Miracle-dz/UniFAR-FTUs huggingface dataset:
Grid-Connected Phase-Locked Loop Technology Based on a Cascade Second-Order IIR Filter

The moving average filter-based phase-locked loop (MAF-PLL) can obtain grid synchronization signals accurately under adverse grid conditions with a large amount of harmonics due to the high filtering capability of the MAF. However, MAF-PLL cannot achieve a fast dynamic response in the case of frequency drift, phase angle steps, and unbalanced voltage sag. MAF is essentially an FIR filter, and its filtering performance is hard to be adjusted. To address this issue, this paper proposes an alternative to MAF consisting of a set of cascading second-order IIR filters (CIIRF). Based on MAF, CIIRF introduces multiple zeros and poles from the zero–pole replacement perspective, and by changing the position of the poles, the filter performance can be adjusted. To improve the anti-interference ability of PLL based on CIIRF (CIIRF-PLL) in the presence of grid frequency drift, a frequency-adaptive scheme is also proposed. Simulation and experimental results show that CIIRF-PLL can accurately track the grid voltage phase in the case of frequency steps, phase angle jumps, harmonics injection, and unbalanced voltage sag and has good steady-state and dynamic performance.
Parametric amplification of density perturbations in the oscillating inflation model

We study the adiabatic density perturbation in the {\it oscillating inflation}, proposed by Damour and Mukhanov. The recent study of the cosmological perturbation during reheating shows that the adiabatic fluctuation behaves like as the perfect fluid and no significant amplification occurs on super-horizon scales. In the oscillating inflation, however, the accelerated expansion takes place during the oscillating stage and there might be a possibility that the parametric amplification on small scales affects the adiabatic long-wavelength perturbation. We analytically show that the density perturbation neglecting the metric perturbation can be amplified by the parametric resonance and the instability band becomes very broad during the oscillating inflation. We examined this issue by solving the evolution equation for perturbation numerically. We found that the parametric resonance is strongly suppressed for the long wave modes comparable to the Hubble horizon. The result indicates that the metric perturbation plays a crucial role for the evolution of scalar field perturbation. Therefore, in the single field case, there would be no significant imprint of the oscillating inflation on the primordial spectrum of the adiabatic perturbation. However, it could be expected that the oscillating inflation in the multi-field system gives the enormous amplification on large scales, which may lead to the production of the primordial black holes.
A sensitivity experiment to the orographic effect on the Bengal storm of Mala during its landing

The Bay of Bengal is among the eight areas where tropic cyclones appear frequently.When a Bengal storm moves northward or eastward,it will affect weather over the Qinghai-Tibet Plateaun and the westnorthern part of China,and also the large-scale topography of the Qinghai-Tibet Plateanu and the Yunnan-Guizhou Plateau will affect the moving path of the Bengal storm.To analyze the effect of the this topography on the path,the structure and the precipitation for the Bengal storm.The Bengal storm of Mala landfall process from 29 to 30 April in 2006 is simulated by the Weather Research and Forecast meso-scale numerical model(WRF). The results show that although there are certain errors between the simulated track and intensity for the storm and the observation,both the general moving tend and the intensity are properly simulated with small errors.The WRF can well simulate the track and precipitation of Mala occurring in Yunnan province.The sensitivity experiment results from the respective schemes with the full height,half height and zero height effect on changes in the storm track are discussed,and the circulation,the dynamical structure and the precipitation over Yunnan are analyzed as well.The results show that before the storm landfall,the topography affects the storm structure in an indirect way,with its structure in higher levels becoming slant.During its landfall,the topographic countercheck and friction are able to significantly affect the moving track and velocity of the storm.After its landfall,the topography caused the storm intensity to weaken and its moving velocity to quicken.On the other hand,its structure goes through the course from a basic symmetric storm to an asymmetric one with evident baroclinicity.The topographic effects on the precipitation are embodies in the two aspects,one is to make the precipitation increase and another is to cause the storm intensity to weaken and thus the precipitation to decrease.
Effect of MnxOy Nanoparticles Stabilized with Methionine on Germination of Barley Seeds (Hordeum vulgare L.)

The aim of this research was to study the effect of MnxOy nanoparticles stabilized with L-methionine on the morphofunctional characteristics of the barley (Hordeum vulgare L.) crop. MnxOy nanoparticles stabilized with L-methionine were synthesized using potassium permanganate and L-methionine. We established that MnxOy nanoparticles have a diameter of 15 to 30 nm. According to quantum chemical modeling and IR spectroscopy, it is shown that the interaction of MnxOy nanoparticles with L-methionine occurs through the amino group. It is found that MnxOy nanoparticles stabilized with L-methionine have positive effects on the roots and seedling length, as well as the seed germination energy. The effect of MnxOy nanoparticles on Hordeum vulgare L. seeds is nonlinear. At a concentration of 0.05 mg/mL, there was a statistically significant increase in the length of seedlings by 68% compared to the control group. We found that the root lengths of samples treated with MnxOy nanoparticle sols with a concentration of 0.05 mg/mL were 62.8%, 32.7%, and 158.9% higher compared to samples treated with L-methionine, KMnO4, and the control sample, respectively. We have shown that at a concentration of 0.05 mg/mL, the germination energy of seeds increases by 50.0% compared to the control sample, by 10.0% compared to the samples treated with L-methionine, and by 13.8% compared to the samples treated with KMnO4.
THE UNIVERSITY OF CHICAGO AVERAGE LUMINOSITY DISTANCE IN INHOMOGENEOUS UNIVERSES A DISSERTATION SUBMITTED TO THE FACULTY OF THE DIVISION OF THE PHYSICAL SCIENCES IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF PHYSICS BY VALENTIN ANGELOV KOSTOV

Using numerical ray tracing, the paper studies how the average distance modulus in an inhomogeneous universe differs from its homogeneous counterpart. The averaging is over all directions from a fixed observer not over all possible observers (cosmic), thus it is more directly applicable to our observations. Unlike previous studies, the averaging is exact, non-perturbative, and includes all possible non-linear effects. The inhomogeneous universes are represented by Sweese-cheese models containing random and simple cubic lattices of mass-compensated voids. The Earth observer is in the homogeneous cheese which has an Einstein de Sitter metric. For the first time, the averaging is widened to include the supernovas inside the voids by assuming the probability for supernova emission from any comoving volume is proportional to the rest mass in it. For voids aligned in a certain direction, there is a cumulative gravitational lensing correction to the distance modulus that increases with redshift. That correction is present even for small voids and depends on the density contrast of the voids, not on their radius. Averaging over all directions destroys the cumulative correction even in a non-randomized simple cubic lattice of voids. Despite the well known argument for photon flux conservation, the average distance modulus correction at low redshifts is not zero due to the peculiar velocities. A formula for the maximum possible average correction as a function of redshift is derived and shown to be in excellent agreement with the numerical results. The formula applies to voids of any size that: (1) have approximately constant densities in their interior and walls, (2) are not in a deep nonlinear regime. The actual average correction calculated in random and simple cubic void lattices is severely damped below the predicted maximum. That is traced to cancelations between the corrections coming from the fronts and backs of different voids at the same
Controlled Synthesis of Silver Nanowires: Production and Characterization

In this study, silver nanowires have been synthesized by the modiﬁed polyol method. Atomic force microscopy and optical microscopy were used to study the morphological properties of nanowires. The average diameter and length of obtained silver nanowires were 40–80 nm and 2–6 µ m, respectively. Moreover, the investigation showed that the morphology of synthesized nanostructures dramatically depends on the concentration of halides. X-ray diﬀractometer study of the nanowires conﬁrmed that the growth process occurs through the deposition of Ag + ions onto the (111) plane. The ultraviolet-visible spectroscopy analysis demonstrated two localized surface plasmon resonance vibration lines of silver nanowires. The study determined that the blue shift of these vibration lines occurred due to the change in the size of the nanowires and depended on the halide concentration. The photoluminescence spectra of samples demonstrated two emission maximums in blue–green regions related to radiative recombination of Fermi level electrons and sp - or d -band holes.
Sinosasagracilis (Poaceae, Bambusoideae), a new combination supported by morphological and phylogenetic evidence

﻿Abstract The results of phylogenetic analysis, based on the whole chloroplast genome and morphological study support the transfer of a long ignored bamboo species, Sasagracilis, to the recently established genus, Sinosasa, in this study. Morphologically, this species differs from all the other known Sinosasa species by having very short (2–3 mm) foliage leaf inner ligules, which is unusual in this genus. A revised description of its morphology and colour photos are also provided.
Clinico-Pathogenic Similarities and Differences between Infection-Related Glomerulonephritis and C3 Glomerulopathy

Recently, the comprehensive concept of “infection-related glomerulonephritis (IRGN)” has replaced that of postinfectious glomerulonephritis (PIGN) because of the diverse infection patterns, epidemiology, clinical features, and pathogenesis. In addition to evidence of infection, hypocomplementemia particularly depresses serum complement 3 (C3), with endocapillary proliferative and exudative GN developing into membranoproliferative glomerulonephritis (MPGN); also, C3-dominant or co-dominant glomerular immunofluorescence staining is central for diagnosing IRGN. Moreover, nephritis-associated plasmin receptor (NAPlr), originally isolated from the cytoplasmic fraction of group A Streptococci, is vital as an essential inducer of C3-dominant glomerular injury and is a key diagnostic biomarker for IRGN. Meanwhile, “C3 glomerulopathy (C3G)”, also showing a histological pattern of MPGN due to acquired or genetic dysregulation of the complement alternative pathway (AP), mimics C3-dominant IRGN. Initially, C3G was characterized by intensive “isolated C3” deposition on glomeruli. However, updated definitions allow for glomerular deposition of other complement factors or immunoglobulins if C3 positivity is dominant and at least two orders of magnitude greater than any other immunoreactant, which makes it challenging to quickly distinguish pathomorphological findings between IRGN and C3G. As for NAPlr, it was demonstrated to induce complement AP activation directly in vitro, and it aggravates glomerular injury in the development of IRGN. A recent report identified anti-factor B autoantibodies as a contributing factor for complement AP activation in pediatric patients with PIGN. Moreover, C3G with glomerular NAPlr deposition without evidence of infection was reported. Taken together, the clinico-pathogenic features of IRGN overlap considerably with those of C3G. In this review, similarities and differences between the two diseases are highlighted.
Algorithms for better decision-making: a qualitative study exploring the landscape of robo-advisors in India

PurposeThis paper explores the current state of Robo-advisory services in India. This paper further highlights the problems experienced by the service providers in disseminating the innovative business model among the Indians.Design/methodology/approachThe study adopts a qualitative approach to investigate the industry experts by conducting semi-structured interviews. The data collected were transcripted and further analyzed using the content analysis technique. Finally, the authors utilized categorization and coding techniques to frame broad study themes.FindingsThe study findings reveal that the three pillars of Robo-advisory are ease and convenience, the time factor and transparency in operations. Robo-advisory services are still at a nascent stage in India. Furthermore, keeping the sentiments of Indians in mind, FinTech companies could combine automated Robo-advisory with a human touch of a wealth manager for optimal advisory services.Research limitations/implicationsSince the present study is qualitative, the authors cannot generalize the study results. Future research can focus on empirically proving the constructs of the study using quantitative methods.Practical implicationsRobo-advisors have a well-established market in developed nations but are still nascent in developing countries like India. The current focus of service providers and regulatory authorities must be to increase awareness among investors by educating the investors and building trust.Originality/valueThe present study is the first to qualitatively synthesize the challenges faced by the FinTech service providers in the Indian market.
A new approach to solve Multi-objective linear bilevel programming problems

Many problems in sciences and industry such as signal optimization, traffic assignment, economic market,… have been modeled, or their mathematical models can be approximated, by linear bilevel programming (LBLP) problems, where in each level one must optimize some objective functions. In this paper, we use fuzzy set theory and fuzzy programming to convert the multiobjective linear bilevel programming (MOLBLP) problem to a linear bilevel programming problem, then we extend the Kth-best method to solve the final LBLP problem. The existence of optimal solution, and the convergence of this approach, are important issues that are considered in this article. A numerical example is illustrated to show the efficiency of the new approach.
On asymptotic distributions of several test statistics for familial relatedness in linear mixed models

In this study, the asymptotic distributions of the likelihood ratio test (LRT), the restricted likelihood ratio test (RLRT), the F and the sequence kernel association test (SKAT) statistics for testing an additive effect of the expected familial relatedness (FR) in a linear mixed model are examined based on an eigenvalue approach. First, the covariance structure for modeling the FR effect in a LMM is presented. Then, the multiplicity of eigenvalues for the log‐likelihood and restricted log‐likelihood is established under a replicate family setting and extended to a more general replicate family setting (GRFS) as well. After that, the asymptotic null distributions of LRT, RLRT, F and SKAT statistics under GRFS are derived. The asymptotic null distribution of SKAT for testing genetic rare variants is also constructed. In addition, a simple formula for sample size calculation is provided based on the restricted maximum likelihood estimate of the effect size for the expected FR. Finally, a power comparison of these test statistics on hypothesis test of the expected FR effect is made via simulation. The four test statistics are also applied to a data set from the UK Biobank.
l1-Graph Based Music Structure Analysis

Anunsupervisedapproachforautomaticmusicstructureanalysis is proposed resorting to the following assumption: If the feature vectors extracted from a specific music segment are drawn from a single subspace, then the sequence of feature vectors extracted from a music recording will lie in a union of as many subspaces as the music segments in this recording are. It is well known that each feature vector stemming from a union of independent linear subspaces admits a sparse representation with respect to a dictionary formed by all other feature vectors with nonzero coefficients associated only to feature vectors that stem from its own subspace. Such sparse representation reveals the relationships among the feature vectors and it is used to construct a similarity graph, the so-called l1-graph. Accordingly, the segmentation of audio features is obtained by applying spectral clustering to the l1-graph. The performance of the just described approach is assessed by conducting experiments on the PopMusic and the UPF Beatles benchmark datasets. Promising results are reported.
Weather Radar Coverage over the Contiguous United States

Abstract Terrain and radar beam-elevation data are used to examine the spatial coverage provided by the national operational network of Doppler weather radars. This information is of importance to a wide variety of users, and potential users, of radar data from the national network. Charts generated for radar coverage at 3 and 5 km above mean sea level show that radar surveillance near 700 and 500 hPa is very limited for some portions of the contiguous United States. Radar coverage charts at heights of 1, 2, and 3 km above ground level illustrate the extent of low-level radar data gathered above the actual land surface. These maps indicate how restricted the national radar network coverage is at low levels, which limits the usefulness of the radar data, especially for quantitative precipitation estimation. The analyses also identify several regions of the contiguous United States in which weather phenomena are sampled by many adjacent radars. Thus, these regions are characterized by very comprehensive rad.
Feasibility Study of Federated Learning on the Distributed Research Network of OMOP Common Data Model

Objectives Since protecting patients’ privacy is a major concern in clinical research, there has been a growing need for privacy-preserving data analysis platforms. For this purpose, a federated learning (FL) method based on the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) was implemented, and its feasibility was demonstrated. Methods We implemented an FL platform on FeederNet, which is a distributed clinical data analysis platform based on the OMOP CDM in Korea. We trained it through an artificial neural network (ANN) using data from patients who received steroid prescriptions or injections, with the aim of predicting the occurrence of side effects depending on the prescribed dose. The ANN was trained using the FL platform with the OMOP CDMs of Kyung Hee University Medical Center (KHMC) and Ajou University Hospital (AUH). Results The area under the receiver operating characteristic curves (AUROCs) for predicting bone fracture, osteonecrosis, and osteoporosis using only data from each hospital were 0.8426, 0.6920, and 0.7727 for KHMC and 0.7891, 0.7049, and 0.7544 for AUH, respectively. In contrast, when using FL, the corresponding AUROCs were 0.8260, 0.7001, and 0.7928 for KHMC and 0.7912, 0.8076, and 0.7441 for AUH, respectively. In particular, FL led to a 14% improvement in performance for osteonecrosis at AUH. Conclusions FL can be performed with the OMOP CDM, and FL often shows better performance than using only a single institution’s data. Therefore, research using OMOP CDM has been expanded from statistical analysis to machine learning so that researchers can conduct more diverse research.
The Impact of Aircraft Data on an Atlantic Cyclone Analyzed in Terms of Sensitivities and Trajectories

A case study of an eastern Atlantic cyclogenesis event is conducted. The focus is on the impact of aircraft data on both the analysis and forecast of the event. The case takes place between 1 and 3 February 1994 and involves a phase of explosive deepening. Several new techniques are brought to bear on this problem. An automatic tracking algorithm of vorticity maxima allows the construction of the cyclogenesis scenario in a relatively objective way. It also provides a clear depiction of some of the problems met in a sample of test forecasts. The origin of these problems is determined by employing the adjoint technique in order to point out which parts of the initial conditions are important in explaining the divergences between forecasts. The cyclogenesis is shown to result from successive baroclinic interactions of a surface vorticity maxima with two upper-level structures in a finite-length baroclinic zone. The largest impact on the forecast is shown to result not from a direct influence of the upper-level observations, but rather from an indirect effect via the observation selection algorithm. While the cyclone development clearly involves upper-level‐low-level interaction, the most detrimental difference in initial conditions originates at low levels.
A Novel Auxiliary Quadrature Particle Filtering Algorithm Based on Target Characteristic

For the nonlinear filtering problem of target tracking in aperiodic sparseness sampling environment,a novel auxiliary quadrature particle filter( AQPF) based on Gauss-Hermite quadrature and target characteristics is proposed.In the proposed algorithm,a set of quadrature point probability densities based on the Gauss-Hermite quadrature is proposed to approximate the important density function.At the same time,the proposed algorithm can incorporate target observation,time interval of the target observation and the target speed into the construction of important density function,which can effectively enhance the diversity of samples and improve the performance.Finally,the experimental results show that the performance of the proposed algorithm is better than these of the unscented Kalman filter( UKF),quadrature Kalman filter( QKF),particle filter( PF),auxiliary particle filtering( APF) and Gaussian particle filter( GPF),and can effectively estimate the target states.