Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics

Cassava as a world food security crop still suffers from an inadequate means to measure early storage root bulking (ESRB), a trait that describes early maturity and a key characteristic of improved cassava varieties. The objective of this study is to evaluate the capability of ground penetrating radar (GPR) for non-destructive assessment of cassava root biomass. GPR was evaluated for this purpose in a field trial conducted in Ibadan, Nigeria. Different methods of processing the GPR radargram were tested, which included time slicing the radargram below the antenna surface in order to reduce ground clutter; to remove coherent sub-horizontal reflected energy; and having the diffracted energy tail collapsed into representative point of origin. GPR features were then extracted using Discrete Fourier Transformation (DFT), and Bayesian Ridge Regression (BRR) models were developed considering one, two and three-way interactions. Prediction accuracies based on Pearson correlation coefficient (r) and coefficient of determination (R2) were estimated by the linear regression of the predicted and observed root biomass. A simple model without interaction produced the best prediction accuracy of r = 0.64 and R2 = 0.41. Our results demonstrate that root biomass can be predicted using GPR and it is expected that the technology will be adopted by cassava breeding programs for selecting early stage root bulking during the crop growth season as a novel method to dramatically increase crop yield.

Mathematical modeling of signals, linear links and responses of telecommunications and radioelectronics systems in time domain

A single mathematical model of time characteristics of signals, links and responses of telecommunications and radioelectronics systems is suggested. It embodies Dirac- and Heaviside responses of all types of linear links, as well as their responses to the input in the form of periodic signals, no periodic finite and no periodic eternal signals. On the basis of the suggested model the algorithm for calculation of time characteristics was developed, which allows creation of effective automated simulations procedure of signals, links and responses in time-domain. The comparative quantitative analysis of accuracy of the suggested algorithm and discrete Fourier transformation (DFT) algorithm was carried out.

All-optical synthesis of an arbitrary linear transformation using diffractive surfaces

Spatially-engineered diffractive surfaces have emerged as a powerful framework to control light-matter interactions for statistical inference and the design of task-specific optical components. Here, we report the design of diffractive surfaces to all-optically perform arbitrary complex-valued linear transformations between an input (Ni) and output (No), where Ni and No represent the number of pixels at the input and output fields-of-view (FOVs), respectively. First, we consider a single diffractive surface and use a matrix pseudoinverse-based method to determine the complex-valued transmission coefficients of the diffractive features/neurons to all-optically perform a desired/target linear transformation. In addition to this data-free design approach, we also consider a deep learning-based design method to optimize the transmission coefficients of diffractive surfaces by using examples of input/output fields corresponding to the target transformation. We compared the all-optical transformation errors and diffraction efficiencies achieved using data-free designs as well as data-driven (deep learning-based) diffractive designs to all-optically perform (i) arbitrarily-chosen complex-valued transformations including unitary, nonunitary, and noninvertible transforms, (ii) 2D discrete Fourier transformation, (iii) arbitrary 2D permutation operations, and (iv) high-pass filtered coherent imaging. Our analyses reveal that if the total number (N) of spatially-engineered diffractive features/neurons is ≥Ni × No, both design methods succeed in all-optical implementation of the target transformation, achieving negligible error. However, compared to data-free designs, deep learning-based diffractive designs are found to achieve significantly larger diffraction efficiencies for a given N and their all-optical transformations are more accurate for N < Ni × No. These conclusions are generally applicable to various optical processors that employ spatially-engineered diffractive surfaces.

Differences and similarities between precipitation patterns of different climates

In recent years water-related issues are increasing globally, some researchers even argue that the global hydrological cycle is accelerating, while the number of meteorological extremities is growing. With the help of large number of available measured data, these changes can be examined with advanced mathematical methods. In the outlined research we were able to collect long precipitation datasets from two different climatical regions, one sample area being Ecuador, the other one being Kenya. Using the methodology of spectral analysis based on the discrete Fourier-transformation, several deterministic components were calculated locally in the otherwise stochastic time series, while by the comparison of the results, also with previous calculations from Hungary, several global precipitation cycles were defined in the time interval between 1980 and 2019. The results of these calculations, the described local, regional, and global precipitation cycles can be a helpful tool for groundwater management, as precipitation is the major resource of groundwater recharge, as well as with the help of these deterministic cycles, precipitation forecasts can be delivered for the areas.

Value of cardiac magnetic resonance imaging derived spectral myocardial strain pattern for non-invasive diagnosis of myocarditis

Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Society of Radiology European Institute for Biomedical Imaging Research Background Traditionally, cardiac function is quantified by measures of peak excursion, for example ejection fraction. However, myocardial strain estimation from cine- cardiac MRI allows quantification of cardiac motion over the whole heart cycle. We propose a spectral decomposition of the strain curves applying Discrete Fourier transformation (DFT). Purpose To evaluate a potential additive diagnostic value of spectral temporal strain curve quantification for non-invasive diagnosis of myocarditis using cardiac MRI. Methods In the single-center prospective study patients with suspected myocarditis underwent comprehensive cardiac MRI followed by biventricular endomyocardial biopsy (EMB) between 2012 and 2014. DFT was applied to myocardial strain curves extracted from cine-Images. As reference model, a L1- and L2-penalized logistic regression model using global native T1 time, T2 time and presence of late-gadolinium enhancement was trained to predict EMB results and compared to two models which additionally include three orders of DFT coefficients and ejection fraction, respectively. Predictive performance was evaluated in a tournament-leave-pair-out cross-validation approach with a bootstrap correction for testing of multiple hyperparameter configurations. Results Out of 100 patients (28 % female, median age 40 [IQR 32 to 56) years) with acute symptom-onset (&lt;30 days) 65 had pathologically proven myocarditis in EMB. The DFT model showed best discrimination (Area under the receiver-operating-curve [AUC] 0.72 [95% CI 52 to 87]). Addition of ejection fraction (AUC 0.60 [95% CI: 0.43 to 0.74]) did not increase AUC compared to the reference (AUC 0.60 [95% CI: 0.43 to 0.74]). Posterior distribution of the bootstrap-corrected AUC difference between DFT and reference model was gaussian (mean 12%, standard deviation 12%) with a posterior probability of 86%, that DFT has a greater AUC. Conclusions Discrimination of myocarditis from similar clinical presentations remains challenging. The results support incremental discriminatory value of DFT-decomposed myocardial strain for non-invasive diagnosis of myocarditis. Future research should address the value of the spectral decomposition of cardiac motion trajectories in larger samples and different disease entities.

Rattle dynamics of noncircular face gear under multifrequency parametric excitation

A noncircular face gear (NFG) conjugated with a pinion is a new type of face gear which can transmit variable velocity ratio and in which two time-varying excitations exist, namely the meshing stiffness excitation and instantaneous center excitation. Considering the tooth backlash, static transmission error and multifrequency parametric excitation, a nonlinear dynamic model of the NFG pair is presented. Based on the harmonic balance method and discrete Fourier transformation, a semi-analytic approach for the nonlinear dynamic model is given to analyze the dynamic behaviors of the NFG. Results demonstrate that, with increase in the eccentric ratio, input velocity and error amplitude, the NFG will undergo a non-rattle, unilateral rattle and bilateral rattle state in succession, and a jump phenomenon will appear in the dynamic responses when the rattle state of the gears is transformed from unilateral rattle to bilateral rattle.

Calculation of tonal rail circuits with consideration of a complicated waveform

The article deals with the problem of calculating modern audio frequency track circuits, the working signal of which is a frequency-manipulated signal transmitting Bauer codes. Such signals have a wide spectrum, which leads to the error in the calculations performed according to the classical method for a single frequency. Increasing the code transfer rate in order to reduce the response time of track circuits further expands the signal spectrum, which negatively affects the safety of such rail circuits. To determine the width and composition of the signal spectrum, a discrete Fourier transformation is used. The new method of calculating rail circuits proposed in this article allows us to determine the root-mean-square value of the signal at the output of the rail circuit with a known amplitude-frequency characteristic of the rail circuit and the form of a complex signal at the input. The obtained ratio of the root-mean-square signal levels at the input and output of the rail circuit allows us to solve the problem of calculating the operating modes of the rail circuit taking into account its nonlinear amplitude-frequency characteristics and taking into account the complex signal form, including consideration of the specific transmitted Bauer code. This solution allows you to increase the reliability of the calculation of the adjustment tables of the tonal track circuits and, as a result, increase the reliability and safety of their operation.