<研究ノート>西成特区構想の展開と課題 : あいりん地域の新たなセーフティネットづくりを中心に

In this report, Mo(VI) ions are transported from an aqueous donor phase into an aqueous acceptor phase by a newly designed method called as multi dropped liquid membrane (MDLM) system prepared by dissolving TNOA as carrier in kerosene. During the extraction of Mo(VI) ions by the liquid membrane system; 100ppm Mo(VI) solutions as donor phase, buffer solution(pH:9.5) and Na2CO3 in different concentrations as acceptor phase and TNOA diluted by kerosen as organic phase are used.In our experimental work, the effect of temperature by using buffer solution and Na2CO3 in the acceptor phase and effect of concentration of acceptor phase on the extraction of Mo(VI) ions were investigated. Appropriate conditions for Mo(VI) transportation were as follows: pH of donor phase is 2.00, concentration of TNOA is 0.005M, 1.00M Na2CO3 as acceptor phase, and flux rate is 50mL/min. Besides, Mo(VI) ion transportation is consecutive first order irreversible reaction and the transportation of Mo(VI) ions is diffusion controlled process. The kinetic parameters (k1, k2, Rm(max), tmax, Jd(max), Ja(max)) were calculated for the interface reactions assuming two consecutive, irreversible first-order reactions

Thermal decomposition kinetics of polypyrrole and its star shaped copolymer

Thermal behavior of 2,4,6-tris(4-(1H-pyrrol-1-yl)phenoxy)-1,3,5-triazine monomer, polypyrrole, and their star shaped copolymer, were investigated using TG and DTA methods. It was found that Tria melts at 517 K and after than it starts to decompose. Decomposition proceeded in two stages which were corresponding to removal of branched groups and remaining core structure degradation, respectively. Polypyrrole and copolymer showed similar thermal behaviors. These compounds decomposed in three stages which are removal of solvent, removal of dopant anion and rest of structure decomposition. The calculation of activation energies of all reactions were realized using model-free (KAS and FWO) methods. The graphs were prepared which show the alteration of activation energy with decomposition ratio. Thermal analysis results showed that dopant anion and solvent removal activation energy values for copolymer are lower than polypyrrole. Star shaped loose-packed novel structure greatly facilitates solvent and dopant anion removal from copolymer. It can be concluded also that thermal analysis can be used as predict package structure of conducting polymers. © 2012 Akadémiai Kiadó, Budapest, Hungary

Thermal and kinetic analysis of uranium salts: Part III. Uranium(IV) oxalate hydrates

Thermal decomposition of U(C 2 O 4 ) 2 · 6H 2 O was studied using TG method in nitrogen, air, and oxygen atmospheres. The decomposition proceeded in five stages. The first three stages were dehydration reactions and corresponded to removal of four, one, and one mole water, respectively. Anhydrous salt decomposed to oxide products in two stages. The decomposition products in nitrogen atmosphere were different from those in air and oxygen atmospheres. In nitrogen atmosphere UO 1.5 (CO 3 ) 0.5 was the first product and U 2 O 5 was the second product, while these in air and oxygen atmospheres were UO(CO 3 ) and UO 3 , respectively. The second decomposition products were not stable and converted to stable oxides (nitrogen: UO 2 , air-oxygen: U 3 O 8 ). The kinetics of each reaction was investigated with using Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa methods. These methods were combined with modeling equations for thermodynamic functions, the effective models were investigated and thermodynamic values were calculated. © 2013 Akadémiai Kiadó, Budapest, Hungary

Fuzzy classification methods based diagnosis of parkinson’s disease from speech test cases

Background: Together with the Alzheimer’s disease, Parkinson’s disease is considered as one of the two serious known neurodegenerative diseases. Physicians find it hard to predict whether a given patient has already developed or is expected to develop the Parkinson’s disease in the future. To overcome this difficulty, it is possible to develop a computing model, which analyzes the data related to a given patient and predicts with acceptable accuracy when he/she is anticipated to develop the Parkinson’s disease. Objectives: This paper contributes an attractive prediction framework based on some machine learning approaches for distinguishing people with Parkinsonism from healthy individuals. Methods: Several fuzzy classifiers such as Inductive Fuzzy Classifier, Fuzzy Rough Classifier and two types of neuro-fuzzy classifiers have been employed. Results: The fuzzy classifiers utilized in this study have been tested using the “Parkinson Speech Dataset with Multiple Types of Sound Recordings Data Set” of 40 subjects available on the UCI repository. Conclusion: The results achieved show that FURIA, MLP-Bagging-SGD, genfis2 and scg1 performed the best among the fuzzy rough, WEKA, adaptive neuro-fuzzy and neuro-fuzzy classifiers, respectively. The worst performance belongs to nearest neighborhood, IBK, genfis3 and scg3 among the formerly mentioned classifiers. The results reported in this paper are better in comparison to the results reported in Sakar et al., where the same dataset was used, with utilization of different classifiers. This demonstrates the applicability and effectiveness of the fuzzy classifiers used in this study as compared to the non-fuzzy classifiers used by Sakar et al. © 2019 Bentham Science Publishers