Chemical composition and nutritional quality of tehineh (sesame butter)

The chemical composition and nutritional quality of tehineh, a paste of dehulled roasted sesame seeds, from Saudi Arabia and other countries, were studied. Results showed 24.7% protein, 58.9% fat, 2.3% fiber, 3.0% ash and <1.0% moisture. The tehineh contained relatively high amounts (mg/100 g) of P (692), Mg (362), Fe (7.19), Cu (1.96), Mn (1.46) and Zn (7.82) and low amounts of Ca (61) and Se (0.05). Gas-liquid chromatography (GLC) analysis of the oil revealed percentages of 42.4 for oleic, 39.7 for linoleic, 9.8 for palmitic and 6.4 for stearic acid. Lysine was the only limiting amino acid with a chemical score of 64, while the sulphur-containing amino acids (methionine + cystine) and tryptophan were present in amounts exceeding the requirement of the FAO/WHO (1973) reference protein. The in vitro protein digestibility (IVPD) value of 83.3% and the calculated protein efficiency ratio (C-PER), 2.14, were slightly higher than those of sesame seeds and both values were lower than the IVPD and C-PER of 90.0% and 2.50, respectively, for ANRC casein.     

Design and control of an olefin metathesis reactive distillation column

This paper considers the design and control of a reactive distillation column in which one reactant is consumed and two products are formed (A?B+C). The volatilities are α_B>α_A>α_C, i.e. the reactant is intermediate boiling between the two products. The metathesis of 2-pentene is considered as the demonstrative example. The column has a single feed of the intermediate boiling reactant. The distillate contains mostly light component and the bottoms mostly heavy.Three designs are considered: the base case (low-conversion/low-pressure), a low-conversion/high-pressure case and a high-conversion/high-pressure case. The base design is obtained from the literature, and the other two steady-state designs are optimized with respect to the total annual cost. All the designs are found to be openloop stable. Five control structures are studied for the base design. Then the best two structures are applied to the remaining two designs. This category of reactive distillation exhibits less challenging problems than other categories since it uses a single feed, which eliminates the need for the control structure to perfectly balance two fresh feeds.Simulation results demonstrate that effective dynamic control is provided by a control structure that uses two temperatures to maintain the purities of both product streams. No internal composition measurement is required. This structure is found to be robust and stable and rejects loads and tracks setpoints very well.     

Using Automated Negotiation for Grid Services

The popularity of grid services has widened their application to numerous domains and increased the utilization of computational resources. In order to create more incentives for the resources owners to lease their resources and prevent users from wasting the resources, the introduction of a market-oriented grid is inevitable. However, the issues for the negotiation between service provider and consumer over the supply and demand of resources can be complex, with highly interdependent issues. In this research, a simulated automated negotiation mechanism including a co-evolutionary mechanism and a modified game theory approach is proposed, to assist them in reaching an agreement over the conflicting issues. In the proposed architecture, the co-evolution process is able to reduce the multiple dimensional search space into a two-dimension search space and identify the appropriate negotiation strategies for the negotiating agents to form a payoff matrix which can be used for the game theory related stage of their interaction. The multiple stage negotiation process is introduced to improve the negotiation result. In this paper, an application which requires a large amount of computational resources to process the data generated from mobile devises is used to demonstrate that the proposed system is able to resolve the conflicts and obtain a valid solution.     

Tumor size and prognosis in aggressively treated osteosarcoma

PURPOSE: The aim of this retrospective analysis was to investigate the prognostic significance and optimal measures of tumor size in osteosarcoma treated with intensive neoadjuvant chemotherapy. PATIENTS AND METHODS: Initial anterior-posterior (AP) and lateral x-ray films of 128 patients treated within the trials Cooperative Osteosarcoma Study (COSS)-80, -82, and -86, were evaluated for the following three tumor diameters: length, width, and depth. Metastasis-free survival (MFS) analyses were performed in univariate and multivariate models with one, two, and three dimensions of the tumor as absolute or relative measures (tumor length, referred to bone length, plane and volume to body-surface area). RESULTS: Univariate analyses of MFS showed a high prognostic significance of all absolute measures. Relative measures, at best, showed a comparable predictive value. Cox regression analysis indicated the high prognostic significance of absolute tumor volume (ATV; P < .0001) and histologic response (P < .0001). None of 19 patients with an ATV < or = 70 cm3 and only four of 53 with an ATV < or = 150 cm3 relapsed, while in patients with an ATV more than 150 cm3, the relapse rate remained 40% to 60%, irrespective of further increase in volume. CONCLUSION: Initial tumor size is an important and easily obtainable prognostic factor in osteosarcoma and may serve as a basis for risk-adapted therapy. It is best represented by the absolute three-dimensional measure ATV. There is a cut-off point regarding the incidence of metastases at a tumor volume of approximately 150 cm3 as calculated from two-plane x-ray films.     

Harmonic and intermodulation performance in an R-LED series network

Analytical expressions are obtained for predicting the harmonic and intermodulation performance of R-LED series networks. These expressions are in terms of the ordinary Bessel functions with arguments depenedent on the modulation index.     

The Bivariate Transmuted Family of Distributions: Theory and Applications

The bivariate distributions are useful in simultaneous modeling of two random variables. These distributions provide a way to model models. The bivariate families of distributions are not much widely explored and in this article a new family of bivariate distributions is proposed. The new family will extend the univariate transmuted family of distributions and will be helpful in modeling complex joint phenomenon. Statistical properties of the new family of distributions are explored which include marginal and conditional distributions, conditional moments, product and ratio moments, bivariate reliability and bivariate hazard rate functions. The maximum likelihood estimation (MLE) for parameters of the family is also carried out. The proposed bivariate family of distributions is studied for the Weibull baseline distributions giving rise to bivariate transmuted Weibull (BTW) distribution. The new bivariate transmuted Weibull distribution is explored in detail. Statistical properties of the new BTW distribution are studied which include the marginal and conditional distributions, product, ratio and conditional momenst. The hazard rate function of the BTW distribution is obtained. Parameter estimation of the BTW distribution is also done. Finally, real data application of the BTW distribution is given. It is observed that the proposed BTW distribution is a suitable fit for the data used.     

A review on fault detection and diagnosis techniques: basics and beyond

Safety and reliability are absolutely important for modern sophisticated systems and technologies. Therefore, malfunction monitoring capabilities are instilled in the system for detection of the incipient faults and anticipation of their impact on the future behavior of the system using fault diagnosis techniques. In particular, state-of-the-art applications rely on the quick and efficient treatment of malfunctions within the equipment/system, resulting in increased production and reduced downtimes. This paper presents developments within Fault Detection and Diagnosis (FDD) methods and reviews of research work in this area. The review presents both traditional model-based and relatively new signal processing-based FDD approaches, with a special consideration paid to artificial intelligence-based FDD methods. Typical steps involved in the design and development of automatic FDD system, including system knowledge representation, data-acquisition and signal processing, fault classification, and maintenance related decision actions, are systematically presented to outline the present status of FDD. Future research trends, challenges and prospective solutions are also highlighted.

     

A dynamic variability management approach working with agile product line engineering practices for reusing features

The Journal of Supercomputing - Agile software development (ASD) and software product line (SPL) have shown significant benefits for software engineering processes and practices. Although both...     

Collaborative detection and mitigation of DDoS in software-defined networks

The Journal of Supercomputing - This research presents the detection and mitigation of distributed denial of service (DDoS) in software defined networks (SDN). The proposed method consists of three...     

Smart home security: challenges,issues and solutions at different IoT layers

The Journal of Supercomputing - The Internet of Things is a rapidly evolving technology in which interconnected computing devices and sensors share data over the network to decipher different...