Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Menstrual Cycle Phase on Fuel Oxidation Post HIT in Women Reproductive Age: A Pilot Study

Women of childbearing age have variations in substrate oxidation rates that can lead to overweight, type II diabetes, and other conditions that may be associated with metabolic inflexibility and the variations in estrogen concentrations observed during the monthly ovarian cycle. Purpose: This study aimed to verify and compare the influence of eight treadmill high-intensity interval training (HIT) sessions on carbohydrate and lipid oxidation rates (CHOox and LIPox, respectively) and intensities of ventilatory anaerobic thresholds (VATs) of women in different phases of the monthly ovarian cycle. Methods: Eleven irregularly active women performed incremental treadmill exercise testing followed by submaximal work-rate running for 45 min to determine VATs, VO2peak, peak velocity (Vpeak), and substrate oxidation rates, before and after a training period, in different phases of their monthly ovarian cycle (follicular phase group, FL, n = 6; luteal phase group, LT, n = 5). The training period consisted of eight HIT sessions, composed each one of eight sets of 60 s running at 100%Vpeak interspersed by 75 s recovery every 48 h. Results: Our results showed no significant differences in VATs intensities between groups. The comparison between groups showed significant differences in relative energy derived from CHO pre- and post-training of −61.42% and −59.26%, respectively, and LIP pre- and post-training of 27.46% and 34.41%, respectively. The relative energy derived from CHO after the training period was 18.89% and 25.50% higher for FL and LT, respectively; consequently, the relative energy derived from LIPox after the training period was 8,45% and 3.46% lower for FL and LT, respectively. Over the training period, Vpeak was ~13.5 km/h, which produced the relative intensities of ~89%VO2peak e ~93%HRpeak for both groups. Conclusion: The monthly ovarian cycle phases promote significant changes in substrate oxidation rates leading to a decrease in CHOox. High-intensity interval training can minimize the differences observed and constitute an alternative intervention.
Numerical simulation of bubble hydrodynamics for pool scrubbing

ABSTRACT Pool scrubbing is an important filtering process that prevents radioactive aerosols from entering the environment in the event of severe accidents in a nuclear reactor. In the process of transporting aerosol particles using bubbles, bubble hydrodynamics plays a crucial role in modeling pool scrubbing and significantly affects particle removal in a bubble. Our future research strategy is to apply the three-dimensional Computational Fluid Dynamics (CFD) approach to understand the detailed bubble interaction, which is difficult to be assessed experimentally. This study validates the applicability of the CFD simulation to bubble hydrodynamics at the flow transition from a globule to a swarm region. Two types of solvers based on the Volume Of Fluid (VOF) and Simple Coupled Volume Of Fluid with Level Set (S-CLSVOF) methods were used to capture the gas–liquid interface in the CFD simulation. We use the experimental data for validation. As a result, the VOF and S-CLSVOF methods accurately predict the bubble size and void fraction distributions. In addition, we confirmed that the bubble rise velocity of the S-CLSVOF method almost agrees with the experimental results. The validated code is expected to play a critical role in evaluating the constitutive equations in the stand-alone pool scrubbing code – SPARC-90.
High-Resolution Load Forecasting on Multiple Time Scales Using Long Short-Term Memory and Support Vector Machine

Electricity load prediction is an essential tool for power system planning, operation and management. The critical information it provides can be used by energy providers to maximise power system operation efficiency and minimise system operation costs. Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) are two suitable methods that have been successfully used for analysing time series problems. In this paper, the two algorithms are explored further for load prediction; two load prediction algorithms are developed and verified by using the half-hourly load data from the University of Warwick campus energy centre with four different prediction time horizons. The novelty lies in comparing and analysing the prediction accuracy of two intelligent algorithms with multiple time scales and in exploring better scenarios for their prediction applications. High-resolution load forecasting over a long range of time is also conducted in this paper. The MAPE values for the LSTM are 2.501%, 3.577%, 25.073% and 69.947% for four prediction time horizons delineated. For the SVM, the MAPE values are 2.531%, 5.039%, 7.819% and 10.841%, respectively. It is found that both methods are suitable for shorter time horizon predictions. The results show that LSTM is more capable of ultra-short and short-term forecasting, while SVM has a higher prediction accuracy in medium-term and long-term forecasts. Further investigation is performed via blind tests and the test results are consistent.
On frequency-domain least squares adaptive algorithms

The simple least mean-square (LMS) algorithm shows slow convergence rate, while the computationally-intensive least squares (LS) algorithm has very fast convergence speed. The LMS algorithm realized in the frequency domain is known to have significantly improved convergence rate with moderate complexity. In this work we study new adaptive algorithms that take advantage of both the LS and frequency-domain techniques. We develop several frequency-domain LS algorithms and investigate their performance characteristics by computer simulation.
The non-monotone conic algorithm

In this paper we present a new algorithm for finding the unconstrained minimum of a continuously differentiate function f (x) in n variables. This algorithm is based on a conic model function, which does not involve the conjugacy matrix or the Hessian of the model function. The conic method in this paper is combined with a non-monotone line search. The method does not guarantee descent in the objective function at each iteration. The use of the stopping criterion introduced by Grippo, Lampariello and Lucidi allows the objective function to increase at some iterations and still guarantees global convergence. The new algorithm has been implemented and tested on several well known test functions.
Impurity gettering by vacancy-type defects in high-energy ion-implanted silicon at Rp /2

Vacancy-type defects were studied after high-energy self-implantation of Si and subsequent rapid thermal annealing by means of a depth-resolution enhanced positron beam technique. Two different types of open-volume defects were found at a depth of Rp/2 and Rp, respectively. The defect type at Rp/2 is an agglomeration of point defects containing vacancies. This defect getters diffusing copper atoms. The vacancy-type defect observed in a depth of Rp could be connected to the interstitial loops formed there. The positron annihilation parameters suggest that this detected defect is not decorated by diffusing copper atoms.
Pulmonary Artery Systolic Pressure and Cava Vein Status in Acute Heart Failure with Preserved Ejection Fraction: Clinical and Prognostic Implications

Background: Peak tricuspid regurgitation (TR) velocity and inferior cava vein (ICV) distention are two recognized features of increased pulmonary artery pressure (PASP) and right atrial pressure, respectively. Both parameters are related to pulmonary and systemic congestion and adverse outcomes. However, few data exist about the assessment of PASP and ICV in acute patients affected by heart failure with preserved ejection fraction (HFpEF). Thus, we investigated the relationship existing among clinical and echocardiographic features of congestion, and we analyzed the prognostic impact of PASP and ICV in acute HFpEF patients. Methods and Results: We analyzed clinical congestion PASP and ICV value in consecutive patients admitted in our ward by echocardiographic examination using peak Doppler velocity tricuspid regurgitation and ICV diameter and collapse for the assessment of PASP and ICV dimension, respectively. A total of 173 HFpEF patients were included in the analysis. The median age was 81 and median left ventricular ejection fraction (LVEF) was 55% [50–57]. Mean values of PASP was 45 mmHg [35–55] and mean ICV was 22 [20–24] mm. Patients with adverse events during follow-up showed significantly higher values of PASP (50 [35–55] vs. 40 [35–48] mmHg, (p = 0.005) and increased values of ICV (24 [22–25] vs. 22 [20–23] mm, p < 0.001). Multivariable analysis showed prognostic power of ICV dilatation (HR 3.22 [1.58–6.55], p = 0.001) and clinical congestion score ≥ 2 (HR 2.35 [1.12–4.93], p = 0.023), but PASP increase did not reach statistical significance (p = 0.874). The combination of PASP > 40 mmHg and ICV > 21 mm was capable of identifying patients with increased events (45% vs. 20%). Conclusions: ICV dilatation provides additional prognostic information with respect to PASP in patients with acute HFpEF. A combined model adding PASP and ICV assessment to clinical evaluation is a useful tool for predicting HF related events.
Comparison on beam hardening correction of CT based on H-L consistency and normal water phantom experiment

An H-L Consistency based beam hardening correction method of CT with polychromatic x-ray tube spectrum has been proposed recently. To identify its effectiveness, a comparison research is completed in the paper between this method and water phantom experiment correction used in current CT devices. For reason of isolating irrelevant influence, the simulated projection data of Forbild head phantom based on physics of medical x-ray imaging are used to evaluate correction effects. Firstly, a virtual circular fan beam CT with known parameters (tube spectrum, added filter, mechanical parameters, etc.) is constructed. Secondly, a simulated isotropic water phantom is used to generate normal correction polynomial in current CT device (called normal correction). Thirdly, for the projection data of given CT phantom, sole-polynomial and bi-polynomial correction based on H-L Consistency, and normal water phantom correction are applied respectively. Fourthly, all the corrected projection data are reconstructed with the same FBP algorithm. The correction effects of beam hardening artifact are compared between those three applied correction methods, especially the differences of correction effects in different slices. Simulation experiments show that the bi-polynomial method can achieve the best effect, although it costs more computation resource, and the H-L Consistency based method exhibit accordant correction effect for different slices, whereas the normal correction cannot adapt all slices equally.
Molecular Mechanisms Behind the Role of Plasmacytoid Dendritic Cells in Systemic Sclerosis

Simple Summary Systemic Sclerosis (SSc) is a rare autoimmune disease characterized by scarring of the tissues and organs. This scarring, or fibrosis, has a major impact on a patient’s quality of life; for example, lung fibrosis reduces the efficiency of breathing and is a significant cause of death for SSc patients. To develop novel therapeutic strategies, it is important to understand what causes fibrosis to occur and progress. It was recently found that plasmacytoid dendritic cells (pDCs) are key immune cells in the development of fibrosis in SSc. These cells are innate immune cells that are specialized in anti-viral responses, and they are also involved in autoimmune diseases. This review will examine the recent research that has started to uncover the molecular mechanisms through which pDCs impact SSc. Abstract Systemic sclerosis (SSc) is a debilitating autoimmune disease that affects multiple systems. It is characterized by immunological deregulation, functional and structural abnormalities of small blood vessels, and fibrosis of the skin, and, in some cases, internal organs. Fibrosis has a devastating impact on a patient’s life and lung fibrosis is associated with high morbimortality. Several immune populations contribute to the progression of SSc, and plasmacytoid dendritic cells (pDCs) have been identified as crucial mediators of fibrosis. Research on murine models of lung and skin fibrosis has shown that pDCs are essential in the development of fibrosis, and that removing pDCs improves fibrosis. pDCs are a subset of dendritic cells (DCs) that are specialized in anti-viral responses and are also involved in autoimmune diseases, such as SSc, systemic lupus erythematosus (SLE) and psoriasis, mostly due to their capacity to produce type I interferon (IFN). A type I IFN signature and high levels of CXCL4, both derived from pDCs, have been associated with poor prognosis in patients with SSc and are correlated with fibrosis. This review will examine the recent research on the molecular mechanisms through which pDCs impact SSc.
Experimental characterization of broadband electrostatic noise due to plasma compression

For a wide variety of laboratory and space plasma environments, theoretical predictions state that plasmas are unstable to inhomogeneous flows over a very broad frequency range. Such sheared flows are generated in the Earth's magnetosphere and intensify during active periods. Specifically, for a velocity shear oriented perpendicular to a uniform background magnetic field, the shear scale length (LE) compared to the ion gyroradius (ρi) determines the character of the shear‐driven instability that may prevail. An interpenetrating plasma configuration is used to create a transverse velocity shear profile in a magnetized plasma column, a condition similar to that found in the natural boundary layers. The continuous variation of ρi/LE and the associated transition of the instability regimes driven by the shear flow mechanism are demonstrated in a single laboratory experiment. Broadband wave emission correlated to increasing/decreasing stress (i.e., ρi/LE), a characteristic signature of a boundary layer crossing, is found under controlled and repeatable conditions. This result holds out the promise for understanding the cause and effect of the in situ observation of broadband electrostatic noise.
Microfibrillated Cellulose with a Lower Degree of Polymerization; Synthesis via Sulfuric Acid Hydrolysis under Ultrasonic Treatment

A new approach is being considered for obtaining microfibrillated cellulose with a low degree of polymerization by sulfuric acid hydrolysis with simultaneous ultrasonic treatment under mild conditions (temperature 25 °C, 80% power control). Samples of initial cellulose, MCC, and MFC were characterized by FTIR, XRF, SEM, DLS, and TGA. It was found that a high yield of MFC (86.4 wt.%) and a low SP (94) are observed during hydrolysis with ultrasonic treatment for 90 min. It was shown that the resulting microfibrillated cellulose retains the structure of cellulose I and has an IC of 0.74. It was found that MFC particles are a network of fibrils with an average size of 91.2 nm. ζ-potential of an aqueous suspension of MFC equal to −23.3 mV indicates its high stability. It is noted that MFC has high thermal stability, the maximum decomposition temperature is 333.9 °C. Simultaneous hydrolysis process with ultrasonic treatment to isolate MFC from cellulose obtained by oxidative delignification of spruce wood allows to reduce the number of stages, reduce energy costs, and expand the scope.
Effect Displays for Multinomial and Proportional-Odds Logit Models

An “effect display” is a graphical or tabular summary of a statistical model based on high-order terms in the model. Effect displays have previously been defined by Fox (1987, 2003) for generalized linear models (including linear models). Such displays are especially compelling for complicated models—for example, those including interactions or polynomial terms. This paper extends effect displays to models commonly used for polytomous categorical response variables: the multinomial logit model and the proportional-odds logit model. Determining point estimates of effects for these models is a straightforward extension of results for the generalized linear model. Estimating sampling variation for effects on the probability scale in the multinomial and proportional-odds logit models is more challenging, however, and we use the delta method to derive approximate standard errors. Finally, we provide software for effect displays in the R statistical computing environment.
On computing the inverse of a sparse matrix

The Gauss-Jordan inversion algorithm requires 0(n3) arithmetic operations. In some practical applications, like state estimation or short-circuit calculation in power systems, the given matrix is sparse and only part of the inverse is needed. Most frequently in the diagonal dominant case this is the diagonal. There are two ways to exploit sparsity to determine elements of the inverse: 1Columnwise inversion via the solution of sparse linear systems with columns of the unit matrix as right-hand sides. 2Application of the algorithm of Takahashi et al6 . The latter algorithm arises very naturally from multiplying the left- and right-hand factors of the Zollenkopf bifactorization in reverse order. We indicate how computing time can be gained in the important symmetric diagonal dominant case if only part of the diagonal is needed and compare computing times of the method of Takahasi et al.6 with several variants of columnwise inversion. Whereas most of the theory holds for general matrices, experiments are performed on the symmetric diagonal dominant case. For band matrices the operation count is 0(n) both for computing a column of the inverse by columnwise inversion and the diagonal by the algorithm of Takahashi et al6.
Using A-Mode Ultrasound to Assess the Body Composition of Soccer Players: A Comparative Study of Prediction Formulas

For elite athletes, monitoring body composition is important for maximizing performance without health risks. Amplitude (A)-mode ultrasound (AUS) has attracted increasing attention as an alternative to skinfold thickness measurements commonly used for assessing the amount of body fat in athletes. AUS accuracy and precision, however, depend on the formula used to predict body fat percentage (%BF) from subcutaneous fat layer thicknesses. Therefore, this study evaluates the accuracy of the 1-point biceps (B1), 9-sites Parrillo, 3-sites Jackson and Pollock (JP3), and 7-sites Jackson and Pollock (JP7) formulas. Relying on the previous validation of the JP3 formula in college-aged male athletes, we took AUS measurements in 54 professional soccer players (aged 22.9 ± 3.83 y, mean ± SD) and compared the results given by different formulas. The Kruskal–Wallis test indicated significant differences (p < 10−6), and Conover’s post hoc test revealed that the JP3 and JP7 data come from the same distribution, whereas the data given by B1 and P9 differ from all the others. Lin’s concordance correlation coefficients for B1 vs. JP7, P9 vs. JP7, and JP3 vs. JP7 were 0.464, 0.341, and 0.909, respectively. The Bland–Altman analysis indicated mean differences of −0.5 %BF between JP3 and JP7, 4.7 %BF between P9 and JP7, and 3.1 %BF between B1 and JP7. This study suggests that JP7 and JP3 are equally valid, whereas P9 and B1 overestimate %BF in athletes.
Economic, social, and cultural capital and ESQ in academic achievement: A comparison of Afghan and Iranian students

The present study aimed to investigate the role of different types of capital, including economic, social, and cultural, as well as emo-sensory intelligence (ESI) in the academic achievement of students in the two contexts of Afghanistan and Iran. For this purpose, 317 students from both countries participated in the study. They were asked to fill out the Social and Cultural Capital Questionnaire (SCCQ) and the Emo-sensory Intelligence Questionnaire (ESI-Q). Their grade point average (GPA) was taken as the indicator of their academic achievement. The findings revealed that students’ level of cultural capital and emo-sensory quotient (ESQ) had a significantly positive role in their academic achievement (p < 0.05). Moreover, significant differences were found between the two contexts in terms of the level of capital, with Afghan students having significantly more cultural capital, and Iranian students having significantly higher economic capital (p < 0.05). Iranian students were also found to have a significantly higher level of ESQ compared to Afghan students (p < 0.05). Finally, the results were discussed, and implications and suggestions for further research were provided.
Electrostatic image theory for an anisotropic boundary of an anisotropic half-space

A novel image solution for the canonical electrostatic problem of a point charge in an anisotropic half-space bounded by an anisotropic surface is presented. The image source is obtained in operator form by using Fourier-transformed Maxwell equations and transmission line theory. After applying methods from Heaviside operator calculus, the image operator can be interpreted as a combination of a point charge and a line-charge-bounded sector of planar charge density. The new theory is shown to coincide with the previously known image solutions of less general anisotropic media. In addition to being applicable to any physically feasible anisotropic medium of electrostatics, the method can be used for steady-current conductivity problems via a duality transformation.
Focus on the physics of magnetic resonance on porous media

Porous media are ubiquitous in our environment and their application is extremely broad. The common connection between these diverse materials is the importance of the microstructure in determining the physical, chemical and biological functions and properties. Magnetic resonance and its imaging modality have been essential for noninvasive characterization of these materials in the development of catalysts, understanding cement hydration, fluid transport in rocks and soil, geological prospecting and characterization of tissue properties for medical diagnosis. This focus issue highlights recent NMR/MRI technical development, the underlying physics associated with the new technology, as well as novel applications of the technologies.
A note on the optimum choice for penalty parameters

This paper looks at the numerical characteristics of penalty methods for evaluating the solution of symmetric systems of equations with imposed constraints. The sources of error resulting from this approach are identified and an estimate for the penalty parameter that minimizes this error is obtained. The results of the error analysis and the effect of penalty parameter on the accuracy and rates of convergence of the solution algorithm are demonstrated with the aid of some numerical examples.