Miracle-dz/UniFAR-FTUs huggingface dataset:
A DC offset removal algorithm based on AR model

ABSTRACTThis work proposes an auto-regressive (AR) model-based algorithm that can eliminate the adverse influence of the exponentially decaying DC offset in the phasor estimation process using discrete Fourier transform (DFT). The proposed algorithm comprises three stages: DFT, AR model implementation, and compensation. First, DFT can eliminate all harmonic components and estimate the phasor of the fundamental frequency component. Second, the AR model is used to calculate the error caused by the exponentially decaying DC offset in the phasor value estimated by DFT. A second-order AR model that uses three successively estimated phasor values is utilized. Finally, the phasor of the fundamental frequency component can be accurately estimated by compensating the error caused by the exponentially decaying DC offset. The performance of the proposed algorithm is evaluated for a-phase to ground fault on a 154 kV 25 km overhead transmission line. Electromagnetic Transients Program is used to generate fault signals.
Development Sequence of Person Markers in Pre-school Children

This study investigates the development sequence of person markers in pre-school children. It observed participants’ accurate use of person markers through a picturesupported elicitation task. Ten children with normal language development, aged between 2.5 and 4 years, participated in the task. Eight different verbs with three person markers for progressive aspect in present tense were elicited from participants. The mean score and standard deviation for each person marker used indicated that participants faced difficulty in producing accurate second person marker. Each participant showed highest accuracy in producing third person marker for each verb form. An implication of the study can be to determine the accuracy order of verbal inflection based on person markers in the process of Bengali language acquisition in children. It can also be helpful in cross-linguistic studies on morphological development of young children.
An Introduction to Elementary Particles

By W. S. C. Williams London: Academic Press Inc. 1961 Pp. ix + 406. Price 88s. This book originated in a lecture course which Dr. Williams gave to experimental research students at Glasgow and is very well adapted to this class of reader. Statements about the elementary particles are liable to fall out of date, but almost all that is presented here is concerned with the ideas and methods that are necessary for understanding high energy scattering experiments in general, and with the more firmly established properties of the particles.
Reconsidering the Nature of Voice

Voices play essential roles in human experience, and carry many kinds of meaning. At present, voice production, acoustics, and perception are treated as separate, independently-studied stages, creating a situation where voice comprises something different to everyone who studies it. This chapter presents arguments for an alternative approach, wherein voice is viewed as a single, integral process. According to this view, voice production, acoustics, aeroacoustics, biomechanics, perception, and all the rest, are conceptually inseparable, and none can be understood without knowing how its relationship to the others contributes to its structure and function. The authors of this chapter submit that development of a comprehensive theory of these interactions and dependencies should be the primary goal of voice research, because such a theory would form a basis on which to build realistic explanations of how voice functions socially and communicatively, how it has evolved, and how it conveys meanings of all sorts, leading to a deeper understanding of what it means to be human and to communicate.
Research on Brand Trust and Financing Risk Preference of E-commerce Based on Neuroeconomic Experiment

Brand trust and financing of e-commerce are two key factors for the development and success of e-commerce enterprises. This paper takes the relationship between brand trust and financing risk preference of e-commerce as the research objective, and adopts the research methods such as literature research, questionnaire survey and neuroeconomics experiment. Based on the research conclusion of laboratory behavioral economics, this paper introduces the latest brain nerve stimulus technique-transcranial direct current stimulus (tDCS) in the field of neuroeconomics. Through analyzing the experimental data obtained after regulating the nerve activities of the dorsolateral prefrontal cortex (DLPFC) of the brain, it reveals from neural network of the brain that the investment behavior of brand trust of e-commerce isn’t based on rational calculation of financing risk, which are different intrinsically. The research in this paper provides a new neuroeconomic basis for the management of brand trust and related financing decision-making for e-commerce managers.
Continuous second order models of spatial variation with application to the efficiency of field crop experiments

This paper develops the approach of using continuous second order models of spatial variation, as described by Matern (1970),for the purposes of comparing the efficiencies of alternative experimental designs and analyses for crop experiments. The development is in three stages. First, a form of model is derived which is capable of describing the most important features of variation of crop yield in the field. In the second stage, techniques for fitting the model to uniformity trial data are developed in such a way that all the important parameters of the model can be estimated and tested. Finally procedures are outlined for evaluating the expected residual mean square resulting from a given design and analysis on a field whose properties obey a given realization of the model. These procedures include classical design and analysis and neighbouring plot methods.
Is physical exercise a protective agent against the way we currently age? A narrative review.

Aging is an inherent process to living beings that involves a deterioration of homeostatic regulation and functional reserve. Currently, the aging population has high levels of physical inactivity that aggravates muscle disuse, which in turn drastically affects functional capacity and quality of life. The aim of this narrative review is to present aging conditions and the protective role of physical exercise in functional reserve and capacity in relation to how we currently age. The regular practice of physical exercise provokes several favorable responses to the preservation of neuromuscular and cardiorespiratory function, which has a direct impact on physical capacity, even benefiting cognitive function. Physical exercise has been shown to have a protective effect on different systems, apart from contributing to the preservation of functionality and self-efficacy, which is why it is essential for healthy aging, since it favors a better resolution to stressful events such as falls and/or diseases. In conclusion, even though physical exercise does not prevent the deleterious conditions of aging, its effects are positively related to the maintenance of systemic functional reserve and capacity, which translates into greater autonomy, independence and quality of life related to health in the last stage of the life cycle.
A Resource Efficient Multi-Dimensional Cache Management Strategy in Content Centric Networks

CCN promises to solve many problems related to traditional network architecture with its receiver-driven, secure and simplistic model. Transparent and ubiquitous in-network caching, mobility management are two active research topics within CCN domain, and we intend to address both in this thesis. This document mainly consists of our work on improving in-network cache management in static and dynamic network environments. In-network cache management in Content-Centric Networking (CCN) has received significant interest from research community in recent years. On the positive aspect, it helps in increasing content availability and quality-of-experience (QoE) by reducing end-to-end delays, and reduces server load. On the other hand, opting the default approach, that is, store a content at every node on the delivery path is not resource-efficient as it introduces high cache redundancy. A multitude of schemes are proposed to increase efficiency of the network, which aim to reduce redundancy by selecting a small fraction of nodes on returning path for storing contents. This selection is generally based on taking into account knowledge about the network or the content itself. However, in many schemes node’s utility is generally determined by analyzing only one concept at a time. For example, some schemes store contents based on popularity, while others select nodes employing only the information about network topology etc. Considering only a single aspect while taking a decision may limit the scope of the cache management scheme to be deployed in diverse scenarios, and might result in sub-optimal performance when the environment is changed. Hence, there is a need to devise an efficient caching mechanism that can dynamically adjust and adapt itself to any environment. With this in mind, we propose an adaptive caching strategy, named as Multi-Attribute Caching Strategy (MACS) based on multi-parameters for CCN. MACS attempts to overcome inefficient cache utilization by intelligently selecting caching locations along the content delivery path. Simulation results show that MACS reduces cache load at each node while providing comparable delay and better cache hit rate using both synthetic and real network topologies.
Research and analysis of force and moment of the cascade asynchronous electric drives.

In the article, the research of force and the moment in the cascade asynchronous electric drives is provided and the analysis of the received decision is carried out. As an object of a research, the special types of electric drives with asynchronous motors possessing glad advantages in comparison with single-engine electric drives were selected. These are optimum mass-dimensional and energetic indices, the improved technological parameters allowing reaching big limits of regulation of rotational speed and the electromechanical moment, and the value of the moment can remain within rated value even in case of small rotational speeds or changes of the direction of movement. For optimum design of such types of electric drives and more exact and correct regulation and the researched parameters of force and the moment on a shaft of an electric drive, it is necessary to realize new approaches to a research and calculation. The carried-out analysis showed that the most optimum method of determination of force and the moment is the method based on electromechanical conversion of energy. The parameters received as a result of a research have necessary accuracy in comparison with the experimental data. The analysis of the conducted research shows that the received decision will allow improving quality, technical and economic indices of difficult technological processes of such industries as oil and gas branch, the heavy industry and mechanical engineering, a pulp-and-paper industry and others.
Protective effect of vitamin C against ethanol induced oxidative stress in Wistar rats

Inflammation is a natural immune response to harmful agents. This study aimed to explore the protective effect of vitamin C against alcohol-induced toxicity on hematological inflammatory markers. Forty healthy adult male Wistar rats were acclimatized and divided into eight groups. Group A served as the control, while Group B received alcohol. Groups C, D, and E were given varying doses of vitamin C, and Groups F, G, and H received alcohol followed by vitamin C treatments. After twenty-one days, blood samples were collected and analyzed for various markers. Rats receiving alcohol only showed increased white blood cell count (WBC), platelet count (PLT), neutrophil to lymphocyte ratio (NLR), and platelet to lymphocyte ratio (PLR), along with decreased antioxidant enzyme activity. However, rats receiving vitamin C alone or in combination with alcohol exhibited reduced inflammatory markers and increased antioxidant activity compared to the alcohol-only group. The study demonstrated that commercial-grade vitamin C at doses of 100 mg/kg, 200 mg/kg, and 300 mg/kg effectively reduced chronic low-grade inflammation. Overall, the findings suggest that vitamin C supplementation may mitigate the inflammatory effects of alcohol consumption.
Review on Heat and Fluid Flow in Micro Pin Fin Heat Sinks under Single-phase and Two-phase Flow Conditions

ABSTRACT This article reviews recent studies on the hydrodynamic and thermal characteristics of micro pin fin heat sink (MPFHS). In the studies reviewed in this article, liquid coolants such as water, HFE-7000, HFE-7200, R-123 were tested under both single-phase and two-phase flow conditions. Analytical, computational and experimental research studies were covered with a focus on configurations with traditional arrangements of micro pin fins (MPF) as well as original designs such as oblique finned MPFs, variable density MPF, vortex generators and herringbone structures. Single-phase flow results highlighted pressure drop penalty with achieved heat transfer enhancement. Many studies revealed the inability of conventional correlations to predict the hydrodynamic and thermal characteristics and proposed new correlations for different operating conditions and geometrical specifications. Regarding the studies on two-phase flows the number of performed studies is less than the ones in single-phase flow regime although the diversity of utilized coolants is more. Under flow boiling conditions, the focus was on determining flow patterns among MPFs for different arrangements and under different operating conditions. Unlike the studies on single-phase flows, the data could be relatively well predicted using the earlier suggested model by Lockhart and Martinelli with appropriate coefficients for different arrangements of MPFs.
Study on the Spatiotemporal Evolution Characteristics and Influencing Factors on Green Building Development of City Clusters in the Yangtze River Delta Region in China

This paper explores the spatiotemporal evolution characteristics and spatial correlation patterns of green building development differences in 41 cities in the Yangtze River Delta region from 2012 to 2020 by means of the gravity center analysis model and spatial autocorrelation analysis. In addition, it further clarifies the impact factors of the spatial differentiation pattern of green building development in combination with GeoDetector based on four dimensional factors of population and economy, market environment, policy, and other factors. The results showed that: (1) According to the analysis of the number of green buildings in each city from 2012 to 2020 and the natural discontinuity method, the development pattern of green buildings in the Yangtze River Delta region city clusters shows an imbalance, being highly concentrated in the eastern coastal areas with Suzhou (1) and Shanghai as the core. The overall trajectory of the center of gravity shows the development from southeast to northwest. (2) The global Moran’s I of green buildings in the Yangtze River Delta region city clusters is greater than 0, and all passed the significance test (Z > 1.96, p < 0.01), indicating that the green buildings in the Yangtze River Delta region city clusters show typical spatial aggregation characteristics. By using the local LISA index, it is found that in the H-H spatial autocorrelation distribution pattern with Suzhou (1) and Shanghai as the core, the core city has a strong attraction ability and relatively low radiation ability. (3) Based on the explanatory power mean, the main driving factors of the spatial differentiation pattern of green building development in the Yangtze River Delta region city clusters are education level (0.6656), technical level (0.6269), and the gross domestic product (0.6091). The factor interaction shows a two-factor enhancement and nonlinear enhancement effect, and there is neither a weakening nor an independent relationship.
Does the great moderation of China’s macroeconomic exist during the reform era?

This paper documents the Great Moderation of China’s macroeconomic volatilities during the reform period. Using the conditional Markov chain model, it is found that with the break date at 1995Q1, China’s business cycle has changed from the ”Boom-bust Cycle” to the ”Great Moderation”. Evidence from the multiresolution wavelet analysis reveals that a decline in output volatility appears to be evenly distributed across frequencies. These results provide some striking evidence consistent with the potential explanations of good institution, good luck and good policy, but weaker evidence for the good practice hypothesis.
Two competing queues with linear costs: the μc-rule is often optimal

A state-space model is presented for a queueing system where two classes of customer compete in discrete-time for the service attention of a single server with infinite buffer capacity. The arrivals are modelled by an independent identically distributed random sequence of a general type while the service completions are generated by independent Bernoulli streams; the allocation of service attention is governed by feedback policies which are based on past decisions and buffer content histories. The cost of operation per unit time is a linear function of the queue sizes. Under the model assumptions, a fixed prioritization scheme, known as the μc -rule, is shown to be optimal when the expected long-run average criterion and the expected discounted criterion, over both finite and infinite horizons, are used. This static prioritization of the two classes of customers is done solely on the basis of service and cost parameters. The analysis is based on the dynamic programming methodology for Markov decision processes and takes advantage of the sample-path properties of the adopted state-space model.
Retrieval of Polarimetric Azimuthal Angular Characteristics via the Application of Target Decomposition to Spectral Domain Circular SAR Images

In this paper, we discuss the application of polarimetric target decomposition (TD) theorems to circular synthetic aperture radar (CSAR) images to retrieve the polarimetric azimuthal angular characteristics of the targets. In CSAR systems, radar-carrying aircraft moves along a circular path. The antenna beam is pointed toward the center of the circular path during the data acquisition to irradiate the spotlighted area from various azimuthal or aspect angles. Therefore, the resultant polarimetric CSAR images contain information about the polarimetric scattering mechanisms of the targets at each aspect angles. To recover this information, we propose the use of spectral decomposition of CSAR images in combination with several TD algorithms. The spectral domain CSAR images can be viewed as the azimuthal angular spectrum images. Thus, the application of TD algorithms to the spectral domain images is expected to be able to obtain the angular dependence and polarimetric scattering properties of the targets simultaneously. We carried out a simple numerical simulation and an indoor laboratory experiment to validate the proposed TD scheme.
Solution of the inverse seismic problem in a layered elastic medium by means of the τ-p Radon transform

Abstract We consider the inverse scattering problem in a layer-homogeneous elastic structure filling a half-plane. Scattering data is the seismic wave field registered on the boundary with a surface point source. We prove that velocities of longitudinal and transverse waves, and a density of the medium are recovered by a unique way. The algorithm of the inverse problem solution is based on the τ-p Radon transform. Also, we present some results of numerical modeling for waves propagation and solving of the inverse problem.
Sensitive aerial hearing within a noisy nesting soundscape in a deep-diving seabird, the common murre (Uria aalge)

: Diving seabirds face a combination of sound exposure in marine and terrestrial environments due to increasing human encroachment on coastal ecosystems. Yet the sound-sensitivity and sensory ecology of this threatened group of animals is largely unknown, complicating effective management and conservation. Here, we characterize aspects of the acoustic ecology of the common murre Uria aalge , one of the deepest diving alcid seabirds. Electrophysiological aerial hearing thresholds were measured for 12 wild, nesting individuals and compared to conspecific vocalizations and short-term aerial soundscape dynamics of their cliff nesting habitat. Auditory responses were measured from 0.5 to 6 kHz, with a lowest mean threshold of 30 dB at 2 kHz and generally sensitive hearing from 1 to 3.5 kHz. The short-term murre nesting soundscape contained biotic sounds from con-and heterospecific avifauna; broadband sounds levels of 56−69 dB re: 20 μPa rms (0.1−10 kHz) were associated with both diel and tidal-cycle factors. Five murre vocalization types showed dominant spectral emphasis at or below the region of best hearing. Common murre hearing appears to be less sensitive than a related alcid, the Atlantic puffin Fratercula arctica , but more sensitive than other non-alcid diving birds described to date, suggesting that adaptations for deep diving have not caused a loss of the species’ hearing ability above water. Overall, frequencies of common murre hearing and vocalization overlap with many anthropogenic noise sources, indicating that the species is susceptible to disturbance from a range of noise types.
Weighted l1‐Penalized Corrected Quantile Regression for High‐Dimensional Temporally Dependent Measurement Errors

This article derives some large sample properties of weighted l1 ‐penalized corrected quantile estimators of the regression parameter vector in a high‐dimensional errors in variables (EIVs) linear regression model. In this model, the number of predictors p depends on the sample size n and tends to infinity, generally at a faster rate than n , as n tends to infinity. Moreover, the measurement errors in the covariates are assumed to have linear stationary temporal dependence and known Laplace marginal distribution while the regression errors are assumed to be independent non‐identically distributed random variables having possibly heavy tails. The article discusses some rates of consistency of these estimators, a model consistency result and an appropriate data adaptive algorithm for obtaining a suitable choice of weights. A simulation study assesses the finite sample performance of some of the proposed estimators. This article also contains analogs of Massart's inequality for independent and short memory moving average predictors, which is instrumental in establishing the said consistency rates of the above mentioned estimators in the current setup of high dimensional EIVs regression models.