Miracle-dz/UniFAR-FTUs huggingface dataset:
The Derivational and Inflectional Morpheme in Dwayne Johnson’s Speech: Morphology Perspective

This research aims to discover the category of words that are taken from an object of speech. The researcher focuses on occurrence frequency and the process of words that have been used in the speech. This research applied a descriptive qualitative method. The researcher collected some words through the speech, and then continued to classify them into morphological analysis, specifically derivational morpheme and inflectional morpheme. The researcher employed the Victoria Fromkin theory to analyze the words and filter them into the derivational morpheme category and inflectional morpheme category. The results reveal the 48 words with 10 of them (21%) represent derivational morphemes. In the derivational morphemes, there are 2 words whose parts of speech do not change and 8 words that do. There are 38 inflectional morphemes (79%) that are divided into 8 categories. These 8 categories consist of 14 plural words, 9 progressive words, 8 past tense words, 2 superlative words, 2 possessive words, 2 third person singular words, and 1 past participle word.
The expansion of Tycho's supernova remnant as determined by a new algorithm for comparing data

On a etudie l'expansion du reste de supernova de Tycho (3C 10) en utilisant deux couples d'observations radio sur des intervalles de 3,07 et 14,86 ans, aux frequences de 2,7 et 1,4 GHz respectivement. L'expansion moyenne est 0,113±0,006 pour cent par an, ce qui correspond a une loi d'expansion R # t 0,462±0,024 . A faible echelle, le milieu constituant la nebuleuse se revele heterogene
Comparison of Different Frequency Allocation Methods for Suburban Areas based on Capacity Analysis

From the first generation (1G) to the fifth generation (5G), an upward trend in demand has been witnessed as wireless technology contributes to more aspects in the daily life of ordinary people. A similar pattern is likely to be seen in the next decade as sixth generation (6G) networks are deployed. Researchers are having a stronger incentive in frequency planning in order to bring a better experience to users. Therefore, by collecting capacity data for a network of nineteen cells with an average of five users and twelve channels per cell, different frequency allocation methods from 1 decibel (dB) to 20 dB (dB) are investigated for their superiority in suburban areas based on the comparison of capacity. The experiments conducted in this paper show that cellular networks outperform Fractional Frequency Reuse (FFR) and that the more intelligent the frequency allocation method, the higher the capacity. Therefore, telecommunication providers may consider prioritizing the 19-cell Forward Looking Game (FLG) method in areas with low population density.
Antifungal Activities of Phytochemicals from Annona muricate (Sour Sop): Molecular Docking and Chemoinformatics Approach

Fungal infection has become a persistent problem in humans and is sometimes life-threatening in immune-compromised individuals. This work aims to study phytochemicals from Annona muricata (sour sop) as probable antifungal agents against Candida albicans sterol 14α-demethylase target receptor by Computer Aided-Drug Design (CADD) approach using voriconazole and fluconazole as standard drugs. A modern method of drug discovery by molecular docking and chemoinformatics was used to screen 131 isolated phytochemicals with medicinal properties from Annona muricata against Candida albicans ‘sterol 14α-demethylase, a prominent target receptor for most anti-fungal drugs, towards the development of new anti-fungal therapeutic agents and a new approach to treat patients with fungal infections. The compounds were all subjected to analyses like ADMET, drug-likeness, bioactivity, oral-bioavailability and PASS. The results of the docking simulation and chemoinformatics analyses showed that muricin M (-7.9 kcal/mol), chlorogenic acid (-8.2 kcal/mol), roseoside (-8.5 kcal/mol) and caffeoylquinic acid (-8.1 kcal/mol) are potential drug candidates for treating fungal infections due to their excellent properties such as binding affinities, ADMET profile, drug-likeness, bioactivity, binding mode and interactions with the target receptor. Thus, muricin M, chlorogenic acid, roseoside and caffeoylquinic acid are recommended for further analyses towards the development of further antifungal drugs.
Measuring age differences among globular clusters having similar metallicities - A new method and first results

A color-difference technique for estimating the relative ages of globular clusters with similar chemical compositions on the basis of their CM diagrams is described and demonstrated. The theoretical basis and implementation of the procedure are explained, and results for groups of globular clusters with m/H = about -2, -1.6, and -1.3, and for two special cases (Palomar 12 and NGC 5139) are presented in extensive tables and graphs and discussed in detail. It is found that the more metal-deficient globular clusters are nearly coeval (differences less than 0.5 Gyr), whereas the most metal-rich globular clusters exhibit significant age differences (about 2 Gyr). This result is shown to contradict Galactic evolution models postulating halo collapse in less than a few times 100 Myr. 77 refs.
Effects of exogenous salicylic acid on alleviation of arsenic-induced oxidative damages in rice

Abstract Salicylic acid (SA) is a phenolic phytohormone that plays a vital role in plant development and mediates plant responses to plenty of adversity including arsenic (As) stress. The effects of exogenous addition of SA on As tolerance and As accumulation were assessed in two cultivars of rice (Oryza sativa L.) Nipponbare and Zhongzao 39, hydroponically grown with Kimura B nutrient solution under arsenite [As (III)] and dimethylarsonic acid (DMA) exposure. In the second ex-periment, the influence of soaking seed with SA on As uptake and As damages was investigated in rice (cv. Nipponbare) exposed to As (III) and DMA. The results showed that exogenous addition of SA significantly decreased the concentrations of hydrogen peroxide (H2O2) and malondialdehyde (MDA) in both As (III)- and DMA-stressed rice, indicating that SA alleviates As-induced oxidative damages in rice. SA increased the activity of antioxidant enzymes and, moreover, increased the relative amount of glutathione (GSH) and ascorbate (ASA) by accelerating the GSH-ASA circle system. Exogenous addition of SA significantly decreased the As concentration in both roots and shoots of rice under As(III) stress by influencing the expression of genes encoding As transporters, viz. OsLsi1, OsLsi2. The addition of SA significantly decreased the As content in shoots under DMA stress, which may be related to the expression of OsPTR7 involved in shoot xylem unloading. This finding may foster a novel perspective for reducing As accumulation in rice grains.
Only Right Makes Might? Center-Right Policy Competition Among Major Japanese Parties After Electoral Reform

The effects of the 1990s reforms to the electoral system of Japan's House of Representatives have been among the most frequently discussed topics in political science research on the country. These reforms saw the replacement of a hitherto single nontransferable vote (SNTV) system by a mixed-member majoritarian (MMM) system with a strong Single Member District (SMD) and a weaker Proportional Representation (PR) component. Many studies have suggested that the reforms may have had significant impact on the strategies of political parties. Generally, SMD systems have been widely thought to favor larger parties, while PR systems are more beneficial to small and medium-sized parties. On the content side, larger parties seeking control of the government would try to win the support of large numbers of floating voters by campaigning on universal/programmatic policy appeals, as opposed to particularistic interests. In contrast, smaller parties would cater towards their core supporters’ preferences. Previous studies have noted that the old SNTV system in Japan had produced results similar to PR systems (Reed 2003). Japan's electoral reform may have thus changed the strategy of large parties, which would need to win more seats in the SMDs to gain (or hold onto) power, while smaller parties have continued to try and win seats via the PR tier. Therefore, the reform provides valuable research material in so far as we can simultaneously observe different effects by the SMD and the PR systems on parties of different sizes.
An over-pressure correction to the slug model for vortex ring circulation

The slug model provides a formula for the circulation of vortex rings formed by starting jets ejected from a nozzle or orifice in terms of the time history of the jet velocity. For rapidly initiated jets, however, the model under-predicts circulation by an amount that remains nearly constant as circulation increases. To remedy this shortcoming, the present study derives an equation for circulation directly from the governing equations for the flow, illustrating that the circulation can be expressed as the sum of a flux term, $\Gamma_U$, determined by the jet centreline velocity and a ‘source’ term, $\Gamma_p$, determined by over-pressure at the jet centreline during vortex ring formation. For impulsively or nearly impulsively initiated jets, $\Gamma_p$ is modelled using potential flow analysis since over-pressure is significant primarily during the rapid jet initiation in these cases. The effects of the jet initiation and boundary-layer growth on the jet centreline velocity are also considered to provide a realistic model for $\Gamma_U$. Models for nozzle and orifice configurations are developed. In the case of a nozzle-type generator, the need to model the jet centreline velocity leads to an approximate solution for starting flow near the exit of an infinitely long pipe. For the nozzle case, the model results agree with available circulation measurements to within ${\pm}$6.2% for a wide range of conditions, except for jet velocity programs that are nearly triangular. In the orifice case, the model agrees with available results to within ${-}$13%. Both cases show substantial improvement over the slug model, which is in error by ${-}$21% to ${-}$67% for the data considered.
The Relationship between Parental Emotional Warmth and Rural Adolescents’ Hope: The Sequential Mediating Role of Perceived Social Support and Prosocial Behavior

Abstract Parental emotional warmth plays a prominent role in adolescents’ hope, but few studies have examined the underlying mechanism between parental emotional warmth and hope in rural adolescents, or have compared the gender differences in the mediation models between parental emotional warmth and hope. Based on the developmental contextualism theory and Bernardo’s hope theory, this study examined the sequential mediating effect of perceived social support and prosocial behavior between parental emotional warmth and hope and test the gender differences between them. Seventeen hundred and one rural adolescents were surveyed with the Short-Form Egna Minnen av Barndoms Uppfostran (s-EMBU-C), Perceived Social Support Scale (PSSS), Prosocial Tendency Measure (PTM), and Hope Scale (HS). Correlation analysis showed that there were positive correlations between parental emotional warmth, perceived social support, prosocial behavior, and hope. The structural equation model showed that parental emotional warmth indirectly affected hope through the separate and sequential mediation of perceived social support and prosocial behavior. Multi-group analysis showed that boys were significantly higher than girls in the relationship between perceived social support and prosocial behavior. The results emphasized that improving parental emotional warmth, perceived social support, and encouraging rural adolescents’ prosocial behavior could effectively promote their hope.
Improving Academic Performance in Geometry Using a Mastery Learning Approach through GeoGebra

The objectives of these quasi-experimental methods were to improve academic performance in geometry using a mastery learning approach through GeoGebra for mathematics teacher students and to investigate students’ satisfaction with using a mastery learning approach through GeoGebra in geometry. The participants were divided into two groups, involving 30 and 29 students, respectively. The experimental group with 30 students received instruction in the mastery learning approach through GeoGebra, while the control group received a traditional education in learning geometry. At the end of the lessons, post-tests were administered to both groups. The statistical difference between the participant’s post-test academic performance in the experimental and control groups was analyzed with an independent sample t-test after examining the assumptions of this test, namely normality and homogeneity in each group, while percentages and means were used to assess the satisfaction of the experimental group. The instruments used were the Geometry Achievement Test (GAT), which consists of 2D and 3D dimensions, and a questionnaire with satisfied students. Results of the study indicated that the scores of academic performances in the experimental group were significantly higher than those of the control group. Analysis of the questionnaire responses indicated a positive overall satisfaction with using a mastery learning approach through GeoGebra in geometry. On the other hand, instruction with a mastery learning approach through GeoGebra supported students’ learning of these subjects meaningfully and conceptually.
Estimating Nonlinear Models

Measurement errors in predictor variables bias multiple regression coefficients, and the problem is particularly complex with nonlinear models containing product variates. This article presents formulas and computing algorithms for correcting data before regression analyses in order to eliminate biases due to measurement errors in models with second- and third-order product variates (e.g., YZ and XYZ). The method requires independent estimates of error variances and covariances for the first-order variates (e.g., X, Y, and Z). An analysis of empirical data illustrates the approach. Errors in estimates are examined through Monte Carlo analyses.
Population-Level Trends in Emergency Department Encounters for Sexual Assault Preceding and During the COVID-19 Pandemic Across Ontario, Canada

Key Points Question What were the population-level changes in emergency department (ED) encounters for sexual assault through 4 waves of the COVID-19 pandemic in 2020 to 2021 compared with 2019 in Ontario, Canada? Findings This cohort study of 14 476 656 ED encounters found that ED encounters for sexual assault increased leading up to the state of emergency, decreased immediately after implementation of the lockdown, and then oscillated as the pandemic continued. The pattern was seen across sex, age, income, and community size. Meaning These findings suggest that the COVID-19 pandemic may be limiting access to ED care for sexual assault, and survivors should be encouraged to present to EDs when clinical care or legal interventions are needed.
Interpretation of the field enhancement factor for electron emission from carbon nanotubes

The local electric fields in the vicinity of the tips of metallic nanotubes are calculated. The variation in the field enhancement factor as a function of internanotube separation, anode-substrate separation, and height and radius of the nanotube is reported. Calculations show that the field induced electron emission current, based on the Fowler–Nordheim theory, is reduced when the intertube separation is less than twice the height of the nanotube. The location of the anode plane is shown to be important when the anode-substrate separation is less than three times the height of the nanotube. The results also predict that the macroscopic threshold field for electron emission should decrease as the anode-substrate separation D decreases. For separations greater than three times the height of the nanotube, the threshold field becomes constant and independent of anode-cathode geometry. Conversely, the manner in which applied electric field is defined is crucial if the results are be understood better. Experim.
Mesoscale Ocean Surface Current Structure Detected by High-Frequency Radar

Abstract The quality and vertical correlation scales of high-frequency (HF) radar-derived ocean surface current measurements from an ocean surface current radar (OSCR) are assessed by comparing surface to subsurface current observations from 11 June to 8 July 1993 at directional discus buoys DW and DE, each instrumented with a three-axis ultrasonic current meter at the 13.8- and 9.5-m depths, respectively. A dual-station OSCR mapped the current fields at 20-min intervals at a horizontal resolution of 1.2 km over a 30 km × 44 km domain inshore of the Gulf Stream using the HF (25.4 MHz) mode. Over a 27-day experimental period, surface current observations were acquired 97% of the time extending to the maximum theoretical range of 44 km. Linear regression analyses indicated a bias of 2–4 cm s−1 and slopes of O(1). While there were periods when the daily averaged complex correlation coefficients were highly correlated (>0.8), periods of low correlation (<0.3) are explained in terms of vertical phase differenc.
A numerical study of water-wave modulation based on a higher-order nonlinear Schrödinger equation

In existing experiments it is known that the slow evolution of nonlinear deep-water waves exhibits certain asymmetric features. For example, an initially symmetric wave packet of sufficiently large wave slope will first lean forward and then split into new groups in an asymmetrical manner, and, in a long wavetrain, unstable sideband disturbances can grow unequally to cause an apparent downshift of carrier-wave frequency. These features lie beyond the realm of applicability of the celebrated cubic Schrödinger equation (CSE), but can be, and to some extent have been, predicted by weakly nonlinear theories that are not limited to slowly modulated waves (i.e. waves with a narrow spectral band). Alternatively, one may employ the fourth-order equations of Dysthe (1979), which are limited to narrow-banded waves but can nevertheless be solved more easily by a pseudospectral numerical method. Here we report the numerical simulation of three cases with a view to comparing with certain recent experiments and to complement the numerical results obtained by others from the more general equations.
Third-order spectral techniques for the diagnosis of motor bearing condition using artificial neural networks

This paper addresses the development of a novel condition monitoring procedure for rolling element bearings which involves a combination of signal processing, signal analysis and artificial intelligence methods. Seven approaches based on power spectrum, bispectral and bicoherence vibration analyses are investigated as signal pre-processing techniques for application in the diagnosis of a number of induction motor rolling element bearing conditions. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the power spectrum, the bispectrum, the bicoherence, the bispectrum diagonal slice, the bicoherence diagonal slice, the summed bispectrum and the summed bicoherence. Selected features are extracted from the vibration signatures so obtained and these are used as inputs to an artificial neural network trained to identify the bearing conditions. Quadratic phase coupling (QPC), examined using the magnitude of bispectrum and bicoherence and biphase, is shown to be absent from the bearing system and it is therefore concluded that the structure of the bearing vibration signatures results from inter-modulation effects. In order to test the proposed procedure, experimental data from a bearing test rig are used to develop an example diagnostic system. Results show that the bearing conditions examined can be diagnosed with a high success rate, particularly when using the summed bispectrum signatures.
Feedback chaotic synchronization of a complex chaotic system with disturbances

In this paper, the basic dynamical properties of a complex chaotic system are investigated by the imaginary part and the real part of the complex chaotic system are separated. Based on Lyapunov stability theorem, a feedback control method is proposed for synchronization of a complex chaotic system with parameters perturbation and external disturbances. The simulation results show the feasibility of the method.
The diamagnetism of free electrons

A rigorous formulation is given of the quantum theory of the diamagnetism of free electrons. It is shown that Z, the partition function in classical statistics, may be calculated for arbitrary magnetic fields and temperatures without explicit knowledge of the energy levels, and complicated arguments involving boundary electrons are therefore unnecessary. It is further shown that the phenomena which arise in Fermi-Dirac statistics are determined by the singularities of Z regarded as a function of a complex variable, and, in particular, that the poles of Z give rise to the de Haas-van Alphen effect (the periodic field dependence of the susceptibility at low temperatures). The theory confirms the results obtained in earlier treatments.
Phenotypic Analysis of Diseased Plant Leaves Using Supervised and Weakly Supervised Deep Learning

Deep learning and computer vision have become emerging tools for diseased plant phenotyping. Most previous studies focused on image-level disease classification. In this paper, pixel-level phenotypic feature (the distribution of spot) was analyzed by deep learning. Primarily, a diseased leaf dataset was collected and the corresponding pixel-level annotation was contributed. A dataset of apple leaves samples was used for training and optimization. Another set of grape and strawberry leaf samples was used as an extra testing dataset. Then, supervised convolutional neural networks were adopted for semantic segmentation. Moreover, the possibility of weakly supervised models for disease spot segmentation was also explored. Grad-CAM combined with ResNet-50 (ResNet-CAM), and that combined with a few-shot pretrained U-Net classifier for weakly supervised leaf spot segmentation (WSLSS), was designed. They were trained using image-level annotations (healthy versus diseased) to reduce the cost of annotation work. Results showed that the supervised DeepLab achieved the best performance (IoU = 0.829) on the apple leaf dataset. The weakly supervised WSLSS achieved an IoU of 0.434. When processing the extra testing dataset, WSLSS realized the best IoU of 0.511, which was even higher than fully supervised DeepLab (IoU = 0.458). Although there was a certain gap in IoU between the supervised models and weakly supervised ones, WSLSS showed stronger generalization ability than supervised models when processing the disease types not involved in the training procedure. Furthermore, the contributed dataset in this paper could help researchers get a quick start on designing their new segmentation methods in future studies.