Detection of Alzheimer's Disease using MRI scans based on Inertia Tensor and Machine Learning

Alzheimer's Disease is a devastating neurological disorder that is increasingly affecting the elderly population. Early and accurate detection of Alzheimer's is crucial for providing effective treatment and support for patients and their families. In this study, we present a novel approach for detecting four different stages of Alzheimer's disease from MRI scan images based on inertia tensor analysis and machine learning. From each available MRI scan image for different classes of Dementia, we first compute a very simple 2 x 2 matrix, using the techniques of forming a moment of inertia tensor, which is largely used in different physical problems. Using the properties of the obtained inertia tensor and their eigenvalues, along with some other machine learning techniques, we were able to significantly classify the different types of Dementia. This process provides a new and unique approach to identifying and classifying different types of images using machine learning, with a classification accuracy of (90%) achieved. Our proposed method not only has the potential to be more cost-effective than current methods but also provides a new physical insight into the disease by reducing the dimension of the image matrix. The results of our study highlight the potential of this approach for advancing the field of Alzheimer's disease detection and improving patient outcomes

Modeling the Field Emission Current Fluctuation in Carbon Nanotube Thin Films

Owing to their distinct properties, carbon nanotubes (CNTs) have emerged as promising candidate for field emission devices. It has been found experimentally that the results related to the field emission performance show variability. The design of an efficient field emitting device requires the analysis of the variabilities with a systematic and multiphysics based modeling approach. In this paper, we develop a model of randomly oriented CNTs in a thin film by coupling the field emission phenomena, the electron-phonon transport and the mechanics of single isolated CNT. A computational scheme is developed by which the states of CNTs are updated in time incremental manner. The device current is calculated by using Fowler-Nordheim equation for field emission to study the performance at the device scale.Comment: 4 pages, 5 figure

HyBIS: Windows Guest Protection through Advanced Memory Introspection

Effectively protecting the Windows OS is a challenging task, since most implementation details are not publicly known. Windows has always been the main target of malwares that have exploited numerous bugs and vulnerabilities. Recent trusted boot and additional integrity checks have rendered the Windows OS less vulnerable to kernel-level rootkits. Nevertheless, guest Windows Virtual Machines are becoming an increasingly interesting attack target. In this work we introduce and analyze a novel Hypervisor-Based Introspection System (HyBIS) we developed for protecting Windows OSes from malware and rootkits. The HyBIS architecture is motivated and detailed, while targeted experimental results show its effectiveness. Comparison with related work highlights main HyBIS advantages such as: effective semantic introspection, support for 64-bit architectures and for latest Windows (8.x and 10), advanced malware disabling capabilities. We believe the research effort reported here will pave the way to further advances in the security of Windows OSes

Texture Segmentation Using Gabor Filters and Wavelets

The present work deals with image segmentation which results in the subdivision of an image into its constituent regions or objects. The result of image segmentation is a set of segments that collectively cover the entire image or a set of contours extracted from the image. Each of the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity or texture. Specifically this project deals with texture segmentation of an image to find out the different types of textures present in the image. In this project different type of procedures have been followed to carry out texture segmentation. Procedures starting from fundamental filter transforms till multi-resolution technique using wavelet transform have been considered. Many texture-segmentation schemes are based on a filter-bank model, where the filters called Gabor filters are derived from Gabor elementary functions. Both linear and circular Gabor filters are studied and analyzed in this aspect and how these filters are better in comparison to linear filters is also analyzed. Different types of wavelet transform techniques like Haar transform, S transform, etc. are followed and their performance regarding texture segmentation is being studied

Dynamical Symmetry Breaking by SU(2) Gauge Bosons

This work explores the possibility of obtaining a mass gap in Yang-Mills theories via the intrinsic gauge bosons, without invoking a separate Higgs boson or fermion-antifermion pairs. Instead, pairs of gauge bosons in the spin and isospin singlet state form a pair of composite Higgs bosons which can be viewed as the simplest possible glueball of Yang-Mills gauge theories. Quadratic and quartic gauge boson self-interactions form a potential that leads to a finite expectation value of the gauge boson amplitude. Transverse polarization ensures Lorentz invariance of the vacuum after averaging over all possible polarization vectors. But the scalar pair products exhibit a finite vacuum expectation value which breaks the gauge symmetry dynamically. Compatibility with the standard Higgs potential determines the quadratic and quartic coupling constants.Comment: 17 pages, 2 figures. Versions 2,3: added Ref. [15], augmented Appendix B, clarified the text. Versions 4,5: added Eq. (35) + text (formula for g), generalized Eq. (B17) + tex

Theoretical study of isolated dangling bonds, dangling bond wires and dangling bond clusters on H:Si(100)-(2×\times1) surface

We theoretically study the electronic band structure of isolated unpaired and paired dangling bonds (DB), DB wires and DB clusters on H:Si(100)-(2$\times$1) surface using Extended H\"uckel Theory (EHT) and report their effect on the Si band gap. An isolated unpaired DB introduces a near-midgap state, whereas a paired DB leads to $\pi$ and $\pi^*$ states, similar to those introduced by an unpassivated asymmetric dimer (AD) Si(100)-(2$\times$1) surface. Such induced states have very small dispersion due to their isolation from the other states, which reside in conduction and valence band. On the other hand, the surface state induced due to an unpaired DB wire in the direction along the dimer row (referred to as $[\bar{1}10]$), has large dispersion due to the strong coupling between the adjacent DBs, being 3.84$\AA$ apart. However, in the direction perpendicular to the dimer row (referred to as [110]), due to the reduced coupling between the DBs being 7.68$\AA$ apart, the dispersion in the surface state is similar to that of an isolated unpaired DB. Apart from this, a paired DB wire in $[\bar{1}10]$ direction introduces $\pi$ and $\pi^*$ states similar to those of an AD surface and a paired DB wire in [110] direction exhibits surface states similar to those of an isolated paired DB, as expected. Besides this, we report the electronic structure of different DB clusters, which exhibit states inside the band gap that can be interpreted as superpositions of states due to unpaired and paired DBs.Comment: 7 pages, 10 figure, 1 tabl

Spillover of Peste des Petits Ruminants Virus from Domestic to Wild Ruminants in the Serengeti Ecosystem, Tanzania

We tested wildlife inhabiting areas near domestic livestock, pastures, and water sources in the Ngorongoro district in the Serengeti ecosystem of northern Tanzania and found 63% seropositivity for peste des petits ruminants virus. Sequencing of the viral genome from sick sheep in the area confirmed lineage II virus circulation