Miracle-dz/UniFAR-FTUs huggingface dataset:
Accretion onto a Moving Black Hole: A Fully Relativistic Treatment

The effect of constant-rate motion through a uniform adiabatic medium on the steady-state accretion of matter onto a Schwarzschild black hole is investigated theoretically by means of numerical simulations. The derivation of the model is given in detail, and the results are presented in extensive graphs. The appearance of the flows and the accretion rates are found to be in good agreement with published data for the Newtonian regime and generally similar for the relativistic case. 28 references.
Prediction of Plasma Discharge Video by Convolutional Long Short-Term Memory

In the National Institute for Fusion Science, high-temperature plasmas have been produced in the Large Helical Device (LHD). A large number of videos having plasma discharge are captured during nuclear fusion operations. An observation of these recorded videos can lead to a new discovery and guarantee the safe operation of the experiments. In order to optimize the operational parameter of the experiment, the future emission states of plasmas should be estimated. Thus, this paper proposes a method to make a prediction of sequential future frames containing plasma light emission using the Convolutional Long Short-Term Memory (ConvLSTM). We confirmed that the future frames of plasma discharge could be well predicted with the satisfactory results of Mean Squared Error as 2.78×10-5 and Cosine Similarity as 0.9997.
That brachycephalic look: Infant-like facial appearance in short-muzzled dog breeds

Brachycephalic dog breeds are highly popular, yet their conformation-related disorders represent a major welfare concern. It has been suggested that the current popularity of such breeds can be explained by their cute, infant-like facial appearances. The concept of ‘kindchenschema’ refers to the observation that certain physical features of infant humans and other animals can automatically stimulate positive and nurturant feelings in adult observers. But the proposal that brachycephalic dogs possess heightened ‘kindchenschema’ facial features, even into adulthood, has never been formally investigated. Here, we hypothesised that relative muzzle shortening across a range of breeds would be associated with known ‘kindchenschema’ facial features, including a relatively larger forehead, larger eyes and smaller nose. Relative fronto-facial feature sizes in exemplar photographs of adult dogs from 42 popular breeds were measured and associated with existing data on the relative muzzle length and height-at-withers of the same breeds. Our results show that, in adulthood, shorter-muzzled breeds have relatively larger (taller) foreheads and relatively larger eyes (i.e. area of exposed eyeball relative to overall face area) than longer-muzzled breeds, and that this effect is independent of breed size. In sum, brachycephalic dog breeds do show exaggeration of some, but not all, known fronto-facial ‘kindchenschema’ features, and this may well contribute to their apparently cute appearance and to their current popularity as companion animals. We conclude that the challenge of addressing conformation-related disorders in companion dogs needs to take account of the cute, ‘kindchenschema’ looks that many owners are likely to be attracted to.
AN EMPIRICAL MODELLING ON SAVINGS BEHAVIOUR IN MALAYSIA

The purpose of this study is to re-investigate the savings behaviour in Malaysia through the cointegration and causality analyses. This study covered the annual data from 1970 to 2004. The results of bounds test confirmed a long run equilibrium relationship between savings and its determinants, namely real income, dependency ratio and real interest rates. The study found that the major causes of savings in Malaysia are real income and dependency ratio. On the other hand, the effect of real interest rate on savings in Malaysia is less. Therefore, monetary policy is not an effective macroeconomic policy instrument to encourage savings in Malaysia although savings and interest rates showed bilateral causality. In addition, savings Granger caused economic growth in Malaysia and the study found that households in Malaysia are very protective and the savings behaviour is driven by the precautionary savings.
A Branch-sensitive 3D Convolutional Neural Networks for Airway Segmentation

CT scans are an exceptional tool for quantitative airway analysis. Due to the complex voxel connectivity and branch structure of the airway, precise and fine segmentation results are difficult to accomplish. We propose a fully automated and end-to-end approach for airway segmentation and branch detection in chest CT based on U-Net architecture. We introduce the SE Normalization as a module for feature calibration and the hard region adaptation loss function based on cross entropy (HRA_CE) for dynamically maintaining class balance throughout the training period. We present a brand-new metric Branch DSC designed exclusively to assess the branch structure. We validate the suggested method on a dataset of 46 airway samples, and the experimental findings demonstrate that our proposed method significantly improves branch detection and segmentation continuity.
Optical performance requirements for MEMS-scanner-based microdisplays

High-resolution and high frame rate dynamic microdisplays can be implemented by scanning a photon beam in a raster format across the viewer's retina. Microvision is developing biaxial MEMS scanners for such video display applications. This paper discusses the optical performance requirements for scanning display systems. The display resolution directly translates into a scan-angle-mirror-size product and the frame rate translates into vertical and horizontal scanner frequencies. (theta) -product and fh are both very important figures of merit for scanner performance comparison. In addition, the static and dynamic flatness of the scanners, off-axis motion and scan repeatability, scanner position sensor accuracy all have a direct impact on display image quality.
A Bibliometric Analysis of Synchronous Computer-Mediated Communication in Language Learning Using VOSviewer and CitNetExplorer

Synchronous computer-mediated communication in the online language classroom has gained growing attention in the wake of the worldwide epidemic. Nevertheless, only a few researchers have studied it through bibliometric analyses. This study aimed to retrospect the previous development and figure out the role of intercultural competence, social presence, and corrective feedback in synchronous computer-mediated communication-based language learning. Both quantitative and qualitative methods were employed to analyze previous studies (n = 1292) by VOSviewer and CitNetExplorer. The findings revealed prolific authors, sources, organizations, and regions in tables, which indicated that scholars in this field were mainly located in the USA and China. With a rising research tendency, several heated topics were also presented with VOSviewer. The findings also signified that intercultural competence, social presence, and corrective feedback all played an important role in synchronous computer-mediated communication-based language learning and they were interdependent. Implications for future studies were also discussed.
The effect of wall interactions in capillary-zone electrophoresis

Capillary-zone electrophoresis (CZE) is an efficient separation method in analytical chemistry. It exploits the difference in electrophoretic migration speeds between charged molecular species in aqueous solution when an external electric field is applied to achieve separation. In most cases the electrophoretic migration of species is also accompanied by a bulk electro-osmotic flow in the capillary due to the presence of a zeta-potential at the capillary wall. Adsorption of charged species at the wall could modify this zeta-potential in a non-uniform manner. This induces axial pressure gradients, so that the flow is no longer uniform over the capillary cross-section. The resulting shear-induced dispersion of the sample is a serious cause of band broadening in CZE particularly for species such as proteins and peptides which adsorb strongly on capillary walls. The problem of the spatio-temporal evolution of the sample concentration is studied in the presence of such wall interactions. An asymptotic theory is developed that is valid provided axial variations have characteristic length scales that are much larger than the capillary radius and temporal variations have a characteristic time scale much larger than the characteristic diffusion time over a capillary radius. These conditions are normally satisfied in CZE, except when the sample is close to the inlet, on account of the capillary length being very much larger than its radius. It is shown that the cross-sectionally averaged sample concentration obeys a one-dimensional partial differential equation. Further, the full three-dimensional concentration field may be calculated once the cross-sectionally averaged concentration field is known. The reduced system is integrated numerically and is shown to lead to predictions consistent with known observations on CZE in the presence of wall interactions.
Approximative solution of the coagulation–fragmentation equation by stochastic particle systems

This paper studies stochastic particle systems related to the coagulation fragmentation equation. For a certain class of unbounded coagulation kernels and fragmentation rates, relative compactness of the stochastic systems is established and weak accumulation points are characterized as solutions. These results imply a new existence theorem. Finally a simulation algorithm based on the particle systems is proposed
Generation and detection of millimeter waves by picosecond photoconductivity

Picosecond photoconductors in the form of dielectric resonators have been used to generate and detect extremely short bursts of millimeter wave radiation at 55 GHz with a repetition rate of 100 MHz. Both the generator and detector are tuned to a frequency which is determined by the length of the photoconducting dielectric resonators. The detector, which is phase coherent, has an estimated noise equivalent power of only 4×10−11 W for an integration bandwidth of 1 Hz, and is capable of resolving time intervals corresponding to a small fraction of one millimeter‐wave cycle.
Deep Learning for Destination Choice Modeling: A Fundamental Approach for National Level People Flow Reconstruction

With the rapid trend of developing Smart Cities and Digital Twins, a better understanding of how humans move and perform a daily routine in the city area is vital. Benefiting from the recent rapidly growing location acquisition techniques, existing deep learning approaches can effectively model and predict human mobility with human mobility big data. However, it is still challenging to simulate human mobility at the population level because only the individuals with plentiful historical data can be well modeled. Moreover, the differences in complex city layouts and functions prevent us from applying the trained models to different cities. Therefore, in this study, we propose an alternative deep learning framework focusing on the destination choice to reconstruct nationwide human mobility at the population level. We design a new embedding mechanism for handling the traveler’s demographics, mobility characteristics, travel intention, and context information of locations to enrich the representations for the model prediction. Then a neural network is trained with the People Flow Dataset. We evaluated our approach based on multiple urban areas using different training data and demonstrated the advantages of our method compared with other baseline approaches.
Environmental sound classification of western black-crowned gibbon habitat based on OpenPAI

In a number of cutting-edge application fields, including image identification, speech and natural language processing, and autonomous driving, machine learning has had considerable success recently. In this study, we use the western black-crowned gibbon song data as the research object and the Kubernetes-based OpenPAI machine learning platform to categorize five environmental sounds in the western black-crowned gibbon habitat in the Mourning Mountains with an accuracy of 97.24%.
Multicritical matter from complex matrices

A large N-matrix model of a general complex matrix generates dynamical triangulations in which the triangles can be chequered (i.e. coloured so that neighbours are opposite colours). Gravity and multicritical matter in such triangulations are described by the KdV-type equations found in the Hermitian matrix model but without the doubling of degrees of freedom. However, by tuning further couplings it is possible to obtain a series of more general string equations with redoubled degrees of freedom.
On the Effects of Moderate Multivariate Nonnormality on Roy's Largest Root Test

Abstract The asymptotic distribution of Roy's largest root statistic in multivariate Edgeworth populations is expanded to terms of the first order. To this order, the effects of non-normality are expressed by Mardia's measures of multivariate skewness and kurtosis, together with a supplementary skewness measure. Tables of corrections to the nominal significance level are presented for the k-sample MANOVA situation. Comparison with simulation results indicates that the correction terms provide a useful indication both of the magnitude and the direction of the effect of nonnormality on the nominal 5 percent Type I error, even when the underlying population is not well represented by an Edgeworth expansion, provided that the skewness and kurtosis are not too large.
Improving the performance of disease detection from chest X-ray images using deep learning

Early diagnosis of thorax diseases is very important for saving lives. Recently, deep learning approaches are applied to multilabel classification of chest X-ray images, which yields an emerging field of AI diagnosis, However, so far, there are still some performance problems when using it in hospitals and clinics. This study aims to compare and analyze different ways to balance data for image classification, as well as propose a method of combining different models to improve classification performance. Furthermore, a web diagnostic system introduced the results of this study is implemented. It will contribute to helping doctors to detect chest diseases more accurately, easily, and quickly.
Outlier Elimination Procedure for Power Curve Modeling of Wind Generation

The estimation of power curve is the central task for efficient operation and prediction of wind power generation. It is often the case, however, that the actual data exhibit a great deal of variations in power output with respect to wind speed, and thus the power curve estimation necessitates the detection and proper treatment of outliers. This study proposes a novel procedure for outlier detection and elimination for estimating power curves of wind farms by employing clustering algorithms. Employing different parametric models of power output curve, the proposed methodology is demonstrated for obtaining power curves of individual wind turbines in a Korean wind farm.
Open-Phase Fault-Tolerant Control Approach for EV PMSM based on Four-Leg VSI

The major malfunction of Permanent Magnet Synchronous Motor (PMSM) in Electric Vehicle (EV) applications is an open-phase defect, which degrades motor efficiency and increases losses due to unbalanced phase currents. Traditional Fault-Tolerant Control (FTC) techniques, on the other hand, could suffer from the monitoring problems of sinusoidal-shaped current references. In this study, a proposed fault-tolerant approach for open-phase during the driving cycle and starting of the PMSM is suggested, which differs from earlier fault-tolerant techniques by suggesting a proposed compensating transformation matrix for current and voltage references in the d-q rotating reference frame will be translated to the phase current and voltage references of the two healthy remaining phases. The proposed setup enables the EV to be operated under open-phase fault-tolerant (OPFT) with simple controller and high performance. Furthermore, since the proposed system depends on a four-leg inverter, it has a higher fault-tolerance capability than the three-phase Voltage Source Inverter (VSI) technique, to also compensate the possibility of loss of any VSI leg, but for sure with additional cost of the overall drive system. Eventually, the simulation output results supported the suggested fault-tolerant approach under Field-Oriented Control (FOC) for different modes of operations.
Dot-Product Similarity based Centroid Clustering for Popular Topic Detection

Huge amount of user generated contents are being created in major social media everyday. It’s very difficult for users to quickly grasp the most important topics from such big data. Document clustering techniques are often used for topic detection from news, but it’s still challenging for social media. Firstly, since social media posts are usually very short, it’s hard to capture their semantic meanings. Secondly, given huge amount of social media posts, clustering effectiveness becomes unacceptable. Among agglomerative hierarchical clustering methods, centroid clustering is much more efficient, but with the issue of inversion or reversals. In this paper, we propose to detect popular topics from social media posts using dot-product similarity based centroid clustering of their word embeddings. Firstly, we extract keywords in posts with word segmentation, where documents are represented by word embedding of keywords. Secondly, various topics are extracted from the clustering results of social media posts by calculating dot-product similarity of their word embeddings. Finally, the popularity of each topic is estimated by the aggregate sentiment ratings from user replies. From the experimental results on PTT discussion forum, centroid clustering with dot-product similarity of word embeddings achieves better clustering efficiency with comparable effectiveness in terms of Adjusted Rand Index (ARI) and Adjusted Mutual Information (AMI). Further investigation is needed to verify the effectiveness in different social media sources.
Research on experimental measurement of regular objects bistatic LRCS and scaling relations

In this paper, the bistatic LRCS of Teflon spheres of different size is measured by laser scattering automatic measurement system in laboratory and bistatic LRCS measurement system outdoor respectively, and the bistatic LRCS of standard Lambert spheres of the same size is calculated. The experimental results show that Teflon sphere has obvious coherent scattering when the bistatic angle is smaller than 10°. The experimental results coincide with the theoretical calculation when the bistatic angle is bigger than 10°. Scaling relations of the bistatic LRCS is also studied in experiment, the relative error between the experimental results of scaling relations and the theoretical calculation results of scaling relations of the same size Lambert sphere is smaller than 10 percent, which satisfies the requirements of Engineering. It is demonstrated that outdoor measurement method has valuable usage in engineering practice to measure the bistatic LRCS of large object.
Simple and complete formulation to compute propagation constants of photonic crystal fibers and predict their total chromatic dispersion

Within the scalar framework, a simple and complete formulation for the normalized propagation constants of the infinite cladding region of a photonic crystal fiber (PCF) with triangular lattice of air-holes is presented, which is dependent only on the ratio of air-hole diameters and their separation. The accuracy of the proposed formulation is depicted by comparing our results with those obtained by Russell. Then the refractive indices of the fundamental space-filling mode (nFSM) in the cladding region of the PCF from Russell's equation and the proposed relations are evaluated and the two indices are observed to match quite excellently for different values of relative air-hole size and wavelength. An equivalence between the two approaches of Russell and Saitoh is also sought. Finally, in order to check the validity of the formulation in problems of practical interest, the proposed relations are applied to evaluate the total chromatic dispersion in a PCF, treating it as a conventional step index fiber having its core and cladding indices as those of silica and nFSM, respectively. On comparison with the available results of Saitoh, the results match nicely.
A compact ring modulator with very large extinction ratio and high quality factor fabricated in AIM photonics technology at Albany Nanotech Complex

In this work, we demonstrate a compact pn junction ring modulator with very large extinction ratio and high quality factor. The modulator consists of a 5-μm radius ring and a single-bus straight waveguide. Both the ring and straight waveguides have a width of 480 nm and heigh of 220 nm. The waveguides are rib-structured and the rib thickness is 110 nm with a slab thickness of 110 nm from a 300mm wafer with 220-nm silicon-on-insulator (SOI) thickness. A 100-nm gap is designed between the rib ring and the bus waveguides. The modulator has three nominal doping levels with concentrations of 1018, 1019, and 1020 cm-3 for the core, slab, and the contact areas, respectively. The device is fabricated using the American Institute for Manufacturing integrated Photonics (AIM Photonics) Multi-Project Wafer (MPW) service. It is tested using the AIM Photonics inline vertical gratting coupled automated tool with a tunable light source that has wavelengths ranging from 1485 nm to 1590 nm and a wavelength resolution of 60 pm. The fabricated 5-μm radius ring modulator exhibits high quality output with a very large extinction ratio of 29 dB over a broad wavelength spectrum of about 100 nm. The device has a very wide free spectral range (FSR) of about 19 nm.
Silver Is Not Equal to Silver: Synthesis and Evaluation of Silver Nanoparticles with Low Biological Activity, and Their Incorporation into C12Alanine-Based Hydrogel

A new type of silver nanoparticles (AgNPs) was prepared and comprehensively studied. Scanning electron microscopy (SEM) and dynamic light scattering (DLS) analyses indicated that 24 nm AgNPs with narrow size distribution were obtained while Z-potential confirms their good stability. The composites of the obtained AgNPs with nontoxic-nature-inspired hydrogel were formed upon cooling of the aqueous solution AgNPs and C12Ala. The thermal gravimetric analysis (TGA) and the differential scanning calorimetry (DSC) do not show significant shifts in the characteristic temperature peaks for pure and silver-enriched gels, which indicates that AgNPs do not strongly interact with C12Ala fibers, which was also confirmed by SEM. Both AgNPs alone and in the assembly with the gelator C12Ala were almost biologically passive against bacteria, fungus, cancer, and nontumor human cells, as well as zebra-fish embryos. These studies proved that the new inactive AgNPs-doped hydrogels have potential for the application in therapy as drug delivery media.
Using Results From Replicated Studies to Estimate Linear Models

This article outlines analyses for the results of a series of studies examining intercorrelations among a set of p + 1 variables. A test of whether a common population correlation matrix underlies the set of empirical results is given. Methods are presented for estimating either a pooled or average correlation matrix, depending on whether the studies appear to arise from a single population. A random effects model provides the basis for estimation and testing when the series of correlation matrices may not share a common population matrix. Finally, I show how a pooled correlation matrix (or average matrix) can be used to estimate the standardized coefficients of a regression model for variables measured in the series of studies. Data from a synthesis of relationships among mathematical, verbal, and spatial ability measures illustrate the procedures.