Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of winter cyclone activity in a transient ECHAM4-OPYC3 GHG experiment

Winter cyclone activity over the Northern Hemisphere is investigated in an ECHAM4/OPYC3 greenhouse gas scenario simulation. The goal of this investigation is to identify changes in cyclone activity associated with increasing concentrations. To this aim, two 50-year time periods are analysed, one representing present day climate conditions and the other a perturbed climate when CO 2 concentrations exceed twice the present concentrations. Cyclone activity is assessed using an automatic algorithm, which identifies and tracks cyclones based on sea level pressure fields. The algorithm detects not only large and long living cyclones over the main ocean basins, but also their smaller counterparts in secondary storm track regions like the Mediterranean Basin. For the present climate, results show a good agreement with NCEP-reanalysis, provided that the spectral and time resolutions of the reanalysis are reduced to those available for the model. Several prominent changes in cyclone activity are observed for the scenario period in comparison to the present day climate, especially over the main ocean basins. A significant decrease of overall cyclone track density is found between 35 and 55 degrees North, together with a small increase polewards. These changes result from two different signals for deep and medium cyclones: for deep cyclones (core pressure below 990 hPa) there is a poleward shift in the greenhouse gas scenario, while for medium cyclones (core pressure between 990 and 1010 hPa) a general decrease in cyclone counts is found. The same kind of changes (a shift for intense cyclones and an overall decrease for the weaker ones) are detected when distinguishing cyclones from their intensity, quantified in terms of ∇ 2 p. Thus, the simulated changes can not solely be attributed to alterations in mean sea level pressure. Instead, corresponding increases in upper-tropospheric baroclinicity suggest more favourable conditions for the development of stronger systems at higher latitudes, especially at the delta regions of the North Atlantic and the North Pacific storm tracks.
Conduction electrons in GaAs: Five-level k⋅p theory and polaron effects

Properties of conduction electrons in GaAs are described theoretically using a five-level k\ensuremath{\cdot}p model, which consistently accounts for inversion asymmetry of the material. The dispersion relation E(k) is computed and it is shown that the conduction band is both nonparabolic and nonspherical. The energy dependence of the electron effective mass, the energy-momentum relation in the forbidden gap, and the spin splitting of the band are calculated. Analytical expressions for the band-edge effective mass, the spin splitting, and the Land\'e factor ${g}^{\mathrm{*}}$ are presented, taking explicitly into account an interband matrix element of the spin-orbit interaction. A five-level P\ensuremath{\cdot}p theory for the conduction band in the presence of an external magnetic field is developed. Resonant and nonresonant effects due to polar electron\char21{}optic-phonon interaction are included in the theory. The spin g value of conduction electrons is calculated as a function of energy and magnetic field. Spin-doublet splitting of the cyclotron resonance and the cyclotron-resonance-mass anisotropy are described. A comparison of the theory with experimental data of various authors is used to determine important band parameters for GaAs. It is shown that away from the band edge the polaron effects in GaAs are comparable to the band-structure effects.
Differences in clinical features and gut microbiota between individuals with methamphetamine casual use and methamphetamine use disorder

Background The transition from methamphetamine (MA) casual use (MCU) to compulsive use is enigmatic as some MA users can remain in casual use, but some cannot. There is a knowledge gap if gut microbiota (GM) play a role in differing MCU from MA use disorder (MUD). We aimed to investigate the clinical features and GM differences between individuals with MCU and MUD. Method We recruited two groups of MA users –MCU and MUD – and matched them according to age and body mass index (n=21 in each group). Participants were accessed using the Semi-Structured Assessment for Drug Dependence and Alcoholism, and their fecal samples were undergone 16S ribosomal DNA sequencing. We compared the hosts’ clinical features and GM diversity, composition, and structure (represented by enterotypes) between the two groups. We have identified differential microbes between the two groups and performed network analyses connecting GM and the clinical traits. Result Compared with the casual users, individuals with MUD had higher incidences of MA-induced neuropsychiatric symptoms (e.g., paranoia, depression) and withdrawal symptoms (e.g., fatigue, drowsiness, and increased appetite), as well as stronger cravings for and intentions to use MA, and increased MA tolerance. The GM diversity showed no significant differences between the two groups, but four genera (Halomonas, Clostridium, Devosia, and Dorea) were enriched in the individuals with MUD (p<0.05). Three distinct enterotypes were identified in all MA users, and Ruminococcus-driven enterotype 2 was dominant in individuals with MUD compared to the MCU (61.90% vs. 28.60%, p=0.03). Network analysis shows that Devosia is the hub genus (hub index = 0.75), which is not only related to the counts of the MUD diagnostic criteria (ρ=0.40; p=0.01) but also to the clinical features of MA users such as reduced social activities (ρ=0.54; p<0.01). Devosia is also associated with the increased intention to use MA (ρ=0.48; p<0.01), increased MA tolerance (ρ=0.38; p=0.01), craving for MA (ρ=0.37; p=0.01), and MA-induced withdrawal symptoms (p<0.05). Conclusion Our findings suggest that Ruminococcus-driven enterotype 2 and the genera Devosia might be two influential factors that differentiate MA casual use from MUD, but further studies are warranted.
Probiotic Supplementation Attenuates Chemotherapy-Induced Intestinal Mucositis in an Experimental Colorectal Cancer Liver Metastasis Rat Model

The use of chemotherapeutic agents is of paramount importance when treating colorectal cancer (CRC). Unfortunately, one of the most frequent chemotherapy (CTx) side effects is intestinal mucositis (IM), which may present with several clinical symptoms such as nausea, bloating, vomiting, pain, and diarrhea and even can result in life-threatening complications. There is a focused scientific effort towards developing new therapies to prevent and treat IM. The aim of this study was to assess the outcomes of probiotic supplementation on CTx-induced IM in a CRC liver metastasis rat model. Six-week-old male Wistar rats received either a multispecies probiotic or placebo mixture. On the 28th experiment day, rats received FOLFOX CTx, and afterwards, the severity of diarrhea was evaluated twice daily. Stool samples were collected for further microbiome analysis. Additionally, immunohistochemical stainings of ileum and colon samples with were performed with MPO, Ki67, and Caspase-3 antibodies. Probiotic supplementation alleviates the severity and length of CTx-induced diarrhea. Additionally, probiotics significantly reduced FOLFOX-induced weight and blood albumin loss. Furthermore, probiotic supplementation mitigated CTx-induced histological changes in the gut and promoted intestinal cell regeneration. This study shows that multispecies probiotic supplementation attenuates FOLFOX-induced IM symptoms by inhibiting apoptosis and promoting intestinal cell proliferation.
The response of a micro-electro-mechanical system (MEMS) cantilever-paddle gas sensor to mechanical shock loads

This work presents an investigation into the effect of nonlinearities on the response of a micro-electro-mechanical system gas sensor under mechanical shock and electrostatic loading. The gas sensor consists of a cantilever microbeam with a rigid microplate (micro-paddle) attached to its tip. A nonlinear Euler-Bernoulli beam theory is used to model the system, accounting for both geometric and inertia nonlinearities, in addition to the nonlinear electrostatic force used to actuate the system. The system of integro-partial-differential equations is discretized using a Galerkin procedure to extract a reduced-order model, which is then used for dynamic simulations of the system responses. The influences of the different components of nonlinearity such as geometric and inertia nonlinearities are examined. The results of the nonlinear model are compared to results obtained from linear beam theory and finite element simulations. For mechanical shock loading, both quasi-static and dynamic responses of a microbeam are considered. The effect of nonlinearity is found to be significant when the deflection of the microbeam exceeds around 30% of its length. The consequence of the large deflection is that the geometric nonlinearity has a much stronger influence on the response in comparison to the inertia nonlinearity. It is also apparent that the effect of the paddle is to enhance the dynamic, as opposed to the quasi-static, response of the microbeam to mechanical shock. For electrostatic actuation, it is found that using a nonlinear beam model to predict the pull-in and the deflection produces a slight improvement over using a linear beam model.
Neutral hydrogen in elliptical radio galaxies

Avec une limite de detection de 3×10 8 M ○. , independante de la distance, on a detecte au moins 4 galaxies sur 22. Elles semblent plus lumineuses a 5,0 GHz mais toute correlation, entre la luminosite radio et le contenu HI, doit etre extremement faible
Optimal power flow solutions under variable load conditions

This work presents a methodology to calculate a sequence of optimal power flow (OPF) solutions under variable load conditions. The aim is to obtain a set of optimal operating points in the neighborhood of the bounds of the region defined by the load flow equations and a set of operational limits. For this, an algorithm based on the continuation method and on a primal-dual interior point optimization method is proposed. Such an algorithm consists of two main steps: the predictor step, which uses a linear approximation of the Karush-Kuhn-Tucker (KKT) conditions to estimate a new operating point for an increment in the system load; and the corrector step, which calculates the optimum corresponding to the new load level via a nonlinear primal-dual interior point method. Indices for critical buses and inequality constraints are a byproduct of the methodology. In addition, sensitivity analysis is performed to calculate the amount of reactive compensation which allows for a pre-specified increase in the system load. Results for realistic test systems are presented.
The enigmatic X-rays from the Herbig star HD 163296: Jet, accretion, or corona?

Context. Herbig Ae/Be stars (HAeBe) are pre-main sequence objects in the mass range 2 M� < M∗ < 8 M� . Their X-ray properties are uncertain and, as yet, unexplained. Aims. We want to elucidate the X-ray generating mechanism in HAeBes. Methods. We present an XMM-Newton observation of the HAeBe HD 163296. We analyse the light curve, the broad band and the grating spectra, fit emission measures and abundances and apply models for accretion and wind shocks. Results. We find three temperature components ranging from 0.2 keV to 2.7 keV. The O vii He-like triplet indicates an X-ray formation region in a low density environment with a weak UV photon field, i.e. above the stellar surface. This makes an origin in an accretion shock unlikely; instead we suggest a shock at the base of the jet for the soft component and a coronal origin for the hot component. A mass outflow of u
Advances in the application of computational fluid dynamics in cardiovascular flow

Abstract Computational Fluid Dynamics (CFD) plays an important role in assessment of genesis and prognosis of atherosclerosis and as a promising tool for risk stratification. CFD is widely used by a majority of the researchers, although, many experimental studies show that the results obtained by CFD are inconsistent with the physio-pathological manifestations, which is mainly due to inconsistent definition of parameters, limited data availability and extreme complexity and heterogeneous behavior of plaque growth and its rupture. In this review, the results obtained by Computational Fluid Dynamics are summarized and an attempt is made to deduce the broad causes of various errors and possible solutions.
E‐CNNet: Time‐reassigned Multisynchrosqueezing transform‐based deep learning framework for MI‐BCI task classification

The classification of electroencephalograms‐based motor imagery signals poses a significant issue in the design and development of brain‐computer interfaces. Neural Networks are observed to be successful in classification of motor imagery brain signals. However, the existing motor imagery data sets are of limited size and suffer from low signal to noise ratio. Hence, to achieve high performance with small datasets, this paper proposes a novel combination of time frequency analysis along with deep learning network to perform the brain signal classification task. The proposed framework consists of two parts: (1) Time‐reassigned Multisynchrosqueezing Transform to efficiently capture the dynamic properties of non‐stationary EEG; and (2) A new hybrid model E‐CNNet is proposed for feature extraction and classification of brain signals. A robust classification pipeline is constructed to classify the extracted features into respective motor imagery tasks. Ensemble of boosting classifiers is used to generate the final predictions, thus, reducing the variance and bias of individual classifiers. The performance of the proposed methodology is evaluated using two publicly available datasets: BCI competition III, dataset IIIa and BCI competition IV, dataset IIa. We have obtained the average classification accuracy of 94.44% on BCI competition III, dataset IIIa and 89.25% on BCI competition IV, dataset IIa.
Single-Stage Active Rectifier With Wide Impedance Conversion Ratio Range for Inductive Power Transfer System Delivering Constant Power

Compared with the constant current (CC) charging mode, the constant power (CP) charging mode can speed up the battery charging rate and free the charger from excessive thermal design problems. However, the range of the battery's equivalent resistance in CP mode is wider than that in CC mode, which makes it difficult to track the optimal resistance of the inductive power transfer (IPT) system for efficiency enhancement. To solve this problem, this article proposes a single-stage active rectifier (SSAR) integrating an interleaved buck converter with a full-bridge active rectifier (FBAR). Compared with the traditional FBAR, the resistance conversion ratio range of the SSAR is extended from <inline-formula><tex-math notation="LaTeX">$[0, 8/\pi ^{2}]$</tex-math></inline-formula> to <inline-formula><tex-math notation="LaTeX">$[0, 8]$</tex-math></inline-formula>, and the output current ripple is reduced due to the interleaved operation. A novel optimal phase angle control strategy is correspondingly proposed for the IPT system with the SSAR, which features advantages of wide impedance conversion ratio range, zero voltage switching turn-<sc>on</sc> of all <sc>mosfet</sc>s, and no communication between the primary and the secondary sides. A 150-W experimental prototype is provided to verify the effectiveness of the proposed rectifier.
Cloud type discrimination via multispectral textural analysis

One of the primary interests in digital image processing is the development of robust methods to perform feature detection, extraction, and classification. Until recently, classification methods for cloud discrimination were mainly based on the spectral information of the imagery. However, because of the spectral similarities of certain features (such as ice clouds and snow) and the effects of atmospheric attenuation, multi-spectral rule based classifications do not necessarily produce accurate feature discrimination. Spectral homogeneity of two different features within a scene can lead to misclassification. Furthermore, the opposite problem can occur when one feature exhibits different spectral signatures locally but is homogeneous in its cyclic spatial variation. The exploration of spatial information is often advantageous in these discrimination problems. A texture-based method for feature identification has been investigated. This method uses a set of localized spatial filters known as two dimensional Gabor functions. Gabor filters can be described as a sinusoidal plane wave within a two-dimensional Gaussian envelope. The frequency and orientation of the sine plane and the width of the Gaussian envelope are determined by the Gabor parameters. These tunable channels yield joint optimal information both in the spatial and the frequency domains. The new method has been applied to the thermal channels of the NOAA-advanced very high resolution radiometer (AVHRR) data for cloud type discrimination.
Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models

Summary. The paper considers health‐related non‐response in the first 11 waves of the British Household Panel Survey and the full eight waves of the European Community Household Panel and explores its consequences for dynamic models of the association between socioeconomic status and self‐assessed health. We describe the pattern of health‐related non‐response that is revealed by the British Household Panel Survey and European Community Household Panel data. We both test and correct for non‐response in empirical models of the effect of socioeconomic status on self‐assessed health. Descriptive evidence shows that there is health‐related non‐response in the data, with those in very poor initial health more likely to drop out, and variable addition tests provide evidence of non‐response bias in the panel data models of self‐reported health. Nevertheless a comparison of estimates—based on the balanced sample, the unbalanced sample and corrected for non‐response by using inverse probability weights—shows that, on the whole, there are not substantive differences in the average partial effects of the variables of interest. The main differences are between unweighted and one form of inverse‐probability‐weighted estimates for the average partial effects of income and education in those countries that have fewer than eight waves of data. Similar findings have been reported concerning the limited influence of non‐response bias in models of various labour market outcomes; we discuss possible explanations for our results.
Average Regression Surface for Dependent Data

We study the estimation of the additive components in additive regression models, based on the weighted sample average of regression surface, for stationary ? -mixing processes. Explicit expression of this method makes possible a fast computation and allows an asymptotic analysis. The estimation procedure is especially useful for additive modeling. In this paper, it is shown that the average surface estimator shares the same optimality as the ideal estimator and has the same ability to estimate the additive component as the ideal case where other components are known. Formulas for the asymptotic bias and normality of the estimator are established. A small simulation study is carried out to illustrate the performance of the estimation and a real example is also used to demonstrate our methodology.
Self-assembly of graphene oxide coated soft magnetic carbonyl iron particles and their magnetorheology

The surface of carbonyl iron (CI) microspheres was modified with graphene oxide (GO) as a coating material using 4-aminobenzoic acid as the grafting agent. The morphology, elemental composition, and magnetic properties of the GO-coated CI (GO/CI) particles were examined by scanning electron microscopy, energy dispersive X-ray spectroscopy and vibrating sample magnetometry, respectively, confirming their composite formation. The magnetorheological (MR) performance of the GO/CI particle-based suspension was examined using a rotational rheometer connected to a magnetic field supply. The GO/CI particles suspension exhibited typical MR properties with increasing shear stress and viscosity depending on the applied magnetic field strength.
P Values as Random Variables—Expected P Values

Abstract p values are extensively reported in practical hypothesis testing situations. Although carefully studied by Dempster and Schatzoff, the stochastic aspect of p values is often neglected. In this expository note we borrow from Dempster and Schatzoff to rekindle interest in—and explore the potential usefulness of—understanding the stochastic behavior of p values. We relate the expected p value (EPV) under the alternative to the more familiar concepts of significance level and power. We then go on to argue that in cases where it is difficult to evaluate the power function, the EPV can be used as a measure of the performance of a test. EPV's are always easily evaluated or simulated. Different test statistics for the same hypotheses can also be compared by means of EPV's. We carry out such a comparison between the two-sample, one-sided Kolmogorov-Smirnov, Mann-Whitney, and t tests, for a variety of underlying distributions. The EPV can also be a valuable tool in sample size determination and in the int.
Emission of electromagnetic radiation in α-decay

The electromagnetic radiation during the non-uniform motion of the fragments resulting from the α-decay of a heavy nucleus is computed in a time-dependent quantum formalism. The dynamical characteristics of the α-particle such as position, velocity and acceleration are computed by taking average values of the position and momentum operators and next the bremsstrahlung emission is determined by resorting to the classical formula for the radiation power. The contribution of the α-particle intra-barrier motion to the total bremsstrahlung yield is evaluated and some hints are given for the case when one considers α-decay from the ground state.
THE EFFECT OF WIND SHEAR ON FALLING PRECIPITATION

Abstract Precipitation particles which fall from a source aloft through a wind shear are sorted as to size, the largest particles reaching the ground closest to the generating source, the smaller particles further from it. If precipitation is assumed to form continuously in cloud, with a fixed size distribution, this sorting affects significantly the size distributions to be observed below the cloud, and so the relationship between the precipitation rate R and the radar scattering-parameter Z (which is ∑D6, where D is the diameter of a raindrop or the water drop to which a snowflake would melt, and the summation is over unit volume). As an approximation to a small isolated shower, a horizontal generating element has been taken, of linear extent 1.6 kilometers in the direction of the wind shear. The quantities R and Z tend to be less at the ground than in the generating region, the size distributions remaining the same except for upper and lower limits of size imposed by the sorting. Several values of R an.