Miracle-dz/UniFAR-FTUs huggingface dataset:
Gold Nanoparticles Introduced ZnO/Perovskite/ Silicon Heterojunction Solar Cell

Renewable energy sources like photovoltaics have the potential to mitigate the negative consequences of pollution and global warming. The solar sector has shown exponential growth and is quickly becoming a viable alternative to fossil fuels. Currently, the great majority of solar modules are composed of crystalline silicon. To make photovoltaics more competitive, affordability and efficiency are two of the most important elements. Metal nanoparticles can be introduced or a heterojunction can be made using appropriate materials to increase the absorption coefficient of a silicon-based solar cell, which boost the total efficiency of the solar module. Therefore, in this study, we used Sentaurus TCAD simulation to examine the effects of gold nanoparticles introduced with various sizes and periodicities on the photoelectric characteristics of ZnO/Si and Perovskite/Si solar cells. Accordingly, all of the photoelectric characteristics of the perovskite/Si solar cell have shown a clear sinusoidal connection with the nanoparticle periodicity. When the gold nanoparticle size changed from 6 nm to 9 nm, the period of the sinusoidal function changed to $\pi $ . The photoelectric parameters of ZnO/Si solar cells changed in a sinusoidal pattern based on the nanoparticle’s periodicity, but this was true only when the nanoparticles size was between 9 nm and 21 nm. According to the obtained results, the maximum values of short-circuit current, open circuit voltage and fill factor are 10.47 mA/cm2, 0.384 V, 71.06% for perovskite/Si and 10.52 mA/cm2, 0.306 V, 71.12% for ZnO/Si. The minimum current density of the perovskite/Si solar cell was identical when compared to the solar cell without nanoparticles. When a gold nanoparticle with a size of 6 nm was introduced into the ZnO/Si solar cell with a periodicity of 120 nm, the short circuit current decreased by a factor of 3.81 compared to the solar cell without the nanoparticle. It has been scientifically proven that Fano interference is responsible for the sinusoidal relationship between the short-circuit current of the solar cells and the periodicity of the nanoparticle.
Stellarator bootstrap current and plasma flow velocity at low collisionality

The bootstrap current and flow velocity of a low-collisionality stellarator plasma are calculated. As far as possible, the analysis is carried out in a uniform way across all low-collisionality regimes in general stellarator geometry, assuming only that the confinement is good enough that the plasma is approximately in local thermodynamic equilibrium. It is found that conventional expressions for the ion flow speed and bootstrap current in the low-collisionality limit are accurate only in the 1/nu -collisionality regime and need to be modified in the root-nu-regime. The correction due to finite collisionality is also discussed and is found to scale as nu^2/5
Convex projective manifolds with a cusp of any non‐diagonalizable type

Recent work of Ballas, Cooper, and Leitner identifies (n+1) types of n ‐dimensional convex projective cusps, one of which is the standard hyperbolic cusp. Work of Ballas–Marquis and Ballas–Danciger–Lee [Ballas, Danciger and Lee, ‘Convex projective structures on nonhyperbolic threemanifolds’,Geom. Topol. 22 (2018) 1593–1646] give examples of these exotic (non‐hyperbolic) type cusps in dimension 3. Here an extension of the techniques of Ballas–Marquis shows the existence of all cusp types in all dimensions, except diagonalizable (type n ) [Ballas, Cooper and Leitner, ‘Generalized cusps in real projective manifolds: classification’, Preprint, 2017, arXiv:1710.03132; Ballas and Marquis, ‘Properly convex bending of hyperbolic manifolds’, Preprint, 2016, arXiv:1609.03046].
A robust BFGS algorithm for unconstrained nonlinear optimization problems

In this paper, a modified BFGS algorithm is proposed. The modified BFGS matrix estimates a modified Hessian matrix which is a convex combination of an identity matrix for the steepest descent algorithm and a Hessian matrix for the Newton algorithm. The coefficient of the convex combination in the modified BFGS algorithm is dynamically chosen in every iteration. It is proved that, for any twice differentiable nonlinear function (convex or non-convex), the algorithm is globally convergent to a stationary point. If the stationary point is a local optimizer where the Hessian is strongly positive definite in a neighborhood of the optimizer, the iterates will eventually enter and stay in the neighborhood, and the modified BFGS algorithm reduces to the BFGS algorithm in this neighborhood. Therefore, the modified BFGS algorithm is super-linearly convergent. Moreover, the computational cost of the modified BFGS in each iteration is almost the same as the cost of the BFGS. Numerical test on the CUTE test set is reported. The performance of the modified BFGS algorithm implemented in our MATLAB function is compared to the BFGS algorithm implemented in the MATLAB Optimization Toolbox function, a limited memory BFGS implemented as L-BFGS, a descent conjugate gradient algorithm implemented as CG-Descent 5.3, and a limited memory, descent and conjugate algorithm implemented as L-CG-Descent. This result shows that the modified BFGS algorithm may be very effective.
Nonequilibrium Kondo-vs.-RKKY scenarios in nanoclusters

Ultrafast manipulations of magnetic phases are eliciting increasing attention from the scientific community because potentially relevant to the understanding of nonequilibrium phase transitions and to novel technologies. Here, we focus on manipulations applied to magnetic impurities in metallic hosts. By considering small nanoring geometries, we show how currents can induce a dynamical switching between different types of exchange interactions in these systems. Our work thus opens a study window on nonequilibrium Doniach's magnetic phase diagrams, and time-dependent Kondo-vs.-RKKY scenarios.
A Unified Gas Kinetic Scheme for Continuum and Rarefied Flows V: Multiscale and Multi-Component Plasma Transport

As a continuation of developing multiscale method for the transport phenomena, a unified gas kinetic scheme (UGKS) for multi-scale and multi-component plasma simulation is constructed. The current scheme is a direct modeling method, where the time evolution solutions from the Vlasov-BGK equations of electron and ion and the Maxwell equations are used to construct a scale-dependent plasma simulation model. The modeling scale used in the UGKS is the mesh size scale, which can be comparable to or much larger than the local mean free path. As a result, with the variation of modeling scales in space and time through the so-called cell's Knudsen number and normalized Larmor radius, the discretized governing equations can recover a wide range of plasma evolution from the Vlasov equation in the kinetic scale to different-type of magnetohydrodynamic (MHD) equations in the hydrodynamic scale. The UGKS provides a general evolution model, which goes to the Vlasov equation in the kinetic scale and many types of MHD equations in the hydrodynamic scale, such as the two fluids model, the Hall, the resistive, and the ideal MHD equations. All current existing governing equations become the subsets of the UGKS, and the UGKS bridges these distinguishable governing equations seamlessly. The construction of UGKS is based on the implementation of physical conservation laws and the un-splitting treatment of particle collision, acceleration, and transport in the construction of a scale-dependent numerical flux across a cell interface. At the same time, the discretized plasma evolution equations are coupled with the Maxwell equations for electro-magnetic fields, which also cover a scale-dependent transition between the Ampere's law and the Ohm's law for the calculation of electric field. The time step of UGKS is not limited by the relaxation time, the cyclotron period, and the speed of light in the ideal-MHD regime. Our scheme is able to give a physically accurate solution for plasma simulation with a wide range of Knudsen number and normalized Larmor radius. It can be used to study the phenomena from the Vlasov limit to the scale of plasma skin depth for the capturing of two-fluid effect, and the phenomena in the plasma transition regime with a modest Knudsen number and Larmor radius. The UGKS is validated by numerical test cases, such as the Landau damping and two stream instability in the kinetic regime, and the Brio-Wu shock tube problem, and the Orszag-Tang MHD turbulence problem in the hydrodynamic regime. The scheme is also used to study the geospace environment modeling (GEM), such as the challenging magnetic reconnection problem in the transition regime. At the same time, the magnetic reconnection mechanism of the Sweet-Parker model and the Hall effect model can be connected smoothly through the variation of Larmor radius in the UGKS simulations. Overall, the UGKS is a physically reliable multi-scale plasma simulation method, and it provides a powerful and unified approach for the study of plasma physics.
Simulations of extragalactic magnetic fields and of their observables

The origin of extragalactic magnetic fields is still poorly understood. Based on a dedicated suite of cosmological magneto-hydrodynamical simulations with the ENZO code we have performed a survey of different models that may have caused present-day magnetic fields in galaxies and galaxy clusters. The outcomes of these models differ in cluster outskirts, filaments, sheets and voids and we use these simulations to find observational signatures of magnetogenesis. With these simulations, we predict the signal of extragalactic magnetic fields in radio observations of synchrotron emission from the cosmic web, in Faraday rotation, in the propagation of ultra high energy cosmic rays, in the polarized signal from fast radio bursts at cosmological distance and in spectra of distant blazars. In general, primordial scenarios in which present-day magnetic fields originate from the amplification of weak (⩽nG) uniform seed fields result in more homogeneous and relatively easier to observe magnetic fields than astrophysical scenarios, in which present-day fields are the product of feedback processes triggered by stars and active galaxies. In the near future the best evidence for the origin of cosmic magnetic fields will most likely come from a combination of synchrotron emission and Faraday rotation observed at the periphery of large-scale structures.
Modeling Physiological Predictors of Running Velocity for Endurance Athletes

Background: Properly performed training is a matter of importance for endurance athletes (EA). It allows for achieving better results and safer participation. Recently, the development of machine learning methods has been observed in sports diagnostics. Velocity at anaerobic threshold (VAT), respiratory compensation point (VRCP), and maximal velocity (Vmax) are the variables closely corresponding to endurance performance. The primary aims of this study were to find the strongest predictors of VAT, VRCP, Vmax, to derive and internally validate prediction models for males (1) and females (2) under TRIPOD guidelines, and to assess their machine learning accuracy. Materials and Methods: A total of 4001 EA (nmales = 3300, nfemales = 671; age = 35.56 ± 8.12 years; BMI = 23.66 ± 2.58 kg·m−2; VO2max = 53.20 ± 7.17 mL·min−1·kg−1) underwent treadmill cardiopulmonary exercise testing (CPET) and bioimpedance body composition analysis. XGBoost was used to select running performance predictors. Multivariable linear regression was applied to build prediction models. Ten-fold cross-validation was incorporated for accuracy evaluation during internal validation. Results: Oxygen uptake, blood lactate, pulmonary ventilation, and somatic parameters (BMI, age, and body fat percentage) showed the highest impact on velocity. For VAT R2 = 0.57 (1) and 0.62 (2), derivation RMSE = 0.909 (1); 0.828 (2), validation RMSE = 0.913 (1); 0.838 (2), derivation MAE = 0.708 (1); 0.657 (2), and validation MAE = 0.710 (1); 0.665 (2). For VRCP R2 = 0.62 (1) and 0.67 (2), derivation RMSE = 1.066 (1) and 0.964 (2), validation RMSE = 1.070 (1) and 0.978 (2), derivation MAE = 0.832 (1) and 0.752 (2), validation MAE = 0.060 (1) and 0.763 (2). For Vmax R2 = 0.57 (1) and 0.65 (2), derivation RMSE = 1.202 (1) and 1.095 (2), validation RMSE = 1.205 (1) and 1.111 (2), derivation MAE = 0.943 (1) and 0.861 (2), and validation MAE = 0.944 (1) and 0.881 (2). Conclusions: The use of machine-learning methods allows for the precise determination of predictors of both submaximal and maximal running performance. Prediction models based on selected variables are characterized by high precision and high repeatability. The results can be used to personalize training and adjust the optimal therapeutic protocol in clinical settings, with a target population of EA.
Current-driven skyrmion motion along disordered magnetic tracks

The motion of skyrmions along ferromagnetic strips driven by current pulses is theoretically analyzed by means of micromagnetic simulations. Analytical expressions describing the skyrmion dynamics during and after the current pulse are obtained from an extended rigid skyrmion model, and its predictions are compared with full micromagnetic simulations for perfect samples with a remarkable agreement. The dynamics along realistic samples with random disorder is also studied by both models. Our analysis describes the relevant ingredients behind the current-driven skyrmion dynamics, and it is expected to be useful to understand recent and future experimental.
OPERADIC APPROACH TO COHOMOLOGY OF ASSOCIATIVE TRIPLE AND N-TUPLE SYSTEMS

Abstract The cup product in the cohomology of algebras over quadratic operads has been studied in the general setting of Koszul duality for operads. We study the cup product on the cohomology of n-ary totally associative algebras with an operation of even (homological) degree. This cup product endows the cohomology with the structure of an n-ary partially associative algebra with an operation of even or odd degree depending on the parity of n. In the cases n=3 and n=4, we provide an explicit definition of this cup product and prove its basic properties.
Spectral analysis for tilted fiber Bragg gratings in the corrosion detection for concrete structure

An effective corrosion monitoring technique is sought after by the engineers for assessing the steel bar corrosion at the early stage for the maintenance and repair works, especially in the corrosive environments, such as coastal and marine. In this work, tilted fiber Bragg grating (TFBG) with the optical sensor is employed in corrosion monitoring of a reinforced concrete structure. Taking advantage of the high sensitivity of TFBG cladding resonance wavelengths to the change in the surrounding medium, the sensor is mounted on the steel bar that is embedded in a concreted block during an accelerated corrosion process. The acquired transmission spectrum of the TFBG during the procedure is digitally processed using Fourier Transform to produce an index that is sensitive to the generated corrosion product surrounding the TFBG sensor. This eases the analysis of the sophisticated TFBG transmission spectra. The generated index can be used as an indicator (indicator J) for the corrosion process of the embedded steel bar in the concrete structure. This indicator J can act as an indicator to describe the corrosion activity and corrosion level at a specific point of the steel bar in concrete structures.
The Snake: A Reconnecting Coil in a Twisted Magnetic Flux Tube

We propose that the curious Galactic center filament known as the Snake is a twisted giant magnetic flux tube, anchored in rotating molecular clouds. The MHD kink instability generates coils in the tube and subsequent magnetic reconnection injects relativistic electrons. Energy-dependent diffusion of electrons away from the coil produces a flat spectral index at large distances from it. Our fit to the existing data shows that the magnetic field of ~0.4 mG is large compared to the ambient ~7 μG field, indicating that the flux tube is force-free. If the relative level of turbulence in the Snake and the general interstellar medium are similar, then electrons have been diffusing in the Snake for about 3 × 105 yr, comparable to the timescale at which magnetic energy is annihilated in the major kink. Estimates of the magnetic field in the G359.19-0.05 molecular complex are similar to our estimate of the magnetic field in the Snake, suggesting a strong connection between the physics of the anchoring molecular regions and the Snake. We suggest that the physical processes considered here may be relevant to other radio filaments near the Galactic center. We also suggest further observations of the Snake and other filaments that would be useful for obtaining further insights into the physics of these objects.
Learning from our neighbours: a novel approach on sinogram completion using bin-sharing and deep learning to reconstruct high quality 4DCBCT

Inspired by the success of deep learning applications on restoration of low-dose and sparse CT images, we propose a novel method to reconstruct high-quality 4D cone-beam CT (4DCBCT) images from sparse datasets. Our approach combines the idea of bin-sharing with a deep convolutional neural network (CNN) model. More specifically, for each respiratory bin, an initial estimate of the patient sinogram is obtained by taking projections from adjacent bins and performing linear interpolation. Subsequently, the estimated sinogram is propagated through a CNN that predicts a full, high-quality sinogram. Lastly, the predicted sinogram is reconstructed with an iterative CBCT algorithms such as the Conjugate Gradient (CG) method. The CNN model, which we referred to as the Sino-Net, was trained under different loss functions. We assessed the performance of the proposed method in terms of image quality metrics (mean square error, mean absolute error, peak signal-to-noise ratio and structural similarity) and tumor motion accuracy (tumor centroid deviation with respect to the ground truth). Lastly, we compared our approach against other state-of-the-art methods that compensate motion and reconstruct 4DCBCTs. Overall, the presented prototype model was able to substantially improve the quality of 4DCBCT images, removing most of the streak artifacts and decreasing the noise with respect to the standard CG reconstructions.
International financial integration and economic growth in developing and emerging economies: an empirical investigation

Abstract This paper explores the relationship between international financial integration (IFI), external vulnerability and economic growth. It proposes a taxonomy of typical IFI profiles and applies it to a sample of 90 developing and emerging economies (DEEs) for the 1992–2016 period using a dynamic panel data model. Drawing from a Post Keynesian and Structuralist analytical framework, it argues that what matters for economic growth is less the degree of IFI per se and more the profile, or “quality,” of this integration. The results suggest that DEEs which succeed in integrating into global financial markets under a more balanced and autonomous profile may experience, at best, negligible benefits for economic growth, while a more financially dependent and vulnerable profile exacerbates the risks of financial globalization, undermining growth in the long run. Moreover, the growth path in the latter tends to be more affected by external financial shocks, even though systemic shocks also impact the former.
Quantitative Acetylome Analysis of Soft Wheat Seeds during Artificial Ageing

Lysine acetylation (Kac) is a protein post-translational modification (PTM) widely found in plants that plays vital roles in metabolic pathways. Although seed germination and development are regulated by Kac, its potential function in seed ageing remains to be investigated. Our preliminary study demonstrated that Kac levels were altered during wheat seed artificial ageing. However, its specific role in this process still needs to be elucidated. Here, we performed quantitative acetylation proteomics analysis of soft wheat seeds with different germination rates during artificial ageing. A total of 175 acetylation proteins and 255 acetylation modification sites were remarkably changed. The differentially acetylated proteins were enriched in metabolism; response to harsh intracellular environment, such as ROS; protein storage and processing. Notably, expression, point mutation to mimic Kac by K to Q mutation at K80 and K138, protein purification and enzyme activity detection revealed that the Kac of ROS-scavenging glutathione transferase attenuated its activity, indicating that the defense ability of wheat seeds to stress gradually diminished, and the ageing process was inevitable. Collectively, our data provide a basis for further understanding the roles of Kac in seed ageing and might aid in the development of new techniques to prolong seed viability and food quality.
Impact on floating thin elastic sheets: A mathematical model

We investigate impact of a sphere onto a floating elastic sheet, and the resulting formation and evolution of wrinkles in the sheet. Following impact, we observe a radially propagating wave, beyond which the sheet remains approximately planar but is decorated by a series of radial wrinkles whose wavelength grows in time. We develop a mathematical model to describe these phenomena by exploiting the asymptotic limit in which the bending stiffness is small compared to stresses in the sheet. The results of this analysis show that, at a time $t$ after impact, the transverse wave is positioned a radial distance $r \sim t^{1/2}$ from the impactor, in contrast to the classic $r \sim t^{2/3}$ scaling observed for capillary-inertia ripples produced by dropping a stone into a pond. We describe the shape of this wave, starting from the simplest case of a point impactor and subsequently addressing a finite-radius spherical impactor. We show also that the coarsening of wrinkles in the flat portion of the sheet is controlled by the inertia of the underlying liquid: short-wavelength, small-amplitude wrinkles form at early times since they accommodate the imposed solid deformation without significantly displacing the underlying liquid. As time progresses, the liquid accelerates and the wrinkles grow larger and coarsen. We explain this coarsening quantitatively using numerical simulations and scaling arguments.
Unravelling Diabetes-related Pathways Using 16S rRNA Microbiome Data from Human Gut and Nasal Cavity

Type 2 Diabetes (T2D) is a complex chronic illness that affects around 90% of diabetic patients worldwide. Prediabetes is an elementary phase for T2D that is recommended to be early diagnosed to prevent its progression. In this study, we used 16S rRNA data from the gut and nasal cavity of prediabetic and control patients to identify common and exclusive diabetic pathways for each body site. Furthermore, using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) as well as MicobiomeExplorer in the pathway enrichment analysis, we also identified the pathways that are able to differentiate between prediabetic and control patients. Moreover, our study highlights some important aspects, (1) the number of differentially enriched pathways in the nasal cavity is two times more than that in the gut; 22 and 11 respectively, (2) Cardiac muscle contraction and Parkinson's disease were the only common pathways identified from the data of gut and nasal cavity, (3) The difference in the values of pathways enrichment in prediabetic and control was more explored in the gut microbial community than in the nasal cavity, (4) the gut's data showed higher diagnostic power than the nasal cavity's data in differentiation between the prediabetic and control patients. In conclusion, the microbiome data could lead to biologically relevant insights on the progression of human diseases. Moreover, the gut microbiome is more susceptible to the prediabetes pathogenesis than the nasal cavity microbiome.