No abstract

Cadmium (Cd) is one of the most phytotoxic elements causing an agricultural problem and human health hazards. This work investigates whether and how silicon (Si) ameliorates Cd toxicity in Alfalfa. The addition of Si in Cd-stressed plants caused significant improvement in morpho-physiological features as well as total protein and membrane stability, indicating that Si does have critical roles in Cd detoxification in Alfalfa. Furthermore, Si supplementation in Cd-stressed plants showed a significant decrease in Cd and Fe concentrations in both roots and shoots compared with Cd-stressed plants, revealing that Si-mediated tolerance to Cd stress is associated with Cd inhibition in Alfalfa. Results also showed no significant changes in the expression of two metal chelators [MsPCS1 (phytochelatin synthase) and MsMT2 (metallothionein)] and PC (phytochelatin) accumulation, indicating that there may be no metal sequestration or change in metal sequestration following Si application under Cd stress in Alfalfa. We further performed a targeted study on the effect of Si on Fe uptake mechanisms. We observed the consistent reduction in Fe reductase activity, expression of Fe-related genes [MsIRT1 (Fe transporter), MsNramp1 (metal transporter) and OsFRO1 (ferric chelate reductase] and Fe chelators (citrate and malate) by Si application to Cd stress in roots of Alfalfa. These results support that limiting Fe uptake through the down-regulation of Fe acquisition mechanisms confers Si-mediated alleviation of Cd toxicity in Alfalfa. Finally, an increase of catalase, ascorbate peroxidase, and superoxide dismutase activities along with elevated methionine and proline subjected to Si application might play roles, at least in part, to reduce H2O2 and to provide antioxidant defense against Cd stress in Alfalfa. The study shows evidence of the effect of Si on alleviating Cd toxicity in Alfalfa and can be further extended for phytoremediation of Cd toxicity in plants.

The simple, fast and highly sensitive anodic stripping voltammetric detection of As(III) at a gold (Au) nanoparticlemodified glassy carbon (GC) (nano-Au/GC) electrode in HCl solution was extensively studied. The Au nanoparticles were electrodeposited onto GC electrode using chronocoulometric technique via a potential step from 1.1 to 0 V vs. Ag j AgCl j NaCl (sat.) in 0.5 M H 2 SO 4 containing Na [AuCl 4 ] in the presence of KI, KBr, Na 2 S and cysteine additives. Surfaces of the resulting nano-Au/GC electrodes were characterized with cyclic voltammetry. The performances of the nano-Au/GC electrodes, which were prepared using different concentrations of Na[AuCl 4 ] (0.05 -0.5 mM) and KI additive (0.01 -1.0 mM) at various deposition times (10 -30 s), for the voltammetric detection of As(III) were examined. After the optimization, a high sensitivity of 0.32 mA cm À2 mM À1 and detection limit of 0.024 mM (1.8 ppb) were obtained using linear sweep voltammetry.

Phishing is a form of electronic identity theft in which a combination of social engineering and web site spoofing techniques are used to trick a user into revealing confidential information with economic value. The problem of social engineering attack is that there is no single solution to eliminate it completely, since it deals largely with the human factor. This is why implementing empirical experiments is very crucial in order to study and to analyze all malicious and deceiving phishing website attack techniques and strategies. In this paper, three different kinds of phishing experiment case studies have been conducted to shed some light into social engineering attacks, such as phone phishing and phishing website attacks for designing effective countermeasures and analyzing the efficiency of performing security awareness about phishing threats. Results and reactions to our experiments show the importance of conducting phishing training awareness for all users and doubling our efforts in developing phishing prevention techniques. Results also suggest that traditional standard security phishing factor indicators are not always effective for detecting phishing websites, and alternative intelligent phishing detection approaches are needed.

Abstract-Phishing websites are forged web pages that are created by malicious people to mimic web pages of real websites and it attempts to defraud people of their personal information. Detecting and identifying Phishing websites is really a complex and dynamic problem involving many factors and criteria, and because of the subjective considerations and the ambiguities involved in the detection, Fuzzy Logic model can be an effective tool in assessing and identifying phishing websites than any other traditional tool since it offers a more natural way of dealing with quality factors rather than exact values. In this paper, we present novel approach to overcome the 'fuzziness' in traditional website phishing risk assessment and propose an intelligent resilient and effective model for detecting phishing websites. The proposed model is based on FL operators which is used to characterize the website phishing factors and indicators as fuzzy variables and produces six measures and criteria's of website phishing attack dimensions with a layer structure. Our experimental results showed the significance and importance of the phishing website criteria (URL & Domain Identity) represented by layer one, and the variety influence of the phishing characteristic layers on the final phishing website rate.