Bovidae-based gelatin: Extractions method,physicochemical and functional properties,applications, and future trends

Gelatin is one of the most important multifunctional biopolymers and is widely used as an essential ingredient in food, pharmaceutical, and cosmetics. Porcine gelatin is regarded as the leading source of gelatin globally then followed by bovine gelatin. Porcine sources are favored over other sources since they are less expensive. However, porcine gelatin is religiously prohibited to be consumed by Muslims and the Jewish community. It is predicted that the global demand for gelatin will increase significantly in the future. Therefore, a sustainable source of gelatin with efficient production and free of disease transmission must be developed. The highest quality of Bovidae-based gelatin (BG) was acquired through alkaline pretreatment, which displayed excellent physicochemical and rheological properties. The utilization of mammalian- and plant-based enzyme significantly increased the gelatin yield. The emulsifying and foaming properties of BG also showed good stability when incorporated into food and pharmaceutical products. Manipulation of extraction conditions has enabled the development of custom-made gelatin with desired properties. This review highlighted the various modifications of extraction and processing methods to improve the physicochemical and functional properties of Bovidae-based gelatin. An in-depth analysis of the crucial stage of collagen breakdown is also discussed, which involved acid, alkaline, and enzyme pretreatment, respectively. In addition, the unique characteristics and primary qualities of BG including protein content, amphoteric property, gel strength, emulsifying and viscosity properties, and foaming ability were presented. Finally, the applications and prospects of BG as the preferred gelatin source globally were outlined.     

From modification to mechanism: Supercritical hydrothermal synthesis of nano-zirconia

Nano-zirconia has been widely applied due to its excellent physical and chemical properties (e.g., high strength, corrosion resistance, oxygen ion conductivity). Existing preparation methods of nano-zirconia tend to require long reaction time, and the sizes of final particles are large with uneven distributions. Sub-/supercritical hydrothermal synthesis of nanoparticles is favored by researchers owing to controllable reaction process, uniform particle size distribution, good reproducibility, short reaction time, high conversion rate and harmlessness to environment. In this paper, the characteristics and mechanisms of dissolution, crystallization and growth of nano-zirconia during sub-/supercritical hydrothermal synthesis are systematically reviewed. The influences of process and material parameters on the size and purity of particles are analyzed. Then, the reaction mechanism and product phase transition mechanism during hydrothermal synthesis of zirconia are summarized to provide a theoretical reference for the oriented preparation. Finally, the improvement and commercialization of sub-/supercritical hydrothermal synthesis technology are evaluated, and the future research topics are proposed.     

Enhanced wide-activated residual network for efficient and accurate image deblocking

To save bandwidth and storage space as well as speed up data transmission, people usually perform lossy compression on images. Although the JPEG standard is a simple and effective compression method, it usually introduces various visually unpleasing artifacts, especially the notorious blocking artifacts. In recent years, deep convolutional neural networks (CNNs) have seen remarkable development in compression artifacts reduction. Despite the excellent performance, most deep CNNs suffer from heavy computation due to very deep and wide architectures. In this paper, we propose an enhanced wide-activated residual network (EWARN) for efficient and accurate image deblocking. Specifically, we propose an enhanced wide-activated residual block (EWARB) as basic construction module. Our EWARB gives rise to larger activation width, better use of interdependencies among channels, and more informative and discriminative non-linearity activation features without more parameters than residual block (RB) and wide-activated residual block (WARB). Furthermore, we introduce an overlapping patches extraction and combination (OPEC) strategy into our network in a full convolution way, leading to large receptive field, enforced compatibility among adjacent blocks, and efficient deblocking. Extensive experiments demonstrate that our EWARN outperforms several state-of-the-art methods quantitatively and qualitatively with relatively small model size and less running time, achieving a good trade-off between performance and complexity.     

Superswelling Microneedle Arrays for Dermal Interstitial Fluid (Prote)Omics

The noninvasive sampling of dermal interstitial fluid (ISF) for the monitoring of clinical biomarkers is a greatly appealing area of research. The identification of molecular biomarkers in biological fluids has been accelerated with -omics analyses but remains limited in ISF because of its time-consuming and complex extraction process. Here, the generation of microneedle (MN) patches made of superabsorbent acrylate-based hydrogels for the rapid sampling of dermal ISF is described to explore its proteome. In depth, iterative optimization allows the identification of novel acrylate-based compositions with the required chemical, mechanical, and biocompatibility properties allowing proteomic analysis of the extracted ISF for the first time after sampling with swelling MNs. The generated MN arrays show no cytotoxic effect, successfully cross the stratum corneum, and can collect up to 6 µL of dermal ISF in 10 min in vivo. Proteomics lead to the detection of 176 clinically relevant biomarkers in the collected samples validating the use of ISF as a relevant bodily fluid for disease monitoring and diagnostic. Importantly, it is discovered that extraction fingerprint is strongly dependent on the MNs chemistry, and thus specific biomarkers could be selectively extracted by tuning the composition of the patch, making the system versatile and specific.     

Ablation behavior of thin-blade co-deposited C/Cx-SiCy composites under the influence of the complex fluid conditions of the oxyacetylene torch

This paper offers a new way of testing the ablation property of material under an oxyacetylene torch using a thin-blade specimen, which costs much less time to reach the maximum temperature and provides a harsh turbulence fluid field that's closer to reality. The thin-blade specimen experiences a higher turbulent intensity than the traditional disk-like specimen, leading to more efficient heat exchange. The fluid field simulation agrees with the testing results. In addition, we manage to synthesize the C/Cx-SiCy composites with the co-deposition chemical vapor infiltration (CVI) method. The C/Cx-SiCy composites exhibit a similar anti-ablation property as C/C composites and consist of enough SiC phase simultaneously, combining the advantages of both C/C composites and C/SiC composites. The thin-blade C/Cx-SiCy composites show a lower linear ablation rate (1.6 μm/s) than C/C composites (4.1 μm/s) and C/SiC composites (19.6 μm/s) during the oxyacetylene test. The glass layer formed on the surface of C/Cx-SiCy could cling to the bulk material instead of peeling off due to the high PyC content in the matrix could protect the SiO₂ from blowing away.     

Optimization of flow in additively manufactured porous columns with graded permeability

Chemical engineering systems often involve a functional porous medium, such as in catalyzed reactive flows, fluid purifiers, and chromatographic separations. Ideally, the flow rates throughout the porous medium are uniform, and all portions of the medium contribute efficiently to its function. The permeability is a property of a porous medium that depends on pore geometry and relates flow rate to pressure drop. Additive manufacturing techniques raise the possibilities that permeability can be arbitrarily specified in three dimensions, and that a broader range of permeabilities can be achieved than by traditional manufacturing methods. Using numerical optimization methods, we show that designs with spatially varying permeability can achieve greater flow uniformity than designs with uniform permeability. We consider geometries involving hemispherical regions that distribute flow, as in many glass chromatography columns. By several measures, significant improvements in flow uniformity can be obtained by modifying permeability only near the inlet and outlet.     

Recent advances in carbon nanotubes-based microwave absorbing composites

With the blossom of information industry, electromagnetic wave technology shows increasingly potential in many fields. Nevertheless, the trouble caused by electromagnetic waves has also drawn extensive attention. For instance, electromagnetic pollution can threaten information safety in vital fields and the normal function of delicate electronic devices. Consequently, electromagnetic pollution and interference become an urgent issue that needs to be addressed. Carbon nanotubes (CNTs) have become a potential candidate to deal with these problems due to many advantages, such as high dielectric loss, remarkable thermodynamic stability, and low density. With the appearance of climbing demands, however, the carbon nanotubes combining various composites have shown greater prospects than the single CNTs in microwave absorbing materials. In this short review, recent advances in CNTs-based microwave absorbing materials were comprehensively discussed. Typically, we introduced the electromagnetic wave absorption mechanism of CNTs-based microwave absorbing materials and generalized the development of CNTs-based microwave absorbers, including CNTs-based magnetic metal composites, CNTs-based ferrite composites, and CNTs-based polymer composites. Ultimately, the growing trend and bottleneck of CNTs-based composites for microwave absorption were analyzed to provide some available ideas to more scientific workers.     

基于面元素重排的三维网格模型数据隐藏算法

目的 为了解决目前三维数据隐藏算法不能兼顾无失真和盲提取的问题，提出一种新的完全无失真的三维网格模型数据隐藏盲算法。方法 首先使用混沌逻辑映射选择嵌入与提取模式，保证数据的安全性。然后利用面元素重排，完全不会造成三维模型失真的性质，通过不同嵌入模式规则对三角面元素进行重排，以嵌入秘密数据。接收端则可根据相应的提取模式规则提取秘密数据。结果 仿真结果与分析表明，该算法不会对三维模型造成任何失真，嵌入容量为每顶点2比特，且能抵抗仿射变换攻击、噪声攻击和平滑攻击等。结论 这种三维数据隐藏盲算法无失真，容量大、安全性高、鲁棒性强，适用于三维载体不容修改的情形，如军事、医学、秘密通信和版权保护等。