Surface modification of ZnO and Ti02 nanoparticles under mild hydrothermal conditions

There are various techniques for synthesizing different Nanoparticles depending upon the desired properties, application, etc. One of these widely applied techniques is Hydrothermal. However, this technique is known for bulky materials and fabrication of nano-scale materials requires adopting some strategies to alter the properties of materials synthesized. We developed surface modification for this drawback. Application of surface modifier, or surfactant, or capping agent, or organic ligands in proper concentration could not only change morphology, reduce particle size, but also change the surface chemistry of the nanoparticles fabricated. The ZnO and TiO2 nanoparticles were modified using n-butylamine and caprylic acid as surface modifier under mild hydrothermal conditions (p= autogenous, T= 150-250°C, and t= 18 h). The nanoparticles modified were systematically characterized using Powder XRD, FTIR, SEM, zeta potential, and BET surface area. The characterization results revealed that nanoparticles have small size range, low agglomeration and highly stable. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/2086

Comparing Three Data Mining Methods to Predict Kidney Transplant Survival

Introduction: One of the most important complications of post-transplant is rejection. Analyzing survival is one of the areas of medical prognosis and data mining, as an effective approach, has the capacity of analyzing and estimating outcomes in advance through discovering appropriate models among data. The present study aims at comparing the effectiveness of C5.0 algorithms, neural network and C & RTree to predict kidney transplant survival before transplant. Method: To detect factors effective in predicting transplant survival, information needs analysis was performed via a researcher-made questionnaire. A checklist was prepared and data of 513 kidney disease patient files were extracted from Sina Urology Research Center. Following CRISP methodology for data mining, IBM SPSS Modeler 14.2, C5.0, C&RTree algorithms and neural network were used. Results: Body Mass Index (BMI), cause of renal dysfunction and duration of dialysis were evaluated in all three models as the most effective factors in transplant survival. C5.0 algorithm with the highest validity (96.77) was the first in estimating kidney transplant survival in patients followed by C&RTree (83.7) and neural network (79.5) models. Conclusion: Among the three models, C5.0 algorithm was the top model with high validity that confirms its strength in predicting survival. The most effective kidney transplant survival factors were detected in this study; therefore, duration of transplant survival (year) can be determined considering the regulations set for a new sample with specific characteristics. © 2016 Leila Shahmoradi, Mostafa Langarizadeh, Gholamreza Pourmand, Ziba Aghsaei fard, and Alireza Borhani

Quality improvement of liver ultrasound images using fuzzy techniques

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. © 2016 Azadeh Bayani, Leila Shahmoradi, Mostafa Langarizadeh, Amir Reza Radmard, and Ahmadreza Farzaneh Nejad

ParaMonte: An Efficient Serial/Parallel MCMC Library

The scientific inference is a multistep process requiring observational data from which a model/hypothesis is derived. The parameters of this physical model then have to be tuned to more accurately represent data in a process known as model calibration. This calibrated model is then validated and is finally used to predict different quantities of interest. The most fundamental tool for model calibration and uncertainty quantification is the Markov Chain Monte Carlo (MCMC). While existing packages achieve many of the goals of the MCMC simulations, none currently addresses all critical aspects of an MCMC simulation. For instance, packages are frequently limited to only one programming language environment, perform serial or parallel simulations, or lack restart functionality. We present ParaMonte, a generic user-friendly, high- performance Monte Carlo simulation toolbox for serial and parallel Monte Carlo simulations accessible from multiple programming languages. ParaMonte features automatically-enabled restart functionality of all simulations in serial or parallel and comprehensive post-processing and visualization of the simulation results. This package is available to the public under the MIT license from its permanent repository: https://github.com/cdslaborg/paramont

The evolution of food security: where are we now, where should we go next?

Food security is one of the most challenging topics globally; however, the concept of food security has taken on additional dimensions that are general and are less detailed. This study aims to identify the intellectual structure of food security research and the changes in this structure. This paper analyzed 3169 documents from the Web of Science database through a bibliometric review. A review of the published documents shows an increasing trend over the past 46 years. In accordance with co-occurrence analysis, 125 keywords were grouped into five clusters: food security and sustainable development; food security and socioeconomic factors; food security policy and governance; coping strategies for poverty, inequality, and hunger; and modern food security management. This study identifies four streams within food security research: sustainability and environmental, socioeconomic, cultural, and political factors. The paper concludes that even though food security might investigate many significant areas, other new dimensions should still be considered. Further gaps in the literature emerge that present avenues for future research directions. Reviewing indicators and techniques of food security assessment and identifying high-risk groups should be a priority

Correlation between the isotropic energy and the peak energy at zero fluence for the individual pulses of GRBs: towards an universal physical correlation for the prompt emission

We find a strong correlation between the peak energy at zero fluence ($\rm E_{peak,0}$) and the isotropic energy ($\rm E_{\gamma,iso}$) of the 22 pulses of 9 Gamma Ray Bursts (GRB) detected by the Fermi satellite. The correlation holds for the individual pulses of each GRB, which shows the reality of the correlation. The derived correlation (Spearman correlation coefficient, $r$, is 0.96) is much stronger compared to the correlations using $\rm E_{peak}$ (in place of $\rm E_{peak,0}$) determined from the time-integrated spectrum ($r$ = 0.8), or the time-resolved spectrum not accounting for broad pulse structures ($r$ = 0.37), or the pulse-wise spectrum ($r$ = 0.89). Though the improvement in the $\rm E_{peak}$ - $\rm E_{\gamma,iso}$ relation (the Amati relation) for a pulse-wise analysis is known earlier, this is the first time a parameter derived from a joint spectral and timing fit to the data is shown to improve the correlation. We suggest that $\rm E_{peak,0}$, rather than $\rm E_{peak}$, is intrinsic to a GRB pulse and a natural choice as the parameter in the pulse-wise correlation studies.Comment: 6 pages, 2 tables, 2 figures, accepted for publication in Ap

Effects of Cimetidine and Glucantime on cutaneous Leishmaniasis in Balb/c mice

سالک یکی از بیماری های بومی و شایع در برخی از نقاط کشور ماست. این عارضه پوستی یک بیماری انگلی است که توسط تک یاخته ای به نام لیشمانی (Leishmania) ایجاد و از طریق گزش پشه خاکی منتقل می شود. پس از گزش پشه و طی دوره کمون، زخمی ایجاد می شود که پس از گذشت مدتی، معمولا بهبود یافته و گاهی از خود جوش باقی می گذارد. درمان بیماری سالک به عوامل متعددی مانند تعداد زخم ها، مدت زمان پیدایش و محل زخم ها و همچنین شرایط سنی و جنسی و اجتماعی بستگی دارد. امروزه برای درمان از روش های شیمیایی، فیزیکی و یا بطور توام استفاده می شود. در این مطالعه داروهای سایمتیدین (Cimetidine) و گلوکانتیم (Glucantime) با مقادیر مختلف برای درمان بیماری لیشمانیوز جلدی (سالک) در موش مورد بررسی قرار گرفته است. موش های خالص نژاد بالب سی (Balb/c) به صورت زیر جلدی با انگل لیشمانیا در قاعده دم عفونی شده و پس از ظهور زخم، به 11 گروه دهه تایی تقسیم شدند و سپس با مقادیر مختلف سایمتیدین و گلوکانتیم بطور مجزا یا مخلوط، تحت درمان قرار گرفتند. از میان رژیم های متعدد درمانی بکار رفته در این تحقیق، استفاده از رژیم ترکیبی شامل سایمتیدین به میزان 80 میلی گرم و گلوکانتیم به مقدار 20 میلی گرم در روز به ازای هر کیلوگرم از وزن بدن از سایر رژیم های درمانی موثرتر بود

The multispecific thyroid hormone transporter OATP1C1 mediates cell-specific sulforhodamine 101-labeling of hippocampal astrocytes

Sulforhodamine 101 (SR101) is widely used for astrocyte identification, though the labeling mechanism remains unknown and the efficacy of labeling in different brain regions is heterogeneous. By combining region-specific isolation of astrocytes followed by transcriptome analysis, two-photon excitation microscopy, and mouse genetics, we identified the thyroid hormone transporter OATP1C1 as the SR101-uptake transporter in hippocampus and cortex. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00429-013-0645-0) contains supplementary material, which is available to authorized users

Hardness as a Spectral Peak Estimator for Gamma-Ray Bursts

Simple hardness ratios are found to be a good estimator for the spectral peak energy in Gamma-Ray Bursts (GRBs). Specifically, a high correlation strength is found between the $\nu F_{\nu}$ peak in the spectrum of BATSE GRBs, \epo, and the hardness of GRBs, \hr, as defined by the fluences in channels 3 and 4, divided by the combined fluences in channels 1 and 2 of the BATSE Large Area Detectors. The correlation is independent of the type of the burst, whether Long-duration GRB (LGRB) or Short-duration (SGRB) and remains almost linear over the wide range of the BATSE energy window (20-2000 KeV). Based on Bayes theorem and Markov Chain Monte Carlo techniques, we also present multivariate analyses of the observational data while accounting for data truncation and sample-incompleteness. Prediction intervals for the proposed \hrep ~relation are derived. Results and further simulations are used to compute \epo estimates for nearly the entire BATSE catalog: 2130 GRBs. These results may be useful for investigating the cosmological utility of the spectral peak in GRBs intrinsic luminosity estimates.Comment: MNRAS submitted, Some technical side analyses removed or reduced following the referee's review, 68 pages, 13 figure

Balanced Scorecard with Fuzzy Inference as a Performance Measurement in an Automotive Manufacturing line

Abstract In recent years, the balanced score card (BSC) has been the focus of considerable methodology for strategic cost management in management accounting area since it was originally proposed by Kaplan ,R.S. and Norton, D.P. in 1992. BSC is an approach to performance measurement based on both financial and nonfinancial information from four perspectives which are called financial, customer, internal business process, and learning and growth, in order to balance the traditional financial performance system by several grouping of performance measures: short-term and long-term, internal and external, and current and future. Over time, it has been developed to a strategic management system from a comprehensive performance measure, and used in many organizations such as business, hospital, and autonomy in many countries. In this paper, we propose a general model based on BSC by introducing fuzzy inference mechanism. From this, specialists' knowledge and experience can be effectively reflected during the construction of the practical model. Then we illustrate a practical example for an Automotive Manufacturing Co