Antenna Element Design Using Characteristic Mode Analysis: Insights and Research Directions

[EN] This article provides a comprehensive review of recent applications of characteristic mode analysis (CMA) to innovative antenna element designs, including multi port, circularly polarized, wideband, reconfigurable, and dielectric resonator antennas (DRAs). Emphasis is placed on the interpretation of the characteristic modes (CMs) for those unfamiliar with the method and physical insights gained from the characteristic eigenvalues and eigenvectors of an antenna. In addition, we review CMA-based design strategies and specific design examples that highlight the application of CMA to vari ous types of antennas. Ultimately, this article seeks to dem onstrate the value of CMA-based design insights for antenna engineering and look toward promising new research directions for CMA and antenna research.Adams, JJ.; Genovesi, S.; Yang, B.; Antonino Daviu, E. (2022). Antenna Element Design Using Characteristic Mode Analysis: Insights and Research Directions. IEEE Antennas and Propagation Magazine. 64(2):32-40. https://doi.org/10.1109/MAP.2022.3145718324064

Quantification and classification of potassium and calcium disorders with the electrocardiogram: What do clinical studies, modeling, and reconstruction tell us?

Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches

Involvement of subcortical brain structures during olfactory stimulation in multiple chemical sensitivity

Multiple chemical sensitivity (MCS) patients usually react to odour compounds and the majority of neuroimaging studies assessed, especially at the cortical level, many olfactory-related correlates. The purpose of the present study was to depict sub-cortical metabolic changes during a neutral (NC) and pure (OC) olfactory stimulation by using a recently validated 18F-2-fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography/computer tomography procedure in 26 MCS and 11 healthy (HC) resting subjects undergoing a battery of clinical tests. Twelve subcortical volumes of interest were identified by the automated anatomical labeling library and normalized to thalamus FDG uptake. In both groups, when comparing OC to NC, the within-subjects ANOVA demonstrated a relative decreased metabolism in bilateral putamen and hippocampus and a relative increased metabolism in bilateral amygdala, olfactory cortex (OLF), caudate and pallidum. The between-groups ANOVA demonstrated in MCS a significant higher metabolism in bilateral OLF during NC. As in HC subjects negative correlations were found in OC between FDG uptake in bilateral amygdala and hippocampus and odor pleasantness scale, the latter positively correlated with MCS subjects\u27 bilateral putamen FDG uptake in OC. Besides FDG uptake resemblances in both groups were found, for the first time a relative higher metabolism increase in OLF in MCS subjects at rest with respect to HC was found. When merging this aspect to the different subcortical FDG uptake correlations patterns in the two groups, the present study demonstrated to describe a peculiar metabolic index of behavioral and neurological aspects of MCS complaints

Genetic and functional interaction network analysis reveals global enrichment of regulatory T cell genes influencing basal cell carcinoma susceptibility

Published online: 06 February 2021BACKGROUND: Basal cell carcinoma (BCC) of the skin is the most common form of human cancer, with more than 90% of tumours presenting with clear genetic activation of the Hedgehog pathway. However, polygenic risk factors affecting mechanisms such as DNA repair and cell cycle checkpoints or which modulate the tumour microenvironment or host immune system play significant roles in determining whether genetic mutations culminate in BCC development. We set out to define background genetic factors that play a role in influencing BCC susceptibility via promoting or suppressing the effects of oncogenic drivers of BCC. METHODS: We performed genome-wide association studies (GWAS) on 17,416 cases and 375,455 controls. We subsequently performed statistical analysis by integrating data from population-based genetic studies of multi-omics data, including blood- and skin-specific expression quantitative trait loci and methylation quantitative trait loci, thereby defining a list of functionally relevant candidate BCC susceptibility genes from our GWAS loci. We also constructed a local GWAS functional interaction network (consisting of GWAS nearest genes) and another functional interaction network, consisting specifically of candidate BCC susceptibility genes. RESULTS: A total of 71 GWAS loci and 46 functional candidate BCC susceptibility genes were identified. Increased risk of BCC was associated with the decreased expression of 26 susceptibility genes and increased expression of 20 susceptibility genes. Pathway analysis of the functional candidate gene regulatory network revealed strong enrichment for cell cycle, cell death, and immune regulation processes, with a global enrichment of genes and proteins linked to TReg cell biology. CONCLUSIONS: Our genome-wide association analyses and functional interaction network analysis reveal an enrichment of risk variants that function in an immunosuppressive regulatory network, likely hindering cancer immune surveillance and effective antitumour immunity.Christelle Adolphe, Angli Xue, Atefeh Taherian Fard, Laura A. Genovesi, Jian Yang and Brandon J. Wainwrigh

Benchmark problem definition and cross-validation for characteristic mode solvers

In October 2016, the Special Interest Group on Theory of Characteristic Modes (TCM) initiated a coordinated effort to perform benchmarking work for characteristic mode (CM) analysis. The primary purpose is to help improve the reliability and capability of existing CM solvers and to provide the means for validating future tools. Significant progress has already been made in this joint activity. In particular, this paper describes several benchmark problems that were defined and analyzes some results from the cross-validations of different CM solvers using these problems. The results show that despite differences in the implementation details, good agreement is observed in the calculated eigenvalues and eigencurrents across the solvers. Finally, it is concluded that future work should focus on understanding the impact of common parameters and output settings to further reduce variability in the results