Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian Differential Analysis of Cell Type Proportions

The analysis of cell type proportions in a biological sample should account for the compositional nature of the data but most analyses ignore this characteristic with the risk of producing misleading conclusions. The recent method scCODA appropriately incorporates these constraints by using a Bayesian Multinomial-Dirichlet model that requires a reference cell type to normalize the distribution of all cell types. However, a reference cell type that is stable across biological conditions may not always be available. Here, we present an approach that uses a Bayesian multinomial regression for the analysis of single cell distribution data without the need for a reference cell type. We show an implementation example using the rjags package within the R software.
Predictive Motor Control Based on a Generative Adversarial Network

Predictive processing models suggest that a brain decides actions through inference using its internal generative model over the world’s states and their transitions. Most of the predictive processing models have been formalized using explicit representations of the probability distributions, with explicit structures and parameters. They are difficult to learn in general and needs explanation about representation of structure and parameters of distributions, and the method for statistical arithmetic on them, each of which are questions not easy to answer. In this study, we explore an alternative representation for predictive processing which is based on an implicit model known as generative adversarial networks, which has been widely explored recently in machine learning studies as they can learn a distribution directly from data. We demonstrate how a generative adversarial network can be trained to learn an implicit generative model of motor dynamics. And then, we show that such a model can perform approximate inference using the trained model, providing the necessary computations for both the forward and inverse model of motor control. Our framework may provide another formalization for brain’s inference model, especially for learning process. Additionally, we suggest that the functional architecture of the cortical-basal ganglia circuit may modeled as the generator and discriminator in the generative adversarial network model.
Transmutation theory and rank for quantum braided groups

Abstract Let f: H1 → H2be any pair of quasitriangular Hopf algebras over k with a Hopf algebra map f between them. We construct in this situation a quasitriangular Hopf algebra B(H1, f, H2) in the braided monoidal category of H1-modules. It consists in the same algebra as H2 with a modified comultiplication and has a quasitriangular structure given by the ratio of those of H1 and H2. This transmutation procedure trades a non-cocommutative Hopf algebra in the category of k-modules for a more cocommutative object in a more non-commutative category. As an application, every Hopf algebra containing the group algebra of ℤ2 becomes transmuted to a super-Hopf algebra.
Binary black holes in stationary orbits and a test of the active galactic nucleus paradigm

We show that under certain astrophysical conditions a binary system consisting of two compact objects can be stabilized against indefinite shrinking of orbits due to the emission of gravitational radiation. In this case, the lighter binary companion settles down to a stable orbit when the loss of the angular momentum due to gravitational radiation becomes equal to its gain from the accreting matter from the disk around the more massive primary. We claim that such systems can be stable against small perturbations and can be regarded as steady emitters of gravitational waves of constant frequency and amplitude. Furthermore, X-rays emitted by the secondary can also produce astrophysically interesting situations when coupled with gravitational lensing and Doppler effects
Building structures within opal photonic crystals

The unique abilities of photonic crystals (PCs) to manipulate light lead to potential applications ranging from simple optical switches to an optical computer. Researchers are learning how to build PCs with better optical abilities by methods that include designing and fabricating deviations from the regular PC pattern. These deviations—called defects, although they are desirable—can channel light efficiently, but building defects in the structure is challenging. We have developed several methods for defining defect patterns inside of synthetic opal. Opals are naturally occurring 3D PCs: their microstructure consists of silica spheres about 150nm to 300nm in diameter, which are tightly packed into repeating hexagonal or cubic arrangements. Synthetic opals use this same pattern, although they can be made from different materials. A type of PC made using the the gaps between the spheres is called an inverse opal. Self-assembly methods allow us to make large polymer opals and inverse opals at low cost. Several research groups are focusing on fabricating complex 3D architectures in opals. David Norris at the University of Minnesota recently used multiphoton polymerization with a laserscanning confocal microscope to tailor air defects in opals. Also, George Zhao at the National University of Singapore described using an advanced photolithographic process to embed line defects in opals. We are developing two additional methods: using UV light to pattern the surface as the structure is built up; and using two-photon lithography to photopolymerize a resin inside an inverse opal structure, then writing embedded 3D patterns. The first method is analogous to patterning photoresists for photolithography, and offers the advantage of patterning the whole opal at once. In combination with a multilayer build-up method or with two-photon lithography, this scheme could even pattern the opal in 3D. To explain this method, we need to describe some of the steps and chemistry involved in making and Figure 1. UV light through a mask forms 3D defects inside photonic crystals during a multilayer growth process. Where crystallized photolabile colloids (red dots) are exposed to UV light, they form a soluble acid (green dots). After photo-stable core-shell-colloids form another layer of crystal, the exposed material can be washed out using an aqueous base. The top layer can be thermally crosslinked.
Remote Fault Diagnosis Method of Wind Power Generation Equipment Based on Internet of Things

According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)- based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value.
Study of Heterogeneous Academic Networks

Academic networks are derived from scholarly data. They are heterogeneous in the sense that different types of nodes are involved, such as papers and authors. This dissertation studies such heterogeneous networks for measuring the academic influence and learning vector representations of authors. Academic influence has been traditionally measured by the citation count and metrics derived from it. PageRank based algorithms have been used to give higher weight to citations from more influential papers. A better metric is to add authors into the citation network so that the importance of authors and papers are evaluated recursively within the same framework. Based on such heterogeneous academic networks, we propose a new algorithm for ranking authors. Tested on two large networks, we find that our method outperforms the other 10 methods in terms of the number of award winners among top-ranked authors. We further improve the method by finding and dealing with the long reference issue. Moreover, we find the mutual citation in paper networks and the self citation issue in author networks. Our new method can reduce the impact of the above three issues and identify more rising stars. To learn efficient author representations from heterogeneous academic networks, we propose a new embedding method called Stratified Embedding for Heterogeneous Networks (SEHN) based on Skip-Gram Negative Sampling (SGNS). We conduct Random Walks to generate the traces that represent the structure of the network, then separate the traces into different layers so that each layer contains the nodes of one type only. Such stratification improves embeddings that are derived from the mixed traces by a large margin. SEHN improves the state-of-the-art Metapath2vec by up to 24% at a certain point. The efficacy of stratification is also demonstrated on two classic network embedding algorithms DeepWalk and Node2vec. The results are validated in two heterogeneous networks. We also demonstrate that SEHN outperforms the embedding of homogeneous author networks that are induced from their corresponding heterogeneous networks.
Quality of older voices processed by hearing aids: Acoustic factors explaining inter-talker differences

Hearing aid signal processing algorithms are often evaluated with professional recordings of voices. However, hearing aid users often listen to older talkers who may have poorer voices than younger talkers. The purpose of this study was to quantify the extent to which the acoustic and perceptual consequences of hearing aid digital signal processing algorithms differ for talkers that vary in their vocal characteristics. There were five talkers (2 male and 3 female) selected from a larger database of 60 talkers; their voices had good, moderate or poor quality based on perceptual data from younger and older listeners. The voices were presented in quiet and in the presence of babble noise (-5 to +20 dB SNR). The voices were processed with varying amounts of frequency compression, wide dynamic range compression and noise suppression (spectral subtraction). There were interactions between signal processing and voice characteristics as measured using the Hearing Aid Speech Quality Index (HASQI) and listener rati.
Deep Level Transient Spectroscopy Analysis of 10 MeV Proton and 1 MeV Electron Irradiation-Induced Defects in p-InGaP and InGaP-based Solar Cells

Minority carrier injection annealing under forward-bias conditions is shown to enhance defect annealing in InGaP and to result in the recovery of solar cells properties. Such peculiar recovery of properties affected by radiation damage demonstrates that InGaP-based devices, under minority-carrier injection-mode operation, have superior radiation resistance compared to GaAs and Si. The first example of a recombination-enhanced mechanism in the ternary compound InGaP is also reported. We have performed detailed studies of the stability of the radiation-induced defect H2 in p-InGaP under various biases in order to determine the dependence of the reaction rate on the position of the Fermi level in the absence of minority carrier injection and recombination. Recombination-enhanced defect annealing of H2 causes a reduction of the minority carrier injection annealing activation energy, compared to thermal annealing from 1.69 eV to 0.52 eV. Analysis of the results reveals that the mechanism involved in the minority carrier injection annealing of the defect is the energy release mechanism, in which enhancement is induced by the energy that is released when a minority carrier is trapped at the defect site.
An Interval-Valued Fuzzy Reasoning Approach Based on Weighted Similarity Measure

This paper presents a new approach for bidirectional interval-valued fuzzy reasoning by employing a weighted similarity measure between the fact and the antecedent portion of production rule, in which the vague terms appearing are represented by interval-valued fuzzy concepts. One numeric example is given to demonstrate the reasonability and flexibility of our proposed approach.
Double white dwarfs as progenitors of R Coronae Borealis stars and type I supernovae

Close double white dwarfs should arise from the second phase of mass exchagne in close binaries which first encountered mass exchange while the more massive star was crossing the Hertzprung gap. Tidal mass transfer in these double degenerate systems is explored. The sequence of double white dwarf divides naturally into three segments. (1) Low-mass helium/helium pairs are unstable to dynamical time-scale mass transfer and probably coalesce to form helium-burning sdO stars. (2) In helium/carbon-oxygen pairs, mass transfer occurs on the time scale for gravitational radiation losses (approx.10/sup -4/ M/sub sun/ yr/sup -1/); the accreted helium is quickly ignited, and the accretor expands to dimensions characteristic of R CrB stars, engulfing its companion star. (3) Carbon-oxygen/carbon-oxygen pairs are again unstable to dynamical time-scale mass transfer and, since their total masses exceed the Chandrasekhar limit, are destined to become supernovae. Inactive lifetimes in these latter systems between creation and interaction can exceed 10/sup 10/ years. Birthrates of R CrB stars and Type I supernovae by evolution of double white dwarfs are in reasonable agreement with observational estimates.
A theoretical technique for evaluating the time-dependent effects of general electrodynamic drifts in the F2 layer of the ionosphere

A technique for solving the full global diffusion equation for the F2 layer, including electrodynamic ‘E x B’ drift, is presented. This involves considering the form of the diffusion equation in axes moving with the electrodynamic ‘E x B’ drift. In addition, it is shown how the region of integration, which involves complicated dipole geometry, may be mapped on to a semi-infinite rectangle. The method is illustrated by calculating world curves of electron density for a simple model atmosphere in which the electrodynamic ‘E x B’ drift and the electron production are time dependent and the electron loss coefficient is time independent. The calculations are compared with previous experimental results and confirm electrodynamic lifting as one of the major factors controlling the dip equatorial F2 layer and the associated trough of ionization as suggested by D. F. Martyn.
Synthesis of ordered large-scale ZnO nanopore arrays

An effective approach is demonstrated for growing ordered large-scale ZnO nanopore arrays through radio-frequency magnetron sputtering deposition on porous alumina membranes (PAMs). The realization of highly ordered hexagonal ZnO nanopore arrays benefits from the unique properties of ZnO (hexagonal structure, polar surfaces, and preferable growth directions) and PAMs (controllable hexagonal nanopores and localized negative charges). Further evidence has been shown through the effects of nanorod size and thermal treatment of PAMs on the yielded morphology of ZnO nanopore arrays. This approach opens the possibility of creating regular semiconducting nanopore arrays for the application of filters, sensors, and templates.
Emergence of agent swarm migration and vortex formation through inelastic collisions

Biologically inspired models of self-propelled interacting agents display a wide variety of collective motion such as swarm migration and vortex formation. In these models, active interactions among agents are typically included such as velocity alignment and cohesive and repulsive forces that represent agents' short- and long-range ‘sensing’ capabilities of their environment. Here, we show that similar collective behaviors can emerge in a minimal model of isotropic agents solely due to a passive mechanism—inelastic collisions among agents. The model dynamics shows a gradual velocity correlation build-up into the collective motion state. The model displays a discontinuous transition of collective motion with respect to noise and exhibits several collective motion types such as vortex formation, swarm migration and also complex spatio-temporal group motion. This model can be regarded as a hybrid model, connecting granular materials and agent-based models.
A critical appraisal of asymptotic 3D-to-2D data transformation in full-waveform seismic crosshole tomography

ABSTRACTSeismic full-waveform inversion (FWI) is often based on forward modeling in the computationally attractive 2D domain. This implies the assumption of a line source extended in the out-of-plane medium invariant direction, with far-field amplitudes decaying inversely with the square root of distance. Realistic point sources, however, generate amplitudes that decay approximately with the inverse of distance. Conventionally, practitioners correct for this amplitude difference and the associated phase shift by transforming the recorded 3D field data to the approximate 2D equivalent by using simplistic asymptotic filter algorithms. Such filters assume straight raypaths, a constant velocity medium, and far-field recordings. We have assessed the validity of 3D-to-2D data transformation in the context of crosshole seismic full-waveform tomography by propagating 3D and 2D wavefields through 2D media and comparing 2D reference synthetics with their filtered 3D equivalent. The filter performs well in simple si.
Low-cost adaptive optical system for a diode-pumped YAG solid-state laser system

A low cost adaptive optical system for improving solid-state laser beam quality has been set up. This system consists of a deformable mirror, a high voltage amplifier, a set of solid-state laser system, a CCD camera, a control software and corresponding optimization algorithm. This adaptive optical system doesn't employ a wave-front sensor to detect the phase information, but optimize the light intensity within a fixed aperture in the focal plane by a 19-element piezoelectricity deformable mirror. In order to find the optimum surface profile of the deformable mirror, which is applied to correct the phase aberrations in a solid-state laser system, a global genetic algorithm is introduced. The far-field light intensity signal, which is measured by a CCD camera, is used as a fitness function of the genetic algorithm. In this paper, the performance and efficiency of this wave-front sensor-less adaptive optical system based on the genetic algorithm are presented. Both the simulation results and the experimental results are given and discussed.
Recursive forgetting algorithms

Fn the first part of this paper, a general forgetting algorithm is formulated and analysed. It contains most existing forgetting schemes as special cases. Conditions are given ensuring that the basic convergence properties will hold. In the second part of the paper, the results are applied to a specific algorithm with selective forgetting. Here, the forgetting is non-uniform in time and space. The theoretical analysis is supported by a simulation example demonstrating the practical performance of this algorithm.
Ensemble-Based Error and Predictability Metrics Associated with Tropical Cyclogenesis. Part II: Wave-Relative Framework

AbstractThe predictability of selected variables associated with tropical cyclogenesis is examined using 10-day ECMWF ensemble forecasts for 21 events from the 2010 Atlantic hurricane season. Variables are associated with the strength of the pregenesis disturbance, quantified via circulation and thickness anomaly, and the favorability of the immediate environment via moisture and vertical wind shear.For approximately half of the cases, the predicted strength of the genesis signal is directly related to the predicted favorability of the environment. For the remainder of the cases, predictability is more directly associated with the strength and location of the analyzed disturbance. Some commonalities among the majority of the sample are also observed. Forecast joint distributions demonstrate that 700-hPa relative humidity of less than 60% within 300 km of the circulation center is a limiting factor for genesis. Genesis is also predicted and found to occur in the presence of significant wind shear (~15 m s−.
SOME TEST THEORY FOR TAILORED TESTING

In a tailored test, each item is selected for administration on the basis of the examinee's responses to previous items, with a view towards optimum measurement of this particular examinee. Various simple rules for 1) selecting the items to be administered and 2) scoring the examinee's responses are compared and evaluated. Some fundamental ideas emerge that will serve as guides in the future design of tailored testing programs.
An exceptionally bright, compact starburst nucleus

Observations are reported of a remarkably bright (V about 13) starburst nucleus, 0833 + 652, which has been detected at radio, infrared, optical, ultraviolet, and X-ray wavelengths. Despite an observed flux at each of these wavelengths which is comparable to that of NGC 7714, often considered the 'prototypical' example of the starburst phenomenon, 0833 + 652 appears to be a previously uncataloged object. Its ease of detectability throughout the electromagnetic spectrum should make it useful for a variety of problems in the study of compact emission-line galaxies. 30 references.
Simultaneous fault detection and control for uncertain linear discrete-time systems

This paper studies the simultaneous fault detection and control problem for linear uncertain discrete-time systems. A design procedure dealing with polytopic uncertainties is proposed for residual generation, where both the fault detection objectives and some control objectives are considered simultaneously through certain performance indexes. To cope with the fault sensitivity performance index in a given frequency range directly, the generalised KYP lemma is introduced in this framework. A two-step procedure is adopted to obtain the solutions through satisfying a set of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed methods.
E×B advection of trace ions in tokamak microturbulence

The E×B advection of trace ions in realistic tokamak microturbulence (as described by nonlinear gyrokinetics) is investigated. In order to understand the consequences of effects such as large gyroradii, fluctuation anisotropies, zonal flows, or poloidal drifts, they are first studied in the framework of a model that is based on self-created stochastic potentials. Direct numerical simulations are performed, and a semi-analytical model is presented that provides qualitative as well as quantitative insight into the nature of passive tracer transport. One finds that the resulting diffusivities may be larger than expected as long as the gyroradii do not exceed the turbulence correlation length(s) and the poloidal drift velocities are sufficiently small.
Improvement of output characteristics of a relativistic magnetron by creating asymmetric radio-frequency magnetic fields

Asymmetric magnetic field geometry is explored by inserting three metal tuners asymmetrically into the resonators of the A6 magnetron. The authors investigate the operating characteristics of a relativistic magnetron with asymmetrically perturbed radio-frequency (rf) magnetic fields caused by metal tuners using a three dimensional, electromagnetic particle-in-cell code MAGIC3D. By configuring perturbed rf magnetic fields, the operating characteristics of a relativistic magnetron are superior compared to those using uniform rf magnetic fields. Most significantly, by creating asymmetrically perturbed rf magnetic fields, the output power of the A6 magnetron increased by about 40% compared to the case of uniform rf magnetic fields.