Graphics Evolutionary Computations in Higher Order Parametric Bezier Curves

This work demonstrates in practical terms the evolutionary concepts and computational applications of Parametric Curves. Specific cases were drawn from higher order parametric Bezier curves of degrees 2 and above. Bezier curves find real life applications in diverse areas of Engineering and Computer Science, such as computer graphics, robotics, animations, virtual reality, among others. Some of the evolutionary issues explored in this work are in the areas of parametric equations derivations, proof of related theorems, first and second order calculus related computations, among others. A Practical case is demonstrated using a graphical design, physical hand sketching, and programmatic implementation of two opposite-faced handless cups, all evolved using quadratic Bezier curves. The actual drawing was realized using web graphics canvas programming based on HTML 5 and JavaScript. This work will no doubt find relevance in computational researches in the areas of graphics, web programming, automated theorem proofs, robotic motions, among others.     

Interfacial energy for solutions of nanoparticles,surfactants, and electrolytes

The addition of surfactants to modify the surface property of nanoparticles (NPs) from hydrophilic to hydrophobic also enhances their interfacial properties. Several approaches were previously proposed to calculate the surface tension/interfacial tension (IFT) for different systems in the presence of NPs, surfactants, and electrolytes. However, most of these approaches are indirect and require several measured parameters. Therefore, a mathematical model is developed here to calculate the surface tension/IFT for these systems. The developed model takes into account the cohesive energy due to the interaction of the surfactant CH₂ groups, the electric double layer effect due to the interaction among the ions of NPs, surfactants, and electrolytes, and the dipole–dipole interaction of NPs and electrolytes. The developed model is compared and validated with the laboratory experimental data in literature. The results reveal further understanding of the mechanisms involved in stabilization of oil/water emulsion in the presence of NPs, surfactants, and electrolytes.     

Phytonutrient,Antioxidant and Mineral Composition of Some Wild Fruits in South West Nigeria

This study was carried out to determine the chemical composition, antinutrient and phytonutrient contents of some wild fruits, namely African star apple (Chrysophyllum albidum G. Don.), hog plum (Spondias mombin Linn.), bush mango (Irvingiagabonensis Baill) and monkey cola (Colamillenii K. Schum). Samples of the wild fruit commonly consumed were collected from some villages in Ido Local Government Area, Oyo State Nigeria. The wild fruits were analysed for phytonutrients, antioxidants and mineral composition. Ranges of total phenolics and total anthocyanin content of these wild fruits were 27.78 ± 6.01 in I. gabonensis, 57.42 ± 4.47 in S. mombin, 121.29 ± 4.97 in C. millenii and 398.23 ± 0.00 in C. albidum respectively. Significant differences (p < 0.05) were found in antinutrient, phytonutrient and mineral composition of C. albidum, I. gabonensis and C. millenii. The analysis of variance revealed that calcium and manganese contents of I. gabonensis were significantly (p < 0.05) higher than those of C. albidum and C. millenii. The antioxidants especially vitamin C content ranged from as low as 15.87 mg/100 g in C. albidum to as high as 204.86 mg/100 g in S. mombin. The values for total carotenoid ranged from 172.77 μg/100 g (in C. millenii) to 1380.17 μg/100 g (in C. albidum). The wild fruits are sources of phytonutrients, antioxidants such as vitamin C, total carotenoids and some minerals. Planting of the wild fruit trees or the incorporation in farming systems should thus be encouraged to increase production and availability to consumers and as industrial raw materials.     

CFD Study of Effects of Module Geometry on Forced Convection in a Channel with Non‐Conducting Fins and Flow Pulsation

CFD simulations were carried out to investigate the effects of the module geometry on forced convection in a rectangular channel containing series of regularly spaced non‐conducting baffles with flow oscillation. The simulations were performed at constant wall temperature. Steady‐flow Reynolds numbers Re in the range of 200 and 600 were studied. The results of the CFD simulations show that, for the effect fin spacing to be significant on heat transfer enhancement in finned system with oscillating flow, the oscillating flow velocity must be higher than the mean flow velocity. Superposition of oscillation yields increasing heat transfer performance with increasing fin height. Fin geometry with pyramidal shape yields highest performance in terms of the heat transfer effectiveness.     

Residence Time Distribution of Steady and Pulsed Flow in a Parallel‐Plate Channel with Staggered Fins

The residence time distribution (RTD) in a parallel‐plate channel with staggered fins for both steady and pulsed flow conditions was experimentally determined. Dispersion and tank‐in‐series models were also adopted to characterize the system. The process fluid was water and the experiments were performed at room temperature. A steady Reynolds number Re ranging from 100 to 1000 was studied. The pulsating flow was generated using a frequency f of 6–20 Hz and an amplitude A of 0–2.3 mm. A pulse injection of sodium chloride solution was used as a tracer and the response in the form of electrical conductivity was measured at the outlet stream. The flow in the staggered finned channel approaches nearly plug‐flow behavior with either higher steady‐flow velocity or superposition of oscillation at low Re.     

Nanoscale strain characterisation for ultimate CMOS and beyond

Strain engineering is used to maintain Moore's Law in scaled CMOS devices and as a technology booster for More-than-Moore devices in the nanoelectronics era. Strain is crucial because of its ability to increase electron and hole mobilities in Si. However, accurate correlations between electrical performance and strain measurements are needed to enable the necessary feedback between materials, processing and devices to achieve best possible solutions. In this work, we outline new methods for sensitive 3D profiling of strain on a nanoscale. High-resolution vertical and lateral strain profiles applicable to both global (biaxial) and process-induced (uniaxial) strained Si devices are demonstrated. Raman spectroscopy is pushed to its present limit for precise analysis of strain in small geometry devices, including the use of tip-enhanced Raman spectroscopy (TERS) to improve the spatial resolution further. TERS maps are compared with atomic force microscopy data collected simultaneously and show that variations in surface morphology correlate directly with strain in the epitaxial layers. Sub-nm strain profiling is applied to strained Si and SiGe MOSFET channels. Strain is profiled across patterned uniaxial strained-Si-on-insulator structures and analysed in bended nanowire transistors. Finally strain is investigated across the channel regions of electrically measured SiGe p-MOSFETs. Good agreement between nanoscale strain measurements and finite element modelling is demonstrated. Sample preparation is included in the analysis and genuine effects of processing are investigated.     

Modelling of heat transfer and pyrolysis reactions in an industrial ethylene cracking furnace

The development of a relatively simple mechanistic model for an industrial ethylene cracking furnace is described, including the estimation of selected model parameters to improve model predictions. Energy balance equations are developed to account for radiative, conductive, and convective heat transfer in the radiant section, and for convection and conduction in the ultra‐selective heat exchanger (USX) and in the transfer line exchanger (TLE). Kinetic schemes by Ranjan et al. and Sundaram and Froment are used to model the cracking reactions. 1 , 2 The heat transfer model is combined with mass and momentum balances to model gas composition, pressure, and temperature changes as a function of position along the reactor tubes. Initial values and uncertainty ranges are assigned to 44 model parameters based on information in the literature and our industrial sponsor. A sensitivity‐based technique and a mean‐squared‐error (MSE) criterion are used to select the appropriate subset of 22 parameters for tuning. Parameters are estimated and model predictions are validated using industrial data. Model predictions provide a good match to data that were not used for estimation.     

Improved self-gain in deep submicrometer strained silicon-germanium pMOSFETs with HfSiOx/TiSiN gate stacks

The self-gain of surface channel compressively strained SiGe pMOSFETs with HfSiO_x/TiSiN gate stacks is investigated for a range of gate lengths down to 55 nm. There is 125% and 700% enhancement in the self-gain of SiGe pMOSFETs compared with the Si control at 100 nm and 55 nm lithographic gate lengths, respectively. This improvement in the self-gain of the SiGe devices is due to 80% hole mobility enhancement compared with the Si control and improved electrostatic integrity in the SiGe devices due to less boron diffusion into the channel. At 55 nm gate length, the SiGe pMOSFETs show 50% less drain induced barrier lowering compared with the Si control devices. Electrical measurements show that the SiGe devices have larger effective channel lengths. It is shown that the enhancement in the self-gain of the SiGe devices compared with the Si control increases as the gate length is reduced thereby making SiGe pMOSFETs with HfSiO_x/TiSiN gate stacks an excellent candidate for analog/mixed-signal applications.     

The Roles of Luteinizing Hormone,Follicle-Stimulating Hormone and Testosterone in Spermatogenesis and Folliculogenesis Revisited

Spermatogenesis and folliculogenesis involve cell–cell interactions and gene expression orchestrated by luteinizing hormone (LH) and follicle-stimulating hormone (FSH). FSH regulates the proliferation and maturation of germ cells independently and in combination with LH. In humans, the requirement for high intratesticular testosterone (T) concentration in spermatogenesis remains both a dogma and an enigma, as it greatly exceeds the requirement for androgen receptor (AR) activation. Several data have challenged this dogma. Here we report our findings on a man with mutant LH beta subunit (LHβ) that markedly reduced T production to 1–2% of normal., but despite this minimal LH stimulation, T production by scarce mature Leydig cells was sufficient to initiate and maintain complete spermatogenesis. Also, in the LH receptor (LHR) knockout (LuRKO) mice, low-dose T supplementation was able to maintain spermatogenesis. In addition, in antiandrogen-treated LuRKO mice, devoid of T action, the transgenic expression of a constitutively activating follicle stimulating hormone receptor (FSHR) mutant was able to rescue spermatogenesis and fertility. Based on rodent models, it is believed that gonadotropin-dependent follicular growth begins at the antral stage, but models of FSHR inactivation in women contradict this claim. The complete loss of FSHR function results in the complete early blockage of folliculogenesis at the primary stage, with a high density of follicles of the prepubertal type. These results should prompt the reassessment of the role of gonadotropins in spermatogenesis, folliculogenesis and therapeutic applications in human hypogonadism and infertility.     

Autonomous Unbiased Study Group Formation Algorithm for Rapid Knowledge Propagation

Knowledge propagation is a necessity, both in academics and in the industry. The focus of this work is on how to achieve rapid knowledge propagation using collaborative study groups. The practice of knowledge sharing in study groups finds relevance in conferences, workshops, and class rooms. Unfortunately, there appears to be only few researches on empirical best practices and techniques on study groups formation, especially for achieving rapid knowledge propagation. This work bridges this gap by presenting a workflow driven computational algorithm for autonomous and unbiased formation of study groups. The system workflow consists of a chronology of stages, each made of distinct steps. Two of the most important steps, subsumed within the algorithmic stage, are the algorithms that resolve the decisional problem of number of study groups to be formed, as well as the most effective permutation of the study group participants to form collaborative pairs. This work contributes a number of new algorithmic concepts, such as autonomous and unbiased matching, exhaustive multiplication technique, twisted round-robin transversal, equilibrium summation, among others. The concept of autonomous and unbiased matching is centered on the constitution of study groups and pairs purely based on the participants’ performances in an examination, rather than through any external process. As part of practical demonstration of this work, study group formation as well as unbiased pairing were fully demonstrated for a collaborative learning size of forty (40) participants, and partially for study groups of 50, 60 and 80 participants. The quantitative proof of this work was done through the technique called equilibrium summation, as well as the calculation of inter-study group Pearson Correlation Coefficients, which resulted in values higher than 0.9 in all cases. Real life experimentation was carried out while teaching Object-Oriented Programming to forty (40) undergraduates between February and May 2021. Empirical result showed that the performance of the learners was improved appreciably. This work will therefore be of immense benefit to the industry, academics and research community involved in collaborative learning.