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Muhammad Yazid Samatra Nor Qhairul Izzreen Mohd Noor Umi Hartina Mohamad Razali Jamilah Bakar Sharifudin Md. Shaarani 《Comprehensive Reviews in Food Science and Food Safety》2022,21(4):3153-3176
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. 相似文献
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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%。 相似文献
4.
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. 相似文献
5.
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。 相似文献
6.
Reliable prediction of flooding conditions is needed for sizing and operating packed extraction columns. Due to the complex interplay of physicochemical properties, operational parameters and the packing-specific properties, it is challenging to develop accurate semi-empirical or rigorous models with a high validity range. State of the art models may therefore fail to predict flooding accurately. To overcome this problem, a data-driven model based on Gaussian processes is developed to predict flooding for packed liquid-liquid and high-pressure extraction columns. The optimized Gaussian process for the liquid-liquid extraction column results in an average absolute relative error (AARE) of 15.23 %, whereas the algorithm for the high-pressure extraction column results in an AARE of 13.68 %. Both algorithms can predict flooding curves for different packing geometries and chemical systems precisely. 相似文献
7.
Keran Su Kim Huey Ee Jingcan Sun Shao Quan Liu Benjamin Lassabliere Ulrich Feiter Yunle Huang Rui Min Vivian Goh Aileen Pua Bin Yu 《International Journal of Food Science & Technology》2022,57(3):1666-1678
The structural diversity of polyphenols and the inherent limitations of current extraction techniques pose a challenge to extract polyphenols using a simple and green method. Hence, in this study, a method was developed to simultaneously fractionate multiple classes of polyphenols by only varying ethanol-water solutions. Honeybush tea, which is rich in polyphenols, was selected as a model for this study. Solvent extraction followed by solid-phase extraction (SPE) was developed to obtain a polyphenol-rich fraction from six honeybush samples. Based on a gradient elution programme (10%, 30%, 50%, 70% and 90% (v/v) ethanol-water solution) of SPE, the Strata X cartridge showed a better recovery of most targeted polyphenols under 0.9 mL of the drying volume and 1 mL min−1 of the dispensing speed. The elution programme for fractionating most polyphenols was as follows: single elution with 50% ethanol, followed by twice elution with 70% ethanol. The antioxidant capacity was used to analyse the differences among the polyphenol-rich fractions from six honeybush samples. Principal component analysis (PCA) revealed that unfermented C. genistoides (GG) has the greatest antioxidant capacity among the honeybush species studied. Additionally, mangiferin, isomangiferin and vicenin-2 were the main contributors to the antioxidant capacity in six honeybush fractions according to the correlation study. 相似文献
8.
Susan Sabra Khalid Mahmood Malik Muhammad Afzal Vian Sabeeh Ahmad Charaf Eddine 《Expert Systems》2020,37(1):e12388
Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE. 相似文献
9.
This paper deals with three-dimensional non-linear finite element analyses to assess the structural behavior of adhesively-bonded double supported tee joint of laminated FRP composites having embedded interfacial failures. The onset of interfacial failures is predicted by using Tsai–Wu coupled stress failure criterion with pre-determined stress values. The concept of fracture mechanics principle is utilized to study the sustainability of the tee joint having interfacial failures pre-existed at the critical locations. Individual modes of the strain energy release rates (SERR) GI, GII and GIII, are considered as the damage growth parameters and, are evaluated using the Modified crack closure integral (MCCI) technique based on the concept of linear elastic fracture mechanics (LEFM). Based on the stress analyses, it has been observed that the interfacial failures in tee joint structure trigger at the interface of base plate and adhesive layer from both ends of base plate. Depending on the SERR magnitudes, it has been noticed that the interfacial failure propagates under mixed mode condition. Therefore total SERR (GT) is considered as the governing parameter for damage propagation. Furthermore, efforts have been made to retard damage propagation rate by employing functionally graded adhesive (FGA) instead of monolithic adhesive material. Series of numerical simulations have been performed for varied interfacial failure length in functionally graded adhesively bonded double supported tee joint structure in order to achieve the significant effect of FGA with various modulus ratios on SERR. Material gradation of adhesive indicates significant SERR reduction at the incipient stage of failure which necessitates the use of functionally graded adhesive for the tee joint and prolong the service life of the structure. 相似文献
10.
为了开发β受体阻断剂新药(S)-噻吗洛尔半水合物,采用3-吗啉-4-氯-1,2,5-噻二唑为起始原料,经水解反应得到中间体1(3-吗啉-4-羟基-1,2,5-噻二唑)。中间体1与R-环氧氯丙烷发生醚化反应,经后处理及重结晶得到中间体2 {(R)-4-[4-(环氧乙烷-2-基甲氧基)-1,2,5-噻二唑-3-基]吗啉}。中间体2经胺化反应、马来酸成盐及重结晶得到(S)-马来酸噻吗洛尔。(S)-马来酸噻吗洛尔经游离、纯水转晶得到符合药典标准的(S)-噻吗洛尔半水合物,总收率14.05%且e.e.值为99.66%。最终成品经IR、1H-NMR、13C-NMR、MS、TGA、DSC表征,并优化各步反应条件。结果表明:以三乙胺为醚化反应缚酸剂75 ℃反应最佳;以乙醇为胺化反应溶剂46 ℃反应16 h最佳;S-噻吗洛尔的转晶拆分以水作溶剂,比传统不对称合成工艺安全稳定,操作简单,适合工业化生产。 相似文献