The investigation of synergistic inhibition effect of rhodanine and iodide ion on the corrosion of copper in sulphuric acid solution

The synergistic inhibition effect of rhodanine (Rdn) and iodide ion on the corrosion of copper in 0.5 M H₂SO₄ solution was studied using electrochemical techniques. The surface morphologies of the substrates were examined by scanning electron microscopy (SEM). Elemental analysis of electrode surface exposed to test solution was determined by energy dispersive X-ray spectroscopy (EDX). It was found that Rdn provided satisfactory inhibition on the corrosion of copper. Moreover, its inhibition efficiency further increased in the presence of iodide ions due to synergistic effect. Finally, a mechanism of inhibition is proposed and discussed.     

Prediction of the heat transfer performance of twisted tape inserts by using artificial neural networks

Journal of Mechanical Science and Technology - A numerical study is undertaken to investigate the effect of twisted tape inserts on heat transfer. Twisted tapes with various aspect ratios and...     

Adsorption and corrosion inhibition effect of 2-((5-mercapto-1,3,4-thiadiazol-2-ylimino)methyl)phenol Schiff base on mild steel

In this study, the inhibition effect of 2-((5-mercapto-1,3,4-thiadiazol-2-ylimino)methyl)phenol Schiff base (MTMP) on mild steel corrosion in 0.5 M HCl solution was studied. For this aim, electrochemical techniques such as potentiodynamic polarization curves, weight loss (WL), electrochemical impedance spectroscopy (EIS) and linear polarization resistance (LPR) were used. It was shown that, the MTMP Schiff base has remarkable inhibition efficiency on the corrosion of mild steel in 0.5 M HCl solution. Polarization measurements indicated that, the studied inhibitor acts as mixed type corrosion inhibitor with predominantly control of cathodic reaction. The inhibition efficiency depends on the concentration of inhibitor and reaches 97% at 1.0 mM MTMP. The remarkable inhibition efficiency of MTMP was discussed in terms of blocking of electrode surface by adsorption of inhibitor molecules through active centers. The adsorption of MTMP molecules on the mild steel surface obeys Langmuir adsorption isotherm.     

Diameter of titanium nanotubes influences anti-bacterial efficacy

Bacterial infection of in-dwelling medical devices is a growing problem that cannot be treated by traditional antibiotics due to the increasing prevalence of antimicrobial resistance and biofilm formation. Here, due to changes in surface parameters, it is proposed that bacterial adhesion can be prevented through nanosurface modifications of the medical device alone. Toward this goal, titanium was created to possess nanotubular surface topographies of highly controlled diameters of 20, 40, 60, or 80 nm, sometimes followed by heat treatment to control chemistry and crystallinity, through a novel anodization process. For the first time it was found that through the control of Ti surface parameters including chemistry, crystallinity, nanotube size, and hydrophilicity, significantly changed responses of both Staphylococcus epidermidis and Staphylococcus aureus (pathogens relevant for orthopaedic and other medical device related infections) were measured. Specifically, heat treatment of 80 nm diameter titanium tubes produced the most robust antimicrobial effect of all surface treatment parameters tested. This study provides the first step toward understanding the surface properties of nano-structured titanium that improve tissue growth (as has been previously observed with nanotubular titanium), while simultaneously reducing infection without the use of pharmaceutical drugs.     

Computerized classification of intraductal breast lesions using histopathological images

In the diagnosis of preinvasive breast cancer, some of the intraductal proliferations pose a special challenge. The continuum of intraductal breast lesions includes the usual ductal hyperplasia (UDH), atypical ductal hyperplasia (ADH), and ductal carcinoma in situ (DCIS). The current standard of care is to perform percutaneous needle biopsies for diagnosis of palpable and image-detected breast abnormalities. UDH is considered benign and patients diagnosed UDH undergo routine follow-up, whereas ADH and DCIS are considered actionable and patients diagnosed with these two subtypes get additional surgical procedures. About 250,000 new cases of intraductal breast lesions are diagnosed every year. A conservative estimate would suggest that at least 50% of these patients are needlessly undergoing unnecessary surgeries. Thus, improvement in the diagnostic reproducibility and accuracy is critically important for effective clinical management of these patients. In this study, a prototype system for automatically classifying breast microscopic tissues to distinguish between UDH and actionable subtypes (ADH and DCIS) is introduced. This system automatically evaluates digitized slides of tissues for certain cytological criteria and classifies the tissues based on the quantitative features derived from the images. The system is trained using a total of 327 regions of interest (ROIs) collected across 62 patient cases and tested with a sequestered set of 149 ROIs collected across 33 patient cases. An overall accuracy of 87.9% is achieved on the entire test data. The test accuracy of 84.6% is obtained with borderline cases (26 of the 33 test cases) only, when compared against the diagnostic accuracies of nine pathologists on the same set (81.2% average), indicates that the system is highly competitive with the expert pathologists as a stand-alone diagnostic tool and has a great potential in improving diagnostic accuracy and reproducibility when used as a "second reader" in conjunction with the pathologists.     

Optimization of Process-Control Parameters for the Diameter of Electrospun Hydrophilic Polymeric Composite Nanofibers

A composite nanofiber composed of three polymers, namely polyvinyl alcohol/polyvinyl pyrrolidone/polyethylene oxide, is produced. The experiments are constructed using three design of experiment techniques, Taguchi L₉, Taguchi L₂₇, and Screening method. The experiments are verified using the analysis of variance (ANOVA) method and later a mathematical model is developed using the regression method. The impact of electrospun processing parameters, namely applied voltage, flow rate, and working distance, on nanofibers' diameter is measured. The working distance is a significant factor in controlling the size of the fiber diameter, while the applied voltage has the lowest effect on it. As a result of the regression equation, a Genetic algorithm is used to find the optimum variables for the required fiber diameter, which is 156 nm for flow rate = 0.001 mL h⁻¹, voltage = 30 kV, and distance = 200 mm with a 3% difference from the experimental fiber diameter.     

Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey

The main objective is to investigate Turkey's fossil fuels demand, projection and supplies by using the structure of the Turkish industry and economic conditions. This study develops scenarios to analyze fossil fuels consumption and makes future projections based on a genetic algorithm (GA). The models developed in the nonlinear form are applied to the coal, oil and natural gas demand of Turkey. Genetic algorithm demand estimation models (GA-DEM) are developed to estimate the future coal, oil and natural gas demand values based on population, gross national product, import and export figures. It may be concluded that the proposed models can be used as alternative solutions and estimation techniques for the future fossil fuel utilization values of any country. In the study, coal, oil and natural gas consumption of Turkey are projected. Turkish fossil fuel demand is increased dramatically. Especially, coal, oil and natural gas consumption values are estimated to increase almost 2.82, 1.73 and 4.83 times between 2000 and 2020. In the figures GA-DEM results are compared with World Energy Council Turkish National Committee (WECTNC) projections. The observed results indicate that WECTNC overestimates the fossil fuel consumptions.     

基于GIS的土耳其国际保护区G(o)ksu河水质的调查与建模

Goksu Delta is an important wetland where the G(o)ksu River reaches to sea in the eastern of the town Tasucu-lce1. The delta is classified as a Wetland of Intemational Impor-tance according to the Ramsar Convention on Wetlands of International Importance. The amount of fertilizers used in this area was 7200 tons in 2006. These pollutants affect the surface and groundwater quality negatively. The intensively used fertilizers and pesticides contain not only N-and P compounds but also some heavy metals. The contents of all pol-lutants in surface waters were determined for four different seasons between 2006 and 2008 and with these data a Geographic Information System(GIS)has been constructed by using Map Info. From the photometric heavy metal analysis, it is inferred that the excess concen-tration of Fe, Ni, Mn, Mo and Cu at some locations is the cause of undesirable quality for drinking purposes. The source of excess concentration of various heavy metals is the agri-cultural activities and fertilizers. It is determined that in all periods between 2006 and 2008 the heavy metals and other pollutants in the fertilizers and pesticides transported easily to river water with irrigation return flow. The organic pollutants, including COD, BOD, NH3 and NO3 followed the sharply increasing trends from Silifke city to Mediterranean Sea. The water quality of G(o)ksu River is modeled and determined that the waste water discharge of 10,700 m3/day from Silifke city does not create a serious problem because of the high amount of flow rate of G(o)ksu River.