Systematic design of transmission-type polarization converters comprising multilayered anisotropic metasurfaces

A simple but efficient approach for the synthesis of transmission-type wideband polarization converters is presented. The proposed configuration comprises multilayer metasurfaces including resonant particles that are progressively rotated layer by layer. The progressive rotation of the particles allows for a polarization conversion over a large frequency band. The polarizing structure is efficiently designed and optimized through a transmission-line-model approach handling the cascade of anisotropic impedance layers and dielectrics. An optimized eight-layer design based on gradually rotated dipole resonators is presented as a proof of concept. The results obtained through the efficient transmission-line model are compared with full-wave simulations once the structure is optimized, showing satisfactory agreement. A prototype of the wideband polarization converter is fabricated and measured

A Simple Equivalent Circuit Approach for Anisotropic Frequency-Selective Surfaces and Metasurfaces

An equivalent circuit (EC) model for the frequency-selective surfaces (FSSs) comprising anisotropic elements is presented. The periodic surface is initially simulated with an arbitrary azimuthal incidence angle, and its surface impedance matrix is derived. The impedance matrix is subsequently rotated by an angle φrot on the crystal axes χ1 and χ2, thus nullifying its extra diagonal terms. The rotation angle φrot is derived according to the spectral theorem by using the terms of the matrix initially extracted. The diagonal terms of the rotated matrix, that is, the impedances Zχ1 and Zχ2, are finally matched with the simple LC networks. The circuit model representation of the anisotropic element can be used to analyze the anisotropic FSSs rotated by a generic azimuth angle. The methodology provides a compact description of the generic FSS elements with only five parameters: The lumped parameters of the LC network Lχ1, Cχ1, Lχ2, Cχ2 and the rotation angle φrot. The circuit model can consider the presence of the dielectric substrates close to the FSS or a variation in the FSS periodicity without additional computational efforts. The EC model is finally applied to the design of the two transmitting polarization converters based on the anisotropic metasurfaces

Elemental analysis of particulate matter by X-ray fluorescence methods: A green approach to air quality monitoring

This review explores X-ray fluorescence (XRF) spectrometry for elemental analysis of particulate matter (PM) for air quality monitoring. The introduction presents PM classification based on size and composition, covering various elemental analysis methods while highlighting the increasing interest in XRF due to its non-destructive, rapid, and green features. The fundamental concepts of XRF and the experimental configurations commonly used are discussed, focusing on Energy Dispersive X-Ray Fluorescence (EDXRF) and Total Reflection X-Ray Fluorescence (TXRF). PM sampling devices and substrate are described, with a specific emphasis on filtering membranes for EDXRF and reflecting substrates for TXRF. Sample preparation strategies and procedures are presented. Qualitative and quantitative analysis is described, with a particular focus on the calibration approaches implemented for PM. Finally, the challenges faced by XRF in becoming a recognized reliable analytical technique for PM analysis, comparable to other standardized techniques for PM filters analysis, while capitalizing on its green advantages

Radar Cross Section of Chipless RFID tags and BER Performance

The performance of different chipless RFID tag topologies are analysed in terms of Radar Cross Section (RCS) and Bit Error Rate (BER). It is shown that the BER is mainly determined by the tag Radar Cross Section (RCS) once that a standard reading scenario is considered and a fixed size of the tag is chosen. It is shown that the arrangement of the resonators in the chipless tag plays a crucial role in determining the cross-polar RCS of the tag. The RCS of the tag is computed theoretically by using array theory where each resonator is treated as a separate scatterer completely characterized by a specific reflection coefficient. Several resonators arrangements (periodic and non-periodic) are compared, keeping the physical area of the tag fixed. Theoretical and experimental analysis demonstrate that the periodic configuration guarantees the maximum achievable RCS thus providing a global lower BER of the chipless RFID communication system. We believe that the BER is the more meaningful and fair figure of merit for comparing the performance of different tags than bt/cm2 or bt/Hz since the increase of encoded information of the tag is useful only if it can be correctly decoded

Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples

Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-validation strategies (CV) for evaluating the ML predictive model performances with not so large datasets. We carried out two classification tasks: histology classification (3 classes) and overall stage classification (two classes: stage I and II). In the first task, the best performance was obtained by a Random Forest classifier, once the analysis has been restricted to stage I and II tumors of the Lung1 and L-RT merged dataset (AUC = 0.72 ± 0.11). For the overall stage classification, the best results were obtained when training on Lung1 and testing of L-RT dataset (AUC = 0.72 ± 0.04 for Random Forest and AUC = 0.84 ± 0.03 for linear-kernel Support Vector Machine). According to the classification task to be accomplished and to the heterogeneity of the available dataset(s), different CV strategies have to be explored and compared to make a robust assessment of the potential of a predictive model based on radiomics and ML

Bidirectional KCNQ1:β-catenin interaction drives colorectal cancer cell differentiation.

The K+ channel KCNQ1 has been proposed as a tumor suppressor in colorectal cancer (CRC). We investigated the molecular mechanisms regulating KCNQ1:β-catenin bidirectional interactions and their effects on CRC differentiation, proliferation, and invasion. Molecular and pharmacologic approaches were used to determine the influence of KCNQ1 expression on the Wnt/β-catenin signaling and epithelial-to-mesenchymal transition (EMT) in human CRC cell lines of varying stages of differentiation. The expression of KCNQ1 was lost with increasing mesenchymal phenotype in poorly differentiated CRC cell lines as a consequence of repression of the KCNQ1 promoter by β-catenin:T-cell factor (TCF)-4. In welldifferentiated epithelial CRC cell lines, KCNQ1 was localized to the plasma membrane in a complex with β-catenin and E-cadherin. The colocalization of KCNQ1 with adherens junction proteins was lost with increasing EMT phenotype. ShRNA knock-down of KCNQ1 caused a relocalization of β-catenin from the plasma membrane and a loss of epithelial phenotype in CRC spheroids. Overexpression of KCNQ1 trapped β-catenin at the plasma membrane, induced a patent lumen in CRC spheroids, and slowed CRC cell invasion. The KCNQ1 ion channel inhibitor chromanol 293B caused membrane depolarization, redistribution of β-catenin into the cytosol, and a reduced transepithelial electrical resistance, and stimulated CRC cell proliferation. Analysis of human primary CRC tumor patient databases showed a positive correlation between KCNQ1:KCNE3 channel complex expression and disease-free survival. We conclude that the KCNQ1 ion channel is a target gene and regulator of the Wnt/β-catenin pathway, and its repression leads to CRC cell proliferation, EMT, and tumorigenesis