A D2D-Based Solution for MTC Connectivity Problem in NOMA-Based Cellular IoT Networks: Dynamic User Grouping and Resource Allocation

Mobile Networks and Applications - In a cellular network (CN), cellular users (CUs) located nearby machine type communications (MTC) devices (MTC-Ds) may act as uplink gateways to relay data to the...     

Self-Assembled Perovskite Nanoislands on CH3NH3PbI3 Cuboid Single Crystals by Energetic Surface Engineering

Organometal perovskite single crystals have been recognized as a promising platform for high-performance optoelectronic devices, featuring high crystallinity and stability. However, a high trap density and structural nonuniformity at the surface have been major barriers to the progress of single crystal-based optoelectronic devices. Here, the formation of a unique nanoisland structure is reported at the surface of the facet-controlled cuboid MAPbI₃ (MA = CH₃NH₃⁺) single crystals through a cation interdiffusion process enabled by energetically vaporized CsI. The interdiffusion of mobile ions between the bulk and the surface is triggered by thermally activated CsI vapor, which reconstructs the surface that is rich in MA and CsI with reduced dangling bonds. Simultaneously, an array of Cs-Pb-rich nanoislands is constructed on the surface of the MAPbI₃ single crystals. This newly reconstructed nanoisland surface enhances the light absorbance over 50% and increases the charge carrier mobility from 56 to 93 cm² V⁻¹ s⁻¹. As confirmed by Kelvin probe force microscopy, the nanoislands form a gradient band bending that prevents recombination of excess carriers, and thus, enhances lateral carrier transport properties. This unique engineering of the single crystal surface provides a pathway towards developing high-quality perovskite single-crystal surface for optoelectronic applications.     

Evaluation of a cocktail of three bacteriophages for the biocontrol of Salmonella of wastewater

Salmonella serovars are increasing in importance as significant pathogens of both human and animals. Although water and wastewater are treated to eliminate pathogenic microorganisms, they still play an important role in the transmission of Salmonella spp. In this study, bacteriophages infecting Salmonella spp. were isolated from wastewater and evaluated; for their potential to lyse environmental Salmonella strains in vitro at different MOIs and temperatures; and to control the wastewater bacterial community. Three distinct phages designated sww65, sww275, and sww297; as defined by plaque morphology, electron microscopy and host range; were obtained from wastewater. Challenge tests were performed at 37, and 30 °C with the infection of the Salmonella cultures with individual phage, a mixture of two phages, and cocktail of three phages at MOIs of 10⁰, 10², and 10⁴ PFU/CFU. At 30, and 37 °C, a cocktail of three phages reduced all of the Salmonella cultures tested. These results required a high multiplicity of infection. However, when infected with only one phage or a mixture of two phages at MOIs of 10⁰ or 10 ² PFU/CFU, an emergence of bacterial resistance was observed. The dynamic monitoring of wastewater enterobacterial community was conducted using Enterobacterial Repetitive Intergenic Consensus-PCR (ERIC-PCR). The number of bands decreased gradually with the use of individual phage or phage cocktails. Moreover, the dynamic monitoring of Salmonella community during wastewater treatment was performed using PCR detection of virulence gene invA. The results correlated with the ERIC-PCR fingerprints, and suggested that Salmonella community was affected by the phage treatment. Indeed, in wastewater, bacteriophages are reducing Salmonella and other members of the Enterobacteriaceae. These results indicated that dynamic changes are closely related with the process of treatment. The introduction of wide host range bacteriophages in wastewater can have a potential impact on the dynamics of the microbial communities, manifested by the reduction or the elimination of microbial species.     

Application of carbon nanostructures toward SO2 and SO3 adsorption: a comparison between pristine graphene and N-doped graphene by DFT calculations

We studied the adsorption of SO_x (x?=?2,3) molecules on the surface of pristine graphene (PG) and N-doped graphene (NDG) by density functional theory (DFT) calculations at the B3LYP/6-31G(d) level. We used Mulliken and NBO charge analysis to calculate the net charge transfer of adsorbed SO_x on pristine and defected graphene systems. Our calculations reveal much higher adsorption energy and higher net charge transfer by using NDG instead of pristine graphene. Furthermore, the density of state (DOS) graphs point to major orbital hybridization between the SO_x and NDG, while there is no evidence of hybridization by using pristine graphene. Based on our results, it is found that SO₂ and SO₃ molecules can be adsorbed on the surface of NDG physically and chemically with adsorption energies (E_ads) of ?27.5 and 65.2?kJ?mol^?1 (19.6 and 51.4?kJ?mol^?1 BSSE), respectively, while low adsorption energies were calculated in the case of using pristine graphene. So we introduced NDG as a sensitive adsorbent/sensor for detection of SO₂ and SO₃.     

Improvement in volume resistivity and morphology of a blend of polyolefin elastomer with linear low-density polyethylene

A silane moisture-cured polyolefin elastomer/linear low-density polyethylene (LLDPE) blend was prepared through a two-step silane-grafting method (Sioplas Process) in an industrial scale twin-screw extruder. The silane-grafted compound was used to make wire and cable coatings. In this work, the effect of some interactive parameters on quality of the products prepared by the above method has been studied, while so far, there have been less experimental investigations. The volume resistivity of cross-linked compound was changed from 2.96 × 10¹⁴ to 7.41 × 10¹⁴ Ω cm with increasing LLDPE component by maximum 10 wt%. Surface morphology of the product was corrected with reduction in benzoyl peroxide (BPO) concentration from 0.2 wt% to 0.13 wt%. BPO at this level acted as an initiator in grafting reaction of vinyl trimethoxysilane. The curing condition and specimen preparation method by injection molding and/or extrusion were factors which influenced the hot-set test results at 200 °C. The results of tensile and elongation studies showed a maximum value of 9 MPa and 397% for the tests, after 6 h curing. With increases in curing time at a specified temperature, the gel content of the cross-linked compound was increased and reached its maximum value. The maximum gel content values were found to be approximately 60%, 80%, and 82% at temperatures of 25, 60, and 85 °C, respectively. The hardness, density, and tear strength of the samples did not vary significantly with the curing temperature.

     

Pressureless sintering of boron carbide

The effect of small Al addition on pressureless-sintering and mechanical properties of B₄C ceramic was analyzed. Different amounts of aluminium powder, from 0% to 5 wt%, were added to the base material and pressureless-sintering was conducted at 2050 and 2150 °C under argon atmosphere. Microstructure, crystalline phases, density evolution, fracture strength, elastic modulus, hardness and fracture toughness were analyzed and correlated to Al additions and firing temperature. Density and grain size of sintered samples increased significantly with Al load while the effect of sintering temperature was less evident; 94% dense material was obtained by adding 4 wt% Al. Bending strength, hardness and fracture toughness of sintered B₄C samples were shown to increase for Al content up to 4 wt% while further additions resulted in a decrease of the mechanical resistance. Conversely, elastic modulus showed an increase with Al load especially between 1 and 3 wt%.     

A self-tuning ANN model for simulation and forecasting of surface flows

Artificial neural networks (ANN) are applicable for and forecasting without the need to calculate complex nonlinear functions. This paper evaluates the effectiveness of temperature, evapotranspiration, precipitation and inflow factors, and the lag time of those factors, as variables for simulating and forecasting of runoff. The genetic algorithm (GA) is coupled with ANN to determine the optimal set of variables for streamflow forecasting. The minimization of the total mean square error (MSE) is considered as the objective function of the ANN-GA method in this paper. Our results show the effectiveness of the ANN-GA for simulating and forecasting runoff with consistent accuracy compared with using pure ANN for runoff simulation and forecasting.