Meet the editors

Ali Samadikuchaksaraei is a Professor of Medical Biotechnology, Tissue Engineering and Regenerative Medicine at Iran University of Medical Sciences. He is an expert in detection, analysis, and interpretation of clinically relevant genomic variations. As a well-known figure in this field, he is regularly consulted by the Iranian Academies, scientific organizations, and industrial sectors.

Dr. Morteza Seifi completed his PhD and postdoctoral training at the University of Alberta. He employs molecular and cellular techniques and bioinformatics tools to provide functional evidence of pathogenicity of genomic variations. Dr. Seifi has received several scholarships, awards, and grants, including one of Canada's largest and most prestigious endowments for academic activities, the Izaak Walton Killam Memorial Scholarship.

Contents

of Elastic Net and Hurst Exponent

*and Juliano Lino Ferreira*

and Prioritization

*and Ilknur Melis Durasi*

*and Emile R. Chimusa*

Variants by NGS Analysis

**Preface III**

**Chapter 1 1**

**Chapter 2 15**

**Chapter 3 35**

**Chapter 4 53**

**Chapter 5 75**

The Bioinformatics Tools for Discovery of Genetic Diversity by Means

Bioinformatics Workflows for Genomic Variant Discovery, Interpretation

*by Leila Maria Ferreira, Thelma Sáfadi, Tesfahun Alemu Setotaw*

Orienting Future Trends in Local Ancestry Deconvolution Models to Optimally Decipher Admixed Individual Genome Variations

Recognition of Multiomics-Based Molecule-Pattern Biomarker for Precise Prediction, Diagnosis, and Prognostic Assessment in Cancer *by Xanquan Zhan, Tian Zhou, Tingting Cheng and Miaolong Lu*

HCV Genotyping with Concurrent Profiling of Resistance-Associated

*by Kok-Siong Poon, Julian Wei-Tze Tang and Evelyn Siew-Chuan Koay*

*by Osman Ugur Sezerman, Ege Ulgen, Nogayhan Seymen*

*by Gaston K. Mazandu, Ephifania Geza, Milaine Seuneu*


*Edited by Samuel Ikwaras Okware*

Significant progress in HIV prevention and control has been achieved worldwide. This book reviews emerging challenges and new opportunities for prevention. Chapters cover such topics as challenges in the media within the context of advancing technologies and societal perceptions, barriers to antiretroviral treatment and suggestions for improvement, opportunities in nanotechnology-based drug delivery systems, the central role of sexual and reproductive health in consolidating a human rights-based program, and much more. Client-focused models for integrating employment as a social determinant in the HIV/AIDS programs are discussed and recommended.

ISBN 978-1-83969-358-8

AIDS Updates - Recent Advances and New Perspectives

Published in London, UK © 2021 IntechOpen © Rost-9D / iStock

## AIDS Updates Recent Advances and New Perspectives

*Edited by Samuel Ikwaras Okware*

## AIDS Updates - Recent Advances and New Perspectives

*Edited by Samuel Ikwaras Okware*

Published in London, United Kingdom

### *Supporting open minds since 2005*

AIDS Updates - Recent Advances and New Perspectives http://dx.doi.org/10.5772/intechopen.91514 Edited by Samuel Ikwaras Okware

#### Contributors

Fausta Mosha, Marcela Gómez-Suárez, Liza Conyers, Jen Yung-Chen Chiu, Sergio Rueda, Mark Misrok, Erin McKinney-Prupis, Vickie Lynn, Inampudi Sailaja, Manoj Kumar Baghel, Ivvala Anand Shaker, Adamu Muhammad Muhammad Hamid, Godwin Matthew Matthew Sule, Samuel Ikwaras Okware

#### © The Editor(s) and the Author(s) 2021

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**5. Discussion**

This review of hyperspectral vegetation classification literature has determined that every aspect of a study can greatly influence selected wavebands and classification performance. However, despite this, we have identified some important and consistent patterns that appear throughout the literature. Visible wavelengths and their associations with photosynthetic pigments have played important discriminatory roles in a wide range of studies, their high levels of selection clearly evident in this review (Figure 1). Selection rates in the VIS showed only minor variations between VIS/SWIR studies and the VIS/NIR (Figure 1), although the comparisons between canopy and leaf scale spectra

demonstrated significant differences (Figure 3). The discriminatory value of the red edge has been well documented with its close relationship to chlorophyll concentration and structural features. This is reflected in the consistently high rates of selection of the red edge as well as the robustness of its selection with only minor variation in magnitude between the comparisons. The inclusion of structural features in canopy spectra can provide high levels of interspecific variation in the NIR, primarily in the form of differences in albedo, rather than spectral shape [68]. However, selection rates from the non-red edge NIR are low, with the selected bands generally being related to water absorption features and potentially high levels of within-class variability. Additionally, the NIR has demonstrated the greatest degree of variability between the canopy and leaf scale spectra studies. Wavebands selected in the SWIR are associated with water absorption and non-photosynthetic biochemicals, with selection rates heavily skewed towards the NSWIR over the FSWIR.

The reported importance of NIR bands [45,52] seems to be contentious, primarily being driven by the use of a single feature selection technique. Comparisons between selection rates for the NIR with and without the use of SDA as the feature selector are starkly contrasted, with the importance of NIR being significantly higher with the use of SDA. The criticisms of SDA and stepwise methods in general perhaps offer an answer to the selection biases presented in this review.

It is apparent that there is no single best feature selection method, with the same method performing very differently within and between studies. This suggests that either multiple methods should be applied to the data, or an ensemble of multiple methods may be the best practice, a conclusion recognized by this review, and previously suggested by some studies [36]. Additionally, multiple subsets of selected features have proven to discriminate species equally well [8], or alternatively, no feature selection, with the original data outperforming feature selected subsets [7,9,36]. Additionally, as computation power, dataset sizes, and machine learning techniques all increase, the need for feature selection as a data reduction technique becomes less necessary.


**1. Introduction**

Since the building of large synchrotron radiation facilities throughout the world in the latter half of the twentieth century, the performance of synchrotron radiation tomography has gradually improved up to the present day [1–3]. Currently, in the Japanese synchrotron radiation facilities, SPring-8, three-dimensional non-distractive observation with a spatial resolution of 50–160 nm is available constantly in the imaging beamline by using an X-ray focusing device of a Fresnel zone plate [4–6]. Phase-contrast imaging techniques have been also developed for those samples for which visualizations are difficult by X-ray absorption contrast (i.e., these densities are very close) [7]. Furthermore, improvement of the performance of X-ray 2D detector system has rapidly shortened scanning time. Therefore, synchrotron radiation tomography can be used for various studies in various fields.

The advantages of X-ray tomography are that three-dimensional morphologies are obtained, and that the observation is non-destructive. In studies of structural materials, material behaviors changing over time can be visualized, for instance, damage and fracture mechanisms [7–14], fatigue and crack propagation phenomena [15–18] and so on. We can deeply understand various phenomena

affected by microstructures from a series of observed images. In Al-Si cast alloys, it is well known that eutectic Si-particle strongly affects mechanical properties. Many studies with regard to the morphology and distribution of eutectic Si-particles have been conducted to date [19–21], because the spheroidizing of Si-particles brings, in particular, ductility improvement by heat treatment. However, most of the research had been performed on the basis of 2D observation by polishing of a heat-treated sample after cross section cutting. Although three-dimensional evaluation also exists using Focus Ion Beam tomography [22], unfortunately this method is destructive.

In the application of hypoeutectic Al–Si alloys for automobile parts which require sufficient toughness, Si-particle refinement is applied by adding trace Sr to improve the mechanical properties [23–25]. The addition of trace Sr prevents aluminum phosphide, AlP which become the nuclei of coarse Si particles [26], and then changes the solidification process of hypoeutectic Al-Si alloys [27]. Note that the origin of phosphorus is the impurity of Si. Si-particles modified by trace Sr addition become very fine at less than 1 μm. A Sr-modified hypoeutectic Al-Si alloy demonstrates excellent mechanical properties. Furthermore, with applying heat treatment to the alloy, its strength and ductility can be controlled. The changes of Si-particles morphology during a heat treatment are considered as follows; firstly, Si-particles with necking divide into parts by Plateau–Rayleigh instability [28,29]. This separation is a change which decreases system energy quickly. Next, the fragmented Si-particles grow into spherical shapes by diffusion-controlled Ostwald ripening to reduce their surface energy.

By contrast, self-modification (self-refinement) of eutectic Si-particles is also possible by killing an impurity element of P, which is contained in Si and forms AlP as the solidification nuclei of Si. This P-free solidification process has been reproduced by phase-field model simulation by Eiken [27]. The morphologies of eutectic Si-particles which are formed in the different solidification processes—self-modification and Sr-modification—are different. Synchrotron radiation nanotomography has revealed that the morphologies of Si-particles in self-modification and Sr-modification are of a rod-like shape and coral-like shape, respectively, by casting self-modified and Sr-modified samples and investigating practically [30]. Therefore, in this study, to clarify the behavior of morphological changes during heat treatment and the effect of them on mechanical properties, hypoeutectic Al-10%Si alloys were cast using two different solidification processes (Self-modification and Sr-modification) that produce different morphology of eutectic Si-particles (rod-like and coral-like). The changes of mechanical properties were investigated in the prepared samples. The three-dimensional morphology changes of eutectic Si-particles during the heat treatment process were observed in both alloys by using nanotomography with a Fresnel zone plate and a Zernike phase plate.

#### **2. Materials and Methods**

Al-10%Si alloy was selected as the sample of this study. Two kinds of Al-10%Si alloy, self-modified and a Sr-modified sample, were prepared by gravity casting. It is known that three-dimensional morphology of eutectic Si-particles is different between the two alloys [30]. High purity Al (99.99%) and high purity Si (99.9999%) were melted in a graphite crucible at 993 K in air atmosphere using an electrical resistance furnace (Hamamatsu heat-tech, Hamatsu, Shizuoka, Japan). The molten metal was degassed by hexachloroethane. After the degassing treatment, molten metal was cast into a boat-shaped iron-mold heated at 473 K with a cavity size of 150 mm × 25 mm × 25 mm as a self-modified sample. For the Sr-modified sample, the degassed molten metal was cast into the mold soon after the 100 ppm Sr addition. The chemical compositions of cast alloy samples detected by spark emission spectrometer (OBLF QSN750-II, Witten, Germany) are listed in Table 1. Hereafter, two prepared cast alloys are named as Al-9.8%Si-3ppmP and Al-10.1%Si-4ppmP-108ppmSr on the basis of the result of composition analysis. Photos of microstructures in Al-9.8%Si-3ppmP cast alloy and Al-10.1%Si-4ppmP-108ppmSr cast alloy are shown in Figure 1. The microstructures of both alloys are almost the same in the two-dimensional image. It is difficult to distinguish them.

**Table 1.** Chemical composition of prepared cast alloys (wt.%).

Specimens for nanotomography were cut from the cast ingot. Very small stick-shaped specimens with a section size of 50 μm × 50 μm and length of about 8 mm were manufactured by hand polishing. Five tensile specimens with 19.75 mm2 section × 30 mm length in a gauge part, which is a half size of JIS No.13 B (JIS Z 2241), were prepared from a position of 2 mm above from the bottom of the cast ingot, then the mechanical properties of the cast alloys were examined by a tensile testing machine (SHIMADZU AG-100 kNX, Kyoto, Japan).

**Figure 1.** Optical micrographs; (**a**) Al-9.8%Si-3ppmP cast alloy and (**b**) Al-10.1%Si-4ppmP-108ppmSr cast alloy.

Synchrotron radiation nanotomography was used for observation of three-dimensional morphology change in eutectic Si-particles during heat treatment. The synchrotron radiation experiment was performed at the undulator beam line of BL47XU in the Japanese synchrotron radiation facility, SPring-8 (Hyogo, Japan). A schematic illustration of the nanotomography set-up ¯ in the experimental hutch is shown in Figure 2. X-ray energy of 8 keV, which was adjusted by a silicon (111) double-crystal monochromator (SPring-8 Standard Monochromator, sKohzu Precision Co.,Ltd, Kawasaki, Kanagawa, Japan), was selected for this observation. A Fresnel zone plate with an outermost zone width of 50 nm was installed as an X-ray objective of an imaging X-ray microscope (NTT-AT, Kawasaki, Kanagawa, Japan). A Zernike phase plate made from tantalum with a thickness of 0.96 μm was also installed at the back focal plane of the Fresnel zone plate. A two-dimensional image detector system consisting of a Gd2O2S:Tb scintillator, an optical relay lens and a complementary metal oxide semiconductor camera (Hamamatsu Photonics K.K., C11440-22C, Hamamatsu, Shizuoka, Japan) was used. Since the difference in atomic number between them is only one, there is little X-ray absorption contrast in the Al phase and Si phase as shown in Figure 3a. Therefore, Si-particles in the inside of the aluminum matrix were visualized by phase contrast using a Zernike phase plate as shown in Figure 3b. Exposure time of 250 ms was used and 1800 projections were captured during a 180◦ rotation, for tomography. Voxel size of (37.8 nm)3 was achieved in the reconstructed volume image in the set-up of this study.

**Figure 2.** The schematic illustration of set-up of nanotomography in the experimental hutch.

**Figure 3.** Slice images of nanotomography in Al-10.1%Si-4ppmP-108ppmSr cast alloy heat-treated at 773 K for 7.2 ks. The same slices are shown by (**a**) absorption contrast and (**b**) phase contrast. Field of view and analyze-volume position are indicated by white dashed-line circle and box. Eutectic Si-particles and precipitate Si-particles can be recognized as white objects in (**b**), though specimen surface only can be seen in (**a**).

Experimental procedure for the synchrotron radiation nanotomography observation was simple. The initial state of the sample, i.e., as-cast sample, was scanned. After the first tomography scan, the sample was heat-treated by taking it in and out of a compact air atmosphere furnace maintained at 773 K, and then was tomography scanned repeatedly at the same position at 450 s, 900 s, 1.8 ks, 3.6 ks, 7.2 ks and 14.4 ks. X-ray scanned data were reconstructed into a three-dimensional volume image by a conventional filtered convolution back-projection algorithm. A three-dimensional median filter (3 × 3 × 3) was applied to three-dimensional volume images reconstructed in order to reduce artifacts and image noise. Si-particles observed in the volume images were binarized and segmented with the thresholds value that were decided by comparing the obtained volume images to one another. The result of Si-particles segmentation was checked by visual inspection. Then if wrong connections existed among particles, such connections were carefully corrected one by one. Volume rendering software (VG studio Max 2.0, Volume Graphics, Heidelberg, Germany; and Amira 4.0, Thermo Fisher Scientific, Waltham, MA, USA) was used to visualize the three-dimensional morphology of Si-particles. The analyzed region for the morphology changes of eutectic Si-particles was extracted from a lower effect region of artifacts inside the sample. The analyzed regions were 56.7 μm × 28.4 μm × 27.2 μm and 37.8 μm × 37.8 μm × 41.8 μm in Al-9.8%Si-3ppmP sample and Al-10.1%Si-4ppmP-108ppmSr, respectively. Si-particles within the analyzed regions were segmented and labeled after binarization. Then, volume and surface area were measured for each of the labeled Si-particles.