Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Dielectric Theory of Electronegativity in Covalent Systems. III. Pressure-Temperature Phase Diagrams, Heats of Mixing, and Distribution Coefficients

Electronegativity difference was redefined in Paper I of this series as a scaling parameter which combines the concepts of valence and size differences. A procedure has been developed for its evaluation in terms of a two-band model. In Paper II of this series it was shown that this model describes and predicts the ionization potentials and electronic interband gaps of binary ${A}^{N}{B}^{8\ensuremath{-}N}$ compounds and their alloys. Here the energy of this model semiconducting-insulating solid is evaluated relative to a free-electron gas, i.e., an idealized metal, as a function of composition, pressure, and temperature. Using this highly simplified scaling approach, we obtain suprisingly accurate predictions for the heat of fusion, melting point, and pressure-temperature phase diagrams of these materials. A revised method of calculating the excess heat of mixing of a substitutional alloy is presented. This calculation is extended to the case of an arbitrary dilute impurity in an arbitrary semiconducting host; the distribution coefficient at the melting point of the host is obtained.
On the Validity of the Markov Interpretation of Path Diagrams of Gaussian Structural Equations Systems with Correlated Errors

Pearl's d‐separation concept and the ensuing Markov property is applied to graphs which may have, between each two different vertices i and j, any subset of {i←j, i→j, i↔j} as edges. The class of graphs so obtained is closed under marginalization. Furthermore, the approach permits a direct proof of this theorem: “The distribution of a multivariate normal random vector satisfying a system of linear simultaneous equations is Markov w.r. t. the path diagram of the linear system”.
hucMSC-Ex Alleviates IBD-Associated Intestinal Fibrosis by Inhibiting ERK Phosphorylation in Intestinal Fibroblasts

Background Intestinal fibrosis, one of the complications of inflammatory bowel disease (IBD), is associated with fistula and intestinal stricture formation. There are currently no treatments for fibrosis. Mesenchymal stem cell-derived exosomes have been proven to exert inhibitory and reversal effects in IBD and other organ fibrosis. In this study, we explored the role of human umbilical cord mesenchymal stem cell-derived exosomes (hucMSC-Ex) in IBD-related fibrosis and its associated mechanism to provide new ideas for the prevention and treatment of IBD-related intestinal fibrosis. Methods We established a DSS-induced mouse IBD-related intestinal fibrosis model and observed the effect of hucMSC-Ex on the mouse model. We also used the TGF-induced human intestinal fibroblast CCD-18Co to observe the role of hucMSC-Ex in the proliferation, migration, and activation of intestinal fibroblasts. Having observed that the extracellular-signal-regulated kinase (ERK) pathway in intestinal fibrosis can be inhibited by hucMSC-Ex, we treated intestinal fibroblasts with an ERK inhibitor to emphasize the potential target of ERK phosphorylation in the treatment of IBD-associated intestinal fibrosis. Results In the animal model of IBD-related fibrosis, hucMSC-Ex alleviated inflammation-related fibrosis as evident in the thinning of the mice's intestinal wall and decreased expression of related molecules. Moreover, hucMSC-Ex inhibited TGF-β-induced proliferation, migration, and activation of human intestinal fibroblasts, and ERK phosphorylation played a key role in IBD-associated fibrosis. The inhibition of ERK decreased the expression of fibrosis-related indicators such as α-SMA, fibronectin, and collagen I. Conclusion hucMSC-Ex alleviates DSS-induced IBD-related intestinal fibrosis by inhibiting profibrotic molecules and intestinal fibroblast proliferation and migration by decreasing ERK phosphorylation.
Effect of Faraday rotation on polarimetric SAR

The effect of ionospheric Faraday rotation on polarimetric synthetic aperture radar (SAR) imagery is evaluated theoretically. Faraday rotation is readily included in the polarimetric SAR system equation describing the received signal if the rotation angle is assumed constant over the synthetic aperture length. Deviations from a constant rotation angle over this length impact the validity of the derived system equation, but an explicit evaluation shows such effects to be negligible for most expected ionospheric conditions. The modified system equation provides a basis for calibration techniques that can be used to either remove or measure Faraday rotation effects in SAR imagery.
Three‐dimensional boundary element analysis of drop deformation in confined flow for Newtonian and viscoelastic systems

An adaptive (Lagrangian) boundary element approach is proposed for the general three-dimensional drop deformation in confined flow. The adaptive method is stable as it includes remeshing capabilities of the deforming interface between drop and suspending fluid, and thus can handle large deformations. Both drop and surrounding fluid are viscous incompressible and can be Newtonian or viscoelastic. A boundary-only formulation is implemented for fluids obeying the linear Jeffrey's constitutive equation. Similarly to the formulation for two-dimensional Newtonian fluids (Khayat RE, Luciani A, Utracki LA. Boundary element analysis of planar drop deformation in confined flow. Part I. Newtonian fluids. Engineering Analysis of Boundary Elements 1997; 19: 279), the method requires the solution of two simultaneous integral equations on the interface between the two fluids and the confining solid boundary. Although the problem is formulated for any confining geometry, the method is illustrated for a deforming drop as it is driven by the ambient flow inside a cylindrical tube. The accuracy of the method is assessed by comparison with the analytical solution for two-phase radial spherical flow, leading to good agreement. The influence of mesh refinement is examined for a drop in simple shear flow. Copyright © 2000 John Wiley & Sons, Ltd.
Identifying and Protecting Cyber-Physical Systems’ Influential Devices for Sustainable Cybersecurity

For sustainable cyber-physical systems (CPS) security, proactive measures to cybersecurity need to be implemented instead of reactive measures. Towards this, we introduce in this paper a proactive methodology implemented in a system called IDI_CPS. It is based on the observation that CPS devices that have LAN-based network sharing (e.g., via Wi-Fi connections) need first to be clustered using some clustering criterion. Then, the influential and central devices in these clusters need to be identified to pay more attention to their file sharing. These influential devices may have network sharing with devices at the WAN level. Therefore, the influential devices at the WAN level that have network sharing with the influential devices in the clusters need also to be identified to pay more attention to their file sharing. We propose novel techniques for: (1) clustering the devices that have LAN-based network sharing using k-clique modeling, (2) employing clustering coefficient-based techniques for identifying the most influential device in each cluster, and (3) employing Independent Cascades model-based techniques for identifying the influential devices at the WAN level that have network sharing with the influential devices in the clusters. We experimentally evaluated our proposed system IDI_CPS and compared it with four comparable methods. Results showed marked improvement.
Time-domain Approaches for Input Disturbance Observer

In the paper, algorithms for disturbance observers are newly presented in the time-domain. Attention is paid to observing a ramp disturbance by introducing an integral term to the output equation of a constant disturbance observer. In order to reduce the sensitivity to the measurement noise, the disturbance observer is combined with the state observer. It will be shown that the estimation dynamics can be arbitrarily chosen by assigning the eigenvalues of a characteristic equation. Also, we provide the analysis of observer behaviors subject to non-ramp-style disturbances. Finally, we propose the generalized disturbance observer that accurately estimates disturbances of higher order in time series expansion.
Slow Heat-Based Hybrid Simulated Annealing Algorithm in Vehicular Ad Hoc Network

Vehicular ad hoc networks (VANETs) using reliable protocols of routing have become crucial in identifying the changes to topology on a continuous basis for a large collection of vehicles. For this purpose, it becomes important to identify an optimal configuration of these protocols. There are several possible configurations that have been preventing the configuration of efficient protocols that do not make use of automatic and intelligent design tools. It can further motivate using the techniques of metaheuristics like the tools, which are well-suited to be able to solve these problems. The glowworm swarm optimization (GSO), simulated annealing (SA), and slow heat-based SA-GSO algorithms have been proposed in this work. The SA is a method of optimization, which imitates the manner in which the thermal system has been frozen down to its lowest state of energy. In the GSO, there is guidance to the rules of feasibility, where the swarm converges to its feasible regions very fast. Additionally, for overcoming any premature convergence, there is a local search strategy that is based on the SA and is used for making a search that is near to its true optimum solutions. Finally, this sluggish temperature-based SA-GSO algorithm will be employed to solve routing problems and problems of heat transfer. There is a hybrid slow heat SA-GSO algorithm with a faster speed of convergence and higher precision of computation that is more effective in solving problems of constrained engineering.
An infinite Legendre integral transform and its inverse

ABSTRACT A consideration of Legendre's equation, of order zero, expressed in terms of the angular variable θ, leads heuristically, but methodically, to an infinite integral representation of the delta function in terms of two independent non-periodic solutions Ev−½(θ), E−v−½(θ). This result yields an integral transform and inverse formula, where in the former the kernel is E−v−½(θ) sin θ and the integration over θ runs from − ∞ to ∞. By rigorous contour integral methods, the inverse is verified when the original function is a rectangular pulse, and the standard series expansion in terms of Legendre polynomials is recovered when the original function is even and of period 2π in θ. Analogies with the theory of Fourier transforms are emphasized.
New Voters and Old Voters: Understanding Volatility in Quebecers’ Federal Election Votes between 2008 and 2019

Abstract Federal elections between 2008 and 2019 saw a great of volatility in Quebec, with important consequences for election outcomes. The surge in New Democratic Party (NDP) support in Quebec led the party to official opposition, while Liberal gains in 2011 led the party to a majority government, and Bloc Québécois gains in 2019 helped to reduce the Liberals to a minority. To what extent was this volatility driven by voters switching parties and to what degree was it driven by voters entering and exiting the electorate? This article uses ecological inference based on riding-level data to examine the dynamics of party competition in Quebec from 2008 to 2019. We show that while voter mobilization mattered to volatility, vote switching was the important driver of changing party fortunes during this period.
Spectral characteristics of Si light emitting diodes in a 0.8 /spl mu/m BiCMOS technology

It is well known that silicon diodes biased in the avalanche breakdown region of operation emit visible light. Silicon light sources in monolithic optoelectronic systems will only be used on a large scale if the devices can be easily integrated with other circuits in the standard VLSI technology. This paper investigates the spectral properties of silicon diode light sources in a 0.8 /spl mu/m BiCMOS technology. The light sources include both avalanche and field emission breakdown devices, and it Is shown that the breakdown mechanism has a significant effect on the spectral properties of the diodes. The emitted light patterns as defined by the layout also play a role, and evidence is provided that point sources have more long wavelength emission than line sources. The emission originating from bulk diodes, e.g. the buried layer, is also compared to the emission from surface-dominated junctions, and a definite shift in spectra towards longer wavelengths is observed.
Point-Interval Forecasting for Electricity Load Based on Regular Fluctuation Component Extraction

The fluctuation and uncertainty of the electricity load bring challenges to load forecasting. Traditional point forecasting struggles to avoid errors, and pure interval forecasting may cause the problem of too wide an interval. In this paper, we combine point forecasting and interval forecasting and propose a point-interval forecasting model for electricity load based on regular fluctuation component extraction. Firstly, the variational modal decomposition is combined with the sample entropy to decompose the original load series into a strong regular fluctuation component and a weak regular fluctuation component. Then, the gate recurrent unit neural network is used for point forecasting of the strong regular fluctuation component, and the support vector quantile regression model is used for interval forecasting of the weak regular fluctuation component, and the results are accumulated to obtain the final forecasting intervals. Finally, experiments were conducted using electricity load data from two regional electricity grids in Shaanxi Province, China. The results show that combining the idea of point interval, point forecasting, and interval forecasting for components with different fluctuation regularity can effectively reduce the forecasting interval width while having high accuracy. The proposed model has higher forecasting accuracy and smaller mean interval width at various confidence levels compared to the commonly used models.
Parameter Identification of Inertia Properties of Space Robot Based on Momentum Conservation

The parameter identification is necessary for precise control orbit and attitude of Space Robot. This paper presents a method for parameter identification of inertia properties of space robot which is based on the momentum conservation. As the initial momentum of the Space Robot is hardly known, we have to discuss detailed in two options. The first option, the initial momentum is known and assumes it is zero, then we can solve all the unknown parameters in the momentum equations; the second it’s unknown, it has to be solved in two steps. The first step is to identify the mass and mass center of the spacecraft; and the second step is to identify the inertia tensor of the spacecraft. In the end, we build the model for simulation; the result shows that the method has the high precise and the error can be ignored.
High performance thin film transistor with low temperature atomic layer deposition nitrogen-doped ZnO

High performance thin film transistor (TFT) with atomic layer deposition (ALD) nitrogen doped ZnO (ZnO:N) as an active layer is demonstrated. The electrical properties of ZnO thin films were effectively controlled by in situ nitrogen doping using NH4OH as a source for reactants. Especially, the electron concentration in ZnO was lowered to below 1015cm−3. Good device characteristics were obtained from the inverted staggered type TFTs with ZnO:N channel and ALD Al2O3 gate insulator; μsat=6.7cm2∕Vs, Ioff=2.03×10−12A, Ion∕off=9.46×107, and subthreshold swing=0.67V∕decade. The entire TFT fabrication processes were carried out at below 150°C, which is a favorable process for plastic based flexible display.
Knowledge, Attitude, and Practice Regarding Fibromyalgia Among Primary Care Physicians in Tabuk, Saudi Arabia

Background: Adequately informed family physicians have the greatest potential to correctly identify the diagnosis of fibromyalgia (FM) and develop an initial treatment plan. Therefore, it is substantial to determine the levels of weakness and inaccuracy among primary care physicians regarding FM diagnostic criteria and management strategies. Aim: This study aimed to assess the knowledge, attitude, and practices regarding FM among primary care physicians in Tabuk, Saudi Arabia. Methods: This cross-sectional study included family physicians who were board-certified or registered in the family medicine training program and working at the government family healthcare centers in Tabuk. A pre-designed, structured questionnaire was distributed either in written form or as an online survey. Results: This study included 52 primary healthcare physicians. Twenty-two (42.3%) participants incorrectly recorded localized pain as a diagnostic symptom, and 45 (86.5%) incorrectly recorded nonsteroidal anti-inflammatory drugs (NSAIDs), prednisolone, and/or opioids as drugs that are used for treating FM. Only 59.6% were confident in recognizing the symptoms of FM, and 55.8% were confident in differentiating FM from other similar diseases. Conclusions: The primary healthcare physicians working in the government’s primary healthcare centers in Tabuk City, Saudi Arabia, have low levels of knowledge about diagnostic criteria and treatment strategies for FM. These findings highlight the need for continuous professional development involving family physicians in the primary healthcare setting with suitable continuous medical education (CME) programs concerning FM.
Existence of periodic solutions of BAM neural networks with time- varying delays and reaction-diffusion terms

Summary In this paper, the periodic solutions have been discussed for a general class of bi-directional associative memory (BAM) neural networks with time-varying delays and reaction-diffusion terms. A simple and new sufficient condition has been obtained to ensure the existence of periodic solutions of bi-directional associative memory neural networks with time-varying delays and reaction-diffusion terms, and the activation functions are not required to be differentiable, bounded, monotone nondecreasing and the weight-connected matrices to be symmetric in the obtained result. In addition, an example has been given to show the effectiveness of the obtained result.
Likelihood-based analysis of longitudinal count data using a generalized Poisson model

Models based on a generalization of the simple Poisson process are discussed and illustrated with an analysis of some longitudinal count data on frequencies of epileptic fits. The models enable a broad class of discrete distributions to be constructed, which cover a variety of dispersion properties that can be characterized in an intuitive and appealing way by a simple parameterization. This class includes the Poisson and negative binomial distributions as well as other distributions with greater dispersion than Poisson, and also distributions underdispersed relative to the Poisson distribution. Comparing a number of analyses of the data shows that some covariates have a more significant effect using this modelling than from using mixed Poisson models. It is argued that this could be due to the mixed Poisson models used in the other analyses not providing an appropriate description of the residual variation, with the greater flexibility of the generalized Poisson modelling generally enabling more critical assessment of covariate effects than more standard mixed Poisson modelling.
Approximation of time-delay systems

We propose a new method for approximating time-delays in dynamical systems. A weighted H/sup /spl infin// norm criterion is minimized to obtain rational approximation of e/sup -sd/. We report the approximation in a diagram relating both the amount of time delay and the bandwidth to the order of the approximating rational function for a given level of infinity norm. The obtained approximations are compared to the widely used Pade's approximation. Examples are used for illustrations.
miR-9a-5p Protects Ischemic Stroke by Regulating Oxidative Stress and Mitochondrial Autophagy

Purpose Present research is aimed at exploring the effect of miR-9a-5p on mitochondrial autophagy and alleviating cellular oxidative stress injury in ischemic stroke. Methods SH-SY5Y cells were cultured with oxygen-glucose deprivation/reoxygenation (OGD/R) to simulate ischemia/reperfusion. The cells were treated in an anaerobic incubator (95% N2, 5% CO2) for 2 h and then reoxygenated in the normoxic condition for 24 h with 2 ml of normal medium. Cells were transfected with miR-9a-5p mimic/inhibitor or negative control. The RT-qPCR assay was utilized to measure the mRNA expression. Western blot was utilized to evaluate the protein expression. The CCK-8 assay was conducted to detect cell viability. Flow cytometry was applied to examine apoptosis and the cell cycle. The ELISA assay was applied to measure the contents of SOD and MDA in mitochondria. Autophagosomes were observed via electron microscopy. Results By comparison with the control group, the miR-9a-5p expression in the OGD/R group obviously declined. Mitochondrial crista breaks, vacuole-like changes, and increased autophagosome formation were observed in the OGD/R group. OGD/R injury enhanced oxidative stress damage and mitophagy. When transfected with the miR-9a-5p mimic, mitophagosome production of SH-SY5Y cells decreased and oxidative stress injury was inhibited. However, the miR-9a-5p inhibitor obviously increased mitophagosome production and enhanced oxidative stress injury. Conclusion miR-9a-5p protects against ischemic stroke by inhibiting OGD/R-induced mitochondrial autophagy and alleviating cellular oxidative stress injury.
Observations on Listener Responses from Multiple Perspectives

In this paper we present three studies that investigate the individual differences in nonverbal listening behavior. Besides collecting a corpus of listener responses, we asked people to watch a video of a speaker and indicate where they would produce a listener response. Also we asked people to judge the appropriateness of listener responses that we generated using a virtual human. The combination of the multiple perspectives collected in these studies provides us with a rich data set in which different types of response opportunities are distinguishable. There are moments where there is high agreement between these multiple perspectives that a listener response is appropriate or inappropriate, moments where a listener response is controversial and moments neither a response was given nor a response was judged inappropriate (neutral). We will show that different contextual characteristics can be used to discriminate these response opportunities. Observations show relations to sentence structure, conversational structure and proximity of earlier responses.
Silicon nanocrystals for nonlinear optics and secure communications

Silicon nanocrystals (Si‐nc) are reviewed here for their interesting optical applications. On the one hand, they do exhibit quantum confinement effects. This allows turning silicon into a light‐emitting material where luminescence can be excited by electrical injection. On the other hand, small sizes, large surfaces, and dielectric mismatch between the core and the surrounding matrix increase dramatically the nonlinear optical coefficients. This allows using Si‐nc as a nonlinear material in different waveguide configurations. In this paper, we discuss specifically two different applications of Si‐nc: (i) as a nonlinear material in various devices, e.g., in bistable optical cavities, in waveguide optical mode monitors that are based on two‐photon excited luminescence detection, and in wavelength shifters by using four‐wave mixing (FWM); (ii) as an entropy source for quantum random number generation, the key device for cryptography.