Indirect spectrophotometric determination of reducing sugars and ascorbic acid using phenolphthalin as reagent

Summary An indirect spectrophotometric method has been developed for the determination of reducing sugars and ascorbic acid. A known excess of ferricyanide is allowed to react with the reductant, and the surplus ferricyanide is determined spectrophotometrically with phenolphthalin. The method is simple and reproducible, with an error of less than 2%.

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Indirekte spektrophotometrische Bestimmung reduzierender Zucker und der Askorbinsäure mit Phenolphthalin

Zusammenfassung Ein gemessener Überschuß von Eisen(III) cyanid wird mit der reduzierenden Probe umgesetzt und der nicht verbrauchte Anteil mit Phenol-phthalin spektrophotometrisch bestimmt. Das Verfahren ist einfach und gut reproduzierbar. Der Fehler ist geringer als 2%.

     

Indirect determination of amino acids by molecular emission cavity analysis

An indirect method for the determination of ca. 10^?4 M amino acids is described which is based on the reaction of the latter with 2,4,6-trinitrobenzene-1-sulphonic acid at pH 11.7 and the measurement of the S₂ emission in a hydrogen-nitrogen flame that is produced from the resulting compound after the addition of hydrochloric acid. The optimum conditions for the determination of amino acids were investigated. The amino acids examined were glycine, alanine, valine, methionine, serine, threonine and histidine.     

Superparamagnetic behaviour of cement clinker and its ferrite phase doped with different impurities

Two oxide mixtures of clinker and its ferrite phase of compositions (66.5 wt.% CaO+24.5 wt.% SiO₂+6.0 wt.% Al₂O₃+3.0 wt.% Fe₂O₃) and (60.4 wt.% CaO+15.4 wt.% Al₂O₃+24.2 wt.% Fe₂O₃) respectively were divided into protions and were mixed individually with 0.5, 1, 1.5 or 3 wt.% of LiF, MgF₂, CaF₂, CaCl₂ or ZnO. Each portion of clinker was fired at 1450°C and each portion of ferrite was fired at 1350°C for 30 min. then quenched in air. Mössbauer effect and X-ray diffraction measurements were performed on each sample. The impurities doping produced small particle size. The LiF doping gave the smallest particle size and the highest blocking temperature. The ferrite with LiF exhibited two Fe³⁺ sites while the other used impurities gave one site only. The superparamagnetic relaxation appeared only in the spectra of ferrite with impurities, which means that the impurities in clinker have a tendency to combine with the calcium silicate phases not with C₄AF.     

Optimal average sample number of the SPRT chart for monitoring fraction nonconforming

The Sequential Probability Ratio Test (SPRT) control chart is a powerful tool for monitoring manufacturing processes. It is highly suitable for the applications where testing is destructive or very expensive, such as the automobile airbags test. This article studies the effect of the Average Sample Number (ASN) (i.e., the average sample size) on the chart’s performance. A design algorithm is proposed to develop the optimal SPRT chart for monitoring the fraction nonconforming p of Bernoulli processes. By optimizing the ASN and other charting parameters, the average detection speed of the SPRT chart is almost doubled. It is also found that the optimal SPRT chart significantly outperforms the optimal np and binomial CUSUM charts, in terms of Average Number of Defectives (AND), under different combinations of the design specifications. It is observed that the SPRT chart using a relatively smaller ASN and a shorter sampling interval (h) has a higher overall detection effectiveness.     

Zero Divisor Graph for the Ring of Gaussian Integers Modulo n

This article studies the zero divisor graph for the ring of Gaussian integers modulo n, Γ (? _n [i]). For each positive integer n, the number of vertices, the diameter, the girth and the case when the dominating number is 1 or 2 is found.

Complete characterizations, in terms of n, are given of the cases in which Γ (? _n [i]) is complete, complete bipartite, planar, regular or Eulerian.     

Unified TeV scale picture of baryogenesis and dark matter

We present a simple extension of the minimal supersymmetric standard model which provides a unified picture of cosmological baryon asymmetry and dark matter. Our model introduces a gauge singlet field N and a color triplet field X which couple to the right-handed quark fields. The out-of-equilibrium decay of the Majorana fermion N mediated by the exchange of the scalar field X generates adequate baryon asymmetry for MN approximately 100 GeV and MX approximately TeV. The scalar partner of N (denoted N1) is naturally the lightest SUSY particle as it has no gauge interactions and plays the role of dark matter. The model is experimentally testable in (i) neutron-antineutron oscillations with a transition time estimated to be around 10(10)sec, (ii) discovery of colored particles X at LHC with mass of order TeV, and (iii) direct dark matter detection with a predicted cross section in the observable range.     

Forecasting of water thermal conductivity enhancement by adding nano-sized alumina particles

Operating fluids play an important role in heat transfer equipment. Water is inexpensive popular operating fluid with extensive applications, but its thermophysical properties are not good enough, especially for high temperature processes. Therefore, modification of its inherent characteristics by adding nano-sized solid particles found high popularities. Thermal conductivity is one of the most important thermophysical properties of an operating fluid in relatively all energy-based processes. Variation of thermal conductivity of nanofluids with different operating conditions is required to be understood in such processes. Therefore, the focus of this study is concentrated on modeling of thermal conductivity of water-alumina nanofluids using four different smart paradigms. Multilayer perceptron, radial basis function, cascade feedforward, and generalized regression neural networks are employed for the considered task. The best structure of these paradigms is determined, and then, their accuracies are compared using different statistical indices. Accuracy analyses confirmed that the generalized regression neural network outperforms other considered smart methodologies. It predicted more than 280 experimental datasets with excellent absolute average relative deviation?=?0.71%, mean square error?=?0.0006, root mean square error?=?0.023 and regression coefficient (R²)?=?0.9675. In the final stage, the proposed paradigm is used for investigation of the effect of influential parameters on the thermal conductivity of water-alumina nanofluids. This type of accurate and straightforward paradigm can broaden our insight about thermal behavior of homogeneous suspension of nano-size alumina particles in water.