Miracle-dz/UniFAR-FTUs huggingface dataset:
How to Express Hail Intensity—Modeling the Hailstone Size Distribution

The local intensity of hail can be expressed by a variety of variables, such as hail kinetic energy, maximum hailstone size, and radar reflectivity–driven algorithms. All of these variables are connected by the hailstone size distribution. In the United States, the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) provides more than 37 000 observations that describe the diameter of the smallest, average, and largest hailstone; duration of hail; and overall hailstone number density. We use these data and the assumption of an exponential hailstone size distribution aloft to model the rate of hailstones hitting the ground per unit area, time, and hailstone size bin during the passage of a hailstorm. We found that total hail kinetic energy is proportional to the diameter of the largest hailstone to a power of less than 2. To validate these results, we compared them with hailpad observations of the largest hailstone diameters and hail kinetic energies in southwestern France. As an example application, we calculate the probability mass function for the largest hailstone observed by a hailpad given the largest hailstone occurring in its vicinity. We use this model at Risk Management Solutions, Ltd. (RMS), to calculate the vulnerability of subjects at risk as a function of the diameter of the largest hailstone.
Implicit common‐mode resonance by parasitic capacitances in LC oscillators for Ka‐band satellite receiver

Parasitic capacitances in high frequency have a significant role in examining the inductor-capacitor tank oscillators (LC oscillators) output signal quality. Here, the authors proposed a new idea for Ka-band satellite receiver oscillator, which considers these parasitic elements, in order to maintain a specific precise frequency where there is no need for a broadband frequency range. By using tuned parasitic elements in differential LC oscillator to resonate the circuit's common mode at twice the oscillation frequency, a better phase noise performance and higher oscillator FOM can be achieved. The developed methodology is employed to design and fabricate an oscillator in 0.25 µm AlGaAs/InGaAs pseudomorphic high-electron-mobility transistors process for 19.25 GHz oscillations.
Vertical β‐Ga2O3 Schottky Barrier Diodes with Enhanced Breakdown Voltage and High Switching Performance

Herein, vertical Schottky barrier diodes (SBDs) based on a bulk β‐Ga2O3 substrate are developed. The devices feature an ion‐implanted planar edge termination (ET) structure, which can effectively smoothen the electric field peak and reduce the electric field crowding at the Schottky junction edge. Greatly enhanced reverse blocking characteristics including ≈103× lower reverse leakage current and 1.5× higher breakdown voltage (VB) are achieved, whereas good forward conduction such as a reasonably high on‐state current density and near‐unity ideality factor is maintained. In addition, the switching performance of the fabricated vertical β‐Ga2O3 SBDs is investigated using a double‐pulse test circuit. When switching from an on‐state current of 350 mA to a reverse‐blocking voltage of −100 V, the vertical β‐Ga2O3 SBDs exhibit fast reverse recovery with a reverse recovery time (trr) of ≈14.1 ns and reverse recovery charge (Qrr) of ≈0.34 nC, outperforming the Si fast recovery diode (FRD) of similar ratings. The results indicate a great promise of vertical β‐Ga2O3 SBDs for high‐voltage fast switching applications.
Eigenvalue Analysis of System Dynamics Models: Another Perspective

Previous work related to eigenvalue analysis in the system dynamics field has primarily focused on linking the model structure to the modes of behavior -i.e. the eigenvalues. While the system eigenvalues define the characteristics of the system’s behavior modes (e.g., exponential growth, expanding oscillations), these behavior modes are not equally represented in all model variables, making it difficult to link the behavior of the behavior mode to the behavior of a particular variable. In this study we propose an alternative perspective and explicitly explore the significance that each behavior mode has on the system state variables. We achieve this by decomposing the behavior of a variable into a sum of the weighted behavior modes in the system (represented by the eigenvalues). We argue that focusing on the weights, rather than on the eigenvalues, is a more efficient way to develop policy recommendations and compute the elasticity of the weights to the gain on any link the model allowing for a more efficient and discriminate way to identify policies. A routine to estimate the weights of any linear model and compute the elasticity of those weights to model links is developed and made available at http://iops.tamu. edu/faculty/roliva/research/sd/.
Computational Investigation of the Effective Mechanical Behavior for 3D Pre-Buckled Auxetic Lattices

Negative Poisson’s ratio materials, or auxetics, have drawn attention for the past 30 years. The auxetic effect could lead to improved mechanical properties such as acoustic damping, indentation resistance, or crashworthiness. In this work, two 3D auxetic lattices are introduced. Auxeticity is achieved by design through pre-buckling of the lattice struts. The influence of geometrical parameters on the effective elastic properties is investigated using computational homogenization method with periodic boundary conditions. Effective Young’s modulus is 3D mapped to reveal anisotropy and identify spatial orientations of interest. The effective Poisson ratio is computed for various geometric configurations to characterize auxeticity. Finally, the influence of effective elastic properties on energy dissipation under compression is explored for elastoplastic lattices with different loading directions, using finite element simulations. Results suggest that loading 3D auxetic lattices along their stiffest direction maximizes their crashworthiness.
Alpha Adjacency: A generalization of adjacency matrices

B. Shader and W. So introduced the idea of the skew adjacency matrix. Their idea was to give an orientation to a simple undirected graph G from which a skew adjacency matrix S(G) is created. The -adjacency matrix extends this idea to an arbitrary field F. To study the underlying undirected graph, the average -characteristic polynomial can be created by averaging the characteristic polynomials over all the possible orientations. In particular, a Harary-Sachs theorem for the average-characteristic polynomial is derived and used to determine a few features of the graph from the average-characteristic polynomial.
Hyperspectral Image Classification Based on Two-Phase Relation Learning Network

Deep learning-based classification methods are competent to achieve an excellent performance under one necessary condition, i.e., there are sufficient labeled samples in each class, which is extremely impractical in most of the remote sensing tasks. To improve the performance with small training sets, we resort to other hyperspectral images and design a two-phase relation learning network that can be transferred between different images for general information sharing and fine-trained on a specific hyperspectral image for individual information learning. Specifically, we use a relation learning method to compare samples and deal with the task inconsistency between different data sets, and we adopt an episode-based training strategy to mimic the testing setup and learn the transferable comparison ability. Benefited from these two strategies, the proposed network takes the advantage of extra knowledge for information supplement and learns to compare rather than to classify for information exploration, which guarantees a reasonable performance even with small training sets. Extensive experiments and analysis on three benchmarks demonstrate that the proposed method can provide an effective solution for hyperspectral image classification with small training sets, which makes it possible to work on large-scale applications of earth observation with less effort on field investigation.
On continuum damage mechanics

A material containing spherical microvoids with a Hookean matrix response was shown to take the appearance usually applied in continuum damage mechanics. However, the commonly used variable damage D was replaced with the void volume fraction f , which has a clear physical meaning, and the elastic strain tensor \Bold {ε}^e with the damage-elastic strain tensor \Bold {ε}^{de}. The postulate of strain equivalence with the effective stress concept was reformulated and applied to a case where the response of the matrix obeys Hooke’s law. In contrast to many other studies, in the derived relation between the effective stress tensor \Bold {\Tilde{σ}} and the stress tensor \Bold {σ}, the tensor \Bold {\Tilde{σ}} is symmetric. A uniaxial bar model was introduce for clarifying the derived results. Other candidates for damage were demonstrated by studying the effect of carbide coarsening on creep rate.
Learning to Mitigate the FAR in Polar Code Blind Detection

Polar codes have been adopted as the coding scheme for control channels in the 5G communication system, where the blind detection is required. In this letter, to mitigate the false-alarm rate (FAR) in the polar code blind detection, we propose a more efficient architecture which combines the conventional list decoding and a binary classifier. After the list decoding, the CRC-passing result will be further checked by the classifier to determine whether the received signal is the intended control information or not. The classifier works by inspecting the squared Euclidean distance ratio (SEDR) between the received signal and the hypotheses, and the decision threshold used in the classifier is automatically learnt by a neural network (NN). The presented results show that very short CRC sequences can be enough to reach the target FAR, and this CRC overhead reduction finally contributes to the performance improvement of polar codes.
Design and Demonstration of an Adiabatic-Quantum-Flux-Parametron Field-Programmable Gate Array Using Josephson-CMOS Hybrid Memories

Adiabatic quantum-flux-parametron (AQFP) logic is a promising technology for future energy-efficient high-performance information processing systems. Its static power is zero because of ac flux bias, and its dynamic power is considerably reduced, thanks to the adiabatic switching of the junctions. The lack of high-density memories in the AQFP logic, however, makes it challenging to realize large-scale information processing systems with the use of pure AQFP circuits. We have been developing a Josephson-CMOS hybrid memory to overcome the memory bottleneck in AQFP digital systems. By utilizing the high sensitivity of the AQFP gate, the output current from CMOS memories can be significantly decreased resulting in the reduction of the power consumption. In this article, we designed and fabricated a low-power area-efficient AQFP-CMOS hybrid field-programmable gate array (FPGA), where a CMOS memory is utilized as a rewritable read-only memory to control the AQFP circuits. The AQFP circuit for the AQFP-CMOS hybrid FPGA is composed of logic blocks, switch blocks, and connection blocks, which are clocked by four-phase excitation currents. The AQFP-CMOS hybrid FPGA is fabricated by using the AIST 10 kA/cm2 Nb high-speed standard process and the Rohm 0.18 μm CMOS process. The area and power consumption of the two-by-two AQFP logic-cell system are estimated to be approximately 6.56 mm2 and 12.4 nW at 5 GHz operations, respectively. The power consumption of the CMOS memory was estimated to be 1.02 μW assuming the CMOS source voltage of 3 mV. We demonstrated the operation of the AQFP-CMOS hybrid FPGA at low speed by combining the AQFP logic and the CMOS memory.
Generation of collocation points in the method of fundamental solutions for 2D Laplace's equation

We propose a new method for generating collocation points that give an accurate approximation in the method of fundamental solutions (MFS). It is known that collocation points that maximize the determinant of the coefficient matrix of the linear system in the MFS give an accurate approximation. However, the maximization problem is intractable. We design an efficient algorithm to automatically take collocation points that do not depend on a boundary condition. Numerical experiments show that the proposed collocation points give a better condition number and an accurate approximation when we use source points far from the boundary.
Development of HPC multiphysics framework for HTS magnets in fusion

High-Temperature Superconductors (HTS) technology show promise for the next generation of fusion devices based on magnetic confinement, enabling higher magnetic fields and current densities, and thus a reduction of overall sizes and running costs due to lower heat load in the cryogenic system. Nevertheless, the use of HTS materials presents some drawbacks concerning quench protection and mechanical stability so that the application in large scale fusion magnets requires the detailed assessment of their thermal, electromagnetic (EM) and mechanical behavior. Computer modeling has played an important role to date in the design of superconducting magnets, but due to the lack of specific tools and to the inherent complexity of such structures, it is often needed either to study the involved phenomena separately or to simulate coupled multiphysics problems on rather simple geometries and models. Our goal is therefore to provide a new High Performance Computing (HPC) unified framework for the multiphysics simulation of HTS devices. The development is intended to build on an existing HPC multiphysics tool and will enable in the near future the design of the most suitable architectures of HTS cables for fusion applications considering mechanical robustness, losses, and quench propagation, detection and protection.
Prediction of parturition and dystocia in Holstein-Friesian cattle, and cesarean section in dystocic beef cattle

Hiew, Wen Han Mark. Ph.D., Purdue University, December 2014. Prediction of Parturition and Dystocia in Holstein-Friesian Cattle, and Cesarean Section in Dystocic Beef Cattle. Major Professor: Peter D. Constable. Dystocia is a major problem in the dairy industry as it causes livestock and economic loss. It is more frequently seen in primiparous cattle compared to their multiparous counterparts due to their smaller stature and the slow maturation of pelvic dimensions. In some instances, human intervention of the parturition process is imperative to avoid pain, injury, and mortality of the neonate and the dam. The ability to accurately predict dystocia and the time of parturition will ensure that timely assistance can be given to animals that are of high risk of dystocia. The present thesis contains four studies that explore methods to predict dystocia and the time of parturition as well as factors that influence the presentation and outcome of cesarean sections. The first study, presented in chapter three, evaluated the clinical utility of measuring the circumference of the calf front and maternal intrapelvic dimensions to predict the incidence of dystocia in late gestation Holstein-Friesian cattle. The ratio of the calf hoof circumference to the maternal intrapelvic area was identified to have clinical utility in predicting the calving difficulty score. The second study, presented in chapter four, assessed the changes in plasma progesterone concentration, rectal temperature, sacrosciatic ligament relaxation, and feed intake to predict the time of parturition in dairy cattle. Results indicated that plasma progesterone concentration had the highest accuracy in predicting the time of parturition. The third study,
Graphene-coated resonators with frequency-selective super-scattering and super-cloaking

Comb-like behavior of the multilayered graphene wrapped nanotubes in multiple scattering channels is investigated and utilized to design a structure for simultaneous super-scattering and super-cloaking. The underlying physics of the proposed structure is studied quantitatively by geometric interpretation through the associated planar structure based on the Bohr model and Foster’s theorem. We observed that due to the presence of multiple dispersion bands in the planar counterpart, each cylindrical scattering Mie coefficient fulfills the resonance and invisibility conditions multiple times, depending on the selected number of layers. By refining the material and geometric parameters for the specified number of layers, resonances and zeros of the first two scattering terms are coincided simultaneously to observe super-scattering and super-cloaking, respectively. The proposed structure has lots of degrees of freedom to control the response in the operating frequency.
Metamodel‐based robust simulation‐optimization assisted optimal design of multiloop integer and fractional‐order PID controller

Classical proportional‐integral‐derivative (PID) tuning methods such as Ziegler‐Nichols simply increase robustness against disturbances that may arise from the load. Thus, uncertainty in the load parameters has generally not been considered in previous methods, and tuning has been done only in fixed and under certain conditions. Moreover, when one or more load parameters are changed, the best previous results for the PID controller lose their validity and need to be adjusted according to the change in those load parameters. In such case, finding an optimal design for a PID controller might be too inefficient in terms of computational time and cost. This paper aims at proposing a new less time‐consuming method for tuning of a multiloop PID controller for robustness when the output of the model is varying due to the changeability of load parameters in multiple subsystems as a source of variability. Kriging and radial basis function (RBF) metamodels as two common global approximation models together with the Latin hypercube sampling (LHS) method are used to fit input‐output models with the least number of running computer experiments. Robust design terminology in the class of dual response is applied to design a multi‐input multi‐output (MIMO) mathematical programming model under disturbance factors. A MIMO numerical case in tuning a multiloop PID controller, proportional‐integral (PI) controller, and fractional‐order PID (FOPID) controller for speed control of a DC motor is provided as an example to show the flexibility and applicability of the proposed method.
Multiwavelength excitation Raman scattering study of Sb2Se3 compound: fundamental vibrational properties and secondary phases detection

This work presents a complete analysis of Raman active modes of Sb2Se3 measured by six different excitation wavelengths from NIR to UV, under different polarization configurations and at low temperature. Simultaneous fitting of spectra allowed the deconvolution and identification of the 28 Raman peaks obtained in monocrystalline Sb2Se3 sample from the 30 modes predicted by the group theory analysis for this crystalline structure. Analysis of the spectra measured under different polarization configurations yielded the preliminary assignment of the peaks symmetry, while the measurements under low temperature resulted in a fine resolution of the peaks in Raman spectra. Additionally, evaluation of the spectra of the most probable secondary phases under different excitation wavelengths allowed to define the most appropriate measurement conditions for experimental discrimination of their Raman peaks in the spectra of Sb2Se3 based thin films solar cells. The combination of different wavelength allows a non-destructive methodology for high sensitivity detection of main secondary phases of the Sb2Se3.
Development of a 1.8mm Percutaneous Applicator with Closed Cycle Cooking for Microwave Tumour Ablation

This thesis reports the development of a novel microwave ablation system for tumour destruction. In addition, a computer model simulating the electromagnetic and thermal behaviour of the designed microwave applicator is presented. Concerning the microwave ablation system development, novelty is seen in four aspects of the work: rstly, in the design of a new percutaneous microwave applicator of 1.8 mm diameter; secondly, in the development of a novel closed-cycle cooling system for the microwave applicator and microwave applicator feed cable; thirdly, in the development of a novel integrated thermocouple as part of the applicator design; and lastly, in the design and development of the complete microwave ablation system consisting of applicator, feed cable and cooling system. Regarding the computer simulations of the developed microwave applicator, novelty is also seen in the de nition of new non-linear temperature-dependent material properties of ex-vivo bovine liver up to 300 ◦C which signi cantly improved the accuracy of the simulation. Figure 1 displays the latest version of the applicator developed within the scope of this thesis which is currently being developed into a commercial product by Acculis Limited and Runfold Medical Limited. Figure 1: Latest version of 1.8 mm percutaneous microwave applicator with internal closed-cycle cooling system developed as part of a microwave ablation system within the scope of this thesis.
Experimental efforts in search of 76Ge Neutrinoless Double Beta Decay

Neutrinoless double beta decay is one of the most sensitive approaches in non-accelerator particle physics to take us into a regime of physics beyond the standard model. This article is a brief review of the experiments in search of neutrinoless double beta decay from 76Ge. Following a brief introduction of the process of double beta decay from 76Ge, the results of the very first experiments IGEX and Heidelberg-Moscow which give indications of the existence of possible neutrinoless double beta decay mode has been reviewed. Then ongoing efforts to substantiate the early findings are presented and the Majorana experiment as a future experimental approach which will allow a very detailed study of the neutrinoless decay mode is discussed.
Bipolar fuzzy soft mappings with application to bipolar disorders

Bipolar disorder is a neurological disorder that consists of two main factors, i.e. mania and depression. There are two main drawbacks in clinical diagnosis of the bipolar disorder. First, bipolar disorder is mostly wrongly diagnosed as unipolar depression in clinical diagnosis. This is, because in clinical diagnosis, the first factor is often neglected due to its approach toward positivity. Consequently, the element of bipolarity vanishes and the disease becomes worse. Second, the types of bipolar disorder are mostly misdiagnosed due to similar symptoms. To overcome these problems, the bipolar fuzzy soft set (BFS-set) and bipolar fuzzy soft mappings (BFS-mappings) are useful to tackle bipolarity and to construct a strong mathematical modeling process to diagnose this disease correctly. This technique is extensive but simple as compared to existing medical diagnosis methods. A chart (relation between different types and symptoms of bipolar disorder) is provided which contains different ranges over the interval [Formula: see text]. A process of BFS-mappings is also provided to obtain correct diagnosis and to suggest the best treatment. Lastly, a generalized BFS-mapping is introduced which is helpful to keep patient’s improvement record. The case study indicates the reliability, efficiency and capability of the achieved theoretical results. Further, it reveals that the connection of soft set with bipolar fuzzy set is fruitful to construct a connection between symptoms which minimize the complexity of the case study.