There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

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Principles Of Fluorescence Spectroscopy

In this chapter, we will restrict our attention to the ferrites and a few other closely related materials. The great interest in ferrites stems from their unique combination of a spontaneous magnetization and a high electrical resistivity. The observed magnetization results from the difference in the magnetizations of two non-equivalent sub-lattices of the magnetic ions in the crystal structure. Materials of this type should strictly be designated as “ferrimagnetic” and in some respects are more closely related to anti-ferromagnetic substances than they are to ferromagnetics in which the magnetization results from the parallel alignment of all the magnetic moments present. We shall not adhere to this special nomenclature except to emphasize effects, which are due to the existence of the sub-lattices.

Ferromagnetic materials

Adsorption of lead ions from aqueous solution using porous carbon derived from rubber tires: experimental and computational study.

An efficient method was developed for the elucidation and quantitative determination of 2-Thiouracil using surface enhanced Raman spectroscopy (SERS) with substrates of silver nanoparticles seeded on graphene nanosheets (Ag/G). Graphene was used as a support to allow for uniform distribution of silver nanoparticles as proved by the TEM images. The assignment of the vibrational modes in SERS was performed with the help of density functional theory. The bands of 2-Thiouracil at 789, 913, 957, 1368, and 1554 cm −1 are assigned to γ (C6-N3), δ (N3-C6-C8), (H-C7-C8-H) twist, ν (C5-N4), and ν (C5-N3). After introducing the Ag/G substrates these bands were shifted to 815, 931, 951, 1377 and 1527 cm −1 respectively. In addition, the results demonstrate that Ag/G enhances the intensity of these bands. The highest SERS enhancement band at 815 cm −1 was used to establish a calibration curve between the SERS signal intensity and 2-Thiouracil concentration ranging from 1 μM to 0.1 μM with a detection limit (S/N = 3) of 10 nM. The corresponding correlation coefficient of the linear equation was 0.9995. Therefore, Ag/G is a highly promising SERS substrate for the detection of 2-Thiouracil at ultra-low concentrations. This will further enhance the application of surface-enhanced Raman scattering in drug detection.

Silver loaded graphene as a substrate for sensing 2-thiouracil using surface-enhanced Raman scattering

Advanced Nanomaterials for Water Engineering, Treatment, and Hydraulics

https://www.econstor.eu/bitstream/10419/243670/1/1683610210.pdf

Advances in functionalized Nanoparticles based drilling inhibitors for oil production

In this study, the specific heat capacity of Alumina (Al2O3)/water nanofluid has been accurately evaluated using genetic algorithm/support vector regression (GA/SVR) model at volume fractions of 3.7–9.3%. The proposed (genetic algorithm/support vector regression) GA/SVR model was formulated using volume fractions and specific heat capacities of the alumina nanoparticles. The developed GA/SVR model is very accurate as determined from 99.998% correlation coefficient with experimentally obtained data and also has a root mean square error of 0.0014. Furthermore, the obtained results from the GA/SVR were compared with existing analytic models. Remarkably, the proposed model achieved an order of magnitude improvement over the model based on thermal equilibrium (Model II) and a two order of magnitude improvement over the model based on simple mixing rule for ideal gases (model I). Given the improvement in the accuracy, the proposed model would be useful for rapid and highly accurate estimation of the specific heat capacity of alumina/water nanofluids.

/pdf/modeling-and-prediction-of-the-specific-heat-capacity-of-al2-4mb7y8hggs.pdf

Tawfik A. Saleh

Papers

Adsorption of lead ions from aqueous solution using porous carbon derived from rubber tires: experimental and computational study.

Silver loaded graphene as a substrate for sensing 2-thiouracil using surface-enhanced Raman scattering

Advanced Nanomaterials for Water Engineering, Treatment, and Hydraulics

Advances in functionalized Nanoparticles based drilling inhibitors for oil production

Modeling and prediction of the specific heat capacity of Al2 O3/water nanofluids using hybrid genetic algorithm/support vector regression model