Pinocembrin flavanone inhibits cell viability in PC-3 human prostate cancer by inducing cellular apoptosis, ROS production and cell cycle arrest

The main purpose of the present study was to evaluate the antitumor effects of pinocembrin in human prostate cancer cells (PC-3) along with investigating its effects on cell apoptosis, endogenous ROS production and cell cycle. MTT assay and clonogenic assays were used to study the effects on cell viability and cancer colony formation, respectively. Fluorescence microscopy along with Western blotting was used to study apoptotic effects induced by pinocembrin. Flow cytometry was used to study effects on ROS production and cell cycle phase distribution. Results indicated that pinocembrin promoted inhibition cell proliferation along with reducing cancer colony formation of PC-3 cells in a dose-dependent manner. Pinocembrin induced regulatory effects over expressions of caspase-3, caspase-9, Bax and Bcl-2, thereby promoting apoptotic cell death in PC-3 cells. It also led to the dose-dependent G0/G1 cell cycle arrest. In conclusion, pinocembrin exhibits strong anticancer effects in human prostate cancer cells mediated via apoptosis, endogenous ROS production and G0/G1 cell cycle arrest

Quality estimation and optimization of adaptive stereo matching algorithms for smart vehicles

Stereo matching is a promising approach for smart vehicles to find the depth of nearby objects. Transforming a traditional stereo matching algorithm to its adaptive version has potential advantages to achieve the maximum quality (depth accuracy) in a best-effort manner. However, it is very challenging to support this adaptive feature, since (1) the internal mechanism of adaptive stereo matching (ASM) has to be accurately modeled, and (2) scheduling ASM tasks on multiprocessors to generate the maximum quality is difficult under strict real-time constraints of smart vehicles. In this article, we propose a framework for constructing an ASM application and optimizing its output quality on smart vehicles. First, we empirically convert stereo matching into ASM by exploiting its inherent characteristics of disparity–cycle correspondence and introduce an exponential quality model that accurately represents the quality–cycle relationship. Second, with the explicit quality model, we propose an efficient quadratic programming-based dynamic voltage/frequency scaling (DVFS) algorithm to decide the optimal operating strategy, which maximizes the output quality under timing, energy, and temperature constraints. Third, we propose two novel methods to efficiently estimate the parameters of the quality model, namely location similarity-based feature point thresholding and street scenario-confined CNN prediction. Results show that our DVFS algorithm achieves at least 1.61 times quality improvement compared to the state-of-the-art techniques, and average parameter estimation for the quality model achieves 96.35% accuracy on the straight road

Multiplierless multirate FIR filter design and implementation

Ph.DDOCTOR OF PHILOSOPH

Energy efficiency optimization of FPGA-based CNN accelerators with full data reuse and VFS

Abstract—While FPGA has been recognized as a promising platform to accelerate Convolutional Neural Networks (CNNs) in embedded computing given its high flexibility and power efficiency, two challenges still have to be addressed to enhance its applicability on the edgecomputing paradigm. First, the power and performance of the CNN accelerator are still bounded by memory throughput, and a CNNcustomized architecture is desirable to fully utilize the on-chip storage. Second, power optimization algorithms are insufficiently explored on CNN-targeted platforms. In this paper, we design a novel FPGA-based CNN accelerator architecture that makes full use of the on-chip storage resources leveraging data reuse and loop unrolling strategies. We also present an efficient FPGA-based voltage and frequency scaling (VFS) system that enables VFS of the CNN accelerator for power optimization. We devise a VFS policy that fully exploits the power efficiency potential of the FPGA. Experiment results show up to 40% energy can be saved with our VFS platform and policy

Computation of Wind Wave Flow Field with Moving Boundary Based on Image Processing

Based on image processing technology, a solution to the interference of moving boundary in wind wave flow field calculation is proposed. Invariant background is extracted from image sequence by means of the minimum method, and the differences between image sequence and invariant background image are used to remove the invariant background of image sequence. The image segmentation threshold is determined based on maximum interclass variance method, and the scatter interference is removed by image filtering and morphological technology, to obtain the target image. Then the flow field is calculated by PIV technology and the results of the flow field before and after the boundary treatment are compared. The experimental results show that the accuracy and speed of flow field calculation are greatly improved after removal of moving boundary disturbance, and the results of wind wave flow field calculation accord with the motion mechanism of hydraulic wind wave

Experimental and Numerical Analysis of Rock Burst Tendency and Crack Development Characteristics of Tianhu Granite

Rock burst is a serious nonlinear dynamic geological hazard in underground engineering construction. In this paper, a true triaxial unloading rock burst experiment and numerical simulation are carried out on Tianhu granite to investigate the rock burst tendency and crack development characteristics of surrounding rock after excavation. The experiment and numerical simulation process monitored the rock burst stress path to determine the rock burst stress. According to the evolution law of the frequency and amplitude of rock burst acoustic emission monitoring, the shape characteristics of rock burst fragments are analyzed. The rock burst numerical simulation analysis is carried out by the PFC software, and the temporal and spatial evolution law of cracks is obtained. The research results show that the laboratory experiment and numerical simulation of Tianhu granite have rock burst strengths of 163.4 MPa and 161 MPa, respectively, and the average rock burst stress ratio is 8.38, that is, the Tianhu granite has a low rock burst tendency. During the rock burst, the development of tensile cracks will produce flaky debris, and the development of shear cracks will produce lumpy debris. Rock burst will happen when the crack growth rate to be exceeded the unloading crack growth rate; therefore, it can be used as a precursor signal for the occurrence of rock burst

A Survey on the Status of Smart Healthcare from the Universal Village Perspective

This survey paper discusses the condition of smart healthcare implementation. It discusses the current healthcare problems and how smart healthcare technologies ease the problems. Our group, Universal Village, realizes that the integration and interaction between parties in a system will maximize the effectiveness and benefit for the system. Based on this idea, this paper considers the smart city system as a whole, and talks about how smart healthcare interacts with infrastructures and functions inside and outside of the smart healthcare field. Then, it analyzes how a more powerful integrated system can be built from the smart healthcare system. In the end, several case studies are listed. Based on our analysis and the case studies, this paper then ended with the future prospects of the smart healthcare.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]