Miracle-dz/UniFAR-FTUs huggingface dataset:
Power Efficiency Improvement of Three-Phase Split-Output Inverter Using Magnetically Coupled Inductor Switching

The conventional three-phase split-output inverter (SOI) has been used for grid-connected applications because it does not require dead time and has no shoot-through problems. Recently, the conventional inverter uses the silicon carbide (SiC) schottky diodes for the freewheeling diodes because of its no reverse-recovery problem. Nevertheless, in a practical design, the SiC schottky diodes suffer from current overshoots and voltage oscillations. These overshoots and oscillations result in switching-power losses, decreasing the power efficiency of the inverter. To alleviate this drawback, we present a three-phase SOI using magnetically coupled inductor switching technique. The magnetically coupled inductor switching technique uses one auxiliary diode and coupled inductor for each switching leg in the three-phase SOI. By the operation of the coupled inductor, the main diode current is shifted to the auxiliary diode without the reverse-recovery process. The proposed inverter reduces switching-power losses by alleviating current overshoots and voltage oscillations of SiC schottky diodes. It achieves higher power efficiency than the conventional inverter. We discuss experimental results for a 1.0 kW prototype inverter to verify the performance of the proposed inverter.
Three-Stage Estimation of the Mean and Variance of the Normal Distribution with Application to an Inverse Coefficient of Variation with Computer Simulation

This paper considers sequentially two main problems. First, we estimate both the mean and the variance of the normal distribution under a unified one decision framework using Hall’s three-stage procedure. We consider a minimum risk point estimation problem for the variance considering a squared-error loss function with linear sampling cost. Then we construct a confidence interval for the mean with a preassigned width and coverage probability. Second, as an application, we develop Fortran codes that tackle both the point estimation and confidence interval problems for the inverse coefficient of variation using a Monte Carlo simulation. The simulation results show negative regret in the estimation of the inverse coefficient of variation, which indicates that the three-stage procedure provides better estimation than the optimal.
Computing μ-Values for Real and Mixed μ Problems

In various modern linear control systems, a common practice is to make use of control in the feedback loops which act as an important tool for linear feedback systems. Stability and instability analysis of a linear feedback system give the measure of perturbed system to be singular and non-singular. The main objective of this article is to discuss numerical computation of the μ -values bounds by using low ranked ordinary differential equations based technique. Numerical computations illustrate the behavior of the method and the spectrum of operators are then numerically analyzed.
Measurements of Young's Modulus of Elasticity of the Canine Aorta with Ultrasound

We have developed an ultrasonic technique for determining the dynamic Young's modulus of elasticity (E) of the canine aorta in vivo. Young's modulus was measured in the descending thoracic aorta (DTA) and the abdominal aorta (AA) of 12 dogs over a range of mean blood pressures from 40 – 200 mm Hg. The vessels were excised and dynamic moduli were determined in vitro post-mortem from pressure-volume curves. The data so obtained were compared to the in vivo values. In vivo and in vitro moduli increased exponentially with mean distending pressure (P). The equation of best fit for these data was of the form E = R0 exp(aP). E0 and a depend on the site of measurement (AA or DTA) and upon the particular animal. In vivo and in vitro moduli were not significantly different in the AA (AA: in vivo E0 = 667 ± 382 mm Hg, a = 0.017 ± 0.004 mm Hg-1 in vitro E0 = 888 ± 367, a = 0.016 ± 0.002). However, in vivo moduli exceeded in vitro moduli in the DTA. (DTA: in vivo E0 = 687 ± 241, a = 0.016 ± 0.004 in vitro E0 = 349 ± 64, a = 0.018 ± 0.003). The increased stiffness of the DTA compared to the AA in vivo may be due to the in situ tethering of the aorta to the spine by the parietal pleura.
Imaging of mice and men : adventures in multispectral imaging

Cancer of the brain and CNS account for only 2% of new cancer cases in the UK however it is responsible for 7% of cancer deaths of those aged under 70 years of age. Although surgery falls short of a cure it is the primary method of treatment. Two of the key problems in tumour surgery in the brain are a) that many tumours are visually indistinguishable from normal tissue even for experienced surgeons and b) that the risk of post-surgical neurological deficit is related to the proximity of functional (or 'eloquent') neurological tissue. In collaboration with surgeons at the Southampton University NHS Hospitals Trust we seek to address both of these problems. Firstly there is literature evidence that normal and neoplastic tissue have different spectral characteristics in the visible and near-infrared region. We investigate whether these can be practically imaged intraoperatively to establish disease state. Secondly the redox state of haemoglobin is known to affect it's visible and near-infrared spectral characteristics. This project investigates whether it is possible to identify the haemodynamic response associated with functional activity intraoperatively in the human brain. Prion diseases are fatal chronic neurodegenerative diseases of animals and man. They have gained notoriety due to recent outbreaks of Bovine Spongiform Encephalopathy (BSE) and the evidence that they can be transmitted between species, including to man. Exposure to BSE infected material has been shown to cause variant Creutzfeldt-Jacob disease in man. Prion disease is also used as a model of other neurodegenerative diseases, such as Alzheimers disease. Remarkably little is known about this class of disease including the specific cause of the neurodegeneration. Prions are a mis-folded protein which have a different conformation than the normal protein. Certain spectral features in the mid infrared region are associated with protein conformation. In collaboration with neuro-biologists within the university and using a synchrotron light source we investigate the application of multispectral imaging in early stage prion disease. By analysis of the protein conformation sensitivity of the mid infrared spectra (with particular interest in the Amide I band) we seek to identify structurally relevant markers in a mouse model before clinical symptoms of the disease are evident. This may lead to better understanding of the disease progression and the neurotoxic element
Relativistic spintronic effects in semiconductor structures

The spin transport and dynamics of optically injected spin polarized carriers are studied with a high spatial and/or time resolution in semiconductor GaAs-based heterostructures in multiple transport regimes. An unexpectedly long-scale and highspeed spin diffusion transport is observed in a long-lived electron sub-system induced optically at an undoped single GaAs/AlGaAs heterointerface. A diffusion and driftdominated spin transport is investigated using an electrical spin-detection via the inverse spin Hall effect in doped GaAs-based systems at room and low temperatures. It is shown that the inverse spin Hall signal and the spin transport parameters can be controlled by a direct application of an electric field or by expanding a depleted zone of a planar pn-junction.
Production Of PGI2 By Cultured Endothelial Cells And Smooth Muscle Cells

Prostacyclin (PGI2) is the main product of the cyclooxygenase pathway in endothelial cells and is a short-lived vasodilator and inhibitor of platelet aggregation. Cultured endothelial cells (EC) make PGI2 from exogenous arachidonic acid (AA) and the unstable endoperoxide PGH2. EC have also been shown to make PGI2 from endogenous AA when stimulated by the calcium ionophore A23187, thrombin, histamine, bradykinin, trypsin, platelet derived growth factor, and uremic plasma. PGI2 synthesis in EC is blocked by aspirin, indomethacin, or 15-HPAA. PGI2 synthesis is partially self-controlled and self-limiting at least in vitro since PGI2 elevates EC cAMP levels and elevated cAMP levels decrease EC PGI2 production. While the proteolytic site of thrombin (and trypsin) is involved in the stimulation of PGI2 production, high affinity binding of thrombin to endothelial cells appears not to be necessary. Alteration of the fatty acid composition of EC by manipulation of the culture media can decrease PGI2 production in response to thrombin or A23187 by 60-751. Cultured aortic smooth muscle cells (SMC) also synthesize PGI2 but at significantly lower levels than EC. SMC PGI2 production is stimulated by PDGF and in some SMC lines by thrombin. SMC grown from atherosclerotic rabbit aortas produce considerably less PGI2 from exogenous AA than do SMC from noimal aortas. Future investigations into this area will further clarify normal biochemical and physiologic pathways and perhaps suggest means by which PGI2 production in EC and SMC may be modulated in order to treat human disease.
Entropy Reduction using K-Mean Clustering Algorithm

: This Clustering is a technique which is used in different organization which is used to organize a large number of unordered text documents into different clusters and obtained high similarity value as compare to the documents that are presents in other clusters. The utilization of document clustering is used in different area such as web mining, large organizations, in health organization and to extract information. In this research work, we are applying K-mean clustering algorithm to organize the un-structured document into structured document. To determine the similarity among them Cosine similarity algorithm is used. At last, the metrics such as entropy and accuracy is computed with the help of the MATLAB simulator.
Improving the Reproductive Health of Married and Unmarried Youth in India

The International Center for Research on Womens (ICRWs) 10-year multi-partner research program Improving the Reproductive Health of Married and Unmarried Youth in India demonstrates that it is possible to create effective programs that in a relatively short time improve adolescents health. This report draws on lessons learned on how to strengthen community and government efforts to improve youth reproductive and sexual health. Youth reproductive and sexual health has become a priority for policy-makers programmers and researchers in India due to the countrys large adolescent population and its high rates of child marriage and early childbearing. India has one of the highest rates of child marriage in the world a practice that often results in early childbearing and thus serious reproductive health problems. India also has one of the worlds highest prevalence rates of iron-deficiency anemia among women including adolescents. Young women and men in India commonly suffer from reproductive tract infections (RTIs) and sexually transmitted infections (STIs) but many do not have information about or access to the treatment they need or are reluctant to seek treatment because they expect negative consequences. (excerpt)
A Novel Stress-Level-Specific Feature Ensemble for Drivers’ Stress Level Recognition

This paper proposes a novel feature set for drivers’ stress level recognition. The proposed feature set consists of data-independent and almost uncorrelated feature pairs for each stress level with very strong intra-class and relatively weak inter-class correlations, constructed by realizing a correlation analysis on the popular features studied in the literature. By using the proposed feature set, a maximum of 100% stress level recognition accuracy is achieved with an average increment of 24.85% while a mean reduction rate of 88.01% is satisfied in false positive rate compared to the full feature set. These outcomes clearly show that the proposed feature set can confidently be integrated into the driving assistance systems.
Interactive Infographics' Effect on Elaboration in Agricultural Communication

In public health, politics, and advertising, interactive content spurred increased elaboration from audiences that were otherwise least likely to engage with a message. This study sought to examine interactivity as an agricultural communication strategy through the lens of the Elaboration Likelihood Model. Respondents were randomly assigned a static or interactive data visualization concerning the production of peaches and blueberries in Georgia, then asked to list their thoughts in accordance with Petty and Cacioppo’s thought-listing measure. Respondents significantly exhibited higher elaboration with the interactive message as opposed to the static, extending the results of past research in other communication realms to agricultural communication as well. This increase in attitude and cognition encourages agricultural communicators to pursue the use of more interactive elements in their messaging.
Direct Examination of the Deactivation of the Boron–Oxygen Center in Cz-Si Solar Cells Under Regeneration Conditions via Electroluminescence

We examine the regeneration kinetics of the boron–oxygen defect in boron-doped <italic>p</italic>-type Czochralski-grown silicon (Cz-Si) solar cells as a function of the excess carrier concentration Δ<italic>n</italic> at the regeneration conditions, i.e., at elevated temperature (140 °C). To perform the regeneration, we apply different forward-bias voltages (<italic>V</italic><sub>appl</sub>) to solar cells in darkness and measure directly the emitted electroluminescence (EL) signal at different time steps during the regeneration of the cell. Measuring the EL signal emitted by the solar cell during regeneration, we are able to directly determine Δ<italic>n</italic> during regeneration for each applied voltage. In addition to the EL signal, we measure the electric current flowing through the solar cell during the regeneration process. This current is proportional to the overall recombination rate in the cell and, hence, reflects the changing bulk recombination during the regeneration process. From the measured time-dependent cell current, we determine the deactivation rate constant <italic>R</italic><sub>de</sub> of the boron–oxygen defect. Our experimental results unambiguously show that <italic>R</italic><sub>de</sub> increases proportionally with Δ<italic>n</italic> during the regeneration process.
A simple design substrate-integrated waveguide horn antenna with reduced back lobe

ABSTRACT A simple technique to design stable gain and low back lobe substrate-integrated waveguide (SIW) horn antenna is proposed. Matching is achieved by placing a metallised via in a specific distance from the aperture of the horn. The proposed design method is based on the analytical equivalent circuit that derived for the impedance of the antenna aperture and the matching metallic via in SIW. The aperture impedance and metallic via in SIW are studied and design curves are extracted for a specified substrate. Also, to reach a directive pattern and reduce the back lobe of the antenna, some chokes are used on the aperture of the horn. The effect of chokes on some parameters such as power flow and radiation pattern, the front to back ratio (FBR), side lobe level (SLL) and increasing directivity of the antenna is reported. The measurement results confirm simulation, appropriately. The proposed structure has high compactness due to the matching technique and design. The proposed SIW horn has compact dimensions as 18.7 * 23.34*7.62 mm (0.93 * 1.16 * 0.37 λ0) and the measured gain of the horn is about 5.5 dB at 15 GHz and bandwidth of six percent.
HSI-BERT: Hyperspectral Image Classification Using the Bidirectional Encoder Representation From Transformers

Deep learning methods have been widely used in hyperspectral image classification and have achieved state-of-the-art performance. Nonetheless, the existing deep learning methods are restricted by a limited receptive field, inflexibility, and difficult generalization problems in hyperspectral image classification. To solve these problems, we propose HSI-BERT, where BERT stands for bidirectional encoder representations from transformers and HSI stands for hyperspectral imagery. The proposed HSI-BERT has a global receptive field that captures the global dependence among pixels regardless of their spatial distance. HSI-BERT is very flexible and enables the flexible and dynamic input regions. Furthermore, HSI-BERT has good generalization ability because the jointly trained HSI-BERT can be generalized from regions with different shapes without retraining. HSI-BERT is primarily built on a multihead self-attention (MHSA) mechanism in an MHSA layer. Moreover, several attentions are learned by different heads, and each head of the MHSA layer encodes the semantic context-aware representation to obtain discriminative features. Because all head-encoded features are merged, the resulting features exhibit spatial–spectral information that is essential for accurate pixel-level classification. Quantitative and qualitative results demonstrate that HSI-BERT outperforms any other CNN-based model in terms of both classification accuracy and computational time and achieves state-of-the-art performance on three widely used hyperspectral image data sets.
Influence of Sampling Frequency on Magneto-Optical Imaging Under Alternating Magnetic Field Excitation

This paper studies the magneto-optical image (obtained by different sampling frequencies) features of weld defects under alternating magnetic field excitation. Weld cracks with different gaps—0.03 mm, 0.05 mm, 0.07 mm, and 0.1 mm—were detected through the magneto-optical imaging method. In order to study the effect of sampling frequency on magneto-optical imaging, different sampling frequencies, such as 5 fps, 15 fps, 25 fps, 35 fps, 45 fps, 55 fps, 65 fps, and 75 fps, were used under the excitation of an alternating magnetic field. The distribution range of the gray-scale value for the magneto-optical image obtained at each sampling frequency was analyzed. The effect of the sampling frequency on the magneto-optical imaging was analyzed by comparing the magneto-optical images of weld defects and their gray-value curves at different sampling frequencies. Experimental results show that the sampling frequency of the magneto-optic sensor affects the distribution range of the gray-scale value of the magneto-optic image. Under the same experimental conditions, as the sampling frequency increases, the whole magneto-optical image becomes dark, and the span of the gray value becomes larger.
Investigation of Induced Charge Mechanism on a Rod Electrode

Rod electrodes based on an electrostatic induction mechanism are widely used in various industrial applications, but the analytic solution of an induced charge mechanism on a metal rod electrode has not yet been systematically established. In this paper, the theoretical model of the induced charge on a rod electrode is obtained through the method of images. Then, the properties of the rod electrode under the action of the point charge are studied, including the induced charge density distribution on the rod electrode, the amount of the induced charge with different diameters and lengths of the electrode, and the effective space region induced by the electrode. On this basis, a theoretical model of the induced current on a rod electrode is established, which is used to study the induced current properties by a moving point charge. It is found that both the magnitude and bandwidth of the induced current increase with the increased point charge velocity. Finally, three experimental studies are conducted, and the experimental results show good consistency with the analysis of the theoretical model, verifying the correctness, and accuracy of the model. In addition, the induced charge mechanism studied in this paper can act as an effective basis for the rod electrode sensor design in terms of the optimal radius and length.
Keeping the balance—Bridge sampling for marginal likelihood estimation in finite mixture, mixture of experts and Markov mixture models

Finite mixture models and their extensions to Markov mixture andmixture of experts models are very popular in analysing data of various kind.A challenge for these models is choosing the number of components basedon marginal likelihoods. The present paper suggests two innovative, genericbridge sampling estimators of the marginal likelihood that are based on con-structing balanced importance densities from the conditional densities arisingduring Gibbs sampling. The full permutation bridge sampling estimator is de-rived from considering all possible permutations of the mixture labels for asubset of these densities. For the double random permutation bridge samplingestimator, two levels of random permutations are applied, first to permute thelabels of the MCMC draws and second to randomly permute the labels ofthe conditional densities arising during Gibbs sampling. Various applicationsshow very good performance of these estimators in comparison to importanceand to reciprocal importance sampling estimators derived from the same im-portance densities.
Quantifying Differences among Ten Fingers in Force Control Capabilities by a Modified Meyer Model

Quantifiable differences among fingers in force control capability have both important practical and theoretical values in characterizing force control of accurate finger-tapping tasks. Following the classical Fitts’ law paradigm, we quantified the differences among ten fingers in term of speed–accuracy trade-off (SAT) in performing repetitive discrete force control tasks. Visual cues displaying targeted force magnitudes and tolerances were provided. Users were required to apply the targeted force within the given tolerance quickly and accurately by pressing a force sensor using the specified finger. We found that ten fingers obeyed the Meyer model in the SAT performance and they differed in reaction time, the index of performance (IP), and the goodness of fit for the Meyer model. A modified Meyer model was proposed to quantify the difference between ten fingers in the SAT performance using only one parameter, making the quantification easier than using the original Meyer model. Pairwise comparisons showed that the differences between symmetrical fingers on both hands were insignificant except for the pair of index fingers. These findings provided us with multiple perspectives on the differentiation among ten fingers in the force control capabilities. Our study helps lay the foundation for engineering systems that rely on finger force control ability.
Multi-Task Scheduling Based on Classification in Mobile Edge Computing

In this paper, a dynamic multi-task scheduling prototype is proposed to improve the limited resource utilization in the vehicular networks (VNET) assisted by mobile edge computing (MEC). To ensure quality of service (QoS) and meet the growing data demands, multi-task scheduling strategies should be specially constructed by considering vehicle mobility and hardware service constraints. We investigate the rational scheduling of multiple computing tasks to minimize the VNET loss. To avoid conflicts between tasks when the vehicle moves, we regard multi-task scheduling (MTS) as a multi-objective optimization (MOO) problem, and the whole goal is to find the Pareto optimal solution. Therefore, we develop some gradient-based multi-objective optimization algorithms. Those optimization algorithms are unable to deal with large-scale task scheduling because they become unscalable as the task number and gradient dimensions increase. We therefore further investigate an upper bound of the loss of multi-objective and prove that it can be optimized in an effective way. Moreover, we also reach the conclusion that, with practical assumptions, we can produce a Pareto optimal solution by upper bound optimization. Compared with the existing methods, the experimental results show that the accuracy is significantly improved.