DD-dimensional charged Anti-de-Sitter black holes in f(T)f(T) gravity

We present a $D$-dimensional charged Anti-de-Sitter black hole solutions in $f(T)$ gravity, where $f(T)=T+\beta T^2$ and $D \geq 4$. These solutions are characterized by flat or cylindrical horizons. The interesting feature of these solutions is the existence of inseparable electric monopole and quadrupole terms in the potential which share related momenta, in contrast with most of the known charged black hole solutions in General Relativity and its extensions. Furthermore, these solutions have curvature singularities which are milder than those of the known charged black hole solutions in General Relativity and Teleparallel Gravity. This feature can be shown by calculating some invariants of curvature and torsion tensors. Furthermore, we calculate the total energy of these black holes using the energy-momentum tensor. Finally, we show that these charged black hole solutions violate the first law of thermodynamics in agreement with previous results.Comment: 11 Pages, will appear in JHE

Rotating charged AdS solutions in quadratic f(T)f(T) gravity

We present a class of asymptotically anti-de Sitter charged rotating black hole solutions in $f(T)$ gravity in $N$-dimensions, where $f(T)=T+\alpha T^{2}$. These solutions are nontrivial extensions of the solutions presented in \cite{Lemos:1994xp} and \cite{Awad:2002cz} in the context of general relativity. They are characterized by cylindrical, toroidal or flat horizons, depending on global identifications. The static charged black hole configurations obtained in \cite{Awad:2017tyz} are recovered as special cases when the rotation parameters vanish. Similar to \cite{Awad:2017tyz} the static black holes solutions have two different electric multipole terms in the potential with related moments. Furthermore, these solutions have milder singularities compared to their general relativity counterparts. Using the conserved charges expressions obtained in \cite{Ulhoa:2013gca} and \cite{Maluf:2008ug} we calculate the total mass/energy and the angular momentum of these solutions.Comment: 11 pages, Version accepted in EPJ

Phase Portraits of general f(T) Cosmology

We use dynamical system methods to explore the general behaviour of $f(T)$ cosmology. In contrast to the standard applications of dynamical analysis, we present a way to transform the equations into a one-dimensional autonomous system, taking advantage of the crucial property that the torsion scalar in flat FRW geometry is just a function of the Hubble function, thus the field equations include only up to first derivatives of it, and therefore in a general $f(T)$ cosmological scenario every quantity is expressed only in terms of the Hubble function. The great advantage is that for one-dimensional systems it is easy to construct the phase space portraits, and thus extract information and explore in detail the features and possible behaviours of $f(T)$ cosmology. We utilize the phase space portraits and we show that $f(T)$ cosmology can describe the universe evolution in agreement with observations, namely starting from a Big Bang singularity, evolving into the subsequent thermal history and the matter domination, entering into a late-time accelerated expansion, and resulting to the de Sitter phase in the far future. Nevertheless, $f(T)$ cosmology can present a rich class of more exotic behaviours, such as the cosmological bounce and turnaround, the phantom-divide crossing, the Big Brake and the Big Crunch, and it may exhibit various singularities, including the non-harmful ones of type II and type IV. We study the phase space of three specific viable $f(T)$ models offering a complete picture. Moreover, we present a new model of $f(T)$ gravity that can lead to a universe in agreement with observations, free of perturbative instabilities, and applying the Om(z) diagnostic test we confirm that it is in agreement with the combination of SNIa, BAO and CMB data at 1$\sigma$ confidence level.Comment: 39 pages, 12 figures, version published in JCA

Investigation of nanodispersion in polystyrene-montmorillonite nanocomposites by solid state NMR

Nanocomposites result from combinations of materials with vastly different properties in the nanometer scale. These materials exhibit many unique properties such as improved thermal stability, reduced flammability, and improved mechanical properties. Many of the properties associated with polymer–clay nanocomposites are a function of the extent of exfoliation of the individual clay sheets or the quality of the nanodispersion. This work demonstrates that solid-state NMR can be used to characterize, quantitatively, the nanodispersion of variously modified montmorillonite (MMT) clays in polystyrene (PS) matrices. The direct influence of the paramagnetic Fe3, embedded in the aluminosilicate layers of MMT, on polymer protons within about 1 nm from the clay surfaces creates relaxation sources, which, via spin diffusion, significantly shorten the overall proton longitudinal relaxation time (T1 H). Deoxygenated samples were used to avoid the particularly strong contribution to the T1 H of PS from paramagnetic molecular oxygen. We used T1 H as an indicator of the nanodispersion of the clay in PS. This approach correlated reasonably well with X-ray diffraction and transmission electron microscopy (TEM) data. A model for interpreting the saturation-recovery data is proposed such that two parameters relating to the dispersion can be extracted. The first parameter, f, is the fraction of the potentially available clay surface that has been transformed into polymer–clay interfaces. The second parameter is a relative measure of the homogeneity of the dispersion of these actual polymer–clay interfaces. Finally, a quick assay of T1 H is reported for samples equilibrated with atmospheric oxygen. Included are these samples as well as 28 PS/MMT nanocomposite samples prepared by extrusion. These measurements are related to the development of highthroughput characterization techniques. This approach gives qualitative indications about dispersion; however, the more time-consuming analysis, of a few deoxygenated samples from this latter set, offers significantly greater insight into the clay dispersion. A second, probably superior, rapid-analysis method, applicable to oxygen-containing samples, is also demonstrated that should yield a reasonable estimate of the f parameter. Thus, for PS/MMT nanocomposites, one has the choice of a less complete NMR assay of dispersion that is significantly faster than TEM analysis, versus a slower and more complete NMR analysis with sample times comparable to TEM, information rivaling that of TEM, and a substantial advantage that this is a bulk characterization method. © 2003 Wiley Periodicals, Inc.* J Polym Sci Part B: Polym Phys 41: 3188–3213, 200

Material properties of nanoclay PVC composites

Nanocomposites of poly(vinyl chloride) have been prepared using both hectorite- and bentonite-based organically-modified clays. The organic modification used is tallow-triethanol-ammonium ion. The morphology of the systems was investigated using X-ray diffraction and transmission electron microscopy and these systems show that true nanocomposites, both intercalated and exfoliated systems, are produced. The mechanical properties have been evaluated and the modulus increases upon nanocomposite formation without a significant decrease in tensile strength or elongation at break. Thermal analysis studies using thermogravimetric analysis, differential scanning calorimetry, and dynamic mechanical analysis were conducted. Thermal stability of the PVC systems was assessed using a standard thermal process evaluating the evolution of hydrogen chloride and by color development through the yellowness index. Cone calorimetry was used to measure the fire properties and especially to evaluate smoke evolution. The addition of an appropriately-modified bentonite or hectorite nanoclay leads to both a reduction in the total smoke that is evolved, and an increase in the length of time over which smoke is evolved. Along with this, a reduction in the peak heat release rate is seen. It is likely that the presence of the clay in some way interferes with the cyclization of the conjugated system formed upon HCl loss

The non-Abelian gauge theory of matrix big bangs

We study at the classical and quantum mechanical level the time-dependent Yang-Mills theory that one obtains via the generalisation of discrete light-cone quantisation to singular homogeneous plane waves. The non-Abelian nature of this theory is known to be important for physics near the singularity, at least as far as the number of degrees of freedom is concerned. We will show that the quartic interaction is always subleading as one approaches the singularity and that close enough to t=0 the evolution is driven by the diverging tachyonic mass term. The evolution towards asymptotically flat space-time also reveals some surprising features.Comment: 29 pages, 8 eps figures, v2: minor changes, references added: v3 small typographical changes

Brain Tumors Detection using Computed Tomography Scans Based on Deep Neural Networks

Brain tumors are one of the deadliest diseases, with numerous implications on human health. A brain tumor is an abnormal cell mass or growth in or around the brain. They are not all cancerous, as they might be benign or malignant. Doctors use a variety of diagnostic techniques to assess the presence of a benign or malignant brain tumor, as well as to estimate its size, location, and growth rate. The proper diagnostic modality is used to provide a complete view of the brain to detect any abnormalities. A computed tomographic (CT) scan of the brain shall be done to check the abnormalities. The benefits of CT scans include accurate detection of calcification, hemorrhage, and bone detail, as well as low cost compared to magnetic resonance imaging (MRI). Therefore, we examine a proposed CT-based detection method to determine whether brain tumor is present or not. The proposed method works on a CT image dataset that collected from Mansoura University hospital. Different pre-trained models are used: VGG-16, ResNet-50, and MobileNet-V2. Comparing the results, that pre-train model MobileNet-V2, despite having the lowest number of parameters, yields better results. It gives an accuracy 97.6%, while its precision, recall, and F1-score values are 96%, 95%, and 96%, respectively