Miracle-dz/UniFAR-FTUs huggingface dataset:
Under review as a conference paper at ICLR 2016

We describe a method for learning word embeddings with stochastic dimensionality. Our Infinite Skip-Gram (iSG) model specifies an energy-based joint distribution over a word vector, a context vector, and their dimensionality. By employing the same techniques used to make the Infinite Restricted Boltzmann Machine (Côté & Larochelle, 2015) tractable, we define vector dimensionality over a countably infinite domain, allowing vectors to grow as needed during training. After training, we find that the distribution over embedding dimensionality for a given word is highly interpretable and leads to an elegant probabilistic mechanism for word sense induction. We show qualitatively and quantitatively that the iSG produces parameter-efficient representations that are robust to language’s inherent ambiguity.
Persistence length convergence and universality for the self-avoiding random walk

In this study, we show the convergence and new properties of persistence length, , for the self-avoiding random walk model (SAW) using Monte Carlo data. We generate high precision estimates of several conformational quantities with a pivot algorithm for the square, hexagonal, triangular, cubic and diamond lattices with path lengths of 103 steps. For each lattice, we accurately estimate the asymptotic limit , which corroborates the convergence of to a constant value, and allows us to check the universality on the curves. Based on the estimates we make an ansatz for dependency with lattice cell and spatial dimension, we also find a new geometric interpretation for the persistence length.
Formation of power law spectra of energetic electrons during multiple X line magnetic reconnection with a guide field

In this paper, with a two-dimensional particle-in-cell simulation model, we study the formation of power-law spectra of energetic electrons in multiple X line magnetic reconnection with a strong guide field. The processes of both magnetic reconnection and electron acceleration can be separated into two stages. In the first stage, two X lines appear at the border and center of the simulation domain, and then, two magnetic islands are formed. In this stage, electrons are accelerated mainly by parallel electric fields, and a power-law spectrum of energetic electrons is generated with the appearance of the second X line. In the second stage, the two magnetic islands are merged into one big island. Besides parallel electric fields, the Fermi mechanism also plays an important role in the production of energetic electrons, and its contribution is comparable to that of parallel electric fields when the electron energy is sufficiently large. In this stage, the generated power-law spectrum of energetic electrons becomes hard. In general, the acceleration efficiencies by both the parallel electric fields and Fermi mechanism become higher with the increase in electron energy, and the tendency is more obvious for the Fermi mechanism. Therefore, both the parallel electric fields and Fermi mechanism are important in the formation of power-law spectra of energetic electrons during multiple X line reconnection. We also investigate the influences of the ion-electron temperature ratio, guide field, and initial flux perturbation on the formed power-law spectra of energetic electrons.In this paper, with a two-dimensional particle-in-cell simulation model, we study the formation of power-law spectra of energetic electrons in multiple X line magnetic reconnection with a strong guide field. The processes of both magnetic reconnection and electron acceleration can be separated into two stages. In the first stage, two X lines appear at the border and center of the simulation domain, and then, two magnetic islands are formed. In this stage, electrons are accelerated mainly by parallel electric fields, and a power-law spectrum of energetic electrons is generated with the appearance of the second X line. In the second stage, the two magnetic islands are merged into one big island. Besides parallel electric fields, the Fermi mechanism also plays an important role in the production of energetic electrons, and its contribution is comparable to that of parallel electric fields when the electron energy is sufficiently large. In this stage, the generated power-law spectrum of energetic electrons be.
jLDADMM : A Java package for the LDA and DMM topic models Dat

The Java package jLDADMM is released to provide alternatives for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models.
Output regulation in the presence of quadratically bounded parameter uncertainties

The problem of robust output regulation is studied for a class of parameter uncertain systems under unity output feedback control. The objective is tracking of the desired reference trajectory in the presence of the disturbance, both generated by a common exosystem. Because of the anti-stability of the exosystem and potentially unbounded reference trajectory, the output tracking error is employed as the measurement signal and used as the input to the feedback controller. The method of p-copy of the internal model is utilised to augment the plant dynamics. Assuming that the output regulation condition is satisfied for all the parameter uncertainties, it is shown that the problem of robust output regulation is equivalent to the problem of robust output stabilisation. Furthermore, for quadratically bounded parameter uncertainties, an application of the notion of the quadratic stability leads to H ∞ -based robust control, and the maximum allowable uncertainty bound can be computed, below which the robust output regulation can be achieved.
An efficient neural network approach for nanoscale FinFET modelling and circuit simulation

The present paper demonstrates the suitability of artificial neural network (ANN) for modelling of a FinFET in nano‐circuit simulation. The FinFET used in this work is designed using careful engineering of source–drain extension, which simultaneously improves maximum frequency of oscillation ƒmax because of lower gate to drain capacitance, and intrinsic gain AV0 = gm/gds, due to lower output conductance gds. The framework for the ANN‐based FinFET model is a common source equivalent circuit, where the dependence of intrinsic capacitances, resistances and dc drain current Id on drain–source Vds and gate–source Vgs is derived by a simple two‐layered neural network architecture. All extrinsic components of the FinFET model are treated as bias independent. The model was implemented in a circuit simulator and verified by its ability to generate accurate response to excitations not used during training. The model was used to design a low‐noise amplifier. At low power (Jds∼10 µA/µm) improvement was observed in both third‐order‐intercept IIP3 (∼10 dBm) and intrinsic gain AV0 (∼20 dB), compared to a comparable bulk MOSFET with similar effective channel length. This is attributed to higher ratio of first‐order to third‐order derivative of Id with respect to gate voltage and lower gds in FinFET compared to bulk MOSFET. Copyright © 2009 John Wiley & Sons, Ltd.
The Effect of Capital Market Knowledge , Return , Risk Perception , and Technological Advancement on Investment Interest in Social Media ( Case Study on Followers of the Instagram Account of @ ngertisaham )

Purpose: This study aims to determine and investigate the effect of capital market knowledge, return, risk perception, and technological advancement on investment interest in social media. Methodology: The present study employs a descriptive research design that utilizes quantitative methods. The study's population consisted of followers of the @ngertisaham account on Instagram. A sample of 100 respondents was collected using the Slovin formula. The data collection methodology applies a questionnaire, and next, the acquired data is processed employing the IBM SPSS Statistics version 25 software application. The data analysis technique uses a validity test, reliability test, classical assumption test, and hypothesis testing (multiple linear regression analysis, coefficient of determination, f-test, and t-test). Findings: The findings of this study show that there is only a partial relationship between capital market knowledge, technological advancement, and investment interest among Instagram followers of the @ngertisaham account. However, this relationship is not significant. In contrast, the return and risk perception variables show positive and statistically significant effects on investment interest among Instagram followers of the @ngertisaham account. Novelty: The novelty aspect of this study is using respondents of Instagram followers of the @ngertisaham account.
Size-Depth Tradeo(cid:11)s for Algebraic Formulae (cid:3)

We prove some tradeo(cid:11)s between the size and depth of algebraic formulae. In particular, we show that, for any (cid:12)xed (cid:15) > 0, any algebraic formula of size S can be converted into an equivalent formula of depth O(logS) and size O(S 1+(cid:15) ). This result is an improvement over previously-known results where, to obtain the same depth bound, the formula-size is (cid:10)(S (cid:11) ), with (cid:11) (cid:21) 2.
Ensemble Sensitivity Analysis for Targeted Observations of Supercell Thunderstorms

Ensemble sensitivity analysis (ESA) has been demonstrated for observation targeting of synoptic-scale and mesoscale phenomena, but could have similar applications for storm-scale observations with mobile platforms. This paper demonstrates storm-scale ESA using an idealized supercell simulated with a 101-member CM1 ensemble. Correlation coefficients are used as a measure of sensitivity and are derived from single-variable and multivariable linear regressions of pressure, temperature, humidity, and wind with forecast response variables intended as proxies for the strength of supercells. This approach is suitable for targeting observing platforms that simultaneously measure multiple base-state variables. Although the individual correlations are found to be noisy and difficult to interpret, averaging across small areas of the domain and over the duration of the simulation is found to simplify the analysis. However, it is difficult to identify physically meaningful results from the sensitivity calculations, and evaluation of the results suggests that the overall skill would be low in targeting observations at the storm scale solely based on these sensitivity calculations. The difficulty in applying ESA at the scale of an individual supercell is likely due to applying the linear model to an environment with highly nonlinear dynamics, rapidly changing forecast metrics, and autocorrelation.
Hypocoercivity

This memoir attempts at a systematic study of convergence to stationary state for certain classes of degenerate diffusive equations, by means of well-chosen Lyapunov functionals. Typical examples are the kinetic Fokker--Planck and Boltzmann equation. Many open problems and possible directions for future research are discussed.
Prototype modelling of body surface maps using tangent distance

In recent years the tangent distance approach of Simard et al (1993) to pattern recognition tasks such as handwritten character recognition has proven successful. Simard’s distance measure could be made locally invariant to any set of transformations of the input and when implemented in one-nearest-neighbour classification of handwritten digits, outperformed all other classification schemes. Hastie et al (1996) propose prototype models which generalise the concept of a centroid of a set of images in the Euclidian metric to a low-dimensional hyperplane in the tangent metric, and these prototypes can be used to reduce lookup time in classification. We propose to apply and extend the tangent distance approach to classify a set of body surface maps, which are recordings of the electrical activity of the heart, of a large number of patients with various cardiac conditions. Using a grid of p electrodes attached to the anterior chest, we calculate a number of p-dimensional observation vectors for each patient and classify input maps on the basis of overall distance of map to prototypes derived from training set maps over all included observation vectors.
Development and characterisation of a Portland cement-based dental root filling material.

Mineral trioxide aggregate (MTA) is a Portland cement (PC)-based endodontic material used for sealing root canals. This study investigated the effect of calcium sulphate additions for improving the undesirably-long setting time of MTA-like dental materials, whilst maintaining the mechanical, biological and sealing properties. 10wt%PoP accelerated initial setting times of grey and white model cements and MTA from >6h to <40min, and did not significantly change compressive strengths and relative porosities with long-term storage in media. Cement pastes containing PoP may „false‟ set or stiffen through gypsum precipitation, seen in scanning electron photomicrographs of MTA-like cements with 30wt%PoP. Similar in vitro responses of adult and neonatal BMSC, periosteal and osteoblastic cultures were noted with PoP-modified and unmodified cements. Inhibition of cell growth was seen with 3day-cultures containing modified model cements and MTA, the possible result of calcium hydroxide release from cements. Sealing properties were characterised using dye leakage studies and concluded that the sealing abilities of model cements and MTA were not compromised by PoP addition. In summary, 10wt%PoP has shown potential as a modification to MTA by reducing the setting time whilst maintaining mechanical stability, solubility, in vitro responses to and the sealing properties of MTA, therefore, warrants further investigation.
Reconfiguration algorithms for high precision communications in time sensitive networks: Time-aware shaper configuration with IEEE 802.1Qcc

As new networking paradigms emerge for different networking applications, e.g., cyber-physical systems, and different services are handled under a converged data link technology, e.g., Ethernet, certain applications with mission critical traffic cannot coexist on the same physical networking infrastructure using traditional Ethernet packet-switched networking protocols. The IEEE 802.1Q Time Sensitive Networking (TSN) Task Group is developing protocol standards to provide deterministic properties, i.e., eliminates non-deterministic delays, on Ethernet based packet-switched networks. In particular, the IEEE 802.1Qcc, centralized management and control, and the IEEE 802.1Qbv, Time-Aware Shaper (TAS), can be used to manage and control Scheduled Traffic (ST) streams with periodic properties along with Best-Effort (BE) traffic on the same network infrastructure. We investigate the effects of using the IEEE 802.1Qcc management protocol to accurately and precisely configure TAS enabled switches (with transmission windows governed by Gate Control Lists (GCLs) with Gate Control Entries (GCEs)) ensuring ultra-low bounded latency, zero packet loss, and minimal jitter for ST TSN traffic. We examine both a centralized network/distributed user model (hybrid model) and a fully-distributed (decentralized) 802.1Qcc model on a typical industrial control network with the goal of maximizing the number of ST streams.
Self-Similar Solution of Spherical Shock Wave Propagation in a Mixture of a Gas and Small Solid Particles with Increasing Energy under the Influence of Gravitational Field and Monochromatic Radiation

Similarity solution for a spherical shock wave with or without gravitational field in a dusty gas is studied under the action of monochromatic radiation. It is supposed that dusty gas be a mixture of perfect gas and micro solid particles. Equilibrium flow condition is supposed to be maintained and energy is varying which is continuously supplied by inner expanding surface. It is found that similarity solution exists under the constant initial density. The comparison between the solutions obtained in gravitating and non-gravitating medium is done. It is found that the shock strength increases with an increase in gravitational parameter or ratio of the density of solid particles to the initial density of the gas, whereas an increase in the radiation parameter has decaying effect on the shock waves.
Learning Convolutional Neural Networks in Frequency Domain

Convolutional neural network (CNN) achieves impressive success in the ﬁeld of computer vision during the past few decades. As the core of CNNs, image convolution operation helps CNNs to achieve good performance on image-related tasks. However, image convolution is hard to be implemented and parallelized. In this paper, we propose a novel neural network model, namely CEMNet, that can be trained in frequency domain. The most important motivation of this research is that we can use the very simple element-wise multiplication operation to replace the image convolution in frequency domain based on Cross-Correlation Theorem. We further introduce Weight Fixation Mechanism to alleviate over-ﬁtting, and analyze the working behavior of Batch Normalization, Leaky ReLU and Dropout in frequency domain to design their counterparts for CEMNet. Also, to deal with complex inputs brought by DFT, we design two branch network structure for CEMNet. Experimental results imply that CEMNet works well in frequency domain, and achieve good performance on MNIST and CIFAR-10 databases. To our knowledge, CEMNet is the ﬁrst model trained in Fourier Domain that achieves more than 70% validation accuracy on CIFAR-10 database.
New assessment of the prognostic significance of histopathology in Hodgkin's disease for laparotomy‐negative stage I and stage II patients

This paper describes preliminary radiotherapy results in 90 patients with Stage I and II Hodgkin's disease who were evaluated by laparotomy, including splenectomy, and liver and bone marrow biopsies. As a result of selection by laparotomy, the estimated five‐year survival rate for these patients was 96%. No statistically significant differences were detected in the disease‐free survival for patients with mixed cellularity, nodular sclerosis, and lymphocytic predominance disease. Since only one patient with lymphocytic depletion was in this series, no statement can be made regarding this rare histopathology. Patterns of new disease differed for Stage I and II patients. The major difference was that patients with nodular sclerosing Stage II presentations involving the mediastinum were at considerable risk of developing subsequent disease in the pulmonary parenchyma or the pleura. This finding, together with the demonstration that a histologic diagnosis of mixed cellularity did not carry an inferior prognosis, indicates the need for reassessment of the appropriateness of applying treatment programs based on results of lymphangiographically staged patients to Stage I and II patients evaluated by laparotomy.
Determination of glucose concentrations using photonic crystal LEDs

As internet of things (IOT) has become a popular topic in current consumer electronics, there is a demand for cost-effective sensors to monitor bio-signals. Traditional optical sensors employ low-dimensional gratings and high-resolution spectrometers to detect the refractive index changes of the solutions. In this work, we develop an alternative approach to correlate the concentration of molecules to the band diagrams of the photonic crystals. A relatively low-resolution spectrum analyzer can be employed, yet achieves higher sensitivity than traditional approaches.
Design of Sierpinski Carpet Fractal Antenna for Multiband Applications

In this paper, the design of Sierpinski Carpet fractal antenna for multiband application is presented. The return loss of designed structures is simulated using 3D electromagnetic simulator CST MWS 14.0. The proposed antenna is designed on (FR-4) Lossy Substrate with thickness 1.58 mm and relativity permittivity 4.44. It is the combination of initial, first and second iterations. Simulated results show that from initial, first and second iteration, it starts showing different frequency which cover the multiband applications. It also covers the C Band communication satellite for their uplink and downlink frequency application. The Broadband and multiple frequency features of fractal antenna will be presented and discussed.
Few-Shot Sequence Labeling with Label Dependency Transfer and Pair-wise Embedding.

While few-shot classification has been widely explored with similarity based methods, few-shot sequence labeling poses a unique challenge as it also calls for modeling the label dependencies. To consider both the item similarity and label dependency, we propose to leverage the conditional random fields (CRFs) in few-shot sequence labeling. It calculates emission score with similarity based methods and obtains transition score with a specially designed transfer mechanism. When applying CRF in the few-shot scenarios, the discrepancy of label sets among different domains makes it hard to use the label dependency learned in prior domains. To tackle this, we introduce the dependency transfer mechanism that transfers abstract label transition patterns. In addition, the similarity methods rely on the high quality sample representation, which is challenging for sequence labeling, because sense of a word is different when measuring its similarity to words in different sentences. To remedy this, we take advantage of recent contextual embedding technique, and further propose a pair-wise embedder. It provides additional certainty for word sense by embedding query and support sentence pairwisely. Experimental results on slot tagging and named entity recognition show that our model significantly outperforms the strongest few-shot learning baseline by 11.76 (21.2%) and 12.18 (97.7%) F1 scores respectively in the one-shot setting.
Exchange torque in noncollinear spin density functional theory with a semilocal exchange functional

We present a new semilocal exchange energy functional for spin density functional theory (SDFT) based on a short-range expansion of the spin-resolved exchange hole. Our exchange functional is directly derived for noncollinear magnetism, U(1) and SU(2) gauge invariant, and gives rise to nonvanishing exchange torques. The functional is tested for frustrated antiferromagnetic chromium clusters and shown to perform favorably compared to the far more expensive Slater potential and optimized eﬀective potential for exact exchange. This provides a path forward for functional development in noncollinear SDFT and the ab initio study of magnetic materials in and out of equilibrium.