Efficient biodegradation of naphthalene by a newly characterized indigenous Achromobacter sp. FBHYA2 isolated from Tehran Oil Refinery Complex

A bacterial strain, FBHYA2, capable of degrading naphthalene, was isolated from the American Petroleum Institute (API) separator of the Tehran Oil Refinery Complex (TORC). Strain FBHYA2 was identified as Achromobacter sp. based on physiological and biochemical characteristics and also phylogenetic similarity of 16S rRNA gene sequence. The optimal growth conditions for strain FBHYA2 were pH 6.0, 30 °C and 1.0% NaCl. Strain FBHYA2 can utilize naphthalene as the sole source of carbon and energy and was able to degrade naphthalene aerobically very fast, 48 h for 96% removal at 500 mg/L concentration. The physiological response of Achromobacter sp., FBHYA2 to several hydrophobic chemicals (aliphatic and aromatic hydrocarbons) was also investigated. No biosurfactant was detected during bacterial growth on any aliphatic/aromatic hydrocarbons. The results of hydrophobicity measurements showed no significant difference between naphthalene- and LB-grown cells. The capability of the strain FBHYA2 to degrade naphthalene completely and rapidly without the need to secrete biosurfactant may make it an ideal candidate to remediate polycyclic aromatic hydrocarbon (PAH)-contaminated sites.     

Parkinson’s Disease Detection Using Biogeography-Based Optimization

In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, ACO and ES method. The outcomes affirm that the MLP-BBO model exhibits higher precision and suitability for PD detection. The proposed diagnosis system as a type of speech algorithm detects early Parkinson’s symptoms, and consequently, it served as a promising new robust tool with excellent PD diagnosis performance.     

In situ observation of morphological change in CdTe nano- and submicron wires

We report growth and characterization of CdTe wires 30–400 nm in diameter by the vapor–liquid–solid technique. Individual nanowires were placed on a movable piezotube, which allowed three-dimensional motion toward a scanning tunneling microscope (STM). A bias was applied to the STM tip in contact with the nanowire, and the morphological changes due to Joule heating were observed in situ using a transmission electron microscope (TEM) in real time. For thick CdTe wires (d > ~150 nm), the process results in the growth of superfine nanowires (SFNWs) of 2–4 nm diameter on the surface of the wire. Smaller diameter nanowires, in contrast, disintegrate under the applied bias before the complete evolution of SFNWs on the surface.     

Operational scheduling of responsive prosumer farms for day‐ahead peak shaving by agricultural demand response aggregators

This paper proposes a novel structure to optimize the operational strategies of responsive farms for day‐ahead peak shaving. To achieve the aim, the modern irrigation system of farms, including groundwater, surface water, and booster water pumps, are modeled mathematically. To develop the demand response (DR) potentials of the farms, electrical storage systems, and self‐generation facilities, including thermal distributed generations and on‐farm solar sites, are addressed. In order to facilitate the integration of the agricultural DR programs into the electricity market, a mathematical formulation for agricultural demand response aggregator (ADRA) is suggested. The ADRA participates in the day‐ahead electricity market on behalf of the responsive farms. To overcome the price uncertainty of the electricity market, a robust optimization approach is addressed. This approach determines the robust decisions of farms in the worst‐case realizations of the uncertain electricity price. Regarding on‐farm solar sites located in rural areas, a data‐driven approach is used to estimate the solar power generation of a significant number of sites without needing to install costly communication and measurement infrastructures. Finally, the proposed approach is implemented on agricultural lands in the northeast of Iran. The numerical results show that the suggested approach provides day‐ahead peak shaving for the power systems meeting the crop's water requirements.     

Nonaxisymmetric elastoacoustic analysis of a submerged eccentric hollow sphere: an exact solution

The classical Navier equations of linear elasticity and the Helmholtz equation for the internal/external acoustic domains in conjunction with the translational addition theorem for spherical vector wave functions are employed to present an exact solution for three-dimensional nonaxisymmetric steady-state sound radiation from an eccentric hollow elastic sphere, immersed in and filled with acoustic fluids, and subjected to arbitrary time-harmonic mechanical drives at its internal/external surface. The analytical results are illustrated with numerical examples in which air-filled, water-submerged, thick-walled concentric and eccentric steel spheres are driven by harmonic concentrated or distributed radial internal/external loads. The numerical results reveal the important effects of sphere eccentricity, loading configuration, and excitation frequency on the sound radiation characteristics of the submerged structure. Limiting cases are considered and the validity of results is established with the aid of a commercial finite element package as well as by comparison with the data in the existing literature.     

Development of a 2-D 2-group neutron noise simulator for hexagonal geometries

In this paper, the development of a neutron noise simulator for hexagonal-structured reactor cores using both the forward and the adjoint methods is reported. The spatial discretisation of both 2-D 2-group static and dynamic equations is based on a developed box-scheme finite difference method for hexagonal mesh boxes. Using the power iteration method for the static calculations, the 2-group neutron flux and its adjoint with the corresponding eigenvalues are obtained by the developed static simulator. The results are then benchmarked against the well-known CITATION computer code. The dynamic calculations are performed in the frequency domain which leads to discarding of the time discretisation. Then, the developed 2-D 2-group neutron noise simulator calculates both the discretised forward and the adjoint reactor transfer function between a point source and its induced neutron noise, by assuming the neutron noise source as an “absorber of variable strength” type. The neutron noise induced by a “vibrating absorber” type of noise source may also be modeled using the calculated transfer function. The viability of the simulator is verified for different benchmark cases.     

A computational and experimental investigation of the mechanical properties of single ZnTe nanowires

One-dimensional nanostructures such as ZnTe, CdTe, Bi(2)Te(3) and others have attracted much attention in recent years for their potential in thermoelectric devices among other applications. A better understanding of their mechanical properties is important for the design of devices. A combined experimental and computational approach has been used here to investigate the size effects on the Young's modulus of ZnTe nanowires (NWs). The mechanical properties of individual ZnTe nanowires in a wide diameter range (50-230 nm) were experimentally measured inside a high resolution transmission electron microscope using an atomic force microscope probe with the ability to record in situ continuous force-displacement curves. The in situ observations showed that ZnTe NWs are flexible nanostructures with the ability to withstand relatively high buckling forces without becoming fractured. The Young's modulus is found to be independent of nanowire diameter in the investigated range, in contrast to reported results for ZnO NWs and carbon nanotubes where the modulus increases with a decrease in diameter. Molecular dynamics simulations performed for nanowires with diameters less than 20 nm show limited size dependence for diameters smaller than 5 nm. The surface atoms present lower Young's modulus according to the simulations and the limited size dependency of the cylindrical ZnTe NWs is attributed to the short range covalent interactions.     

Delay-sensitive approaches for anonymizing numerical streaming data

Streaming data are widely used in today’s world. Data come from different sources in streams and must be processed online and with minimum delay. These data stream can contain confidential data such as customers’ purchase information and need to be mined in order to reveal other useful information like customers’ purchase patterns. Privacy preservation throughout these processes plays a crucial role. K-anonymity is a well-known technique for preserving privacy. The principle issues in k-anonymity are information loss and running time. Although some of the existing k-anonymity techniques are able to generate anonymized data with acceptable information loss, their main drawback is that they are very time-consuming and are not applicable in a streaming context since streaming data are usually very sensitive to delay and need to be processed quite fast. In [32], we proposed a cluster-based k-anonymity algorithm called fast anonymizing algorithm for numerical streaming data (FAANST) which can anonymize numerical streaming data quite fast while providing an admissible information loss. The main drawback of FAANST is that some tuples may remain in the system for a long time and are output when they might be considered to have expired. In this paper, we propose two extensions for FAANST, passive and proactive solutions. These two solutions put a soft deadline, called $delay$ , on the time each tuple can stay in the system, and if a tuple passes this deadline, these algorithms force the tuple to be output. The proactive solution goes even one step further and utilizes a simple heuristic function to predict when a tuple in the system may expire and outputs the tuple if it will expire in the next round of the algorithm’s execution.