Synthesis and application of novel tricyanofuran hydrazone dyes as sensors for detection of microbes

Acknowledging the need to develop rapid and sensitive bacterial recognition approaches, we functionalised the tricyanofuran hydrazone molecular switch. Of significant interest in relation to the synthesised hydrazones is the formation of two different conjugated structures upon exposure to different pH values. Many bacteria release ammonia gas, which alkalises environments. Herein we report the synthesis of a tricyanofuran hydrazone having the function of a colorimetric pH sensor. The UV‐visible absorption and fluorescence spectra exhibit reversible colour changes of the tricyanofuran hydrazone solution in acetonitrile under acid–base conditions. Our results indicate that the tricyanofuran hydrazone probe can identify the bacterial targets quickly with high sensitivity. The infected samples exhibit a significant colour change from orange to blue and in the mean time there is a decrease in fluorescence emission as a function of ammonia and volatile amines released from bacterial metabolites. This tricyanofuran hydrazone chromophore is proposed for use in food packaging with a pH‐sensing capability.     

Gamma ray interaction with copper-doped sodium phosphate glasses

Copper-doped sodium phosphate glasses of various compositions and with varying copper contents were prepared. UV-visible and infrared spectroscopic studies were measured before and after successive gamma irradiation. Experimental results indicate that copper ions occupy different local sites depending on the host glass composition and concentration of copper ions. The changes in UV, visible and infrared spectral data, are discussed in relation to the structural evolution caused by the change in composition and states of copper ions. Copper ions have been found to show a shielding behavior toward the effects of progressive gamma irradiation causing a retardation of the growth of the induced defects caused by irradiation.     

Load Balancing Based on Multi-Agent Framework to Enhance CloudEnvironment

According to the advances in users’ service requirements, physical hardware accessibility, and speed of resource delivery, Cloud Computing (CC) is an essential technology to be used in many fields. Moreover, the Internet of Things (IoT) is employed for more communication flexibility and richness that are required to obtain fruitful services. A multi-agent system might be a proper solution to control the load balancing of interaction and communication among agents. This paper proposes a multi-agent load balancing framework that consists of two phases to optimize the workload among different servers with large-scale CC power with various utilities and a significant number of IoT devices with low resources. Different agents are integrated based on relevant features of behavioral interaction using classification techniques to balance the workload. A load balancing algorithm is developed to serve users’ requests to improve the solution of workload problems with an efficient distribution. The activity task from IoT devices has been classified by feature selection methods in the preparatory phase to optimize the scalability of CC. Then, the server’s availability is checked and the classified task is assigned to its suitable server in the main phase to enhance the cloud environment performance. Multi-agent load balancing framework is succeeded to cope with the importance of using large-scale requirements of CC and (low resources and large number) of IoT.     

An entropy approach for abnormal activities detection in video streams

Detection of aberration in video surveillance is an important task for public safety. This paper puts forward a simple but effective framework to detect aberrations in video streams using Entropy, which is estimated on the statistical treatments of the spatiotemporal information of a set of interest points within a region of interest by measuring their degree of randomness of both directions and displacements. Entropy is a measure of the disorder/randomness in video frame. It has been showed that degree of randomness of the directions (circular variance) changes markedly in abnormal state of affairs and does change only direction variation but does not change with displacement variation of the interest point. Degree of randomness of the displacements has been put in for to counterbalance this deficiency. Simple simulations have been exercised to see the characteristics of these crude elements of entropy. Normalized entropy measure provides the knowledge of the state of anomalousness. Experiments have been conducted on various real world video datasets. Both simulation and experimental results report that entropy measures of the frames over time is an outstanding way to characterize anomalies in videos.     

Diffusion as a method for producing architectured materials

We describe the use of controlled diffusion treatments to arrange the distribution of alloying elements within a material. The Fe–C system is particularly interesting because of the strong effect of carbon on the mechanical properties and phase stability of steel. We demonstrate, through multi-step treatments, both one-dimensional and two-dimensional distributions of carbon within steel. A sample two-dimensional architecture is prepared and characterized to demonstrate feasibility. We briefly introduce a global optimization algorithm as a method for computationally optimizing treatment schedules.     

Purification of metallurgical-grade silicon powder via chemical attack by hydrofluoric and nitric acids followed by thermal treatment

We investigated a novel process for purifying metallurgical-grade silicon (MG-Si). MG-Si powder was first treated to form a thin porous silicon layer. This was heated at 900 °C under oxygen to weaken impurity–Si bonds. Samples were then chemically etched with dilute aqueous hydrofluoric acid. To understand the mechanisms in this purification process, structural, chemical composition and optical properties of MG-Si powder before and after treatment were characterized using Fourier-transform infrared (FTIR), inductively coupled plasma-atomic emission (ICP-AES), and photoluminescence (PL) spectroscopy techniques. FTIR studies of treated MG-Si powder revealed the formation of a thin porous silicon layer on the top surface, as evidenced by SiH_x vibration peaks. PL spectra show that 30-min HF etching of MG-Si led to an increase in red emission, indicating the formation of porous silicon and suggesting a decrease in impurities. ICP-AES revealed that the process led to significant decreases in the concentrations of 15 different elemental impurities.     

Optimal Power Allocation and Harvesting Duration for NOMA Systems in the Presence of Nakagami Channels

In this paper, we derive and optimize the total throughput of non orthogonal multiple access (NOMA) with energy harvesting. The source S harvests energy from radio frequency signal received from node A. The source uses the harvested energy to transmit data to N NOMA users classified using instantaneous or average power of channel gains. We optimize the powers allocated to NOMA users and harvesting duration to maximize the total throughput. We also derive packet waiting time and total delays for all NOMA users. We optimize powers allocated to NOMA users and harvesting duration to minimize a combination of total delays of all users. Our results are valid for Nakagami channels with arbitrary positions of users.

     

Adaptive cooperation for free space optical communications

Telecommunication Systems - In this paper, we propose a new Adaptive Cooperation (AC) protocol for Free Space Optical (FSO) communications. Two versions of the protocol are presented. The first...     

Facet-Dependent Intrinsic Activity of Single Co3O4 Nanoparticles for Oxygen Evolution Reaction

Deciphering the influence of nanocatalyst morphology on their catalytic activity in the oxygen evolution reaction (OER), the limiting reaction in water splitting process, is essential to develop highly active precious metal-free catalysts, yet poorly understood. The intrinsic OER activity of Co₃O₄ nanocubes and spheroids is probed at the single particle level to unravel the correlation between exposed facets, (001) vs. (111), and activity. Single cubes with predominant (001) facets show higher activity than multi-faceted spheroids. Density functional theory calculations of different terminations and reaction sites at (001) and (111) surfaces confirm the higher activity of the former, expressed in lower overpotentials. This is rationalized by a change in the active site from octahedral to tetrahedral Co and the potential-determining step from *OH to *O for the cases with lowest overpotentials at the (001) and (111) surfaces, respectively. This approach enables the identification of highly active facets to guide shape-selective syntheses of improved metal oxide nanocatalysts for water oxidation.     

An energy efficient Genetic Algorithm based approach for sensor-to-sink binding in multi-sink wireless sensor networks

Wireless sensor networks (WSNs) are ad-hoc networks in which sensors, that are designed to relay data back to sink nodes and/or Base Stations, are deployed in an area and may be configured in real time. Sensors, however, have limited energy supplies and are often left untouched after deployment, thus making battery replacement very difficult or even impossible. Therefore, energy should be efficiently conserved to extend the WSNs lifetime. One of the existing solutions is to deploy multiple sinks, more capable nodes in comparison to sensors, in the network to increase the coverage area and shorten the communication distance between sensors and sinks. However, this raises the issue concerning which sensors should bind to which sinks in order to avoid overloading particular sinks. In this paper, we devise a Genetic Algorithm based approach to solve the problem of balancing the load of sensors amongst sinks in a multi-sink WSN, while ensuring that the best routes to sinks are found for the sensors that cannot directly reach a sink. We evaluate the performance of our approach and compare it to an existing one using the network simulator NS-2 through measuring several metrics such as the variance of remaining energy among sinks, and energy consumption in sinks. The obtained results show that the proposed approach promising.