Role of the bolus degree of structure on the protein digestibility during in vitro digestion of a pea protein-fortified sponge cake chewed by elderly

This study investigated the digestibility of proteins in a pea protein-fortified sponge cake, as well as the impact of the degree of structure of the bolus produced by elderly subjects on the digestibility of proteins by combining ex vivo and in vitro approaches via the standardized protocol INFOGEST. The sponge cakes were consumed by a group of 20 elderly subjects with contrasting physiology, their boli were recovered just before swallowing, and their apparent viscosity was measured to delineate the bolus degree of structure. According to this criterion, two pools were formed with boli from subjects selected at the extremes: low viscosity and high viscosity, with apparent viscosity values (at 120 s⁻¹) of 124 ± 18 and 208 ± 19 Pa s, respectively. The sponge cakes and the two pools underwent in vitro digestion. Protein hydrolysis kinetics was followed by measuring the released primary amino groups (NH₂) and by sodium-dodecyl-sulfate polyacrylamide gel electrophoresis at different time points. For all samples, the representative bands of pea proteins disappear gradually during digestion, accompanied by the appearance of bands indicating the presence of proteins with M_W < 15 kDa. In addition, the NH₂ concentrations increase over time and do not differ between sponge cake and pea protein isolate. Moreover, the degree of structure of the food bolus has no significant effect on the concentration of NH₂ released. These results showed that pea proteins in a fortified sponge cake are bioaccessible under standardized conditions and that the degree of structure of the bolus did not influence protein digestibility for these foods.     

The effects of ozone,ultrasound and coating with shellac and lysozyme–chitosan on fresh egg during storage at ambient temperature – part 1: interior quality changes

The objective of this research was to investigate and compare the effect of different treatments including gaseous ozone (6-ppm/4-min), ultrasound (450 W/4 min) and coating of shellac, lysozyme–chitosan (L-C) on fresh eggs internal quality during storage for six weeks at ambient temperature. The internal quality attributes such as weight loss (WL), albumen viscosity, Haugh unit (HU), yolk index, total soluble solids, albumen and yolk's pH were monitored. Control groups had the worst HU (50.04), WL (8.35%), albumen pH (9.27) and viscosity (7.72 mPa·s) values after storage. The best interior qualities were obtained by shellac coating [HU (72.37), WL (1.37) and viscosity (30.10 mPa·s)] and sonication (albumen pH: 8.22). Thus, the shellac-coated eggs maintained all the internal quality parameters at the highest values, while the ozone and ultrasound only helped to keep the internal quality and enhance the shelf life of eggs.     

Synthesizing a uniformly spaced array pattern using integral operator for removing progressive phase shift

In this article, an analytical technique is introduced to obtain the excitation coefficients of uniformly spaced linear antenna arrays in order to achieve a desired array factor. By integration of the prescribed array factor, the array factor dependency to the progressive phase shift is eliminated. A new system of linear equations is consequently obtained whose solution represents the excitation coefficients of the array. Some examples are presented to verify the accuracy of the introduced method. The performance of this strategy is compared with those obtained by the other well‐known techniques such as Woodward‐Lawson and Fourier transform. It is shown that the presented method estimates the desired array pattern with a very good precision.     

CLOI-NET: Class segmentation of industrial facilities’ point cloud datasets

Shape segmentation from point cloud data is a core step of the digital twinning process for industrial facilities. However, it is also a very labor intensive step, which counteracts the perceived value of the resulting model. The state-of-the-art method for automating cylinder detection can detect cylinders with 62% precision and 70% recall, while other shapes must then be segmented manually and shape segmentation is not achieved. This performance is promising, but it is far from drastically eliminating the manual labor cost. We argue that the use of class segmentation deep learning algorithms has the theoretical potential to perform better in terms of per point accuracy and less manual segmentation time needed. However, such algorithms could not be used so far due to the lack of a pre-trained dataset of laser scanned industrial shapes as well as the lack of appropriate geometric features in order to learn these shapes. In this paper, we tackle both problems in three steps. First, we parse the industrial point cloud through a novel class segmentation solution (CLOI-NET) that consists of an optimized PointNET++ based deep learning network and post-processing algorithms that enforce stronger contextual relationships per point. We then allow the user to choose the optimal manual annotation of a test facility by means of active learning to further improve the results. We achieve the first step by clustering points in meaningful spatial 3D windows based on their location. Then, we apply a class segmentation deep network, and output a probability distribution of all label categories per point and improve the predicted labels by enforcing post-processing rules. We finally optimize the results by finding the optimal amount of data to be used for training experiments. We validate our method on the largest richly annotated dataset of the most important to model industrial shapes (CLOI) and yield 82% average accuracy per point, 95.6% average AUC among all classes and estimated 70% labor hour savings in class segmentation. This proves that it is the first to automatically segment industrial point cloud shapes with no prior knowledge at commercially viable performance and is the foundation for efficient industrial shape modeling in cluttered point clouds.     

肉桂特色资源加工利用产业发展现状

肉桂是我国特色经济林树种，我国肉桂种植面积和年产量均居世界首位。我国肉桂主要分布在两广地区，其中广西为14.9万hm²，广东为8.9万hm²，两地面积占全国肉桂分布总面积的95%以上。肉桂既是著名的香料又是传统的名贵中药，具有极高的经济价值，发展肉桂产业对于促进农民增收、维护健康中国有着重要的意义。本研究综述了肉桂资源量、分布情况及主要利用部位，介绍肉桂主要产品（如桂皮，桂枝，肉桂粉及肉桂油）及加工技术现状、产品质量控制及其分析检测方法，分析了产业未来的发展趋势，并提出了产业发展的对策和措施：加强肉桂标准化示范基地建设，提高优质资源供给能力；提高肉桂加工利用技术水平，延长产业链；培育肉桂龙头企业，提高产品市场竞争力。为我国肉桂特色资源加工利用产业的可持续发展提供一定的思路。     

Differences between oculomotor and perceptual artifacts for temporally limited head mounted displays

We used perceptual and oculomotor measures to understand the negative impacts of low (phantom array) and high (motion blur) duty cycles with a high‐speed, AR‐likehead‐mounted display prototype. We observed large intersubject variability for the detection of phantom array artifacts but a highly consistent and systematic effect on saccadic eye movement targeting during low duty cycle presentations. This adverse effect on saccade endpoints was also related to an increased error rate in a perceptual discrimination task, showing a direct effect of display duty cycle on the perceptual quality. For high duty cycles, the probability of detecting motion blur increased during head movements, and this effect was elevated at lower refresh rates. We did not find an impact of the temporal display characteristics on compensatory eye movements during head motion (e.g., VOR). Together, our results allow us to quantify the tradeoff of different negative spatiotemporal impacts of user movements and make subsequent recommendations for optimized temporal HMD parameters.     

An efficient method of generating vortex electromagnetic wave based on double‐layer transmissive metasurface

A broadband double‐layer transmissive metasurface (TMS) for effective generate vortex electromagnetic wave is presented in this paper. The proposed TMS consists of two types of elements. The first element is composed of a multi‐resonant dipole and four metal vias. The metal vias increase the coupling strength between the upper and lower layers to improve transmission efficiency. On the basis of the first element, the second element adds stubs to ensure sufficient phase shift. The far‐field cross polarisation is eliminated by special element arrangement. Then, a centre‐fed linear polarisation TMS is designed to generate orbital angular momentum beams with mode l = ? 1. The proposed TMS is designed, manufactured and measured to verify the proposed design. The measured results indicate that a maximum gain of 20.8 dBi and narrow divergence angle of ±5° are achieved at 18 GHz. Furthermore, mode purity is higher than 86.1% within the 17 to 19 GHz band. The proposed double‐layer TMS saved costs, reduced weight and without assembly error is a good candidate for OAM generator.     

薄壁弱刚性钛合金结构件制造工艺

随着新型材料冶金技术的发展与进步,钛合金作为“崛起的第三代金属”已完全替代了铝镁合金和钢构件,成为航天飞行器上应用范围最广的材料之一。从某新研制航天飞行器外部结构件用钛合金材料的特性及切削特点入手,针对薄壁弱刚性钛合金结构件在实际加工过程中遇到的诸多难点,提出了相应的解决办法,并重新设计了零件工装。结果表明,改进措施不仅保证了零件质量,而且提高了零件加工效率,使单件零件的生产周期缩短了近10h。     

用宽带超表面产生阵列贝塞尔光束

通过在空间光调制器（SLM）上加载相位图或通过光刻加工微型圆锥状结构可以产生贝塞尔光束阵列。然而，典型空间光调制器具有比波长大一个数量级的像素尺寸，这限制了相位梯度的可用范围，用光刻法加工的微型锥透镜的顶端不是标准的圆锥，这影响了贝塞尔光束的质量。为了克服这些缺点，将复杂的相位图加载到电介质超表面上，设计了一种可以产生阵列贝塞尔光束（在波长700 nm处，NA=0.3）的超表面器件。该器件可以宽波段工作，其单元结构在波长580~800 nm范围内的偏振转换效率均超过57%。利用时域有限差分算法（FDTD）对该器件（厚度为380 nm，直径仅为40 μm）进行了仿真，所产生的阵列光束都垂直于超表面器件。所提出的阵列贝塞尔光束发生器具有纳米级别的厚度和几十微米的直径，这对于未来的集成光学领域具有很大的应用前景。