A Study on the Damping Ratio of the Viscous Fluid Dampers in the Braced Frames

The main task of a structure is to bear the lateral loads and transfer them to the foundation. Since the lateral loads imposed on a structure have a dynamic nature, they cause vibrations through the structure. In order to have resistant structures to the seismic vibrations, two viewpoints have been suggested. According to the first viewpoint, the resistance of the structure results from providing non-elastic shapeable capacity and resistance for the structural members. To achieve this purpose, different structural components such as shear walls, braced frames, moment frames, diaphragms, and trusses should be provided and combined to form a resistant system to the lateral loads. The present paper intends to study the optimal damping ratio of the viscous fluid dampers (VFD) in the braced frames. In order to reach the purposes of the present paper, the library studies, and proper software have been used to analyze data and make a conclusion

A Study on the Damping Ratio of the Viscous Fluid Dampers in the Braced Frames

The main task of a structure is to bear the lateral loads and transfer them to the foundation. Since the lateral loads imposed on a structure have a dynamic nature, they cause vibrations through the structure. In order to have resistant structures to the seismic vibrations, two viewpoints have been suggested. According to the first viewpoint, the resistance of the structure results from providing non-elastic shapeable capacity and resistance for the structural members. To achieve this purpose, different structural components such as shear walls, braced frames, moment frames, diaphragms, and trusses should be provided and combined to form a resistant system to the lateral loads. The present paper intends to study the optimal damping ratio of the viscous fluid dampers (VFD) in the braced frames. In order to reach the purposes of the present paper, the library studies, and proper software have been used to analyze data and make a conclusion

Synthesis of Zinc Oxide Nanoparticles and Their Effect on the Compressive Strength and Setting Time of Self-Compacted Concrete Paste as Cementitious Composites

In the present study, the mechanical properties of self-compacting concrete were investigated after the addition of different amounts of ZnO nanoparticles. The zinc oxide nanoparticles, with an average particle size of about 30 nm, were synthesized and their properties studied with the help of a scanning electron microscope (SEM) and X-ray diffraction. The prepared nanoparticles were partially added to self-compacting concrete at different concentrations (0.05, 0.1, 0.2, 0.5 and 1.0%), and the mechanical (flexural and split tensile) strength of the specimens measured after 7, 14, 21 and 28 days, respectively. The present results have shown that the ZnO nanoparticles were able to improve the flexural strength of self-compacting concrete. The increased ZnO content of more than 0.2% could increase the flexural strength, and the maximum flexural and split tensile strength was observed after the addition of 0.5% nanoparticles. Finally, ZnO nanoparticles could improve the pore structure of the self-compacted concrete and shift the distributed pores to harmless and less-harmful pores, while increasing mechanical strength

Synthesis of ZnO nanoparticles and their antibacterial effects

The zinc oxide nanoparticles with the average particle size of about 30 nm were synthesized by the chemical technique and their properties were studied with the help of scanning electron microscope and X-ray diffraction. The aim of this study was to detect the antibacterial properties of 0.01, 0.5 and 1% nano-ZnO against Escherichia coli. E. coli was cultured in liquid and agar nutrient medium to evaluate the antibacterial effects of 0.01, 0.05 and 1% of ZnO via the optical density (OD) and log CFU/ml measurements. Non-significant effect was seen for 0.01% of ZnO nano-particles, while 0.05 and 1% of nanoparticles showed considerably decreased bacterial number. A 4.385 and 2.04 times decrease in the OD value was found in the presence of 1 and 0.5% nano-ZnO, respectively (P<0.001) as compared to the control. In the second study, 6.3 log CFU/ml of E. coli were present in the cultures treated with 1% nano-ZnO at 4°C in water. Control E. coli cells survived for 12 days, while complete cell death was seen when 1% nano-ZnO was applied for 24 h. In the third study, E. coli was grown in the agar medium with and without nanoparticles and suppressed growth (8.56 times; P<0.001) was seen in the presence of 1% nano-ZnO.Keywords: ZnO-nanoparticle, antibacterial, bactericidal, Escherichia col

Classification of Mental Stress Levels by Analyzing fNIRS Signal Using Linear and Non-linear Features

Background: Mental stress is known as one of the main influential factors in development of different diseases including heart attack and stroke. Thus, quantification of stress level can be very important in preventing many diseases and in human health.Methods: The prefrontal cortex is involved in body regulation in response to stress. In this research, functional near infrared spectroscopy (fNIRS) signals were recorded from FP2 position in the international electroencephalographic 10–20 system during a stressful mental arithmetic task to be calculated within a limited period of time. After extracting the brain’s hemodynamic response from fNIRS signal, different linear and nonlinear features were extracted from the signal which are then used for stress levels classification both individually and in combination.Results: In this study, the maximum accuracy of 88.72% was achieved in classification between high and low stress levels, and 96.92% was obtained for the stress and rest states.Conclusion: Our results showed that using the proposed linear and nonlinear features it is possible to effectively classify stress levels from fNIRS signals recorded from only one site in the prefrontal cortex. Comparing to other methods, it is shown that the proposed algorithm outperforms other previously reported methods using the nonlinear features extracted from the fNIRS signal. These results clearly show the potential of fNIRS signal as a useful tool for early diagnosis and quantify stress

Mapping Groundwater Resource using Multispectral Sentinel 2 and Fuzzy Logic method, Case Study: Salafchegan, Qom, Iran

Groundwater is one of the essential freshwater sources for human consumption, with the highest reserves of fresh water on earth after glaciers and glaciers. Conservation and maintenance of groundwater quality in a large area require an overview of the status and potential of groundwater resources in that area, which can be applied to potential areas using remote sensing technology. In this study, after extracting the factors influencing the formation of groundwater aquifers from the Sentinel satellite image, appropriate information layers were prepared and integrated into the ArcGIS using different fuzzy operators and potential maps prepared with the location of groundwater wells. The area was validated. The results of combining slope layers, slope direction, lithology, drainage length density, lineament length density, lineament buffer, drainage buffer, and vegetation in the area showed that fuzzy multiplication and gamma operators could be used as suitable operators for Introducing information layers to identify groundwater potential in the area. Also, using the gamma numbers 0.1 gave better results than larger gamma numbers. The research results showed that 15.9% of the studied area has good and very good potential for the presence of underground water in the production map using the fuzzy gamma with gamma 0.1 method. Also, this map was validated by 70.1% of water wells in the region. The normalized ratio of accuracy to validity in the final production model with this method was estimated to be 54%, which is entirely acceptable compared to other methods

Millimeter-wave Evolution for 5G Cellular Networks

Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.Comment: 17 pages, 12 figures, accepted to be published in IEICE Transactions on Communications. (Mar. 2015

Serum-based metabolic alterations in patients with papillary thyroid carcinoma unveiled by non-targeted 1H-NMR metabolomics approach

Objective(s): As the most prevalent endocrine system malignancy, papillary thyroid carcinoma had a very fast rising incidence in recent years for unknown reasons besides the fact that the current methods in thyroid cancer diagnosis still hold some limitations. Therefore, the aim of this study was to improve the potential molecular markers for diagnosis of benign and malignant thyroid nodules to prevent unnecessary surgeries for benign tumors. Materials and Methods: In this study, 1H-NMR metabolomics platform was used to seek the discriminating serum metabolites in malignant papillary thyroid carcinoma (PTC) compared to benign multinodular goiter (MNG) and healthy subjects and also to better understand the disease mechanisms using bioinformatics analysis. Multivariate statistical analysis showed that PTC and MNG samples could be successfully discriminated in PCA and OPLS-DA score plots. Results: Significant metabolites that differentiated malignant and benign thyroid lesions included citrate, acetylcarnitine, glutamine, homoserine, glutathione, kynurenine, nicotinic acid, hippurate, tyrosine, tryptophan, β-alanine, and xanthine. The significant metabolites in the PTC group compared to healthy subjects also included scyllo- and myo-inositol, tryptophan, propionate, lactate, homocysteine, 3-methyl glutaric acid, asparagine, aspartate, choline, and acetamide. The metabolite sets enrichment analysis demonstrated that aspartate metabolism and urea cycle were the most important pathways in papillary thyroid cancer progression. Conclusion: The study results demonstrated that serum metabolic fingerprinting could serve as a viable method for differentiating various thyroid lesions and for proposing novel potential markers for thyroid cancers. Obviously, further studies are needed for the validation of the results

Investigation of metabonomics technique by analyze of NMR data, which method is better? Mean center or auto scale?

The factors such as disease can disrupt homeostasis, resulting in perturbations of endogenous biochemicals that are involved in key metabolic profiles. Metabonomics is useful technique to quantitative description of endogenous metabolites present in a biological sample such as urine, plasma and tissue. High resolution 1H nuclear magnetic resonance (NMR)-based metabonomics is a technique used to analyze and interpret multivariate metabolic data that correlate with changes of physiological conditions. Before any explanation for metabolite data, preprocessing the spectroscopic data is essential. In this paper, we show scaling effects in metabonomics investigation of patients diagnosed with Crohn's and Celiac disease. two techniques of scaling were applied as follows: mean centering and auto scaling. Results reveal that the mean centering is more useful to segregate patients from healthy subjects in the data set of Crohn's and Celiac disease