Miracle-dz/UniFAR-FTUs huggingface dataset:
Heat transfer measurements and CFD simulations of an impinging jet

Heat transport in impinging jets makes a part of many experimental and numerical studies because some similarities can be identified between a pure impingement jet and industrial processes like, for example, the heat transfer at the bottom of an agitated vessel. In this paper, experimental results based on measuring the response to heat flux oscillations applied to the heat transfer surface are compared with CFD simulations. The computational cost of a LES-based approach is usually too high therefore a comparison with less computationally expensive RANS-based turbulence models is made in this paper and a possible improvement of implementing an anisotropic explicit algebraic model for the turbulent heat flux model is evaluated.
Fingerprint Positioning for Massive MIMO Systems Based on Machine Learning

Fingerprint-based positioning is promising for mobile cellular systems in dense scattering environments. Massive multiple-input multiple-output (MIMO) has significant advantages in providing accurate positioning due to the high angular resolution. This paper investigates the fingerprint-based positioning problem in massive MIMO systems utilizing machine learning. Adopting a improved spatial beam-based channel model, we exploit a novel beam domain channel amplitude matrix as the location-related fingerprint. We transform the positioning problem into a pattern recognition problem through fingerprint information. The base station can independently classify and distinguish the position fingerprints of different mobile user terminals via machine learning. Then, we propose a categorization-based positioning method by using the neural network. The performance of the proposed machine learning based fingerprint positioning method is evaluated with a geometry-based stochastic channel model. Simulation results demonstrate that the proposed positioning method can perform better than conventional approaches.
On the heat capacities of M2AlC (M=Ti,V,Cr) ternary carbides

In this paper, we report on the heat capacities cp of bulk polycrystalline samples of Ti2AlC, V2AlC, and Cr2AlC in the 3–260K temperature range. Given the structural and chemical similarities of these compounds it is not surprising that the cp’s and their temperature dependencies were quite similar. Nevertheless, at all temperatures the heat capacity of Cr2AlC was higher than the other two. The density of states at the Fermi level were 3.9, 7.5, and 14.6(eVunitcell)−1 for Ti2AlC, V2AlC, and Cr2AlC, respectively. The results obtained are analyzed using the Debye and Einstein model approximations for cp. Good description of cp is obtained if one assumes that nine phonon modes vibrate according to the Debye model approximation whereas the remaining 3 of 12 modes expected for M2AlC formula unit fulfill an Einstein-like phonon vibration pattern. Debye temperatures θD describing acoustic phonon and Einstein temperature θE describing optical phonon contributions have been estimated for the studied compounds. The.
Earnings Inequality Between and Within Firms in Canada’s Commercial Sector

Abstract:Des données administratives appariées employeur-employé tirées du Fichier de données longitudinales sur la main-d’œuvre de Statistique Canada, qui s’étendent sur presque trente ans, de 1991 à 2019, nous permettent d’analyser l’évolution de l’inégalité des gains entre les entreprises du secteur commercial au Canada et à l’intérieur de ces entreprises. Un modèle économétrique tenant compte des effets fixes des travailleurs et des entreprises suggère une inégalité croissante entre les entreprises, attribuable principalement à la disparité de leurs gains moyens et à l’évolution de la composition de leur main-d’œuvre respective.Abstract:Using almost three decades of administrative matched employer-employee data from Statistics Canada’s Longitudinal Worker File from 1991 to 2019, we analyze the evolution of earnings inequality between and within firms in Canada’s commercial sector. An econometric model controlling for worker and firm fixed effects suggests increasing inequality which has been predominantly driven by average earnings disparities between firms and changing composition of workers between firms.
Thermal conductivity of platinum and periclase under extreme conditions of pressure and temperature

ABSTRACT We have measured the thermal diffusivity and conductivity of platinum and MgO periclase at high pressures (P) and high temperatures (T) by combining the pulsed light heating thermoreflectance technique with a laser-heated diamond anvil cell. The obtained thermal conductivity of platinum shows positive pressure and temperature dependences, reaching about 210 W/m/K at the highest P–T condition of 125 GPa and 1850 K. The thermal conductivity of periclase was determined up to 140 GPa and 1950 K, corresponding to the Earth's lowermost mantle, where the conductivity was about 90 W/m/K. Our measurements allow us to test models for the combined P–T dependence of the thermal conductivity of both metals and insulating materials up to Mbar pressures and thousands of kelvins.
A Comparative Study on Predication of Appropriate Mechanical Ventilation Mode through Machine Learning Approach

Ventilation mode is one of the most crucial ventilator settings, selected and set by knowledgeable critical care therapists in a critical care unit. The application of a particular ventilation mode must be patient-specific and patient-interactive. The main aim of this study is to provide a detailed outline regarding ventilation mode settings and determine the best machine learning method to create a deployable model for the appropriate selection of ventilation mode on a per breath basis. Per-breath patient data is utilized, preprocessed and finally a data frame is created consisting of five feature columns (inspiratory and expiratory tidal volume, minimum pressure, positive end-expiratory pressure, and previous positive end-expiratory pressure) and one output column (output column consisted of modes to be predicted). The data frame has been split into training and testing datasets with a test size of 30%. Six machine learning algorithms were trained and compared for performance, based on the accuracy, F1 score, sensitivity, and precision. The output shows that the Random-Forest Algorithm was the most precise and accurate in predicting all ventilation modes correctly, out of the all the machine learning algorithms trained. Thus, the Random-Forest machine learning technique can be utilized for predicting optimal ventilation mode setting, if it is properly trained with the help of the most relevant data. Aside from ventilation mode, control parameter settings, alarm settings and other settings may also be adjusted for the mechanical ventilation process utilizing appropriate machine learning, particularly deep learning approaches.
Testing Hypotheses in Nonparametric Models of Production

Data envelopment analysis (DEA) and free disposal hull (FDH) estimators are widely used to estimate efficiency of production. Practitioners use DEA estimators far more frequently than FDH estimators, implicitly assuming that production sets are convex. Moreover, use of the constant returns to scale (CRS) version of the DEA estimator requires an assumption of CRS. Although bootstrap methods have been developed for making inference about the efficiencies of individual units, until now no methods exist for making consistent inference about differences in mean efficiency across groups of producers or for testing hypotheses about model structure such as returns to scale or convexity of the production set. We use central limit theorem results from our previous work to develop additional theoretical results permitting consistent tests of model structure and provide Monte Carlo evidence on the performance of the tests in terms of size and power. In addition, the variable returns to scale version of the DEA estimator is proved to attain the faster convergence rate of the CRS-DEA estimator under CRS. Using a sample of U.S. commercial banks, we test and reject convexity of the production set, calling into question results from numerous banking studies that have imposed convexity assumptions. Supplementary materials for this article are available online.
Neuropsychological Functions and Audiological Findings in Elderly Cochlear Implant Users: The Role of Attention in Postoperative Performance

Objectives: The present study aimed to investigate in a group of elderly CI users working memory and attention, conventionally considered as predictors of better CI performance and to try to disentangle the effects of these cognitive domains on speech perception, finding potential markers of cognitive decline related to audiometric findings. Methods Thirty postlingually deafened CI users aged >60 underwent an audiological evaluation followed by a cognitive assessment of attention and verbal working memory. A correlation analysis was performed to evaluate the associations between cognitive variables while a simple regression investigated the relationships between cognitive and audiological variables. Comparative analysis was performed to compare variables on the basis of subjects’ attention performance. Results: Attention was found to play a significant role in sound field and speech perception. Univariate analysis found a significant difference between poor and high attention performers, while regression analysis showed that attention significantly predicted recognition of words presented at Signal/Noise +10. Further, the high attention performers showed significantly higher scores than low attentional performers for all working memory tasks. Conclusion: Overall findings confirmed that a better cognitive performance may positively contribute to better speech perception outcomes, especially in complex listening situations. WM may play a crucial role in storage and processing of auditory-verbal stimuli and a robust attention may lead to better performance for speech perception in noise. Implementation of cognitive training in auditory rehabilitation of CI users should be investigated in order to improve cognitive and audiological performance in elderly CI users.
Modulation and free-space link characteristics of monolithically integrated vertical-cavity lasers and photodetectors with microlenses

We present temperature, modulation, and free-space link characteristics of monolithically integrated vertical-cavity lasers (VCLs) and resonant photodetectors. The devices have been integrated using a novel structure that makes it possible to fabricate devices with through-the-substrate emission and detection. Taking advantage of the substrate emitting/detecting architecture, we monolithically integrate microlenses on the substrate side of the devices and flip-chip bond arrays without via processes or substrate removal. Low-threshold high-efficiency VCLs exhibit maximum small-signal modulation bandwidths, which are limited by parasitics, of /spl sim/9.5 GHz at 20/spl deg/C and /spl sim/8.4 GHz at 70/spl deg/C. The VCLs have the lowest reported bias currents required to reach bandwidths of up to /spl sim/8 GHz. A free-space optical link is demonstrated with flip-chip-bonded arrays of microlensed, monolithically integrated VCLs and detectors. The link is found to be tolerant to temperature differences of /spl plusmn/75/spl deg/C between the VCL and detector, with error free (BER<10/sup -12/) data transmission demonstrated in each case.
Short circuits in the Corrsin–Obukhov cascade

Experiments show that a blob of scalar released in the inertial range of scales of a turbulent medium is rapidly converted into a set of disjointed sheets whose spectrum exhibits a k−1 shape for wave numbers larger than the injection wave number 1/d. The sheets diffusive uniformization onsets at a time ts=(d/u)f(Sc) with f(Sc)∼ln(Sc) function of the injection time of the blob in the medium d/u, of the Schmidt number Sc, independently of the Reynolds number. This time is appreciably smaller than the time needed to cross the Kolmogorov cascade, which is “bypassed” by a strong and constant stretching rate acting at the injection scale.
Complementary Electromagnetic Metasurfaces in a Dual Dielectric Half-Space

In this letter, we study the boundary conditions of complementary metasurfaces whose theoretical basis is the Babinet’s principle. Nevertheless, the metasurface is usually fabricated on the substrate interface, whereas the standard Babinet’s principle requests the metasurface to be in a homogenized space. In order to solve complementary metasurfaces, they are placed on dual substrate interfaces. By introducing the effective permittivity and dual effective permeability, the problem can be converted into complementary metasurfaces in the dual effective substrates, which exactly corresponds to the existing Babinet’s principle. Finally, an intrinsic equation can be established for complementary metasurfaces on the dual substrate interfaces, in which the effective permittivity and dual effective permeability can be exactly offset with each other. Thus, the proposed model provides a fresh and insightful perspective about the electromagnetic mechanism of complementary metasurfaces on the substrate interface.
A Note on the Type I Error Rate of the PARSCALE G2 Statistic for Long Tests

The PARSCALE G2 statistic is arguably the most popular item fit statistic in operational testing. For long tests, the Type I error rates of the statistic have often been found to be satisfactory. However, the Type I error rates of the statistic have only been studied for sample sizes of up to several thousands. The authors examined the Type I error rates of the PARSCALE G2 statistic in a simulation study using sample sizes much larger than those considered in the literature. For any fixed test length, the Type I error rate of the PARSCALE G2 statistic is found to increase to 1 as the sample size increases. The findings contradict the claim in the PARSCALE software manual that the PARSCALE G2 statistic leads to a large-sample test and also contradict the common belief that the statistic has reasonable Type I error rates for long tests. Thus, this simulation study conveys the important practical message that the use of the PARSCALE G2 statistic cannot always be recommended even for long tests. The Type I error rates of the item fit statistics of Orlando and Thissen were found to be close to the nominal level for all simulation conditions considered here.
Computational Biology Helps Understand How Polyploid Giant Cancer Cells Drive Tumor Success

Precision and organization govern the cell cycle, ensuring normal proliferation. However, some cells may undergo abnormal cell divisions (neosis) or variations of mitotic cycles (endopolyploidy). Consequently, the formation of polyploid giant cancer cells (PGCCs), critical for tumor survival, resistance, and immortalization, can occur. Newly formed cells end up accessing numerous multicellular and unicellular programs that enable metastasis, drug resistance, tumor recurrence, and self-renewal or diverse clone formation. An integrative literature review was carried out, searching articles in several sites, including: PUBMED, NCBI-PMC, and Google Academic, published in English, indexed in referenced databases and without a publication time filter, but prioritizing articles from the last 3 years, to answer the following questions: (i) “What is the current knowledge about polyploidy in tumors? ”; (ii) “What are the applications of computational studies for the understanding of cancer polyploidy? ”; and (iii) “How do PGCCs contribute to tumorigenesis? ”
An Analysis for the Applicability of Monin–Obukhov Similarity Theory in Stable Conditions

AbstractAn analysis in a plane of the stability parameters ζ = z/L (where z is a height above the ground surface and L is the Obukhov length) and bulk Richardson number RiB is proposed to examine the applicability of Monin–Obukhov similarity (MOS) theory in stable conditions. In this analysis, the data available from two different experimental datasets [(i) Cooperative Atmosphere–Surface Exchange Study-1999 (CASES-99) and (ii) Cardington] are divided into four quadrants. An unexpected behavior of decreasing ζ with increasing RiB was observed with both datasets in quadrant II characterized by ζ 0.2 and in quadrant IV with ζ > 1 and RiB 1 and RiB > 0.2) and III (with ζ < 1 and RiB < 0.2), whereas it may not be applicable for the points in quadrants II .
The three-dimensional structure of the wake of a circular cylinder

A critical scrutiny of the nature of the three-dimensional characteristics of the vortex wake of a circular cylinder serves to suggest lines for further investigation and furnishes some ideas on the nature of the growth and development of these non-uniformities. It is suggested that the basic occurrence in the growth of three-dimensionality is the continuation of vortex lines, oriented more or less parallel to the body, into the direction of the free stream. The causes of this vary, as do the details of the development with the particular situation considered. Experiments were performed in a wind tunnel at Reynolds numbers based on cylinder diameter of 85, 235 and 2 × 104, at which stable, transitional and turbulent vortices were investigated.
Effects of White and Blue-Red Light on Growth and Metabolism of Basil Grown under Microcosm Conditions

Indoor farming of basil (Ocimum basilicum L.) under artificial lighting to support year-round produce demand is an area of increasing interest. Literature data indicate that diverse light regimes differently affect downstream metabolic pathways which influence basil growth, development and metabolism. In this study, basil was grown from seedlings to fully developed plants in a microcosm, an innovative device aimed at growing plants indoor as in natural conditions. Specifically, the effects of white (W) and blue-red (BR) light under a photosynthetic photon flux density of 255 μmol m−2 s−1 on plant growth, photochemistry, soluble nutrient concentration and secondary metabolism were investigated. Plants grew taller (41.8 ± 5.0 vs. 28.4 ± 2.5 cm) and produced greater biomass (150.3 ± 24.2/14.7 ± 2.0 g vs. 116.2 ± 28.3/12.3 ± 2.5 g fresh/dry biomass) under W light compared to BR light. The two lighting conditions differently influenced the soluble nutrient concentration and the translocation rate. No photosynthetic stress was observed under the two lighting regimes, but leaves grown under W light displayed higher levels of maximum quantum yield of PSII and electron transport rate. Sharp differences in metabolic patterns under the two lighting regimes were detected with higher concentrations of phenolic compounds under the BR light.
90-m/660-Mbps Underwater Wireless Optical Communication Enabled by Interleaved Single-Carrier FDM Scheme Combined With Sparse Weight-Initiated DNN Equalizer

In this paper, we first utilize the interleaved single-carrier frequency division multiplexing (I-SC-FDM) scheme with a novel sparse weight-initiated deep neural network (SWI-DNN) equalizer for underwater optical communication (UWOC) systems. In addition to the superior characteristics of I-SC-FDM over the original OFDM and localized SC-FDM (L-SC-FDM), such as lower peak-to-average power ratio (PAPR) and lower computational complexity, the implementation of a special sparse weight-initiated (SWI) structure can significantly reduce the necessary training epochs up to 10.3%, which enables the proposed SWI-DNN equalizer to outperform the traditional random weight-initiated DNN equalizer. Besides, further pruning operation can dramatically enhance the final sparsity of the SWI-DNN equalizer to 96.88% at the expense of an inappreciable performance penalty, thereby effectively saving occupied computing resources. Following this, a data rate of up to 660 Mbps over a 90-m underwater transmission can be achieved in a standard 50-m swimming pool, with a relatively low received optical power of −31.12 dBm (at the BER of 3.8 × 10−3). Such a data rate is 17.9% higher than that obtained with a common hybrid time-frequency domain (TFD) equalizer. Moreover, the computational complexity of the SWI-DNN equalizer after pruning operation is only 11.83% of that of the hybrid TFD equalizer and can still support a 625-Mbps transmission. This is the first time to employ I-SC-FDM combined with an SWI-DNN equalizer for long-distance high-speed UWOC transmission, and it can be highly beneficial to the cost-sensitive and power-sensitive systems in future deployment.
An Improved DFC-Based Cooperative Spectrum Sensing for Cognitive Radio in the Presence of Malicious Users

In cognitive radio networks (CRNs), cooperative spectrum sensing (CSS) can effectively improve sensing performance by taking advantage of spatial diversity of participating second users (SUs). However, the spectrum sensing data falsifying attack (SSDFA) caused by malicious second users (MSUs) severely degrades the performance of CSS networks. In this paper, to defend against the SSDFA of MSUs, we propose a new CSS mechanism based on distributed fusion centers and overlapping clusters (DFCs-OCs). With this new architecture, our proposed linear combining CSS algorithm improves the CSS performance by mitigating the effects of MSUs on decision making through updating the reputations of SUs and OCs. Extensive simulation results prove that the proposed CSS scheme performs far better than related recent studies under both high and low signal-to-noise ratio conditions in CRNs, where MSUs occupy nearly half of all SUs.
Some comments on informational masking

While informational masking (IM) has been investigated for almost a half century, only recently have there been efforts to develop a principled definition of this class of interference effects among sensory stimuli. This paper briefly reviews the history of IM and discusses some recent efforts toward a definition. Some experiments with tonal patterns are then described that demonstrate close associations between the effects of IM on detection and on discrimination. It is proposed that the varieties of IM revealed in recent research may not all be reasonably attributed to a single explanatory mechanism, even a fairly complex one. At the least, IM effects associated with signal-masker similarity (S) are readily distinguished from those resulting from trial-to-trial stimulus uncertainty (U). A corresponding distinction may usefully be made in definitions and models, dealing separately with S and U types of IM.