In Vitro Antiprotozoal Activity of Abietane Diterpenoids Isolated from Plectranthus barbatus Andr.

Chromatographic separation of the n-hexane extract of the aerial part of Plectranthus barbatus led to the isolation of five abietane-type diterpenes: dehydroabietane (1); 5,6-didehydro-7-hydroxy-taxodone (2); taxodione (3); 20-deoxocarnosol (4) and 6α,11,12,-trihydroxy-7β,20-epoxy-8,11,13-abietatriene (5). The structures were determined using spectroscopic methods including one- and two-dimensional NMR methods. Compounds (1)–(3) and (5) are isolated here for the first time from the genus Plectranthus. The isolated abietane-type diterpenes tested in vitro for their antiprotozoal activity against erythrocytic schizonts of Plasmodium falciparum, intracellular amastigotes of Leishmania infantum and Trypanosoma cruzi and free trypomastigotes of T. brucei. Cytotoxicity was determined against fibroblast cell line MRC-5. Compound (2) 5,6-didehydro-7-hydroxy-taxodone showed remarkable activity with acceptable selectivity against P. falciparum (IC₅₀ 9.2 μM, SI 10.4) and T. brucei (IC₅₀ 1.9 μM, SI 50.5). Compounds (3)–(5) exhibited non-specific antiprotozoal activity due to high cytotoxicity. Compound (1) dehydroabietane showed no antiprotozoal potential.     

Analysis of Distribution of Nonmetallic Inclusions in Aluminum DC-Cast Billets and Slabs

Inclusion distribution was studied in commercial aluminum DC-cast billets and slabs using a newly developed deep-etching method. Analyses revealed a nonuniform distribution of nonmetallic inclusions across billet diameters and lengths, and also across slab thicknesses and widths. In as-cast billets, more inclusions were found at the beginning and end of the billet length; more were present near the cross-section center than near the surface. In slabs, inclusions were located mostly within 13 mm of the surface and in a band between the centerline and the surface. Few inclusions were found 60 to 100 mm from the slab surface or at the centerline. In addition, comparing slab quality after casting using three types of ceramic foam filters (CFFs; i.e., 30 ppi, 50 ppi, and 50 ppi + HF) revealed significant differences in inclusion size, number, and distribution. Casting slabs using a finer pore-size filter (50 ppi) reduced the number of non-metallic inclusions greatly. The inclusion distribution patterns observed in the solidified slabs are discussed in terms of melt flow during casting.     

Tea and coffee consumption in relation to vitamin D and calcium levels in Saudi adolescents

ABSTRACT: BACKGROUND: Coffee and tea consumption was hypothesized to interact with variants of vitamin D-receptor polymorphisms, but limited evidence exists. Here we determine for the first time whether increased coffee and tea consumption affects circulating levels of 25-hydroxyvitamin D in a cohort of Saudi adolescents. METHODS: A total of 330 randomly selected Saudi adolescents were included. Anthropometrics were recorded and fasting blood samples were analyzed for routine analysis of fasting glucose, lipid levels, calcium, albumin and phosphorous. Frequency of coffee and tea intake was noted. 25-hydroxyvitamin D levels were measured using enzyme-linked immunosorbent assays. RESULTS: Improved lipid profiles were observed in both boys and girls, as demonstrated by increased levels of HDL-cholesterol, even after controlling for age and BMI, among those consuming 9--12 cups of coffee/week. Vitamin D levels were significantly highest among those consuming 9--12 cups of tea/week in all subjects (p-value 0.009) independent of age, gender, BMI, physical activity and sun exposure. CONCLUSION: This study suggests a link between tea consumption and vitamin D levels in a cohort of Saudi adolescents, independent of age, BMI, gender, physical activity and sun exposure. These findings should be confirmed prospectively.     

Application-aware virtual paths insertion for NOCs

Network-on-chip (NoC) has rapidly become a promising alternative for complex system-on-chip architectures including recent multicore architectures. Additionally, optimizing NoC architectures with respect to different design objectives that are suitable for a particular application domain is crucial for achieving high-performance and energy-efficient customized solutions. Despite the fact that many researches have provided various solutions for different aspects of NoCs design, a comprehensive NoCs system solution has not emerged yet. This paper presents a novel methodology to provide a solution for complex on-chip communication problems to reduce power, latency and area overhead. Our proposed NoC communication architecture is based on setting up virtual source–destination paths between selected pairs of NoCs cores so that the packets belonging to distance nodes in the network can bypass intermediate routers while traveling through these virtual paths. In this scheme, the paths are constructed for an application based on its task-graph at the design time. After that, the run time scheduling mechanism is applied to improve the buffer management, virtual channel and switch allocation schemes and hence, the constructed paths are optimized dynamically. Moreover, in our design the router complexity and its overheads are reduced. Additionally, the suggested router has been implemented on Xilinx Virtex-5 FPGA family. The evaluation results captured by SPLASH-2 benchmark suite reveal that in comparison with the conventional NoC router, the proposed router takes 25% and 53% reduction in latency and energy, respectively besides 3.5% area overhead. Indeed, our experimental results demonstrate a significant reduction in the average packet latency and total power consumption with negligible area overhead.     

Robust tools for prediction of variability and optimization in structural dynamics

The aims of this work were to quantify the effects of uncertainties of design parameters on the variability of linear and non-linear behaviour of mechanical structures that we wish to optimize, and to calculate optimal and robust solutions resulting from numerical simulations. We propose a method that takes into account the propagation of uncertainties in finite-element models in a multi-objective optimization procedure. This method is based on coupling the stochastic response surface method (SRSM) and the non-dominated sorting genetic algorithm (NSGA). SRSM is based on application of the stochastic finite-element method via the polynomial chaos expansion method or the modal perturbation method. This strategy avoids the use of Monte Carlo simulation, in which costs can become prohibitive in optimization problems, especially when the finite-element models are large and have a considerable number of design parameters. The robust design described here has been developed to obtain an optimum value that is insensitive to changes of design variables within a feasible range.     

A simple and accurate method for calibrating the oscillation amplitude of tuning-fork based AFM sensors

We have developed a simple and accurate method for calibrating the amplitude of vibration of quartz tuning fork sensors commonly used in atomic force- and near field optical-microscopy. Unlike interferometric methods, which require a complex optical setup, the method we present requires only a simple measurement of the electro-mechanical properties of the tuning-fork oscillator and can be performed in a matter of minutes without disturbing the experimental setup. Comparison with interferometric methods shows that an accuracy of better than few percent can be routinely achieved.     

Multilayer Self-Defense System to Protect Enterprise Cloud

A data breach can seriously impact organizational intellectual property, resources, time, and product value. The risk of system intrusion is augmented by the intrinsic openness of commonly utilized technologies like TCP/IP protocols. As TCP relies on IP addresses, an attacker may easily trace the IP address of the organization. Given that many organizations run the risk of data breach and cyber-attacks at a certain point, a repeatable and well-developed incident response framework is critical to shield them. Enterprise cloud possesses the challenges of security, lack of transparency, trust and loss of controls. Technology eases quickens the processing of information but holds numerous risks including hacking and confidentiality problems. The risk increases when the organization outsources the cloud storage services through the vendor and suffers from security breaches and need to create security systems to prevent data networks from being compromised. The business model also leads to insecurity issues which derail its popularity. An attack mitigation system is the best solution to protect online services from emerging cyber-attacks. This research focuses on cloud computing security, cyber threats, machine learning-based attack detection, and mitigation system. The proposed SDN-based multilayer machine learning-based self-defense system effectively detects and mitigates the cyber-attack and protects cloud-based enterprise solutions. The results show the accuracy of the proposed machine learning techniques and the effectiveness of attack detection and the mitigation system.