A comprehensive survey on 'circular polarized antennas' for existing and emerging wireless communication technologies

Circular polarized (CP) antennas are well suited for long-distance transmission attainment. In order to be adaptable for beyond 5G communication, a detailed and systematic investigation of their important conventional features is required for expected enhancements. The existing designs employing millimeter wave, microwave, and ultra-wideband (UWB) frequencies form the elementary platform for future studies. The 3.4-3.8 GHz frequency band has been identified as a worthy candidate for 5G communications because of spectrum availability. This band comes under UWB frequencies (3.1-10.6 GHz). In this survey, a review of CP antennas in the selected areas to improve the understanding of early-stage researchers specially experienced antenna designers has presented for the first time as best of our knowledge. Design implementations involving size, axial ratio, efficiency, and gain improvements are covered in detail. Besides that, various design approaches to realize CP antennas including (a) printed CP antennas based on parasitic or slotted elements, (b) dielectric resonator CP antennas, (c) reconfigurable CP antennas, (d) substrate integrated waveguide CP antennas, (e) fractal CP antennas, (f) hybrid techniques CP antennas, and (g) 3D printing CP antennas with single and multiple feeding structures have investigated and analyzed. The aim of this work is to provide necessary guidance for the selection of CP antenna geometries in terms of the required dimensions, available bandwidth, gain, and useful materials for the integration and realization in future communication systems

A Comprehensive Survey on 'Various Decoupling Mechanisms with Focus on Metamaterial and Metasurface Principles Applicable to SAR and MIMO Antenna Systems'

Nowadays synthetic aperture radar (SAR) and multiple-input-multiple-output (MIMO) antenna systems with the capability to radiate waves in more than one pattern and polarization are playing a key role in modern telecommunication and radar systems. This is possible with the use of antenna arrays as they offer advantages of high gain and beamforming capability, which can be utilized for controlling radiation pattern for electromagnetic (EM) interference immunity in wireless systems. However, with the growing demand for compact array antennas, the physical footprint of the arrays needs to be smaller and the consequent of this is severe degradation in the performance of the array resulting from strong mutual-coupling and crosstalk effects between adjacent radiating elements. This review presents a detailed systematic and theoretical study of various mutual-coupling suppression (decoupling) techniques with a strong focus on metamaterial (MTM) and metasurface (MTS) approaches. While the performance of systems employing antenna arrays can be enhanced by calibrating out the interferences digitally, however it is more efficient to apply decoupling techniques at the antenna itself. Previously various simple and cost-effective approaches have been demonstrated to effectively suppress unwanted mutual-coupling in arrays. Such techniques include the use of defected ground structure (DGS), parasitic or slot element, dielectric resonator antenna (DRA), complementary split-ring resonators (CSRR), decoupling networks, P.I.N or varactor diodes, electromagnetic bandgap (EBG) structures, etc. In this review, it is shown that the mutual-coupling reduction methods inspired By MTM and MTS concepts can provide a higher level of isolation between neighbouring radiating elements using easily realizable and cost-effective decoupling configurations that have negligible consequence on the arrays characteristics such as bandwidth, gain and radiation efficiency, and physical footprint

Internet of Things in Agricultural Innovation and Security

The agricultural Internet of Things (Ag-IoT) paradigm has tremendous potential in transparent integration of underground soil sensing, farm machinery, and sensor-guided irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. The aim of the IoT in agricultural innovation and security chapter is to present agricultural IoT research and paradigm to promote sustainable production of safe, healthy, and profitable crop and animal agricultural products. This chapter covers the IoT platform to test optimized management strategies, engage farmer and industry groups, and investigate new and traditional technology drivers that will enhance resilience of the farmers to the socio-environmental changes. A review of state-of-the-art communication architectures and underlying sensing technologies and communication mechanisms is presented with coverage of recent advances in the theory and applications of wireless underground communications. Major challenges in Ag-IoT design and implementation are also discussed

Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations

The Optical TRApezoid Model (OPTRAM) has recently been proposed for estimation of soil moisture using only optical remote sensing data. The model relies on a physical linear relationship between the soil moisture content and shortwave infrared transformed reflectance (SIR) and can be parameterized universally (i.e., a single calibration for a given area) based on the pixel distribution within the STR-Normalized Difference Vegetation Index (NDVI) trapezoidal space. The main motivation for this study was to evaluate how the universal parameterization of OPTRAM works for long periods of time (e.g., several decades). This is especially relevant for uncovering the soil moisture and agricultural drought history in response to climate change in different regions. In this study, MODIS satellite observations from 2001 to 2017 were acquired and used for the analysis. Cosmic ray neutron (CRN) soil moisture data, collected with the Cosmic-ray Soil Moisture Observing System (COSMOS) at five different sites in the U.S. covering diverse climates, soil types, and land covers, were applied for evaluation of the MODIS-OPTRAM-based soil moisture estimates. The OPTRAM soil moisture estimates were further compared to the Soil Moisture Active and Passive (SMAP) (L-band), the Soil Moisture Ocean Salinity (SMOS) (L band), and the Advanced AScatterometer (ASCAT) (C-band) soil moisture retrievals. OPTRAM soil moisture data were also analyzed for potential monitoring of agricultural drought through comparison of the OPTRAM-based Soil Water Deficit Index (OPTRAM-SWDI) with the widely-applied Crop Moisture Index (CMI). Evaluation results indicate that OPTRAM-based soil moisture estimates provide overall unbiased RMSE and R between 0.050 and 0.085 cm(3) cm(-3) and 0.10 to 0.70, respectively, for all investigated sites. The performance of OPTRAM is comparable with the ASCAT retrievals, but slightly less accurate than SMAP and SMOS. OPTRAM and the three microvave satellites captured CRN soil moisture temporal dynamics very well for all five investigated sites. A close agreement was observed between the OPTRAM-SWDI and CMI drought indices for most selected sites. In conclusion, OPTRAM can estimate temporal soil moisture dynamics with reasonable accuracy for a range of climatic conditions (semi-arid to humid), soil types, and land covers, and can potentially be applied for agricultural drought monitoring.National Science Foundation (NSF) [1521469]; US National Science Foundation [ATM-0838491]24 month embargo; published online: 25 April 2018This 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]

Soil moisture prediction of bare soil profiles using diffuse spectral reflectance information and vadose zone flow modeling

Soil hydraulic property information of the vadose zone is key to quantifying the temporal and spatial variability of soil moisture, and for modeling water flow and contaminant transport processes in the near surface. This study deals with exploring the feasibility of using diffuse soil spectral information in the visible, near-infrared and shortwave infrared range (350–2500 nm) to estimate coarse-scale soil hydraulic parameters and predict soil moisture profiles using a topography-based aggregation scheme in conjunction with a 1D mechanistic water flow model. Three different types of parametric transfer functions (so-called spectrotransfer functions, STFs; pedotransfer functions, PTFs; and spectral pedotransfer functions, SPTFs) were aggregated from the point scale to 1 km2 pixel size. to provide coarse scale estimates of van Genuchten-Mualem (VGM) hydraulic parameters. The coarse scale hydraulic parameters were evaluated by simulating soil water dynamics of the 1 km2 pixels across the Zanjanrood River sub-watershed (ZRS) in northwest Iran. Resultant soil water states were compared with ground-truth measurements and advanced synthetic aperture radar (ASAR) estimates of soil water content. The topography-based aggregation scheme was found to provide effective values of the VGM hydraulic parameters across the ZRS study site. The coarse scale STFs performed best in terms of simulating surface, near-surface and subsurface soil water dynamics, followed by the coarse scale SPTFs and PTFs, which performed similarly. The average simulated soil water contents of the surface layer closely correlated with ASAR estimates during relatively wet periods. Simulated subsurface soil water dynamics matched well with the ground-truth measurements. These findings indicate the feasibility of using spectral data to predict VGM hydraulic parameters and, ultimately, to predict soil water dynamics at the larger scales

Soil moisture prediction of bare soil profiles using diffuse spectral reflectance information and vadose zone flow modeling

Soil hydraulic property information of the vadose zone is key to quantifying the temporal and spatial variability of soil moisture, and for modeling water flow and contaminant transport processes in the near surface. This study deals with exploring the feasibility of using diffuse soil spectral information in the visible, near-infrared and shortwave infrared range (350–2500 nm) to estimate coarse-scale soil hydraulic parameters and predict soil moisture profiles using a topography-based aggregation scheme in conjunction with a 1D mechanistic water flow model. Three different types of parametric transfer functions (so-called spectrotransfer functions, STFs; pedotransfer functions, PTFs; and spectral pedotransfer functions, SPTFs) were aggregated from the point scale to 1 km2 pixel size. to provide coarse scale estimates of van Genuchten-Mualem (VGM) hydraulic parameters. The coarse scale hydraulic parameters were evaluated by simulating soil water dynamics of the 1 km2 pixels across the Zanjanrood River sub-watershed (ZRS) in northwest Iran. Resultant soil water states were compared with ground-truth measurements and advanced synthetic aperture radar (ASAR) estimates of soil water content. The topography-based aggregation scheme was found to provide effective values of the VGM hydraulic parameters across the ZRS study site. The coarse scale STFs performed best in terms of simulating surface, near-surface and subsurface soil water dynamics, followed by the coarse scale SPTFs and PTFs, which performed similarly. The average simulated soil water contents of the surface layer closely correlated with ASAR estimates during relatively wet periods. Simulated subsurface soil water dynamics matched well with the ground-truth measurements. These findings indicate the feasibility of using spectral data to predict VGM hydraulic parameters and, ultimately, to predict soil water dynamics at the larger scales

Genome Wide Association Study Uncovers the QTLome for Osmotic Adjustment and Related Drought Adaptive Traits in Durum Wheat

Osmotic adjustment (OA) is a major component of drought resistance in crops. The genetic basis of OA in wheat and other crops remains largely unknown. In this study, 248 field-grown durum wheat elite accessions grown under well-watered conditions, underwent a progressively severe drought treatment started at heading. Leaf samples were collected at heading and 17 days later. The following traits were considered: flowering time (FT), leaf relative water content (RWC), osmotic potential (ψs), OA, chlorophyll content (SPAD), and leaf rolling (LR). The high variability (3.89-fold) in OA among drought-stressed accessions resulted in high repeatability of the trait (h2 = 72.3%). Notably, a high positive correlation (r = 0.78) between OA and RWC was found under severe drought conditions. A genome-wide association study (GWAS) revealed 15 significant QTLs (Quantitative Trait Loci) for OA (global R2 = 63.6%), as well as eight major QTL hotspots/clusters on chromosome arms 1BL, 2BL, 4AL, 5AL, 6AL, 6BL, and 7BS, where a higher OA capacity was positively associated with RWC and/or SPAD, and negatively with LR, indicating a beneficial effect of OA on the water status of the plant. The comparative analysis with the results of 15 previous field trials conducted under varying water regimes showed concurrent effects of five OA QTL cluster hotspots on normalized difference vegetation index (NDVI), thousand-kernel weight (TKW), and/or grain yield (GY). Gene content analysis of the cluster regions revealed the presence of several candidate genes, including bidi-rectional sugar transporter SWEET, rhomboid-like protein, and S-adenosyl-L-methionine-dependent methyltransferases superfamily protein, as well as DREB1. Our results support OA as a valuable proxy for marker-assisted selection (MAS) aimed at enhancing drought resistance in wheat. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.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]