Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly Efficient and Linearity-Enhanced Quasi-Balanced Doherty Power Amplifier at 3.5 GHz: Linear Quasi-Balanced Doherty Power Amplifier Design Methodology

The prestigious High-Efficiency Power Amplifier (HEPA) Student Design Competition (SDC) has been held annually for 17 years. In 2021, the competition was held virtually, live streamed from Keysight Technology’s Microwave Measurements Lab on 15 October 2021. The contest, organized by the IEEE Microwave Theory and Technology Society in collaboration with Keysight Technology, provides an opportunity for students from around the world to compete in the design of power amplifiers (PAs) with high linearity and high efficiency over a specified instantaneous bandwidth.
Effects of tensile, compressive, and zero strain on localized states in AlInGaN/InGaN quantum-well structures

The recombination dynamics of optical transitions as well as strain effects in AlInGaN/In0.08Ga0. 92N quantum wells (QWs) were studied. QW emission energy, photoluminescence decay behavior, photoluminescence emission line shape, and nonradiative recombination behavior were found to be strong functions of strain as well as localization. The degree of carrier localization was inferred by modeling several aspects of optical behavior obtained from variable temperature time-resolved photoluminescence experiments. According to the modeling results, the degree of localization was found to be a minimum for unstrained QWs and increased as either tensile or compressive strain increased, indicating that InGaN QW microstructure is a function of the lattice-mismatch-induced strain experienced during deposition.
Preset time count rate meter using adaptive digital signal processing

Two presented methods were developed to improve classical preset time count rate meters by using adapt able signal processing tools. An optimized detection algorithm that senses the change of mean count rate was implemented in both methods. Three low-pass filters of various structures with adaptable parameters to implement the control of the mean count rate error by suppressing the fluctuations in a controllable way, were considered and one of them implemented in both methods. An adaptation algorithm for preset time interval calculation executed after the low-pass filter was devised and implemented in the first method. This adaptation algorithm makes it possible to obtain shorter preset time intervals for higher stationary mean count rate. The adaptation algorithm for preset time interval calculation executed before the low-pass filter was devised and implemented in the second method. That adaptation algorithm enables sensing of a rapid change of the mean count rate before fluctuations suppression is carried out. Some parameters were fixed to their optimum values after appropriate optimization procedure. Low-pass filters have variable number of stationary coefficients depending on the specified error and the mean count rate. They implement control of the mean count rate error by suppressing fluctuations in a controllable way. The simulated and realized methods, using the developed algorithms, guarantee that the response time shall not exceed 2 s for the mean count rate higher than 2 s-1 and that controllable mean count rate error shall be within the range of ±4% to ±10%.
Design of a Helium-Free Test Cryostat for Superconducting Wires, Cables, and Windings

A helium-free test cryostat is being built to support testing of superconducting wires, cables, and windings. Three cryocoolers are mounted on the top hat of an LN2-shielded open-top cryostat and used to heat-sink thermal intercept shells at 50 K, 20 K, and 4.2 K. Ternary leads are used for supply and return of a 10 kA circuit (for a background-field dipole) and a 20 kA circuit for a test sample. Each lead is a series connection of a N2 vapor-cooled lead and a Bi-2223 Type G lead. A closed-flow liquid helium loop is used to maintain the Nb3Sn CIC windings of a 10 T background field dipole at 5 K. The objective of the design is to make it possible to sustain the test environment relying solely on LN2 and three cryocoolers, without the expense of a helium liquefier or a large inventory of liquid helium.
A random kinetic energy model for rock avalanches: Eight case studies

[1] We apply a numerical avalanche dynamics model to predict runout, velocity, and spatial distribution of deposit thickness of eight rock avalanches. The model solves depth-averaged mass and momentum conservation equations for avalanche flow in general three-dimensional terrain using a second-order finite-volume method. In this paper, these standard mass and momentum equations are supplemented with an additional relation describing the production and decay of the kinetic energy associated with the random motion of rock fragments within the avalanche flow. Using results from full-scale experiments with granular snow avalanches, we show that the random energy cannot perform mechanical work. Therefore, fundamental thermodynamic constraints exist between frictional shearing and the production of random energy that explain the reduction of flow friction as a function of the random kinetic energy fluxes. We utilize this result to extend the Voellmy avalanche rheology and simulate the eight case studies using one parameter set to avoid site-specific parameter tuning. This procedure allows us to evaluate and compare simulation results of the case studies and gauge model performance. Our results support the hypothesis that the production of random kinetic energy within the flow is of relevance in the runout of rock avalanches. Although this random kinetic energy description is capable of reproducing a wide range of avalanche behavior, including extreme runout, more work is required to relate material properties of different rock types to the coefficients governing the production and decay processes. Furthermore, the fragmentation process itself must be included in the model to limit production rates.
Prediction of FTSE Bursa Malaysia KLCI Stock Market using LSTM Recurrent Neural Network

Stock market prediction is vital in the financial world. Investors and people interested in investing would be interested in the future value of the stock market before they invest in it. By using the method of time series, this research gives a contribution to forecast and modelling the FTSE Bursa Malaysia KLCI (FBM KLCI) stock market. In this research, the stock market is forecasted to identify the stock market trend in the future. The FBM KLCI closing prices data was utilized to build Long Short-Term Memory (LSTM) models to predict the stock market. The performance of the model has been evaluated using the root mean squared error (RMSE) and the mean absolute error (MAE) in order to choose the best model. The researcher used the Bursa Malaysia data to forecast the stock market for five years, from October 20, 2016, to October 20, 2021, which has been scrapped from the Yahoo Finance website. The data is analyzed by running Python coding in Google Colab. The result proves that the accuration of the LSTM model by using Recurrent Neural Network (RNN) approach is accurate and the predicted value of the stock market at the date 2021-10-05 is increased by 1.87%. It can be used to predict the future closing stock prices in stock market prediction in FBM KLCI stock market. The results are expected to provide an accurate prediction for a better profit. Thus, prediction in stock market investment can support long-term economic growth, or in other words, it can help economic sustainability.
First estimates of volume distribution of HF-pump enhanced emissions at 6300 and 5577 Å: a comparison between observations and theory

We present bi-static observations of radio-wave induced optical emissions at 6300 and 5577 ˚ A from a night- time radio-induced optical emission ionospheric pumping experiment at the HIPAS (Fairbanks) facility in Alaska. The optical observations were made at HIPAS and from HAARP located 285 km south-east. From these observa- tions the altitude distribution of the emissions is estimated with tomography-like methods. These estimates are com- pared with theoretical models. Other diagnostics used to support the theoretical calculations include the new Poker Flat AMISR UHF radar near HIPAS. We find that the alti- tude distribution of the emissions agree with electron trans- port modeling with a source of accelerated electrons located 20 km below the upper-hybrid altitude.
Physical design method of MPSoC

Floorplan, clock network and power plan are crucial steps in deep sub-micron system-on-chip design. A novel diagonal floorplan is integrated to enhance the data sharing between different cores in system-on-chip. Custom clock network containing hand-adjusted buffers and variable routing rules is constructed to realize balanced synchronization. Effective power plan considering both IR drop and electromigration achieves high utilization and maintains power integrity in our MediaSoC. Using such methods, deep sub-micron design challenges are managed under a fast prototyping methodology, which greatly shortens the design cycle.
Biologically Active Supplements Affecting Producer Microorganisms in Food Biotechnology: A Review

Microorganisms, fermentation processes, and the resultant metabolic products are a key driving force in biotechnology and, in particular, in food biotechnology. The quantity and/or quality of final manufactured food products are directly related to the efficiency of the metabolic processes of producer microorganisms. Food BioTech companies are naturally interested in increasing the productivity of their biotechnological production lines. This could be achieved via either indirect or direct influence on the fundamental mechanisms governing biological processes occurring in microbial cells. This review considers an approach to improve the efficiency of producer microorganisms through the use of several types of substances or complexes affecting the metabolic processes of microbial producers that are of interest for food biotechnology, particularly fermented milk products. A classification of these supplements will be given, depending on their chemical nature (poly- and oligosaccharides; poly- and oligopeptides, individual amino acids; miscellaneous substances, including vitamins and other organic compounds, minerals, and multicomponent supplements), and the approved results of their application will be comprehensively surveyed.
A long-range capacitive displacement sensor having micrometre resolution

Describes a capacitive displacement sensor using the spatial sampling principle. A first experimental prototype has been manufactured. Measurements show that this prototype achieves a resolution of 1 mu m and an accuracy of 3 mu m over a displacement of 150 mm. The linear displacement range can be as large as several metres. The prototype confirms low sensitivity to both alignment inaccuracies and external influences like dust and electromagnetic disturbances.
A Graph-Attention-Based Method for Single-Resident Daily Activity Recognition in Smart Homes

In ambient-assisted living facilitated by smart home systems, the recognition of daily human activities is of great importance. It aims to infer the household’s daily activities from the triggered sensor observation sequences with varying time intervals among successive readouts. This paper introduces a novel deep learning framework based on embedding technology and graph attention networks, namely the time-oriented and location-oriented graph attention (TLGAT) networks. The embedding technology converts sensor observations into corresponding feature vectors. Afterward, TLGAT provides a sensor observation sequence as a fully connected graph to the model’s temporal correlation as well as the sensor’s location correlation among sensor observations and facilitates the feature representation of each sensor observation through receiving other sensor observations and weighting operations. The experiments were conducted on two public datasets, based on the diverse setups of sensor event sequence length. The experimental results revealed that the proposed method achieved favorable performance under diverse setups.
Calculation of eddy current losses in nonlinear ferromagnetic materials

A complex analysis of the nonlinear diffusion problem in ferromagnetic materials under steady-state excitation is presented. The problem is solved by considering an equivalent fictitious material where the relative permeability is assumed to be constant in time but different from point to point and is related to the nonlinear B-H characteristic curve with the help of the stored magnetic co-energy density. Eddy current losses are calculated in a one-dimensional thick steel plate. A comparison made with results obtained from the classical step-by-step method shows a good agreement. >
Nude and Modified Electrospun Nanofibers, Application to Air Purification

Air transports several pollutants, including particulate matter (PM), which can produce cardiovascular and respiratory diseases. Thus, it is a challenge to control pollutant emissions before releasing them to the environment. Until now, filtration has been the most efficient processes for removing PM. Therefore, the electrospinning procedure has been applied to obtain membranes with a high filtration efficiency and low pressure drop. This review addressed the synthesis of polymers that are used for fabricating high-performance membranes by electrospinning to remove air pollutants. Then, the most influential parameters to produce electrospun membranes are indicated. The main results show that electrospun membranes are an excellent alternative to having air filters due to the versatility of the process, the capacity for controlling the fiber diameter, porosity, high filtration efficiency and low-pressure drop.
Do Platelet-Rich Plasma Injections for Knee Osteoarthritis Work?

Background: Recent evidence suggests a benefit in platelet-rich plasma injections (PRP) for the knee in the management of mild to moderate osteoarthritis (OA). There is a reported reduction in pain, stiffness, and improved function. However, there is very little level-one literature available that supports this practice and conclusively proves a benefit gained throughout the course. Three main randomized control trials (RCTs) conducted in North America are often referenced and cited to prove their efficacy. This study aimed to look at the outcomes of patients having undergone this treatment to determine if there was any benefit. Aims: This study aimed to determine if PRP injections administered in patients with knee OA over a six to eight-week time period demonstrated any benefit. Methods: The Western Ontario and McMaster Universities arthritis index (WOMAC) tool was used before each of the three PRP injections over the six to eight-week period, and six weeks after the final injection in 31 patients. Each injection was given spaced two to three weeks apart. The outcomes observed were pain, stiffness, and physical function, and the total WOMAC score was calculated. Results: The third injection showed a reduction in total WOMAC score, pain, stiffness, and physical function by 16.36%, 16.37%, 5.12%, and 18.03%, respectively. However, all scores returned close to baseline at the sixth-week follow-up post treatment. Conclusion: Results showed a trend of reduction in the WOMAC score. However, they are overall indicative of a placebo effect from the injections. Further studies are needed to explore whether the grade of OA and patients’ weight have a significant impact on the results.
Functional analysis of missense mutations in GLI2 and GLI3 involved in congenital heart disease

Objective: In this study, we aimed to explore the biological functions of 10 rare case-specific missense mutations in GLI2 and 4 in GLI3, which were previously screened in a cohort of 412 patients with congenital heart disease (CHD) and 213 normal controls from Shandong Province, China. Methods: A dual-luciferase reporter assay was used to assess the effects of these mutations in GLI2 and GLI3 on the activity of the sonic Hedgehog signaling pathway in HEK293T cells. Differences in protein levels between mutant and wild-type GLI2 and GLI3 were detected in HEK293T cells using Western blotting. Results: The dual-luciferase reporter assay showed that compared to the wild-type GLI2 protein, p.A1113V significantly increased activation of the sonic Hedgehog signaling pathway, whereas p.H78P and p.I1451S did not have a significant effect. The other mutations largely reduced the activation effect. Compared with the wild-type GLI3 protein, only p.A286V, among the four mutations, significantly reduced the activation effect on the SHH signaling pathway. Western blotting data showed reduced expression of GLI2 p.G716V, GLI2 p.K736N, GLI2 p.I1451S, and GLI3 p.A286V, whereas the remaining mutations had no significant effects. Conclusion: The mutations GLI2 c.2147G>T (p.G716V), GLI2 c.2208G>C (p.K736N), and GLI3 c.857C>T (p.A286V) involved in CHD affect the regulation of the sonic Hedgehog signaling pathway; thus, these rare missense mutations in GLI2 and GLI3 might increase the risk of CHD.
Temporally resolved PIV for space–time correlations in both cold and hot jet flows

Temporally resolved particle image velocimetry (TR-PIV) is the newest and most exciting tool recently developed to support our continuing efforts to characterize and improve our understanding of the decay of turbulence in jet flows—a critical element for understanding the acoustic properties of the flow. A new TR-PIV system has been developed at the NASA Glenn Research Center which is capable of acquiring planar PIV image frame pairs at up to 25 kHz. The data reported here were collected at Mach numbers of 0.5 and 0.9 and at temperature ratios of 0.89 and 1.76. The field of view of the TR-PIV system covered six nozzle diameters along the lip line of the 50.8 mm diameter jet. The cold flow data at Mach 0.5 were compared with hotwire anemometry measurements in order to validate the new TR-PIV technique. The axial turbulence profiles measured across the shear layer using TR-PIV were thinner than those measured using hotwire anemometry and remained centred along the nozzle lip line. The collected TR-PIV data illustrate the differences in the single point statistical flow properties of cold and hot jet flows. The planar, time-resolved velocity records were then used to compute two-point space–time correlations of the flow at the Mach 0.9 flow condition. The TR-PIV results show that there are differences in the convective velocity and growth rate of the turbulent structures between cold and hot flows at the same Mach number.
Low-flux hard state of 1E 1740.7-2942

GRANAT observations of 1E 1740.7-2942 in 1991 October revealed the source at low 40-150 keV flux level, ∼20-30 mCrab (∼1/5 of the typical 1990 value). The source spectrum in the 150-600 keV energy domain exhibits notable excess above a power-law extrapolation of the lower energy part (4-150 keV) of the spectrum. Comparison of the 1991 October spectrum with the «standard» state spectrum observed in 1990 suggests some analogy with γ 2 -γ 1 states transition, observed for the well-known black bole candidate Cygnus X-1 by HEAO 3 (Ling et al.)
DISCOVERY AND ANALYSIS OF 21 μm FEATURE SOURCES IN THE MAGELLANIC CLOUDS

Spitzer Space Telescope mid-infrared spectroscopy has been obtained for 15 carbon-rich protoplanetary nebulae (PPNe) in the Large Magellanic Cloud (LMC) and for two other such stars in the Small Magellanic Cloud (SMC). Of these 17 PPNe, the unidentified 21 μm feature is strong in 7 spectra, weak in 2 spectra, and very weak or questionable in 4 spectra. Two of the four spectra without the 21 μm feature have a very strong feature near 11 μm, similar to a feature observed in some carbon-rich planetary nebulae (PNe) in the LMC. We attribute this feature to unusual SiC dust, although the feature-to-continuum ratio is much larger than for SiC features in Galactic or Magellanic Cloud carbon star spectra. The remaining two objects show typical carbon-rich PPNe spectra with no 21 μm features. One of the LMC objects that lacks the 21 μm feature and one SMC object with a questionable 21 μm detection may have mixed dust chemistries based upon their spectral similarity to Galactic [WC] PNe. The 13 objects that either definitely or may show the 21 μm feature have distinct dust shell properties compared to the Galactic 21 μm objects—the 21 μm features are weaker, the estimated dust temperatures are significantly higher, the unidentified infrared (UIR) bands are stronger, and the UIRs show more structure. Four of the 21 μm objects appear to show normal SiC emission features in their spectra. Many of the PPNe show strong 30 μm features, although this feature carries less of the total mid-infrared emission than is normally the case for the Galactic 21 μm PPNe. The LMC objects are in the LMC halo rather than in the LMC bar. The estimated luminosities of these PPNe vary from 4700 to 12,500 L☉.
A statistical method for global optimization

An algorithm for finding global optima using statistical prediction is presented. Assuming a random function model, lower confidence bounds on predicted values are used for sequential selection of evaluation points and as a convergence criterion. Comparison with published results for several test functions indicates that the procedure is very efficient in finding the global optimum of a multimodal function, and in terminating with relatively few evaluations. <<ETX>>
Foundational Aspects of Smart Cities Leading the Digital Economy - An Review

Due to the proliferation of advanced computing devices, it is now possible to attain faster data availability, data transportation, intuitive programming, and efficient infrastructures. In addition to enhancing the economy in terms of financial assets, and energy in the management of cities, the projected advantage is that it will have a positive impact on the quality of services provided to urban citizens. This article analyzes the foundational aspects of smart cities within the context of the digital economy by examining the roles of the digital economic developing in the construction of cities using China as a case study. This paper further explores the challenges facing the construction of the digital economy and smart cities, and provides a recommendation to Belarus to enhance its influence of the digital economy in their smart cities and e-government development. Based on a critical survey provided in this article, researchers and city developers are provided with insights and recommendations for bolstering the smart city's "digital radiation drive. "