Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Excitation and Detection of Piezoelectric Surface Waves in Quartz by Means of Surface Electrodes

The power extracted from a piezoelectric surface wave in quartz by an arrangement of electrodes on the surface is determined by a perturbation technique, which is extremely accurate for low‐coupling materials. The mechanical portion of the surface wave is found by neglecting the piezoelectric coupling, which is very small in quartz. The elastic solution then yields both volumetric and surface source terms, which are generated by the piezoelectric coupling and drive the steady‐state electrostatic solution. A technique is introduced for reducing the remaining electrostatic problem to Laplace's equation, subject to such boundary conditions that the solution is amenable to conformal mapping techniques for several interesting, and possibly useful, electrode arrangements. Surface waves propagating along the digonal axis for all rotated Y cuts are considered, as well as those propagating in all directions along the surface of an X‐cut crystal. A reciprocal relation between the excitation and detection problems i.
Lee-wave breaking over obstacles in stratified flow

Experimental results are presented on the lee-wave breaking process which occurs at low Froude numbers when uniform and strongly stratified flow approaches two-dimensional and quasi two-dimensional Gaussian-shaped obstacles. It was found that the lee-wave breaking process is essentially independent of the two-dimensional and the quasi two-dimensional shape of the obstacles. The attainment of the critical condition where the steepening wave becomes statically unstable does not mark a threshold to breakdown. Instead, the wave remains dynamically stable for several buoyancy periods, overturning into an “S”-shape with maximum overturning reaching about 55° past the vertical. It is observed that the primary instability forms a quasi two-dimensional spanwise vortex over the central portion of the obstacles and is mainly shear driven. The quasi two-dimensional spanwise vortex persists for a few buoyancy periods before undergoing a three-dimensional convective instability, similar to a Rayleigh–Taylor instability.
Combined XANES and EXAFS analysis of Co2+, Ni2+, and Zn2+ aqueous solutions

A combined x-ray-absorption near edge structure (XANES) and extended x-ray-absorption fine-structure (EXAFS) quantitative analysis of Co 2 + , Ni 2 + , and Zn 2 + in water solutions based on fitting procedures of both low- and high-energy ranges has been carried out. The hydrogen contribution has been accounted for in both analyses and the effect of its inclusion on the structural parameters has been highlighted. The structural results obtained from the XANES and EXAFS analyses are in good agreement, confirming the validity of the application of the multiple-scattering theory in the low-energy range of the x-ray-absorption spectra. A systematic shortening of the ion-water first shell distance of about 0.03 A is obtained from the XANES analyses, as compared to the EXAFS one. The origin of this systematic effect has been deeply investigated and it has been found to be due to the low-energy behavior of the real part of the Hedin-Lundqvist potential used in the calculations.
The effect of Organizational justice on employee turnover with the mediating role of Job embeddedness

Employee turnover remains a serious issue among organisations irrespective of their size and nature. In this sense, there is a growing interest in identifying the antecedents of employee turnover to enhance high employee retention. In line with this trend, this study aims to test the mediating role of job embeddedness in the relationship between organisational justice and employee turnover. A cross-sectional empirical study was carried out on stock broking dealers in Chennai city. Hundred and fifty-five participants completed the self-administered questionnaire. Pearson correlation and regression analysis was used to test the hypothesis. The study results indicate that distributive, procedural, and interpersonal justice perceptions relate to employee turnover and job embeddedness mediates the relationship between organizational justice and employee turnover. Business leaders and human resource professionals could consider the research results to implement employee retention strategies to enhance high retention within their organisations.
Trust in Adoption of Internet of Things: Role of Perceived Ease of Use and Security

This study was designed to examine the effect of perceived ease of use, security, integrity, and trustworthiness on the adoption of the Internet of things. The mediating role of trust was also examined in the context of the UAE hospitality sector. The data were collected using a survey approach including the tourists of UAE and using convenient sampling. The questionnaire was distributed to 400 respondents and the usable questionnaires which were received back were 269. The data were examined using Smart-PLS 3.3. 9. The results revealed that trust is directly affected by security and perceived ease of use. Besides, trust has a direct effect on the adoption of IOT. This study confirms the mediating role of trust as well. This study addresses the research gap of limited studies conducted on IoT adoption in the context of the hospitality industry of UAE.
Analysis models for the estimation of oceanic fields

Abstract A general model for statistically optimal estimates is presented for dealing with scalar, vector and multivariale datasets. The method deals with anisotropic fields and treats space and time dependence equivalently. Problems addressed include the analysis, or the production of synoptic lime series of regularly gridded fields from irregular and gappy datasets, and the estimate of fields by compositing observations from several different instruments and sampling schemes. Technical issues are discussed, including the convergence of statistical estimates, the choice of representation of the correlations, the influential domain of an observation, and the efficiency of numerical computations.
Finnish upper secondary students’ collaborative processes in learning statistics in a CSCL environment

This design-based research project focuses on documenting statistical learning among 16–17-year-old Finnish upper secondary school students (N = 78) in a computer-supported collaborative learning (CSCL) environment. One novel value of this study is in reporting the shift from teacher-led mathematical teaching to autonomous small-group learning in statistics. The main aim of this study is to examine how student collaboration occurs in learning statistics in a CSCL environment. The data include material from videotaped classroom observations and the researcher's notes. In this paper, the inter-subjective phenomena of students’ interactions in a CSCL environment are analysed by using a contact summary sheet (CSS). The development of the multi-dimensional coding procedure of the CSS instrument is presented. Aptly selected video episodes were transcribed and coded in terms of conversational acts, which were divided into non-task-related and task-related categories to depict students’ levels of collaboration. The results show that collaborative learning (CL) can facilitate cohesion and responsibility and reduce students’ feelings of detachment in our classless, periodic school system. The interactive . pdf material and collaboration in small groups enable statistical learning. It is concluded that CSCL is one possible method of promoting statistical teaching. CL using interactive materials seems to foster and facilitate statistical learning processes.
News Media and Political Participation in the Middle East: Jordan as an example

This study aims to understand the relationship between the types of news-media use and political conversation and participation in Jordan. It also examines the main factors that impact political participation among people in Jordan. Particularly, democracy in Jordan is an under-discussion topic, that needs further consideration and investigation. This study assessed the role ofnews media in Jordanian democracy and factors that affect one's voting decisions. A self- reported survey was used and distributed to a random sample of 398 citizens at University of Jordan, findings showed strong support to relationship between types of news media, political conversation, and political participation, especially in relation to gender and age, but not provincial affiliation. Education was found to directly affect voting decisions. Almost less than two thirds (61%) of the sample preferred using old mediafor news / political information. Respondents also appreciated media's power in strengthen democracy (60.8%), suggesting in-depth studies, recommendations, implications, and limitations.
The symmetry reductions of a turbulence model

In this paper we obtain symmetry reductions of the system of two coupled parabolic partial differential equations which model the evolution of turbulent bursts using the classical Lie method of infinitesimals. The reduction to systems of ordinary differential equations (ODEs) are obtained from the optimal system of subalgebras. These systems admit symmetries which lead to further reductions. An algorithm presented by Bluman for reducing the order of ODEs allows us to reduce some of these systems, invariant under a two-parameter group, directly to first-order ODEs systems. The hidden symmetries of some of these systems are obtained and some new exact solutions have been derived.
A single cell potency inference method based on the local cell-specific network entropy

At present, some methods have been proposed to solve the problem from the perspective of the chaos degree in gene functions or interaction network. However, errors in differentiation potency estimates arise if the scRNA-seq profile and underlying interaction network are disturbed by technique-induced or biological-induced noise. Thus, we proposed SPIDE, a single cell potency inference method based on local cell-specific network entropy. SPIDE constructs the weighted cell-specific network for each cell to preserve the heterogeneity of PPI network during differentiation, then estimates the entropy based on each network. The results show that SPIDE reveals better decreasing trends of cells’ differentiation potency than other state-of-the-art methods on most datasets. To conclude, our study provides a universal framework for cell entropy estimation with higher prediction accuracy and universal applicability.
Energy balance in coronal funnels

The energy balance in magnetic flux tubes is examined semianalytically for the case in which thermal conduction balances radiation or in which enthalpy transport occurs. Different values are considered for areal constriction, shape, length, and maximum temperature. The overall energy budget of the solar corona is not significantly affected by magnetic constriction. A bowl-shaped funnel with a constriction factor of 4 describes the empirical differential-emission measure for log-T values between approximately 5.3 and 6.0. Loop-scaling relationships are derived for the full range of models to illustrate the dependence of the constant of proportionality on the properties of the magnetic constriction. Constriction can reduce the total energy requirement of the funnel by a factor of 5 and not affect the differential emission in flow-dominated models.
The effects of interactions on spiral galaxies. II - Disk star-formation rates

H-alpha emission-line and IRAS far-IR observations of interacting spiral and irregular galaxies are here used to assess the influence of interactions on their global star-formation rates. Two samples of interacting galaxies were observed: a complete sample of close pairs, and an Arp atlas sample of peculiar systems. When compared to a control sample of single galaxies, both samples of interacting systems exhibit systematically higher levels of H-alpha and infrared emission on average, and a larger dispersion in emission properties. Emission levels in the very active system are much more strongly correlated with the properties of the interaction than with the internal properties of the galaxies themselves. Strong disk emission is almost always accompanied by unusually strong nuclear activity. Simple star-formation burst models can reproduce the observed H-alpha equivalent widths and broadband colors of most of the galaxies. The bursts are relatively short (few times 10 million yr) and rarely involve more than 1-2 percent of a galaxy's total mass. 56 references.
Are Existing Analytical Models for LoRa Networks Accurate?

Long range (LoRa) is one of the most flourishing low-power wide-area (LPWA) technologies, designed to satisfy the requirements of IoT (Internet of Things) devices. Several researches have recently proposed complex analytical models encompassing both single-cell and multi-cells LoRa networks, and that can be used for scalability evaluation or network dimensioning. These models rely on either stochastic geometry tools or enhanced modelling of Aloha channel access, to derive closed-from expressions of LoRa performance metrics such as packet delivery ratio (PDR) or data extraction rate (DER). However, the obtained expressions need to be validated by realistic simulations as pointed out by some of the authors themselves [1]. We also noted that different models seem to yield different results. In this paper, we briefly introduce the two main analytical modelling approaches and summarize their mathematical results. We then proceed to fill the validation gap by customizing the packet-level simulator LoRaSim and running extensive simulations in order to assess the accuracy of these models. Our study shows that the stochastic geometry-based models provide accurate DER values that match the simulation results.
Measurement and analysis of instantaneous radio height-gain curves at 8.6 millimeters over rough surfaces

By the use of an array of ten vertically-spaced antennas and a rotating wave guide switch, a portion of the height-gain pattern for a short radio path was obtained as a function of time for a wave length of 8.6 millimeters. In the analysis of the data taken across a small lake, the reflection from the water is assumed to be made up of two components. One component is a constant value equal to the median signal received at the antennas over the sampling period and the other component is a variable signal of the proper phase and magnitude to give the measured total signal at each instant. The angle of arrival, phase and magnitude of the fluctuating signal are obtained for a short sample of data and their characteristics described.
Interface traps creation by sub‐band gap irradiation in silicon dioxide on silicon without applied electric field

The effective recombination lifetime of thermally oxidized silicon wafers is found to vary little following 4.2 eV ultraviolet irradiation but decrease dramatically when the photon energy is elevated up to 4.9 eV, indicating generation of the interface traps. This finding is discussed with the model of the hot‐electrons induced hydrogen redistribution in which about 2 eV energy is necessary for the electrons in the oxide conduction band to liberate a trapped hydrogen atom and generate in turn interface traps. It is stressed, however, that if the model is true the release of hydrogen atoms trapped inside the oxide should be, at least partly, responsible for the generation of interface traps because the samples used in this article are gate‐free.
An Approximate Carry Disregard Multiplier with Improved Mean Relative Error Distance and Probability of Correctness

Nowadays, a wide range of applications can tolerate certain computational errors. Hence, approximate computing has become one of the most attractive topics in computer architecture. Reducing accuracy in computations in a premeditated and appropriate manner reduces architectural complexities, and as a result, performance, power consumption, and area can improve significantly. This paper proposes a novel approximate multiplier design. The proposed design has been implemented using 45 nm CMOS technology and has been extensively evaluated. Compared to existing approximate architectures, the proposed approximate multiplier has higher accuracy. It also achieves better results in critical path delay, power consumption, and area up to 47.54 %, 75.24%, and 92.49%, respectively. Compared to the precise multipliers, our evaluations show that the critical path delay, power consumption, and area have been improved by 39%, 18%, and 6 %, respectively.
Implementing Transformer Architectures for Audio Source Separation

Audio source separation, utilized for speech denoising and music production, involves extracting individual sources from a mixed track. The project goal was to reduce training times for separation models with limited computing resources while improving accuracy, measured through signal-to-distortion ratio (SDR) and signal-to-interference ratio (SIR). We replaced the Bi-directional Long Short-Term Memory (BiLSTM) block with a transformer in the open-source Open-Unmix model, training it on the MUSDB18-HQ dataset. Ultimately, the transformer implementation trained faster than the unmodified Open-Unmix model while achieving a higher SIR but a lower SDR, demonstrating the potential of transformers in increasing efficiency and decreasing track bleed-through.
Some Reconsiderations of Simon's City-Size Distribution Model

In conjunction with the empirical findings that the form of city-size distributions is stable over time, this paper reexamines Simon's (1955) model and provides a better understanding of that model. First, a Simon-type model is proposed which is a generalization of Simon's model. Second, Simon's model is reexamined with respect to the ‘steady state’. Third, in the context of the Simon-type model, the necessary and sufficient conditions for the ‘steady state’ with the Yule (1924) city-size distributions are investigated. Last, the necessary and sufficient conditions for the ‘asymptotically steady state’ are obtained.
Improving Velocity Prediction in Electric Vehicles using Hybrid Artificial Neural Network (ANN)

Velocity prediction is an integral part for the development of robust Energy Management System (EMS) of an Electric Vehicle (EV) which essentially enhances the performance and life cycle of the vehicle. In this paper an ANN based approach combining Back-propagation Neural Network (BPNN) and Radial Basis Function Neural Network (RBFNN) is used to forecast velocity on different prediction horizons. These methods are tested on two conventional driving cycles viz. Manhattan and WYU driving cycle and one mixed cycle which is created by combining different random driving cycles. The results are studied in terms of Root Mean Square Error (RMSE) where the proposed network yields the least value in all the cases as compared to conventional BPNN method. The results proved the robustness and adaptability of the proposed method which can be used in practical applications.
Morphological, structural, and emission characterization of trench defects in InGaN/GaN quantum well structures

In a wide variety of InGaN/GaN quantum well (QW) structures, defects are observed which consist of a trench partially or fully enclosing a region of the QW having altered emission properties. For various different defect morphologies, cathodoluminescence studies suggest that the emission is redshifted in the enclosed region. Based on transmission electron microscopy and atomic force microscopy data, we suggest that the sub-surface structure of the trench defect consists of a basal plane stacking fault bounded by a stacking mismatch boundary, which terminates at the apex of a V-shaped trench.
The Impact of Emergency Remote Teaching on Postgraduate Engineering Students

Emergency Remote Teaching (ERT) resulted in postgraduate (PG) students moving from working closely within institutions, to working from home. The implicit assumption was that PG students would adapt more easily to ERT measures than undergraduate students, as a result of being more mature, academically experienced, and more resilient. This study sought to explore how ERT implemented during Covid-19 lockdowns impacted on the progress of PG students, and to provide a nuanced view on the factors that lead to student success. Through considering roads to success, enablers, as well as blocks and bottlenecks, the experience of ERT might provide insights into how to structure future (in person) PG experiences for improved productivity, self-efficacy and progress. A collation of three surveys, analysed using consideration of factors split into the cognitive, affective and systemic, highlighted factors that influence wellbeing and productivity and the relationship between the two. Respondents provide insights into how Higher Education institutions might improve support to their postgraduate cohorts. Within the systemic arena, PG students noted that success requires sufficient access to physical infrastructure, data, power and other physical enablers. In the cognitive space, respondents highlighted (amongst other points) that the blurring of work times and non-work times can result in unproductive (and stressful) time wasted; an idea which can be pulled through to future PG students: clearly delineate work and leisure times. The area which was reported to have the largest impact on PG student success was in the affective space. PG students require support (from peers, supervisors, friends and family) to thrive. The normal PG program evidently does well at supporting both systemic and cognitive needs in postgraduates, however, further attention might be paid to their affective needs.
Steady state estimation of soil organic carbon using satellite‐derived canopy leaf area index

Estimation of soil organic carbon (SOC) stock using models typically requires long term spin‐up of the carbon‐nitrogen (CN) models, which has become a bottleneck for global modeling. We report a new numerical approach to estimate global SOC stock that can alleviate long spin‐up. The approach uses satellite‐based canopy leaf area index (LAI) and takes advantage of a reaction‐based biogeochemical module—Next Generation BioGeoChemical Module (NGBGC) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as in CLM4CN, it can be easily configured to run prognostic or steady state simulations. The new approach was applied at point and global scales and compared with SOC derived from spin‐up by running NGBGC in the prognostic mode, and SOC from the Harmonized World Soil Database (HWSD). The steady state solution is comparable to the spin‐up value when the satellite LAI is close to that from the spin‐up solution, and largely captured the global variability of the HWSD SOC across the different dominant plant functional types (PFTs). The correlation between the simulated and HWSD SOC was, however, weak at both point and global scales, suggesting the needs for improving the biogeochemical processes described in CLM4 and updating HWSD. Besides SOC, the steady state solution also includes all other state variables simulated by a spin‐up run, which makes the tested approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare multiple aspects simulated by different CN mechanisms in the model.
Wavelet-Based Estimation of Hurst Exponent Using Neural Network

The paper proposes a method for estimating the Hurst exponent of time realizations using a regression neural network. The basis was the wavelet estimation method using a discrete wavelet transform. Wavelet energy spectra of fractional Brownian motion realizations were fed to the input of the neural network. The results showed that the accuracy of the Hurst exponent estimation, performed using a neural network, is ten times higher than the accuracy of statistical wavelet-based estimation.