference was found for phenolics and antioxidant activities within the seeds and seedless pomaces. The patty pH decreased as the pomace was added for 2% and 4%. Colour values (L*, a* and b*) of patties lowered as the pomace was added. Allo-Kramer shear force and hardness values increased while cooking yield decreased (P < 0.05) with the addition of pomace. No significant difference between control and Merlot patties was found for flavour, juiciness and colour, whereas lower sensory attributes were observed for texture, taste and overall acceptability. It is observed that the addition of fermented red-wine grape pomace provides hamburger patties with health promoting factors such as antioxidant and other functional components, but it also provided darker, sourer and lower cooking yield.     

子集模拟中马尔可夫链蒙特卡洛抽样算法比较

文章着重研究子集模拟中马尔可夫链蒙特卡洛(MCMC)抽样算法的抽样效率与计算精度。首先，阐述可靠度子集模拟的基本原理与中间状态样本生成的各种MCMC抽样算法，在稳态马尔可夫链构造基础上提出延迟拒绝MMH(Modified Metropolis Hasting)算法，通过在MMH算法上增加备选样本的延迟拒绝步提高MMH算法的抽样效率；阐述基于随机游走与基于扩散方程MCMC方法中建议分布的差异，进一步对备选样本接受率为1的preconditioned Crank-Nicolson(pCN)算法和条件抽样(Conditional sampling, CS)算法开展研究，证明两种算法的等价性；推导有效样本量的计算方法，提出采用有效样本量与总样本量的比值定义MCMC方法的抽样效率。通过复杂目标分布的样本生成研究不同MCMC抽样算法建议分布及其参数对备选样本接受率与抽样效率的影响，最后通过计算实例研究子集模拟过程采用不同MCMC抽样算法得到失效概率的相对误差及其变异性，揭示不同MCMC抽样算法对失效概率计算精度的影响。研究表明：不同MCMC抽样算法生成备选样本的接受率及其自相关性受建议分布及其参数影响较大，对于复杂的目标分布，pCN算法和CS算法的抽样效率较高，延迟拒绝MMH算法次之；采用CS算法和延迟拒绝MMH算法进行子集模拟得到的失效概率精度较高且变异性较低；增加子集模拟中间状态样本量可以提高失效概率计算精度并降低其变异性。     

基于移动窗口法的城市遥感生态质量评价研究

为进一步提高城市生态监测的精确度，在前人开展的城市生态遥感监测研究的基础上引入“区域尺度”的概念，充分考虑小区域范围内不同地物间的交互作用，并利用移动窗口模型(Moving Window-Remote Sensing Ecology Index, MW-RSEI)对沈阳市浑南区的遥感影像进行逐像元分析。实验结果表明，MW-RSEI模型和生态遥感监测模型（Remote Sensing Ecology Index, RSEI)在整体生态评价趋势上表现出一致性。但MW-RSEI模型对城市生态中的细节区域表征更明显。考虑到建筑及裸地周围植被的影响，其较差生态区域的占比仅为6%，生态评价为优的区域占比为11%。研究区生态评价结果表现得较为连续，并未出现明显的断层现象。该结果具有现实意义且与实际生态分布更为符合。MW-RSEI模型在城市生态监测中更为适用，可为相关部门提供一定的技术参考。     

基于大数据深度学习的输电塔结构抗风易损性评估

为了有效预测输电网系统在强风作用下的响应，并开展高效精准的性能评估，文章提出了基于深度学习模型的风致易损性评估框架。以某具备健康监测系统的输电塔结构为例，首先对监测数据进行清洗和重构，通过大数据深度学习建立荷载输入和响应输出的等效映射模型，然后通过数值模拟生成灾害强度均匀的风场数据并由深度学习模型预测输电塔关键杆件响应，计算不同性能水准的易损性曲线。研究结果表明，经训练的深度学习模型可以涵盖实际工程中存在的各类不确定性因素，有效映射复杂风环境下输电塔结构的动力响应。提出的框架方法可以避免单纯通过数值模型制备大量动态响应数据，更高效地进行输电网系统风致易损性评估。     

A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.