Beneficial effects of tea and its polyphenols against prostate cancer

Tea, next to water, is the most widely consumed beverage in the world. Depending upon the level of fermentation, tea can be categorized into three types: green (unfermented), oolong (partially fermented), and black (highly to fully fermented). In general, green tea has been found to be superior to black and oolong tea in terms of antioxidant and health promoting benefits owing to the higher content of (-)-epigallocatechin-3-gallate. Tea polyphenols comprise about one-third of the weight of the dried leaf, and they exhibit biochemical and pharmacological activities including antioxidant activities, inhibition of cell proliferation, induction of apoptosis, cell cycle arrest and modulation of carcinogen metabolism. Several studies demonstrate that most tea polyphenols exert their effects by scavenging reactive oxygen species (ROS) since excessive production of ROS has been implicated in the development of a variety of ailments including cancer of the prostate gland (CaP). Using cell culture and animal model systems, molecular targets for these remarkable beneficial effects of green tea drinking on CaP prevention and therapy have been defined. Geographical and case-control studies are showing that green tea drinking could afford CaP chemopreventive effects in human population. In this review we attempt to summarize the experimental as well as the epidemiological basis for the possible role of tea and its polyphenols for chemoprevention and chemotherapy of CaP.     

Dynamically adaptive real-time disparity estimation hardware using iterative refinement

The computational complexity of disparity estimation algorithms and the need of large size and bandwidth for the external and internal memory make the real-time processing of disparity estimation challenging, especially for High Resolution (HR) images. This paper proposes a hardware-oriented adaptive window size disparity estimation (AWDE) algorithm and its real-time reconfigurable hardware implementation that targets HR video with high quality disparity results. Moreover, an enhanced version of the AWDE implementation that uses iterative refinement (AWDE-IR) is presented. The AWDE and AWDE-IR algorithms dynamically adapt the window size considering the local texture of the image to increase the disparity estimation quality. The proposed reconfigurable hardware architectures of the AWDE and AWDE-IR algorithms enable handling 60 frames per second on a Virtex-5 FPGA at a 1024×768 XGA video resolution for a 128 pixel disparity range.     

Deep learning model for estimating the mechanical properties of concrete containing silica fume exposed to high temperatures

In this study, the deep learning models for estimating the mechanical properties of concrete containing silica fume subjected to high temperatures were devised. Silica fume was used at concentrations of 0%, 5%, 10%, and 20%. Cube specimens (100 mm × 100 mm × 100 mm) were prepared for testing the compressive strength and ultrasonic pulse velocity. They were cured at 20°C±2°C in a standard cure for 7, 28, and 90 d. After curing, they were subjected to temperatures of 20°C, 200°C, 400°C, 600°C, and 800°C. Two well-known deep learning approaches, i.e., stacked autoencoders and long short-term memory (LSTM) networks, were used for forecasting the compressive strength and ultrasonic pulse velocity of concrete containing silica fume subjected to high temperatures. The forecasting experiments were carried out using MATLAB deep learning and neural network tools, respectively. Various statistical measures were used to validate the prediction performances of both the approaches. This study found that the LSTM network achieved better results than the stacked autoencoders. In addition, this study found that deep learning, which has a very good prediction ability with little experimental data, was a convenient method for civil engineering.     

Structural, Electrical, and Microstructure Properties of Nanostructured Calcium Doped Ba-Hexaferrites Synthesized by Sol-Gel Method

Nanostructured M-type hexaferrite Ba_1?x Ca _x Fe_11.5Cr_0.5O₁₉ (x=0.0–0.5) powders have been synthesized by means of the sol-gel autocombustion method. The materials are characterized by differential scanning calorimetry, thermogravimetry, Fourier transform infra-red spectroscopy, X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, and vibrating sample magnetometry. X-ray diffraction analysis confirms the formation of M-type hexagonal phase and few traces of α-Fe₂O₃ are also observed. The c/a ratio falls in the expected range from a value of 3.97 to 3.94 of M-type hexaferrites. The average crystallite size is found to be in the range 15 to 36 nm, which is good enough to obtain the suitable signal-to-noise ratio in the high-density recording media. DC electrical resistivity at room temperature enhances up to 11.2×10⁹ Ω?cm (x=0.4) and then drops upon increasing the Ca²⁺ contents further. The magnetic properties such as saturation magnetization (M _s ), remanence (M _r ), squareness ratio (M _r /M _s ) and coercivity (H _c ) are calculated from the M–H-loops. The maximum magnetization and remanence reduces from a value of 52 to 33 and 33 to 16 emu/g, respectively, which attributes to the decrease of magnetic moment, and hence reduction in the superexchange interaction. The coercivity enhances from 4378 to 4706 Oe, which attributes to the increase in magnetocrystalline anisotropy due to the reduction of particle size. Owing to these properties, the synthesized nanomaterials can be considered useful for high-density recording media and permanent magnets.     

Image Blending in a High Frame Rate FPGA-based Multi-Camera System

Panoptic is a custom spherical light field camera used as a polydioptric system where imagers are distributed over a hemispherical surface, each having its own vision of the surroundings and a distinct focal plane. The spherical light field camera records light information from any direction around its center. This paper revises previously developed Nearest Neighbor and Linear blending techniques. Novel Gaussian blending and Restricted Gaussian blending techniques for vision reconstruction of a virtual observer located inside the spherical geometry are presented. These new blending techniques improve the output quality of the reconstructed image with respect to the ordinary stitching techniques and simpler image blending algorithms. A comparison of the developed blending algorithms is also given in this paper. A hardware architecture based on Field Programmable Gate Arrays (FPGA) enabling the real-time implementation of the blending algorithms is presented, along with the imaging results and resource utilization comparison. A recorded omnidirectional video is attached as a supplementary material.     

Hydrogen generation from sodium borohydride with Ni and Co based catalysts supported on Co3O4

Hydrogen is an alternative and clean energy carrier, but there are still some production related problems. In this aspect, it is crucial to efficiently generate hydrogen from hydrogen rich materials such as sodium borohydride. In this study, Co₃O₄ supported Ni and Co catalysts are synthesized via microwave irradiation technique for hydrogen generation from sodium borohydride. In this context, firstly, Co₃O₄ support material is synthesized by chemical method. Then, Ni and Co catalysts are decorated onto Co₃O₄ support material by microwave irradiation-polyol method. Prepared catalysts and support material are characterized by using X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and inductively coupled plasma-mass spectrometer (ICP/MS). A new system is designed by our group in order to determine the activity of the prepared catalysts for hydrogen generation. The effects of different initial NaOH concentrations on hydrogen generation rate are investigated. It is observed that the rate of hydrogen generation increased with an increase in initial NaOH concentration. Co-Co₃O₄ catalyst at 10% NaOH initial concentration shows the highest hydrogen generation rate as 2823 ml/g_cat.min. In summary, Co-based catalysts are exhibited more activity than Ni-based catalysts in terms of hydrogen generation.