A bigraphical model for specifying cloud-based elastic systems and their behaviour

The few recent years have witnessed the appearance of a new kind of self-adaptive systems called cloud based-elastic systems. These systems are particularly appealing for their ability to maintain a decent quality of service and reduce a system’s operating cost at the same time. They achieve this by dynamically adjusting resources allocation in terms of elasticity. Meanwhile, complexity of structural and behavioural aspects related to cloud-based elastic systems increase the difficulty of designing and developing such systems. In this paper, we address this challenge by proposing a formal approach based on bigraphical reactive systems for modelling both structural and behavioural aspects of cloud-based elastic systems. In particular, we represent their behaviour in terms of client/application interactions and elasticity methods at different levels using bigraphical reaction rules. The feasibility of the proposed approach is illustrated through a motivating example running on the top of an Amazon Elastic Compute Cloud (EC2) infrastructure.     

Influences of superheated steaming and roasting on the quality and antioxidant activity of cooked sweet potatoes

Roasted sweet potato is a popular food because of the attractive aroma produced by the Maillard reaction. However, the roasting process may lead to charred skin. Cooking with superheated (saturated) steam provides a solution to this problem. As the results show, when comparing sweet potatoes cooked by superheated steam, and those roasted for 40 min, respectively, the degree of gelatinisation could reach as high as 95% with only 140 °C superheated steam, while roasting required temperatures up to 240 °C. Moreover, in appearance, the skins of the sweet potatoes cooked using superheated steam were not charred like the roasted ones. However, sweet potatoes roasted at 240 °C for 60 min had the highest overall sensory score. When comparing the antioxidant activity, the sweet potatoes cooked by superheated steam had the highest content of total phenol and flavonoids, the best scavenging ability of 1,1‐diphenyl‐2‐picrylhydrazyl (DPPH) and the highest ferric‐reducing ability of plasma (FRAP).     

Morphological, structural, and functional properties of maranta (Maranta arundinacea L) starch

Starch isolated from maranta (Maranta arundinacea) tuber and studied for its various physicochemical characteristics. The amylose content of the starch was 24.8%. SEM showed that the granules were small indented and spherical. Maranta starch granule size has a range of 2.92–6.42 μm, (mean of 4.84 μm), length/degree of 1.20, and roundness of 0.73. Maranta starch has a gelatinization temperature of 74.8°C, peak viscosity of 498 BU, and cold paste viscosity of 669 BU. It also possessed higher freeze-thaw stability. Dynamic rheological properties of maranta starch, measured using parallel plate geometry showed increased storage modulus (G’) values, while loss modulus (G″) values were decreased with increasing frequency values (0–100 Hz). The low gelatinization temperature and high freeze thaw stability of starch indicates its potential for application as a thickener in food industries.     

Preparation and properties of probiotic concentrated yoghurt (labneh) fortified with conjugated linoleic acid

Milk of high conjugated linoleic acid (CLA) level (1.25 g per 100 g milk fat) was produced by inclusion of fish oil and rousted soy bean in the ration of Holstein cows as compared to 0.55 g per 100 g milk fat in the milk of animals receiving control diet. Milk of normal (control) and high CLA content (treatment) was spray‐dried. Labneh was made from 20 g L^?1 reconstituted milk using 3 mL per 100 mL yoghurt starter and 2 mL per 100 mL of probiotic cultures of Lactobacillus casei or Lactobacillus acidophilus. The control (C) and high CLA (T) labneh were analysed chemically and microbiologically, and their viscosities were determined during cold storage for 15 days. The fat content of labneh of high CLA was less than that of the control, but the total solids (TS) were unaffected by the CLA level. Labneh made with Lb. acidophilus had lower TS and higher acidity, exopolysaccharides and acetaldehyde contents and viscosity than that made with the use of Lb. casei. Labneh from the different treatments retained high counts of the added probiotic (>10⁸ cfu g^?1) throughout the storage period. The storage period had significant effects on all parameters determined.     

A self-constructing cascade classifier with AdaBoost and SVM for pedestriandetection

In this paper, we propose a cascade classifier combining AdaBoost and support vector machine, and applied this to pedestrian detection. The pedestrian detection involved using a window of fixed size to extract the candidate region from left to right and top to bottom of the image, and performing feature extractions on the candidate region. Finally, our proposed cascade classifier completed the classification of the candidate region. The cascade-AdaBoost classifier has been successfully used in pedestrian detection. We have improved the initial setting method for the weights of the training samples in the AdaBoost classifier, so that the selected weak classifier would be able to focus on a higher detection rate other than accuracy. The proposed cascade classifier can automatically select the AdaBoost classifier or SVM to construct a cascade classifier according to the training samples, so as to effectively improve classification performance and reduce training time. In order to verify our proposed method, we have used our extracted database of pedestrian training samples, PETs database, INRIA database and MIT database. This completed the pedestrian detection experiment whose result was compared to those of the cascade-AdaBoost classifier and support vector machine. The result of the experiment showed that in a simple environment involving campus experimental image and PETs database, both our cascade classifier and other classifiers can attain good results, while in a complicated environment involving INRA and MIT database experiments, our cascade classifier had better results than those of other classifiers.     

Digital preservation of a Taiwanese historical settlement: Using 3D post-construction scan to develop an application framework and reference for Beipu Township

The purpose of this study is to build a post-construction 3D computer model of the historical settlement of Beipu Township in Taiwan as an application and reference framework. The cultural assets were digitally preserved in a post-construction and modified form as an attempt to fulfill the life-cycle management of data for culture workers, researchers and architects. The scan process was managed in four hierarchies: the whole region, the seven historical buildings, the four streets and the special features, in different scales. The final digital model integrates research results from all involved parties, integrates local practice needs, represents hypothesis in city development, enhances historical understanding and interpretation, and facilitates remote access.     

Postponement growth and antioxidative response of Brassica nigra on CuO and ZnO nanoparticles exposure under soil conditions

Due to unique physiochemical properties, nanoparticles (NPs) have acquired substantial attention in the field of research. However, threats of ecotoxicity and phytotoxicity have limited their biological applications. In this study in vivo experiments were performed to determine the effect of CuO (12.5, 25 and 50 mg/kg) and ZnO (200, 400 and 600 mg/kg) NPs on growth, and antioxidant activities of Brassica nigra. The results showed that CuO NPs did not affect the seed germination while presence of ZnO NPs in the soil generated an inhibitory effect. Both CuO and ZnO NPs positively influenced the growth of stem and other physiological parameters i.e. stem height increased (23%) at 50 mg/kg CuO while root length decreased (up to 44%) with an increase in the concentration of NPs. Phytochemical screening of apical, middle and basal leaves showed elevated phenolic and flavonoid contents in the range of 15.3–59 μg Gallic Acid Equivalent (GAE)/mg Dry Weight (DW) and 10–35 μg Querceitin Equivalent (QE)/mg DW, respectively, in NPs‐treated plants. Antioxidant activity was higher in CuO NPs‐treated plants as compared to ZnO and control plants. Results conclude that CuO and ZnO NPs at low concentrations can be exploited as nanofertilisers in agriculture fields.Inspec keywords: biochemistry, enzymes, renewable materials, crops, nanoparticles, soil, nanofabrication, zinc compounds, organic compounds, agricultural products, toxicology, nanobiotechnologyOther keywords: antioxidative response, ZnO nanoparticles exposure, soil conditions, unique physiochemical properties, germination, antioxidant activities, brassica nigra plant, antioxidant activity, CuO NP‐treated plants, control plants, ZnO NPs effect, mass 15.3 mug to 59.0 mug, mass 10.0 mug to 35.0 mug, CuO, ZnO