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

Activated carbon (AC) composites as adsorbents for mercury removal in water treatment. The AC composites comprise an AC as the core particle, with aluminum oxide (Al 2 O 3 ) and polyethylenimine (PEI) grafted on the surface of the AC core particle to increase the surface area, number of active sites and adsorption capacity. Methods of preparing and characterizing the AC composites by scanning electron microscope (SEM), energy dispersive X-ray (EDX) and Fourier transform infrared absorption spectroscopy (FTIR) are also provided.

Activated carbon/aluminum oxide/polyethylenimine composites and methods thereof

Spinel ferrites nanomaterials are magnetic semiconductors with excellent chemical, magnetic, electrical, and optical properties which have rendered the materials useful in many technological driven applications such as solar hydrogen production, data storage, magnetic sensing, converters, inductors, spintronics, and catalysts. The surface area of these nanomaterials contributes significantly to their targeted applications as well as the observed physical and chemical features. Experimental doping has shown a great potential in enhancing and tuning the specific surface area of spinel ferrite nanomaterials while the attributed experimental challenges call for viable theoretical model that can estimate the surface area of doped spinel ferrite nanomaterials with high degree of precision. This work develops stepwise regression (STWR) and hybrid genetic algorithm-based support vector regression (GBSVR) intelligent model for estimating specific surface area of doped spinel ferrite nanomaterials using lattice parameter and the size of nanoparticle as descriptors to the models. The developed hybrid GBSVR model performs better than STWR model with the performance improvement of 7.51% and 22.68%, respectively, using correlation coefficient and root mean square error as performance metrics when validated with experimentally measured specific surface area of doped spinel ferrite nanomaterials. The developed GBSVR model investigates the influence of nickel, yttrium, and lanthanum nanoparticles on the specific surface area of different classes of spinel ferrite nanomaterials, and the obtained results agree excellently well with the measured values. The accuracy and precision characterizing the developed model would be of immense importance in enhancing specific surface area of doped spinel ferrite nanomaterial prediction with circumvention of experimental stress coupled with reduced cost.

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Modeling the Specific Surface Area of Doped Spinel Ferrite Nanomaterials Using Hybrid Intelligent Computational Method

The study was conducted for the biosorption of Pb(II) from aquatic solution treated with Escherichia coli (E. coli) waste biomass immobilized with carbon nanofibers. Physicochemical characteristic studies were conducted by applying FTIR, SEM, and XRD. The study for biosorption of Pb(II) were optimized by different experimental parameters, contact pH 2–7, temperature 20–60 °C, contact time 10–50 min, amount of E. coli/carbon nanofibers(CNFs) composite biosorbent 4–16 g/L, and initial Pb(II) solution 1–20 mg/L. The factorial statistical design was also selected to evaluate parameters performance and define the relationships among factors and optimum response. Based on the equilibrium study, high regression correlation coefficient value (R2 = 0.995) was obtained for the non-linear Langmuir model and was best fitted for biosorption of Pb(II) by E. coli/ CNFs composite with a sorption capacity of 166.3 mg g−1. Experimental data for the kinetic model was best fitted with a pseudo-second-order model with a high correlation coefficient, R2 = 0.996. The binding mechanism of Pb(II) to the composite was characterized by some physicochemical attractions such as the electrostatic force of interaction, metal ion chelation, and ion exchange. The study revealed that E. coli/CNFs composite was an effective biosorbent to remove Pb(II) ions from aquatic solution. 

Influential Biosorption of Lead from Aquatic Solution using Escherichia coli/Carbon Nanofibers Protocols

A metal adsorbent that includes silver-decorated graphene nano-platelets and a polymer matrix that comprises polyamide, wherein the metal adsorbent is a highly porous material with a specific surface area of 200 to 300 m 2 /g and an average pore size of 50 to 100 A, which effective removes heavy metals and cations from a liquid. Various embodiments of the metal adsorbent and a method of making thereof are also provided.

Metal adsorbent and a method of making thereof

The development of facile and highly efficient materials for oil/water separation has recently attracted significant attention. Herein, a novel approach for the development of tungsten oxide-based meshes modified with palmitic acid (hexadecanoic) is reported. The stainless steel meshes were first coated with tungsten oxide thin film using a direct current (DC) sputtering system followed by post-annealing treatments at different temperatures specifically at room temperature, 200, 400, 600, and 800 °C. After that, the as-fabricated films were chemically functionalized with palmitic acid. The fabricated samples were then characterized using SEM-EDX, XRD, and contact angle measurement. Their separation efficiency towards oil/water separation was evaluated. Excellent reproducibility was obtained by the functionalized tungsten-oxide film treated at 600 °C. The same sample showed excellent flux (up to 30,000 L·m −2 ·h −1 ) with excellent separation efficacy of around 98.0 ± 1.5 %. The modified mesh showed excellent separation efficiency even with saline mixtures. The reported facile approach can pave the way for more practical utilization of coating nanomaterials for oil/water separation. • WO 3 modified-mesh coated with palmitic acid was prepared. • Annealing temperature influences the phase and water contact angel. • WO 3 modified-mesh at 600 °C showed ≈100 % separation of oil from water. 

Tawfik A. Saleh

Papers

Activated carbon/aluminum oxide/polyethylenimine composites and methods thereof

Modeling the Specific Surface Area of Doped Spinel Ferrite Nanomaterials Using Hybrid Intelligent Computational Method

Influential Biosorption of Lead from Aquatic Solution using Escherichia coli/Carbon Nanofibers Protocols

Metal adsorbent and a method of making thereof

Hydrophobic tungsten oxide-based mesh modified with hexadecanoic branches for efficient oil/water separation