Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements

Abstract Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) space-based rain estimates, and, hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar–gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar–gauge differences into the gauge area–point error variance and radar-rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar-rain estimates at var.
Learning About the Incidence and Lethality of COVID-19 in Vulnerable Neighborhoods: The Case of Malaga (Spain)

This research delves into the need to use granular analyses at the neighborhood level to study the preexisting conditions of vulnerability that best explain the waves of COVID-19 incidence and mortality. It seems most appropriate to use the comprehensive approach of the sustainable development with variables that analyze the economic, social, environmental, and governance dimensions, given the extensive literature that identifies each as a determining factor for the impact of disease. The work utilizes a composite vulnerability index that allows the city of Malaga to be divided into 434 census sections; waves of incidence and mortality for each section are constructed for the period of March 2020 to March 2021. Cluster analysis reveals that there are five different cluster incidence patterns, whereas the lethality waves are found to behave as a hot-spot phenomenon. The results reveal that neighborhoods that are the most vulnerable in terms of their demographic conditions (large proportion over 65 years of age and dependent) and socioeconomic conditions (severe material deprivation), have been the most affected by COVID-19 infection and mortality.
Underwater acoustic ambient noise levels on the eastern Canadian continental shelf

This paper reports the analysis of shallow‐water ambient noise levels collected by Defence Research Establishment Atlantic during 14 cruises over the period 1972 to 1985. A weighted average is formed to de‐bias the samples, with the aim of answering the question: ‘‘If one were to pick a site randomly on the eastern Canadian continental shelf at a random time, and perform an ambient noise measurement, what would be the expected noise level? ’’ The samples are also grouped according to whether they were taken on the Scotian Shelf, the Grand Banks, or the Flemish Cap, and according to season. The frequency range covered is 30 to 900 Hz. The weighted mean and standard deviation of the noise levels are presented, as well as the correlation coefficient between the noise levels and wind speed. The results show that the eastern Canadian continental shelf as a whole presents levels that are characteristic of areas with high shipping density and good acoustic propagation, with the Scotian Shelf showing generally hig.
Stability and Dynamics of Numerical Methods for Nonlinear Ordinary Differential Equations

La stabilite de methodes numeriques pour des equations differentielles ordinaires autonomes non lineaires est approchee du point de vue des systemes dynamiques. Il est prouve que des methodes multipas avec des trajectoires bornees produisent toujours un comportement asymptotique correct, mais ce n'est pas le cas avec la methode de Runge-Kutta. On donne des exemples de schemas de Runge-Kutta convergeant vers de fausses solutions d'une maniere apparemment reguliere, et on presente une caracterisation de telles methodes a deux degres
Big-Fish-Little-Pond effect: The negative effects of academically selective schools

Academically selective schools (i.e. schools in which the average ability of students in the school is high) are intended to have positive effects on academic self-concept. A positive self-belief about one’s academic accomplishments is an important outcome and has been shown to facilitate the attainment of a wide variety of other desirable educational outcomes (Marsh & Craven, 2006). However, a growing body of theoretical and empirical research demonstrates that the effects of school-average ability on academic self-concept can be negative. Thus, attending academically selective schools tends to diminish academic self-concepts rather than to enhance them. These empirical results are consistent with the big-fish-little-pond effect (BFLPE), which predicts that equally able students have lower academic self-concepts when attending schools where the average ability levels of classmates is high, and higher academic self-concepts when attending schools where the school-average ability is low. Here we briefly summarise theoretical, empirical, and policy-related implications of the BFLPE.
Enhanced slow light in superconducting electromagnetically induced transparency metamaterials

We characterized and compared the electromagnetically induced transparency (EIT) response of superconducting niobium nitride (NbN) and NbN–Au hybrid metamaterials. In our design, the two resonators in a unit cell have strong coupling and are directly excited under terahertz (THz) radiation. A stronger slow light effect was achieved using superconducting metamaterials than hybrid metamaterials. The enhanced slow light effect could be attributed to the remarkably low Ohmic loss and strong interaction of the resonators.
Interconnecting Vipassana with Human Health and School Curriculum

A desk review was done to analyze the relevance of Vipassana with the overall dimensions of health and to find out its interconnection with the school curriculum for enhancing the education sector and shifting the paradigm. Secondary data were collected via an internet online portal and analyzed by making a theme. Literature shows that Vipassana has a tremendous positive impact on human health dimensions like physical, mental, social, psychological, and spiritual health. Vipassana with its moral code and precepts is found to help in fostering peaceful feelings, equanimity, and compassion, thus assisting social integrity. Relying on this fact, there is a great possibility of interconnecting Vipassana with the school curriculum. No review has been found on social well-being and spiritual health in a collaborative form which could be a future recommendation.
Phase Angle and Nutritional Status: The Impact on Survival and Health-Related Quality of Life in Locally Advanced Uterine Cervical Cancer

The phase angle, an indicator of muscle mass status and membrane cell integrity, has been associated with low survival, poorer clinical outcomes, and worse quality of life among cancer patients, but information on women with uterine cervical cancer (UCCa) is scarce. In this prospective study, we used a bioelectrical impedance analyzer to obtain the PA of 65 women with UCCa. We compared the health-related quality of life and inflammatory and nutritional indicators between low PA and normal PA. The mean age was 52 ± 13. The low PA and normal PA groups differed in terms of the C-reactive protein (15.8 ± 19.6 versus 6.82 ± 5.02, p = 0.022), glucose (125.39 ± 88.19 versus 88.78 ± 23.08, p = 0.021), albumin (3.9 ± 0.39 versus 4.37 ± 0.30, p = 0.000), EORTC QLQ-C30 loss of appetite symptom scale score (33.33 (0.0–100.00) versus 0.0 (0.0–0.0), p = 0.005), and EORTC QLQ-CX24 menopausal symptoms scale score (0.0 (0.0–33.33) versus 0.0 (0.0–100.0), p = 0.03). The main finding of the present study is the interaction between PA and obesity as critical cofactors in the UCCa adeno and adenosquamous histologic variants, to a greater extent than cervical squamous cell carcinoma.
Explosive plasma flows in a solar flare

Solar Maximum Mission soft X-ray data and Sacramento Peak Observatory H-alpha observations are combined in a study of the impulsive phase of a solar flare. A blue asymmetry, indicative of upflows, was observed in the coronal Ca XIX line during the soft X-ray rise phase. A red asymmetry, indicative of downflows, was observed simultaneously in chromospheric H-alpha emitted from bright flare kernels during the period of hard X-ray emission. Combining the velocity data with a measurement of coronal electron density, it is shown that the impulsive phase momentum of upflowing soft X-ray-emitting plasma equalled that of the downflowing H-alpha-emitting plasma to within one order of magnitude. In particular, the momentum of the upflowing plasma was 2 x 10 to the 21st g cm/s while that of the downflowing plasma was 7 x 10 to the 21st g cm/s, with a factor of 2 uncertainty on each value. This equality supports the explosive chromospheric evaporation model of solar flares, in which a sudden pressure increase at the footprint of a coronal loop produces oppositely directed flows in the heated plasma. 21 references.
Lipidomic Profiling of Rice Bran after Green Solid–Liquid Extractions for the Development of Circular Economy Approaches

Rice bran is a rather underutilized by-product of the rice industry that nowadays is far from being valorized. In this study, the lipidomic profile of bran of the Italian rice variety, Roma, has been evaluated through ultra performance liquid chromatography—tandem mass spectrometry. Crude lipid extracts were obtained from rice bran treated with different green solvents (1-butanol, ethanol and methyl tert-butyl ether/methanol mixture) in combination with an ultrasonic pre-treatment, and then compared with extracts obtained with standard solvents (chloroform/methanol mixture). Lipid yield, number and type of lipids and composition of prevalent lipid classes extracted were evaluated in order to provide an exhaustive lipid profile of the rice bran and to identify the most efficient green solvent for solid–liquid extractions. Twelve different lipid classes and a maximum of 276 lipids were identified. Ethanol and methyl tert-butyl ether/methanol solvents provided higher lipid extraction yields, the former being the most effective solvent for the extraction of triglycerides and N-acylethanolamines and the latter the most effective for the extraction of diglycerides, phospholipids and ceramides at 4 °C. Moreover, extraction with ethanol at 20 °C gave similar results as at 4 °C in terms of lipid yield and for most of the classes of lipids extracted. Taken together, our results indicate ethanol and methyl tert-butyl ether/methanol as excellent solvents for lipid extraction from rice bran, with the aim to further valorize this food by-product in the perspective of a circular economy.
The organization of near-wall turbulence: a comparison between boundary layer SPIV data and channel flow DNS data

The vortical structures of near-wall turbulence at moderate Reynolds number are analyzed and compared in datasets obtained from stereoscopic particle image velocimetry (SPIV) in a turbulent boundary layer and from direct numerical simulations (DNS) in a turbulent channel flow. The SPIV data are acquired in the LTRAC water tunnel at Re=+=820 in a streamwise/wall-normal plane, and in the LML wind tunnel at Re=+=2590 in a streamwise/wall-normal plane and in a plane orthogonal to the mean flow. The DNS data is taken from DelAlamo et al. (Self-similar vortex clusters in the turbulent logarithmic region, J. Fluid Mech. 561 (2006), pp. 329-358), at Re=950. The SPIV database is validated through an analysis of its mean velocity profile and power spectra, which are compared with reference profiles. A common detection algorithm is then applied to both the SPIV and DNS datasets in order to retrieve the streamwise and spanwise vortices. The algorithm employed is based on the 2D swirling strength and on a fit of an Oseen vortex model, which allows to retrieve the vortex characteristics, including its radius, vorticity, and position of the center. At all Reynolds numbers, the near-wall region is found to be the most densely populated region, predominantly with streamwise vortices that are on average smaller and more intense than spanwise vortices. In contrast, the logarithmic region is equally constituted of streamwise and spanwise vortices having equivalent characteristics. Two different scalings were employed to analyze the vortex radius and vorticity: the wall unit scaling and the Kolmogorov scaling. In wall unit scaling, a good universality in Reynolds numbers of the vortices radius and vorticity is observed in the near-wall and logarithmic regions: the vorticity is found to be maximum at the wall, decreasing first rapidly and then increasing slowly with wall-normal distance; the radius is increasing slowly with wall-normal distance in both the regions, except for the streamwise vortices, for which a sharp increase in radius is observed in the near-wall region. However, wall units scaling is found to be deficient in the outer region, where Reynolds number effects are observed. The Kolmogorov scaling appears to be universal both in Reynolds number and wall-normal distance across the investigated three regions, with a mean radius of the order of 8 and a mean vorticity of the order of 1.5-1, but for the SPIV data only. In the DNS dataset, the radius in the Kolmogorov scaling slowly decreases with wall-normal distance. This difference between the SPIV and DNS datasets may be linked to a difference between the boundary layer flow and the channel flow, rather than to the techniques themselves. Finally, the distribution of the vorticity of the detected vortices seems to follow faithfully a log-normal distribution, in good agreement with Kolmogorov's theory (A refinement of previous hypothesis concerning the local structure of turbulence in a viscous incompressible fluid at high Reynolds number, J. Fluid Mech. 13 (1962), pp. 82-85).
Effect of Motion Cues on Highway Driving Performance in Simulated Driving

The motion system is a major component of a driving simulator. It provides motion cues in various directions with different degrees of freedom (DOF). Different DOF could influence response variables widely used in highway design safety evaluation conducted in simulators. Few studies, though, have comprehensively explored the effect of driving simulator motion cues on driving performance. The high-fidelity Tongji University Driving Simulator (TUDS) was used to separately compare five dependent variables: speed, speed change, lane deviation, longitudinal acceleration, and lateral acceleration. The Wilcoxon signed-rank test was used to examine the difference for each variable using 8-DOF and fixed-base motion system configurations for nine types of combined highway alignments. A subjective assessment of participants’ driving experience was conducted, and the chi-square test for each term was used to compare the difference in motion system fidelity and adverse reactions between the two configurations. Results show that: (1) speed and lateral acceleration are more likely to be significantly affected by motion cues than speed change, lane deviation, and longitudinal acceleration; (2) the horizontal curve with up-grade is the type of combined alignment where speed and lateral acceleration are mostly affected; (3) characteristics of the five variables in different combined alignments vary between the two simulators; (4) the 8-DOF motion system provides better perceived motion fidelity than the fixed-base system does, and the 8-DOF simulator causes less discomfort and tiredness in simulator sickness; and (5) the presence of motion cues is suggested for highways with complex combined curves when focusing on speed and lateral acceleration.
The Galerkin Method Based on Hermite Cubics

The Galerkin method for $u_t + u_x = 0$ with Hermite cubic polynomials as basis functions may be viewed as a method of lines with mesh h. A Fourier analysis of this method of lines shows that the solution has two waves, one with speed 1 and another with speed $ - 7$. If the initial data is smooth, then the amplitude of the backward wave is $O(h^4 )$. By filtering out the backward wave, we obtain an accuracy $O(h^6 )$.
Non-Cryopreserved Peripheral Blood Stem Cell Graft for Autologous Hematopoietic Stem Cell Transplantation in Multiple Myeloma and Lymphoma Patients

Background Hematopoietic stem cell transplantation (HSCT) using cryopreserved grafts is time-consuming, expensive treatment, and may associated with dimethyl sulfoxide (DMSO) toxicity. Here, we assess the clinical utility and safety of non-cryopreserved peripheral blood stem cell graft in autologous HSCT. Material/Methods Medical data of multiple myeloma or lymphoma patients who underwent autologous non-cryopreserved HSCT were reviewed. Results A total of 58 patients (40 myeloma and 18 lymphoma) were reviewed. The median myeloma and lymphoma CD34+ cell doses were 7.59 and 6.9 million/kg, respectively, with good viability after storage. The median times in neutrophil and platelet engraftment were 9 and 13 days and 11 and 14 days in myeloma and lymphoma, respectively. Only 5 patients in this cohort developed serious post-transplant complications. After transplantation, the cumulative incidence of relapse at 5 years was 34.4% in myeloma versus 19.1% in lymphoma patients. Notably, the mortality incidence rate rapidly increased within the first year and reached a plateau after 4 years, with cumulative incidence of 5.9% and 30.9% in myeloma and lymphoma, respectively. With a median follow-up time of 60 months, the median progression-free survival (PFS) and overall survival (OS) for lymphoma patients was 123.8 and 130 months, respectively. For the myeloma group, the median follow-up time was 38.6 months, the median PFS was 99.5 months, and OS was 157 months. Conclusions Non-cryopreserved HSCT is effective and safe. The long-term survival outcomes could be achieved by the shortening the duration of neutrophil and platelet engraftments and the complication rates are acceptable.
A comparative study of nonparametric two–sample tests after Levene's transformation

The Levene test is a widely used test for detecting differences in dispersion. The modified Levene transformation using sample medians is considered in this article. After Levene's transformation the data are not normally distributed, hence, nonparametric tests may be useful. As the Wilcoxon rank sum test applied to the transformed data cannot control the type I error rate for asymmetric distributions, a permutation test based on reallocations of the original observations rather than the absolute deviations was investigated. Levene's transformation is then only an intermediate step to compute the test statistic. Such a Levene test, however, cannot control the type I error rate when the Wilcoxon statistic is used; with the Fisher–Pitman permutation test it can be extremely conservative. The Fisher–Pitman test based on reallocations of the transformed data seems to be the only acceptable nonparametric test. Simulation results indicate that this test is on average more powerful than applying the t test after Levene's transformation, even when the t test is improved by the deletion of structural zeros.
Accurate Crack Detection Based on Distributed Deep Learning for IoT Environment

Defects or cracks in roads, building walls, floors, and product surfaces can degrade the completeness of the product and become an impediment to quality control. Machine learning can be a solution for detecting defects effectively without human experts; however, the low-power computing device cannot afford that. In this paper, we suggest a crack detection system accelerated by edge computing. Our system consists of two: Rsef and Rsef-Edge. Rsef is a real-time segmentation method based on effective feature extraction that can perform crack image segmentation by optimizing conventional deep learning models. Then, we construct the edge-based system, named Rsef-Edge, to significantly decrease the inference time of Rsef, even in low-power IoT devices. As a result, we show both a fast inference time and good accuracy even in a low-powered computing environment.
Phase Transitions and Equations of State of Alkaline Earth Fluorides CaF2 SrF2 and BaF2 to Mbar Pressures

Phase transitions and equations of state of the alkaline earth fluorides CaF{sub 2}, SrF{sub 2}, and BaF{sub 2} were examined by static compression to pressures as high as 146 GPa. Angle-dispersive x-ray diffraction experiments were performed on polycrystalline samples in the laser-heated diamond-anvil cell. We confirmed that at pressures less than 10 GPa all three materials undergo a phase transition from the cubic (Fm{bar 3} m) fluorite structure to the orthorhombic (Pnam) cotunnite-type structure. This work has characterized an additional phase transition in CaF{sub 2} and SrF{sub 2}: these materials were observed to transform to a hexagonal (P6{sub 3}/mmc) Ni{sub 2}In-type structure between 63-79 GPa and 28-29 GPa, respectively, upon laser heating. For SrF{sub 2}, the Ni{sub 2}In-type phase was confirmed by Rietveld refinement. Volumes were determined as a function of pressure for all high-pressure phases and fit to the third-order Birch-Murnaghan equation of state. For CaF{sub 2} and SrF{sub 2}, the fluorite-cotunnite transition results in a volume decrease of 8-10%, while the bulk modulus of the cotunnite-type phase is the same or less than that of the fluorite phase within uncertainty. For all three fluorides, the volume reduction associated with the further transition to the Ni{sub 2}In-type phase ismore » {approx}5%. The percentage increase in the bulk modulus ({Delta}K) across the transition is greater when the cation is smaller. While for BaF{sub 2}, {Delta}K is 10-30%, {Delta}K values for SrF{sub 2} and CaF{sub 2} are 45-65% and 20-40%. Although shock data for CaF{sub 2} have been interpreted to show a transition to a highly incompressible phase above 100 GPa, this is not consistent with our static equation of state data. « less
Neural network-based CAD model for the design of square-patch antennas

An artificial neural network (ANN) has been developed and tested for square-patch antenna design. It transforms the data containing the dielectric constant (/spl epsiv//sub r/), thickness of the substrate (h), and antenna's dominant-mode resonant frequency (f/sub r/) to the patch length (l).