In vitro cytotoxic and anti-cancer effects of body wall for sea cucumber (Holothuria leucospilota)

In recent years efforts to find bioactive compounds from live organisms especially marine animals have been increased. In the present study, the anticancer and cytotoxic effects of sea cucumber body walls (Holothuria leucospilota) were investigated. For this purpose, sea cucumbers were collected from Larak Island at depths of 10 to 30 m and extraction process was done with methanol and diethyl ether solvent which then concentrated by rotary evaporator (40℃) following lyophilization with vacuum freeze dryer. XTT method was used to investigate anticancer and cytotoxic effects of body wall extracts. The results showed that the methanolic extract could prevent proliferation of human oral epidermoid carcinoma cells (KB) at concentrations of 100 and 500 μg/ml. The diethyl etheric extract also could prevent proliferation of KB at 500 μg/ml concentration. Overall result showed that sea cucumber body wall had a strong cytotoxic effect on normal cell line (Human embryonic kidney cell [HEK]) which can be used as potent cytotoxic material. However these extracts did not show significant therapeutic value against KB cells

Comparison of antibacterial activities of Ircinia mutans extracts in two different seasons from Kish Island, Persian Gulf, Iran

Sponges, which constitute the phylum Porifera, are the most primitive of the multicellular animals, among all marine organisms screened. Marine sponges produce the largest number of structurally diversified natural products. In this study we investigated in vitro antimicrobial activity of Ircinia mutans collected from the Kish Island in the Persian Gulf against strains of bacteria Escherichia coli (ATCC 15224), Pseudomonas aeruginosa (ATCC 25619), Staphylococcus aureus (ATCC 1764), and Bacillus subtilis spizizenii (ATCC 6633). Diethyl etter, methanol and aqueous extracts of sponge were evaluated by using the Bacterial Broth Dilution Method. The results showed that the aqueous extracts didn’t have any antibacterial activity. Minimum Inhibitory Concentrations (MIC) of the winter diethyl etter extract was 2 mg/ml for E.coli and 20 mg/ml for P. aeruginosa, whereas the summer diethyl etter extract and both of methanol extracts did not show any activity. The MIC and MBC (Minimum Bacterial Concentration) of summer diethyl etter extracts were 2 mg/ml and 3mg/ml against S. aureus; and 5mg/ml and 10mg/ml when tested on B. subtilis. The MIC and MBC of winter diethyl etter extracts were measured as 1.5 mg/ml and 2mg/ml against S. aurous; and 5mg/ml and 10mg/ml when examined on B. subtilis. Summer and winter methanol and aqueous extracts of I. mutans did not show any activity against these bacteria. Therefore secondary metabolite solutions in diethyl etter contain components with antibacterial properties and can be used as antibiotics products

Preparation of nanostructured nickel aluminate spinel powder from spent NiO/Al2O3 catalyst by mechano-chemical synthesis

In this paper, the possibility of mechano-chemical synthesis, as a single step process for preparation of nanostructured nickel aluminate spinel powder from NiO/Al2O3 spent catalyst was investigated. Powder samples were characterized in terms of composition, morphology, structure, particle size and surface area using complementary techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), differential thermal analysis (DTA) and volumetric adsorption of nitrogen. It was found that formation of spinel was possible after 60 h of milling with no heat treatment. Additionally, influence of mechanical activation on the heat treatment temperature was discussed. It was observed that heat treatment of 15 h milled sample at 1100 °C is enough to produce nickel aluminate spinel. A product of direct mechanical milling showed higher value of surface area (42.3 m2/g) and smaller crystallite size (12 nm) as compared to the heat treated product.Gobierno de España ENE 2007-67926-C02-0

Distributed optimization framework for in-network data processing

In-Network Processing (INP) is an effective way to aggregate and process data from different sources and forward the aggregated data to other nodes for further processing until it reaches the end user. There is a trade-off between energy consumption for processing data and communication energy spent on transferring the data. Specifically, aggressive data aggregation consumes much energy for processing, but results in less data for transmission, thus using less energy for communications, and vice versa. An essential requirement in the INP process is to ensure that the user expectation of quality of information (QoI) is delivered during the process. Using wireless sensor networks for illustration and with the aim of minimising the total energy consumption of the system, we study and formulate the trade-off problem as a nonlinear optimisation problem where the goal is to determine the optimal data reduction rate, while satisfying the QoI required by the user. The formulated problem is a Signomial Programming (SP) problem, which is a non-convex optimisation problem and very hard to be solved directly. We propose two solution frameworks. First, we introduce an equivalent problem which is still SP and non-convex as the original one, but we prove that the strong duality property holds, and propose an efficient distributed algorithm to obtain the optimal data reduction rates, while delivering the required QoI. The second framework applies to the system with identical nodes and parameter settings. In such cases, we prove that the complexity of the problem can be reduced logarithmically. We evaluate our proposed frameworks under different parameter settings and illustrate the validity and performance of the proposed techniques through extensive simulation

Electric Power Grid Resilience to Cyber Adversaries: State of the Art

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The smart electricity grids have been evolving to a more complex cyber-physical ecosystem of infrastructures with integrated communication networks, new carbon-free sources of powergeneratio n, advanced monitoring and control systems, and a myriad of emerging modern physical hardware technologies. With the unprecedented complexity and heterogeneity in dynamic smart grid networks comes additional vulnerability to emerging threats such as cyber attacks. Rapid development and deployment of advanced network monitoring and communication systems on one hand, and the growing interdependence of the electric power grids to a multitude of lifeline critical infrastructures on the other, calls for holistic defense strategies to safeguard the power grids against cyber adversaries. In order to improve the resilience of the power grid against adversarial attacks and cyber intrusions, advancements should be sought on detection techniques, protection plans, and mitigation practices in all electricity generation, transmission, and distribution sectors. This survey discusses such major directions and recent advancements from a lens of different detection techniques, equipment protection plans, and mitigation strategies to enhance the energy delivery infrastructure resilience and operational endurance against cyber attacks. This undertaking is essential since even modest improvements in resilience of the power grid against cyber threats could lead to sizeable monetary savings and an enriched overall social welfare

A Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems

In this paper, a computational intelligence method is used for solution of fractional optimal control problems (FOCPs) with equality and inequality constraints. According to the Ponteryagin minimum principle (PMP) for FOCP with fractional derivative in the Riemann- Liouville sense and by constructing a suitable error function, we define an unconstrained minimization problem. In the optimization problem, we use trial solutions for the states, Lagrange multipliers and control functions where these trial solutions are constructed by a feed-forward neural network model. We then minimize the error function using a numerical optimization scheme where weight parameters and biases associated with all neurons are unknown. Examples are included to demonstrate the validity and capability of the proposed method. The strength of the proposed method is its equal applicability for the integer-order case as well as fractional order case. Another advantage of the presented approach is to provide results on entire finite continuous domain unlike some other numerical methods which provide solutions only on discrete grid of point

Knowledge Sharing Idiosyncrasies of University Students in Ghana

Part 6: Decision Making and Knowledge ManagementInternational audienceThis study explored the factors affecting knowledge sharing behaviour of students in a higher institution of learning. Using a model derived from the Social Cognitive Theory and the Theory of Reason Action, six hypotheses were tested from a cross-sectional data collected from 371 undergraduate students on a 4-year degree programme in the University of Ghana. Five out of the six hypotheses were supported. The results showed that the knowledge sharing behaviour (KSB) of the students was significantly related to five of the human and environmental factors (F=639.9, df=5, 290, p<0.05) with a co-efficient of variation of R2=0.917 (91.7%). The knowledge sharing behavior of the students was, however, not significantly dependent on their personal characteristics. The study makes a case for increased attention in understanding the human and environmental factors of knowledge sharing since knowledge sharing is largely a people activity shaped by culture