Single and Dual-GPU Generalized Sparse Eigenvalue Solvers for Finding a Few Low-Order Resonances of a Microwave Cavity Using the Finite-Element Method

This paper presents two fast generalized eigenvalue solvers for sparse symmetric matrices that arise when electromagnetic cavity resonances are investigated using the higher-order finite element method (FEM). To find a few low-order resonances, the locally optimal block conjugate gradient (LOBPCG) algorithm with null-space deflation is applied. The computations are expedited by using one or two graphical processing units (GPUs) as accelerators. The performance of the solver is tested for single and dual GPU hardware setups, making use of two types of GPU: NVIDIA Kepler K40s and NVIDIA Pascal P100s. The speed of the GPU-accelerated solvers is compared to a multithreaded implementation of the same algorithm using a multicore central processing unit (CPU, Intel Xeon E5-2680 v3 with twelve cores). It was found that, even for the least efficient setups, the GPU-accelerated code is approximately twice as fast as a parallel CPU-only implementation

Low-cost surrogate models for microwave filters

A novel low-cost kriging-based multivariable parametric macromodeling technique for microwave filters is presented. Kriging is used to model both the residues and poles of a microwave filter's reflection coefficient, and the zeros of the transmission coefficient. The proposed residue-pole-zero (RPZ) technique is demonstrated to efficiently model a high dimensional (8D) microwave filter with pseudoelliptic characteristics

Targeting the Ser/Thr Protein Kinase RSK to Reduce Breast Cancer Metastasis

RSK is a family of four Ser/Thr protein kinases activated by ERK1/2 signaling. RSK has been found to be misregulated in a variety of cancers, including breast and prostate. More recently, RSK1 and RSK2 have been shown to promote metastasis in vivo. Currently, no targeted therapies to inhibit metastasis are available. Our laboratory has described the first potent and selective small molecule of RSK, SL0101. We found that this compound is not suitable for in vivo studies, therefore we set out to develop and validate new analogues based on the SL0101 pharmacophore. Here, we report a series of modifications improving the in vivo properties of SL0101. We characterize the mode of inhibition of RSK by SL0101. We find that this molecule acts as an allosteric non-competitive inhibitor of RSK. We postulate that this unusual mode of inhibition of RSK accounts for a remarkable selectivity of SL0101 for this kinase. We identify a number of modifications to the parent molecule that increase its in vitro affinity and stability in cell-based assays. We characterize new analogues that maintain the selectivity of the inhibitor for RSK. In addition, we discover that SL0101 is an isoform-selective inhibitor of RSK1/2 and not RSK3/4. The importance of these findings is highlighted by the fact that RSK1/2 serve tumor-promoting functions, while RSK3/4 are thought to be tumor suppressors. Therefore, SL0101 displays a desired isoform-selectivity as a potential novel therapeutic strategy to treat cancers. Isoform-specific functions of RSK are not very well understood. Here, we describe development of a biotin labeling-mediated proteomic screen to identify novel RSK1 interacting partners. We find that a portion of RSK1 interacts with intracellular membranes, while RSK2 does not. We identify potential novel RSK1-binding partners among the proteins of the endoplasmic reticulum and mitochondrial membranes. Therefore, we postulate that RSK1 may be involved in regulation of protein synthesis and energy homeostasis. Finally, we uncover a novel function of RSK1/2 in stimulating mitochondrial oxidative phosphorylation in breast cancer cells. We find that this function of RSK1/2 is specific to transformed cells. Therefore, we postulate that RSK1 can be involved in the metabolic transformation of breast cancer cells. Blocking this function by means of small molecules we develop could constitute a novel therapeutic strategy to target alterations in metabolism of cancer cells. Given the emerging roles of RSK1/2 in promoting metastasis, we envision that RSK inhibitors could constitute a novel class of drugs targeting this aspect of cancers. Our studies open new avenues of investigation of RSK-mediated cellular processes and their role in various disease states

Bayesian optimization for solving high-frequency passive component design problems

In this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all problems. Here, BO was applied to different types of microwave and antenna engineering problems, including matching circuit design, multiband antenna and antenna array design, or microwave filter design. Since each of the presented problems has a different nature and characteristics such as different scales (i.e. number of design variables), we try to address the question about the generality of BO and identify the problem areas for which the technique is or is not recommended