A Lightweight Radio Propagation Model for Vehicular Communication in Road Tunnels

Radio propagation models (RPMs) are generally employed in Vehicular Ad Hoc Networks (VANETs) to predict path loss in multiple operating environments (e.g. modern road infrastructure such as flyovers, underpasses and road tunnels). For example, different RPMs have been developed to predict propagation behaviour in road tunnels. However, most existing RPMs for road tunnels are computationally complex and are based on field measurements in frequency band not suitable for VANET deployment. Furthermore, in tunnel applications, consequences of moving radio obstacles, such as large buses and delivery trucks, are generally not considered in existing RPMs. This paper proposes a computationally inexpensive RPM with minimal set of parameters to predict path loss in an acceptable range for road tunnels. The proposed RPM utilizes geometric properties of the tunnel, such as height and width along with the distance between sender and receiver, to predict the path loss. The proposed RPM also considers the additional attenuation caused by the moving radio obstacles in road tunnels, while requiring a negligible overhead in terms of computational complexity. To demonstrate the utility of our proposed RPM, we conduct a comparative summary and evaluate its performance. Specifically, an extensive data gathering campaign is carried out in order to evaluate the proposed RPM. The field measurements use the 5 GHz frequency band, which is suitable for vehicular communication. The results demonstrate that a close match exists between the predicted values and measured values of path loss. In particular, an average accuracy of 94% is found with R² = 0.86.     

Adaptive Neuro-Fuzzy Methodology for Noise Assessment of Wind Turbine

Wind turbine noise is one of the major obstacles for the widespread use of wind energy. Noise tone can greatly increase the annoyance factor and the negative impact on human health. Noise annoyance caused by wind turbines has become an emerging problem in recent years, due to the rapid increase in number of wind turbines, triggered by sustainable energy goals set forward at the national and international level. Up to now, not all aspects of the generation, propagation and perception of wind turbine noise are well understood. For a modern large wind turbine, aerodynamic noise from the blades is generally considered to be the dominant noise source, provided that mechanical noise is adequately eliminated. The sources of aerodynamic noise can be divided into tonal noise, inflow turbulence noise, and airfoil self-noise. Many analytical and experimental acoustical studies performed the wind turbines. Since the wind turbine noise level analyzing by numerical methods or computational fluid dynamics (CFD) could be very challenging and time consuming, soft computing techniques are preferred. To estimate noise level of wind turbine, this paper constructed a process which simulates the wind turbine noise levels in regard to wind speed and sound frequency with adaptive neuro-fuzzy inference system (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.     

An Automated System for Skeletal Maturity Assessment by Extreme Learning Machines

Assessing skeletal age is a subjective and tedious examination process. Hence, automated assessment methods have been developed to replace manual evaluation in medical applications. In this study, a new fully automated method based on content-based image retrieval and using extreme learning machines (ELM) is designed and adapted to assess skeletal maturity. The main novelty of this approach is it overcomes the segmentation problem as suffered by existing systems. The estimation results of ELM models are compared with those of genetic programming (GP) and artificial neural networks (ANNs) models. The experimental results signify improvement in assessment accuracy over GP and ANN, while generalization capability is possible with the ELM approach. Moreover, the results are indicated that the ELM model developed can be used confidently in further work on formulating novel models of skeletal age assessment strategies. According to the experimental results, the new presented method has the capacity to learn many hundreds of times faster than traditional learning methods and it has sufficient overall performance in many aspects. It has conclusively been found that applying ELM is particularly promising as an alternative method for evaluating skeletal age.     

Adaptive Neuro-Fuzzy Appraisal of Plasmonic Studies on Morphology of Deposited Silver Thin Films Having Different Thicknesses

This work presents an experimental analysis on the tunable localized surface plasmon resonance (LSPR), obtained from deposited silver (Ag) thin films of various thicknesses. Silver thin films are prepared using electron beam deposition and undergo an annealing process at different temperatures to produce distinctive sizes of Ag metal nanoparticles (MNPs). The variability of structure sizes and shapes provides an effective means of tuning the position of the LSPR within a wide wavelength range. This paper provides an estimation of LSPR over a broad wavelength range by a process in which the resonance spectra of silver nanoparticles differing in thickness are simulated using an adaptive neuro-fuzzy inference system (ANFIS) method. The ANFIS methodology allows for estimation of sizes of granular structures formed on top of a wafer at certain temperatures, whereupon these intelligent estimators are implemented using MATLAB and their subsequent performances are investigated. The results presented in this paper show the effectiveness of the method of simulation.     

Effect of lithium on secretory factors and growth stimulation by bombesin in rat pancreas and salivary glands

Lithium, a drug of choice in bipolar affective disorders, also affects the metabolism and cell proliferation in a diverse array of organisms. In this study, we investigated the effect of lithium on bombesin-mediated function in excretion and growth of the pancreas and the salivary glands. The weight, protein content, amylase concentration and salivary flow rate of the pancreas, parotid and the submandibular glands were determined in male Wistar rats after consumption of either water or lithium chloride (600 mg/l) for 14 days and each group received s.c. injection of either saline or bombesin (10 microg/kg) during the last 4 days of experiment. Our results revealed that administration of bombesin in lithium-treated group not only suppressed pancreas and parotid weight augmentation due to bombesin, but also significantly decreased pancreas growth. Chronic lithium consumption significantly inhibited the protein content augmentation due to bombesin in the salivary glands. Getting bombesin, as well as saline in lithium-treated group, resulted in notable decrease in salivary protein content. Protein content of pancreatic gland increased considerably in the bombesin-injected groups either treated with saline or lithium. In conclusion, the stimulatory effect of bombesin on the growth and protein content of the pancreas and the salivary gland was inhibited by lithium. Lithium seems to be a potent inhibitor of growth factors induced by bombesin probably through inhibiting phosphatidylinositol 4,5,bisphosphate hydrolysis.     

ROS-mediated heme degradation and cytotoxicity induced by iron nanoparticles: hemoglobin and lymphocyte cells as targets

Nanoparticles (NPs) due to their small size and high surface area induce remarkable adverse effects on the biological systems. However, the exact mechanism by which NPs interacted with biological system and induce their adverse effects is still an enigma. Herein, the interaction of zero valent iron NPs (ZVFe NPs) with human hemoglobin (Hb) was evaluated using a variety of techniques including circular dichroism, fluorescence, and UV–visible (UV–vis) spectroscopy methods. Also, the cytotoxicity of ZVFe NPs on the human lymphocyte cell line as a model of blood system cell line was investigated by reactive oxygen species (ROS), caspase-9, and caspase-3 activities assays. It was revealed that ZVFe NP interaction resulted in heme displacement and degradation and induction of protein cabonylation. It was also shown that ZVFe NPs impaired the complexity of lymphocyte cells through ROS generation and apoptotic pathway. Together, these data suggest that NPs influence the biological system and induce adverse effects through ROS generation.     

Statistical Screening of Medium Components for Recombinant Production of Pseudomonas aeruginosa ATCC 9027 Rhamnolipids by Nonpathogenic Cell Factory Pseudomonas putida KT2440

Rhamnolipids (RLs) produced by the opportunistic human pathogen Pseudomonas aeruginosa are considered as potential candidates for the next generation of surfactants. Large-scale production of RLs depends on progress in strain engineering, medium design, operating strategies, and purification procedures. In this work, the rhlAB genes extracted from a mono_RLs_producing strain of P. aeruginosa (ATCC 9027) were introduced to an appropriate safety host Pseudomonas putida KT2440. The capability of the recombinant strain was evaluated in various media. As a prerequisite for optimal medium design, a set of 32 experiments was performed in two steps for screening a number of macro-nutritional compounds. In the experiments, a two-level fractional factorial design resolution IV was followed by a two-level full factorial one. By means of this approach, it was observed that glycerol, yeast extract, and peptone have significant positive influence on recombinant RLs production while the yeast extract/peptone two-factor and glycerol/yeast extract/peptone three-factor interactions have considerable negative effects. A wide range of variation from 0 to 570 mg/l was obtained for RLs production during the screening experiments indicating the importance of medium optimization. The results point out the opportunity for possible higher yields of RLs through further screening, mixture/combined mixture designs, and high-cell-density cultivations.     

A CB2 Receptor Agonist Reduces the Production of Inflammatory Mediators and Improves Locomotor Activity in Experimental Autoimmune Encephalomyelitis

Background:Cannabinoids (CBs) have been found to regulate the immune system, affect innate and adaptive immune responses, and reduce inflammatory reactions. This study assessed the therapeutic effects of GW-405833 synthetic CB2 agonist on inflammatory factors as well as locomotor activity in experimental autoimmune encephalomyelitis (EAE).Methods:In this experimental study, 48 adult male C57BL/6 mice were randomly and equally assigned to eight groups. By injecting 250 mg of MOG35-55 peptide, EAE was induced. Every other day for 17 days after EAE onset, EAE-afflicted mice in groups 1–3 received an intraperitoneal injection of GW-405833 at a dose of 3, 10, and 30 mg/kg, respectively. Clinical status and locomotor activity, measured using the beam walking assay, were assessed every other day during the first 17 days after EAE onset. Mice were euthanized in day 17th of treatment and the serum levels of the IL-1β, IL-12, CRP, and TNF-α proinflammatory cytokines as well as IL-4 and TGF-β anti-inflammatory cytokines were measured by ELISA method.Results:Clinical manifestations of EAE in groups 2 and 3 were significantly milder than group 4 and locomotor activity in groups 1–3 was significantly better than group 4 in days 5–17 (p< 0.05). GW-405833 also significantly decreased the levels of IL-12, TNF-α, and CRP and significantly increased the levels of IL-4 and TGF-β but had no significant effects on the level of IL-1β. GW-405833 was not associated with significant side effects.Conclusion:The CB2 receptor agonist GW-405833, improves clinical conditions and reduces inflammation in mice with EAE.Key Words: Clinical evaluation, Experimental autoimmune encephalomyelitis, GW-405833, Locomotor activity, Multiple sclerosis, Proinflammatory cytokines     

Relationship between γ‐interferon gene polymorphisms and susceptibility to brucellosis infection

Interferon‐gamma (IFN‐γ) is a pro‐inflammatory cytokine that plays a pivotal role in the defense mechanism against Brucella infection. It was hypothesized that the IFN‐γ in (+874 A/T in intron 1) TT and +5644 T/A, TT genotypes, which are reportedly associated with high IFN production, are associated with susceptibility to brucellosis in Iranian subjects. Genotyping of these IFN‐γ variants by an allele‐specific polymerase chain reaction method was performed in 281 subjects, comprising 153 patients with active brucellosis and 128 healthy controls. It was found that the +874 minor allele (A) and homozygote genotype (AA) were significantly more frequently present in brucellosis patients than in controls (OR = 2.588; 95% CI, 1.313–5.104; P = 0.006 for the AA genotype; OR = 1.575; 95% CI, 1.124–2.216; P = 0.010 for the A allele). However, the allelic and genotypic distribution of the IFN‐γ polymorphism at position UTR5644 A>T did not differ significantly between patients and controls (P > 0.05). The distribution of haplotypes in this study suggests that the T/A haplotype (+874/UTR5644), which was present more frequently in controls than in patients, may protect subjects against Brucella infection. It is suggested that IFN‐γ +874 AA genotype and A allele are risk factors for developing brucellosis infection in Iranian subjects.