Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling of a water plasma flow: I. Basic results

One-fluid MHD equations are numerically solved for an axisymmetric flow of thermal water plasma inside and outside a discharge chamber of a plasma torch with water vortex stabilization of electric arc. Comparisons with experimental data and previous calculations are given. For arc currents of 300–600 A, the respective temperatures and velocities in the range 16 700–26 400 K and 2300–6900 m s−1 are obtained at the centre of the nozzle exit. The flow velocity on axis increases by 1–2 km s−1 in the 5 mm long nozzle. Ohmic heating and radiative losses are two competitive processes influencing most the plasma temperature and velocity. The radiative losses represent 39% to 46% of the torch power of 69–174 kW when optical thickness of 3 mm is assumed for the plasma column. In front of the cathode, inside the discharge chamber, a recirculation zone is predicted and discussed. Effects of the temperature dependence of the plasma viscosity and sound velocity and of the optical thickness are examined. It is shown that the results such as waviness of the Mach number isolines are direct consequences of these dependences. Different lengths of 55 and 60 mm of the water vortex stabilized part of the electric arc do not substantially influence the plasma temperature and velocity at the nozzle exit.
Catch the Pitch of 5G FWA: EMF and Throughput Measurements of 3.5-GHz Standalone Deployment in a Baseball Stadium

The provisioning of 5G technology does not only involve mobile terminals, but also new services such as Fixed Wireless Access (FWA). The aim of this study is to examine the ElectroMagnetic Field (EMF) and throughput performance of a FWA deployment utilizing Standalone technology operating at 3.5 GHz. To address the unique characteristics of 5G FWA signals, an innovative framework has been designed based on the measurement of 5G FWA spectrum using four independent chains and an additional traffic generation chain to saturate the radio link capacity at the measurement location. Methodologies for evaluating 5G FWA exposure under conservative conditions, such as measurements of exposure during active traffic generation and maximum power extrapolations, are also introduced. Results from real measurements taken at a baseball stadium show that 5G FWA exposure is consistently low, typically below 0.4 [V/m], with an upper bound of 0.59 [V/m], while the achieved throughput is up to 250 [Mbps]. Additionally, the measured 5G exposure levels are a small fraction compared to those emitted by other technologies such as 4G. Furthermore, the values estimated by simulation from the output power counters of the base station are found to be in close agreement with the measured exposure levels.
Particle Growth and Drop Collection Efficiency of Warm Clouds as Inferred from Joint CloudSat and MODIS Observations

This study describes an approach for combining CloudSat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations to investigate the microphysical processes of warm clouds on the global scale. MODIS column optical thickness is vertically distributed between the cloud top and cloud bottom according to adiabatic and condensational growth assumptions and used as a vertical coordinate system to analyze profiles of CloudSat-observed radar reflectivity. The reflectivityprofiles thus rescaled as a function of the in-cloud optical depth clearly depict how the cloud-to-rain particle growth processes take place within the cloud layer and how these processes vary systematically with variations in MODIS-derived effective particle radius. It is also found that the effective radii retrieved using two different wavelengths of MODIS tend totracethe microphysical change of reflectivity profiles in a different way because of the difference in the layer depth that characterizes these two effective radii. The reflectivity profiles as a function of optical depth are also interpreted in terms of drop collection processes based on the continuous collection model. The slope of the reflectivity change with optical depth provides a gross measure of the collection efficiency factor. The systematic changes of reflectivity profiles with MODIS-derived particlesizesaretheninterpretedasdemonstratingastrongdependencyofthecollectionefficiencyonparticlesize. Theseresultsprovideaquantitativeinsightintothedropcollectionprocessofwarmcloudsintherealatmosphere.
Estimating Heston's and Bates’ models parameters using Markov chain Monte Carlo simulation

Heston's model and Bates’ model are very important in option pricing. It is mentioned in Mendoza's paper [Bayesian estimation and option mispricing (job market paper). Cambridge, MA: Massachusetts Institute of Technology; 2011] that Mexican Stock Exchange introduced options over its main index (the Índice de Precios y Cotizaciones) in 2004 which used Heston's model to price options on days when there was no trading. The estimation of the parameters in both models is not easy. One of the methods is Markov chain Monte Carlo algorithm (MCMC for short). In this paper, we adopt Li, Wells and Yu's MCMC algorithm [A Bayesian analysis of return dynamics with levy jumps. Rev Financ Stud. 2008;21(5):2345–2377]. We provide the necessary derivation utilizing prior distributions since they are otherwise unavailable in the literature. As Li et al. used their model to analyse S&P 500 data from 2 January 1980 to 29 December 2000, we likewise recreate their analysis, this time using data from 1987 to 2012. We would like to involve the financial crisis and analyse how stable the method is while applying to the financial crisis. Unlike Li et al., we find that the estimation is very sensitive to the prior distribution assumption. In addition, we have R-code available by request. We hope to offer tools for people doing empirical research in financial mathematics or quantitative finance.
Positive classroom climate buffers against increases in loneliness arising from shyness, rejection sensitivity and emotional reactivity

Loneliness is detrimental to well-being, particularly during the transition into and early years of adolescence when peer relations are ascendant. Shy and emotionally sensitive youth, who often spend considerable time alone, have known vulnerabilities to loneliness. Studies of young children suggest that a supportive classroom context may mitigate adjustment risks, reducing victimization and improving a sense of belonging. Herein we extend this work to older students, testing the hypothesis that a positive classroom climate protects temperamentally vulnerable children (i.e., those who are shy, emotionally reactive, or sensitive to rejection) from escalating levels of loneliness across the course of a school year. A community sample of 540 (277 boys, 263 girls) Lithuanian students in grades 5–7 (10–14 years old) completed identical surveys twice, 4–5 months apart. Self-reports assessed shyness, emotional reactivity, and rejection sensitivity, as well as perceived positive classroom climate and loneliness. Path analyses indicated that longitudinal associations from shyness, emotional reactivity, and rejection sensitivity to increased loneliness were mitigated by positive classroom climate. In each case, temperamental vulnerability anticipated greater loneliness for youth reporting low but not high positive classroom climate. The results held after accounting for several potential confounding variables. The findings have practical implications, suggesting that scholars and practitioners redouble efforts to improve classroom support, particularly for temperamentally vulnerable children who are at elevated risk for solitude, loneliness, and attendant mental health challenges.
Optic disc and retinal vascular features in first 6 years of Chinese children

Purpose Retinal microvasculature plays an important role in children's fundus lesions and even in their later life. However, little was known on the features of normal retina in early life. The purpose of this study was to explore the normal retinal features in the first 6 years of life and provide information for future research. Methods Children, aged from birth to 6 years old and diagnosed with various unilateral ocular diseases were included. Venous phase fundus fluorescein angiography images with the optic disc at the center were collected. Based on the ResUNet convolutional neural network, optic disc and retinal vascular features in the posterior retina were computed automatically. Results A total of 146 normal eyes of 146 children were included. Among different age groups, no changes were shown in the optic disc diameter (y = −0.00002x + 1.362, R2 = 0.025, p = 0.058). Retinal vessel density and fractal dimension are linearly and strongly correlated (r = 0.979, p < 0.001). Older children had smaller value of fractal dimension (y = −0.000026x + 1.549, R2 = 0.075, p = 0.001) and narrower vascular caliber if they were less than 3 years old (y = −0.008x + 84.861, R2 = 0.205, p < 0.001). No differences were in the density (y = −0.000007x + 0.134, R2 = 0.023, p = 0.067) and the curvature of retinal vessels (lnC = −0.00001x − 4.657, R2 = 0.001, p = 0.667). Conclusions Age and gender did not impact the optic disc diameter, vessel density, and vessel curvature significantly in this group of children. Trends of decreased vessel caliber in the first 3 years of life and decreased vessel complexity with age were observed. The structural characteristics provide information for future research to better understand the developmental origin of the healthy and diseased retina.
Hard wall - soft wall - vorticity scattering in shear flow

An analytically exact solution, for the problem of low Mach number incident vorticity scattering at a hard-soft wall transition, is obtained in th e form of Fourier integrals by using the Wiener-Hopf method. Harmonic vortical perturbations of inviscid linear shear flow are scattered at the wall transition. This results in a fa r field which is qualitatively different for low shear and high shear cases. In particular, for high shear the pressure (apparently driven by the mean flow) does not decay and its Fou rier representation involves a diverging integral which is to be interpreted in generalised sense. Then the incompressible hydrodynamic (Wiener-Hopf) “inner” solution is matched asymptotically to an acoustic outer field in order to determi ne the sound associated to the scattering. The qualitative difference between low and high shear is also apparent here. The low shear case matches successfully. In the high shear case only a partial matching was possible.
Joint Active-Passive Beamforming and User Association in IRS-Assisted mmWave Cellular Networks

Intelligent reflecting surfaces (IRSs) are a promising technology for future-generation wireless networks by extending coverage region to blind spots and increasing mmWave propagation paths in non-line of sight environments. User association (UA) in dense millimeter wave (mmWave) networks is vital to characterizing connections among base stations (BSs) and mobile users for load balancing, interference management, and maximizing network utility. However, it has yet to be examined thoroughly in a multi-IRS-aided network. This paper presents a new UA scheme that takes cell interference into account for a multi-cell mmWave cellular network aided with multiple IRSs. We formulate a network spectral efficiency maximization problem by jointly optimizing active beamforming (AB) at the BSs, passive beamforming (PB) at the IRSs, and user-BS association with consideration of the impact of IRSs. We then propose a computationally efficient iterative algorithm based on alternating optimization (AO) to resolve this intractable mixed-integer non-convex problem. A fractional programming technique is used to optimize active beamforming at the BSs and passive beamforming at the IRSs, and a penalization method combined with successive convex programming is applied for UA optimization, which is shown to reach the optimal solution. Simulation results show significant performance improvements obtained by the proposed algorithm, providing higher spectral efficiency compared to several benchmark algorithms, while having a low computational complexity.
Effect of balanced fertilization on production, quality, energy use efficiency of baby corn (Zea mays) and soil health

Field experiment was conducted on baby corn (Zea mays L.) in sandy loam soil during the pre-kharif season of 2012 and 2013 at Varanasi to assess the effect of balanced fertilization (NPKS and Zn) on productivity, quality, energetics and soil health of baby corn. Results revealed that application of 125% RDF (187.5, 93.75, 75.0 kg NPK/ha) produced significantly higher yields of total baby cob yield with husk (9.55 tonnes/ha) and total baby corn yield without husk (2.15 tonnes/ha). Similarly, the higher nutrients (NPKS) and protein content in baby corn and green husk were recorded with application of 125% RDF. Among different levels of S and Zn, application of 50 kg S and 10 kg Zn/ha produced significantly higher yields of total baby cob with husk (9.38 and 9.24 tonnes/ha) and total baby corn without husk (2.15 and 2.10 tonnes/ha), respectively. Further, the crop fertilized with 50 kg S and 10 kg Zn/ha increased the nutrients (NPKSZn) and protein contents in babycorn and green husk but it was noted being on a par with application of 25 kg S and 5 kg Zn/ha. In terms of energetics, the higher values of energy inputs (20.71 x 103 MJ/ha), energy returns (226.98 x 103 MJ/ha), net energy returns (205.98 x 103 MJ/ha), energy use efficiency (10.80), energy productivity (0.454/kg/MJ), human profitability (65.20), energy productivity (9.80), energy intensiveness (0.354 MJ/Rupees), energy output efficiency (3.78 x 103 MJ/ha/day) and energy intensity in economic terms (3.82 MJ/Rupees) were recorded with application of 125% RDF and the lowest with 100% RDF. Similarly, application of 50 kg S and 10 kg Zn/ha gave the highest values of energy inputs (18.33 and 17.91 x 103 MJ/ha), energy returns (223.12 and 219.69 x 103 MJ/ha), net energy returns (203.31and 200.09 x 103 MJ/ha), energy use efficiency (11.25 and 11.19), energy productivity (0.473 and 0.471 kg/MJ), energy intensiveness (0.330 and 0.328 MJ/Rupees), energy output efficiency (3.72 and 3.66 x 103 MJ/ha/day), energy intensity in economic terms (3.71 and 3.67 MJ/Rupees), human energy profitability (64.09 and 63.11) and energy profitability (10.25 and 10.19), respectively as compared to its preceding doses. The highest actual loss of S and Zn were recorded with application of 125% RDF, 50 kg S and 10 kg Zn/ha whereas, the maximum positive balance of S and Zn were associated with 50 kg S and 10 kg Zn/ha, respectively.
Validation of an operational product to determine L1 to Earth propagation time delays

We describe the development and validation of an operational space weather tool to forecast propagation delay times between L1 and Earth using the Weimer and King (2008) tilted phase front technique. A simple flat plane convection delay method is currently used by the NOAA Space Weather Prediction Center (SWPC) to propagate the solar wind from a monitoring satellite located at L1 to a point upstream of the magnetosphere. This technique assumes that all observed solar wind discontinuities, such as interplanetary shocks and interplanetary coronal mass ejection boundaries, are in a flat plane perpendicular to the Sun‐Earth line traveling in the GSE X direction at the observed solar wind velocity. In reality, these phase plane fronts can have significantly tilted orientations, and by relying on a ballistic propagation method, delay time errors of ±15 min are common. In principle, the propagation time delay product presented here should more accurately predict L1 to Earth transit times by taking these tilted phase plane fronts into account. This algorithm, which is based on the work of Weimer and King (2008), is currently running in real time in test mode at SWPC as part of the SWPC test bed. We discuss the current algorithm performance, and via our detailed validation study, show that there is no significant difference between the two propagation methods when run in a real‐time operational environment.
Regression applied to legal judgments to predict compensation for immaterial damage

Immaterial damage compensation is a controversial matter in the judicial practice of several law systems. Due to a lack of criteria for its assessment, the judge is free to establish the value based on his/her conviction. Our research motivation is that knowing the estimated amount of immaterial damage compensation at the initial stage of a lawsuit can encourage an agreement between the parties. We thus investigate text regression techniques to predict the compensation value from legal judgments in which consumers had problems with airlines and claim for immaterial damage. We start from a simple pipeline and create others by adding some natural language processing (NLP) and machine learning (ML) techniques, which we call adjustments. The adjustments include N-Grams Extraction, Feature Selection, Overfitting Avoidance, Cross-Validation and Outliers Removal. An special adjustment, Addition of Attributes Extracted by the Legal Expert (AELE), is proposed as a complementary input to the case text. We evaluate the impact of adding these adjustments in the pipeline in terms of prediction quality and execution time. N-Grams Extraction and Addition of AELE have the biggest impact on the prediction quality. In terms of execution time, Feature Selection and Overfitting Avoidance have significant importance. Moreover, we notice the existence of pipelines with subsets of adjustments that achieved better prediction quality than a pipeline with them all. The result is promising since the prediction error of the best pipeline is acceptable in the legal environment. Consequently, the predictions will likely be helpful in a legal environment.
Teaching effective Instagram marketing strategies using an experiential learning project for cotton fibres and textiles

ABSTRACT Social media and social media education has permeated fashion merchandising programmes. At the same time, social media influencers have become an essential marketing and advertising strategy for fashion brands to reach consumers. Traditional educational models, such as classroom lectures and textbooks help expose students to theoretical learning outcomes, but they can lack real-world applications, problem-solving, and self-reflection. Therefore, this paper introduces an experiential learning project that provides students real-world applications regarding social media influencer marketing as ‘lived experiences’. Specifically, the project provided students with an opportunity to become an Instagram influencer by creating unique and engaging content for cotton fibres and textiles. An experiential learning model was used as the framework for this project and assisted in the creation of a student competition. Through the project’s four-stage process, students demonstrated positive learning outcomes, skills, and knowledge relevant to social media, social media influencers, and fashion marketing.
A Novel Family of Lysosomotropic Tetracyclic Compounds for Treating Leukemia

Simple Summary In spite of the recent expansion of the therapeutic landscape for acute myeloid leukemia (AML), resistance mechanisms and relapsed disease still pose a serious barrier to achieve curation for most patients. Considering the high inter- and intrapatient heterogeneity, disruptive therapeutic approaches are expected to provide a clinical solution for this unmet need. An in silico drug discovery program identified a new family of lysosome- and mitochondria-targeting compounds that specifically eradicate leukemia ex vivo and in vivo in relevant preclinical models by inducing both mitochondrial damage and apoptosis, and the simultaneous lysosomal membrane leakiness. Moreover, the compounds are effective in a wide panel of cancer cell lines, as their mechanism of action targets a common neoplastic feature. These compounds possess adequate pharmacological properties rendering them promising drug candidates for AML and unrelated neoplasias, and support their further clinical development. Abstract Acute myeloid leukemia (AML) is a heterogeneous hematological cancer characterized by poor prognosis and frequent relapses. Aside from specific mutation-related changes, in AML, the overall function of lysosomes and mitochondria is drastically altered to fulfill the elevated biomass and bioenergetic demands. On the basis of previous results, in silico drug discovery screening was used to identify a new family of lysosome-/mitochondria-targeting compounds. These novel tetracyclic hits, with a cationic amphiphilic structure, specifically eradicate leukemic cells by inducing both mitochondrial damage and apoptosis, and simultaneous lysosomal membrane leakiness. Lysosomal leakiness does not only elicit canonical lysosome-dependent cell death, but also activates the terminal differentiation of AML cells through the Ca2+–TFEB–MYC signaling axis. In addition to being an effective monotherapy, its combination with the chemotherapeutic arsenic trioxide (ATO) used in other types of leukemia is highly synergistic in AML cells, widening the therapeutic window of the treatment. Moreover, the compounds are effective in a wide panel of cancer cell lines and possess adequate pharmacological properties rendering them promising drug candidates for the treatment of AML and other neoplasias.
Analysis of genetic diversity and population structure of Babesia gibsoni

Babesia gibsoni is a tick-borne apicomplexan protozoan causing canine babesiosis. This parasite has diploid sexual reproduction in ticks, during which genetic exchanges can occur leading to increased genetic diversity, which is an important factor in adapting to environmental changes. Exploring the genetic variation of B. gibsoni population can provide a foundation for understanding the patterns of disease transmission and developing babesiosis control strategies. Partial 18S rRNA fragment sequences were obtained from 11 B. gibsoni isolates collected from different regions in China and 117 publicly available sequences were from 12 geographical areas including China. The genetic variation, demographic expansion and population structure were examined. A total of 34 haplotypes were identified among B. gibsoni populations. Analysis of molecular variance, pairwise Fst and structure analysis showed that high genetic variation within populations, low genetic differentiation and obvious mixture haplotype were apparent in a single continent, but higher genetic differentiation was detected across different continents. Neutrality tests implied that B. gibsoni populations had experienced population extension. These findings will contribute to understand the genetics and evolution of B. gibsoni and will be useful for formulating effective management strategies to prevent and control this parasite.