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Abstract In recent years, with the rapid development of mobile communication networks, some new services such as cloud virtual reality, holographic communication, and etc. continue to emerge. Service composition has been researched in cloud computing. however, as the fast development of edge clouds, the service components can be deployed on the edge clouds to reduce the composition latency, so the more flexible and intelligent service composition algorithms are urgently need to study. Based on this, we propose a service composition strategy under the multi-cloud environment, and we propose an ant colony optimization algorithm (ACO) based on the multi-pheromone mechanism to optimize the quality of service (QoS). To avoid the occurrence of local optima, we further introduce the mutation operation of the genetic algorithm. Finally, the simulation results show that the proposed algorithm can achieve better QoS parameters such as latency and response time while ensuring the stability of services.

In this study, the flavor components of double-low fragrant rapeseed oils (cv. “Zhongyouza 19”) from nine different planting areas were qualitatively and quantitatively analyzed by headspace solid phase microextraction (HS-SPME) and gas chromatography-mass spectrometry coupled with olfactometry (GC-MS-O). The results showed that a total of 63 aroma-active compounds were identified using two columns (polar and non-polar) at a total concentration of 222.0 to 468.9 mg/kg. The total concentration of aroma compounds was highest in the Hunan sample and lowest in the Jiangxi sample. Out of the identified flavor substances, 38 had odor activity value (OAV) greater than 10. The results of partial least squares-discriminant analysis (PLS-DA) and sensory evaluation showed that 2-methylpyrazine, 2,3,5-trimethylpyrazine, and 2-methyl-3,5-diethylpyrazine were the main contributors to roasted aroma notes, 3-butenylisothiocyanate provided spicy notes, and 5-hexenenitrile and 4-methylthionitrile led to green notes. Based on variable important in the projection (VIP) values, nine key differential substances were selected, namely, methanthiol, 2-methylpyrazine, 2,3-diethyl-5-methylpyrazine, dimethyl disulfide, 5-methylthiopentonitrile, 5-hexenenitrile, (E,Z)-2,4-pentadienonitrile, hexanal and dimethyl trisulfide. They could be considered as potential flavor markers for the discrimination of double-low fragrant rapeseed oils from different planting areas. This research can provide a theoretical guide for the screening of raw materials for fragrant rapeseed oils.

Three kinds of silicon dioxide including S655, R92 and R40F were characterized, and their application in low-temperature adsorption refining of fragrant rapeseed oil was studied. The results showed that all three kinds of silicon dioxide had a loose porous structure, but the particle size distribution, specific surface area, pore volume and pore size were obviously different. After being treated with 1.0% silicon dioxide at 45 ℃ for 30 min, the dephosphorization rates of rapeseed oil by S655, R92 and R40F were 90.3%, 99.6% and 88.5%, the lightness increased by 49.9%, 52.5% and 53.9%, the redness decreased by 31.5%, 23.4% and 37.8%, the yellowness increased by 17.3%, 20.0% and 20.6%, respectively. Meanwhile, the retention rate of sterols (above 97.1%) was high, and there were no significant differences in deacidification rate, fatty acid composition or tocopherol retention rate among the three treatment groups. The highest retention rates of total phenol and canolol (98.1% and 99.4%) were found in the samples treated with R92. The contents of glucosinolate degradation products, pyrazines, aldehydes and ketones in fragrant rapeseed oil all increased significantly after refining with the three kinds of silicon dioxide.

为了探明油菜籽微波预处理过程中的水分变化情况，建立油菜籽微波预处理干燥模型，对油菜籽在料层厚度12 mm、不同微波功率（1.0、1.5、2.0 kW）以及微波功率1.5 kW、不同料层厚度（6、12、18 mm）下预处理后的含水率、水分比和失水速率的变化情况进行了研究，并以常用的3种干燥模型指数模型、单项扩散模型和Page模型进行了数据拟合。结果表明:微波功率越高、料层越薄，油菜籽水分流失越快，微波预处理时间越短；微波预处理过程中油菜籽水分变化情况与Page模型拟合度最好。 In order to clarify the moisture changes during rapeseed microwave pretreatment process and establish rapeseed microwave pretreatment drying model, the changes in moisture content, moisture ratio and water loss rate of rapeseed after microwave pretreatment were investigated at a layer thickness of 12 mm and different microwave powers (1.0,1.5,2.0 kW), and at a microwave power of 1.5 kW and different layer thicknesses (6,12,18 mm), and data fitting was carried out with the common drying models of exponential model, single diffusion model and Page model. The results showed that the higher the microwave power and the thinner the material layer, the faster the moisture loss of rapseed and the shorter the pretreatment time. The changes in moisture of rapeseed during the microwave pretreatment process fitted best with the Page model.

Background: Age-related macular degeneration (AMD) is a progressive ocular ailment causing age-associated vision deterioration, characterized by dysregulated immune cell activity. Notably, follicular helper T (Tfh) cells have emerged as pivotal contributors to AMD pathogenesis. Nonetheless, investigations into Tfh-associated gene biomarkers for this disorder remain limited. Methods: Utilizing gene expression data pertinent to AMD procured from the Gene Expression Omnibus (GEO) repository, we employed the "DESeq2" R software package to standardize and preprocess expression levels. Concurrently, CIBERSORT analysis was utilized to compute the infiltration proportions of 22 distinct immune cell types. Subsequent to weighted gene correlation network analysis (WGCNA), coupled with differential expression scrutiny, we pinpointed genes intricately linked with Tfh cells. These potential genes underwent further screening using the MCODE function within Cytoscape software. Ultimately, a judicious selection of pivotal genes from these identified clusters was executed through the LASSO algorithm. Subsequently, a diagnostic nomogram was devised based on these selected genes. Results: Evident Tfh cell disparities between AMD and control cohorts were observed. Our amalgamated analysis, amalgamating differential expression data with co-expression patterns, unveiled six genes closely associated with Tfh cells in AMD. Subsequent employment of the LASSO algo-rithm facilitated identification of the most pertinent genes conducive to predictive modeling. From these, GABRB3, MFF, and PROX1 were elected as prospective diagnostic biomarkers for AMD. Conclusions: This investigation discerned three novel biomarker genes, linked to inflammatory mechanisms and pivotal in diagnosing AMD. Further exploration of these genes holds potential to foster novel therapeutic modalities and augment comprehension of AMD's disease trajectory. [ABSTRACT FROM AUTHOR]