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

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

Transcranial Magnetic Resonance Imaging-Guided Focused Ultrasound Treatment at 1.5 T: A Retrospective Study on Treatment- and Patient-Related Parameters Obtained From 52 Procedures

Objective: To present a retrospective analysis of patient- and sonication-related parameters of a group of patients treated with a transcranial magnetic resonance imaging (MRI)-guided focused ultrasound (tcMRgFUS) system integrated with a 1.5-T MRI unit. Methods: The data obtained from 59 patients, who underwent the tcMRgFUS procedure from January 2015 to April 2019, were retrospectively reviewed for this study. The following data, among others, were mainly collected: skull density ratio (SDR), skull area (SA), number of available transducer elements (Tx), and estimated focal power at target (FP). For each of the four different treatment stages, we calculated the number of sonication processes (S-n), user-defined sonication power (S-p), effective measured power (S-mp), sonication duration (S-d), user-defined energy (E), effective measured energy (E-m), maximum temperature (T-max), and MR thermometry plane orientation. Furthermore, the time delay between each sonication (S-t) and the total treatment time (T-t) were recorded. Results: Fifty-two patients (40 males and 12 females; age 64.51 +/- SD 11.90 years; range 26-86 years), who underwent unilateral Vim thalamotomy (left = 50, 96.15%; right = 2, 3.85%) for medication-refractory essential tremor (n = 39; 78%) or Parkinson tremor (n = 13; 22%) were considered. A total of 1,068 (95.10%) sonication processes were included in our final analysis (average S-n per treatment: 20.65 +/- 6.18; range 13-41). The energy released onto the planned target was found to decrease with the SDR for all temperature ranges. A positive correlation was observed between the slope of T-max vs. E-m plot and the SDR (R-2 = 0.765; p < 0.001). In addition, the T-max was positively correlated with SDR (R-2 = 0.398; p < 0.005). On the contrary, no significant correlation was found between SDR and SA or Tx. An analysis of the MR thermometry scanning plane indicated that, at our site, the axial and the coronal planes were used (on average) 10.4 (SD +/- 3.8) and 7.7 (SD +/- 3.0) times, respectively, whereas the sagittal plane was used only 2.5 (SD +/- 3.0) times per treatment. Conclusion: Our results confirm the factors that significantly influence the course of a tcMRgFUS procedure even when a 1.5-T MRI scanner is used for procedure guidance. The experience we gained in this study indicates that the SDR remains one of the most significant technical parameters to be considered in a tcMRgFUS procedure. The possibility of prospectively setting the sonication energy according to the presented curves of energy delivery as a function of SDR for each treatment stage could provide a further understanding and a greater awareness of this emerging technology

Application of benchtop total-reflection X-ray fluorescence spectrometry and chemometrics in classification of origin and type of Croatian wines

The contents of selected metals (K, Ca, Fe, Cu, Zn, Mn, Sr, Rb, Ba, Pb, Ni, Cr and V) in 70 wine samples from Continental and Adriatic part of Croatia and different types of wine (red and white) were determined by TXRF. The aim of this study was to compare the elemental composition of wines from two different regions and to determine the discriminant ability of each variable and to indicate which variables discriminate between the four categories considered. Principal component analysis and cluster analysis showed that K, Mn, Ba and Ni can be considered as the most important characteristics to distinguish between Continental red and white wines, Rb, Ni and Ba for Continental red and Adriatic red wines while Sr is the only metal that completely distinguishes the samples of each category. Finally, linear discriminant analysis showed good recognition (100%) and prediction abilities (96.43%) using these selected elements

Model for eukaryotic tail-anchored protein binding based on the structure of Get3

The Get3 ATPase directs the delivery of tail-anchored (TA) proteins to the endoplasmic reticulum (ER). TA-proteins are characterized by having a single transmembrane helix (TM) at their extreme C terminus and include many essential proteins, such as SNAREs, apoptosis factors, and protein translocation components. These proteins cannot follow the SRP-dependent co-translational pathway that typifies most integral membrane proteins; instead, post-translationally, these proteins are recognized and bound by Get3 then delivered to the ER in the ATP dependent Get pathway. To elucidate a molecular mechanism for TA protein binding by Get3 we have determined three crystal structures in apo and ADP forms from Saccharomyces cerevisae (ScGet3-apo) and Aspergillus fumigatus (AfGet3-apo and AfGet3-ADP). Using structural information, we generated mutants to confirm important interfaces and essential residues. These results point to a model of how Get3 couples ATP hydrolysis to the binding and release of TA-proteins

Targeting and Function of the Mitochondrial Fission Factor GDAP1 Are Dependent on Its Tail-Anchor

Proteins controlling mitochondrial dynamics are often targeted to and anchored into the mitochondrial outer membrane (MOM) by their carboxyl-terminal tail-anchor domain (TA). However, it is not known whether the TA modulates protein function. GDAP1 is a mitochondrial fission factor with two neighboring hydrophobic domains each flanked by basic amino acids (aa). Here we define GDAP1 as TA MOM protein. GDAP1 carries a single transmembrane domain (TMD) that is, together with the adjacent basic aa, critical for MOM targeting. The flanking N-terminal region containing the other hydrophobic domain is located in the cytoplasm. TMD sequence, length, and high hydrophobicity do not influence GDAP1 fission function if MOM targeting is maintained. The basic aa bordering the TMD in the cytoplasm, however, are required for both targeting of GDAP1 as part of the TA and GDAP1-mediated fission. Thus, this GDAP1 region contains critical overlapping motifs defining intracellular targeting by the TA concomitant with functional aspects

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