Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulations of the supernova-dominated interstellar medium in disk galaxies

A three-dimensional simulation of the evolution of an SNR-dominated ISM from an initially homogeneous, uniform substrate is presented. Systems with only bremsstrahlung cooling are compared with those cooled by radiation from metals. This distinction translates into a size difference in the resulting SNRs, and thus in the ability of isolated SNRs to affect the evolution of the galactic ecosystem. At a given SN rate, correlating the SNe decreases the global evolution of the galaxy if the SNRs individually can affect the system. It is shown that, when the density of the ISM varies widely, the N(R) test can give the reverse of standard expectations. It is shown that strong SNRs can impede interstellar tunnel production because of their ability to transport material and fill a previously evacuated volume, and that cloud size affects the final picture of the system. 113 refs.
Appressoria—Small but Incredibly Powerful Structures in Plant–Pathogen Interactions

Plant-pathogenic fungi are responsible for many of the most severe crop diseases in the world and remain very challenging to control. Improving current protection strategies or designating new measures based on an overall understanding of molecular host–pathogen interaction mechanisms could be helpful for disease management. The attachment and penetration of the plant surface are the most important events among diverse plant–fungi interactions. Fungi evolved as small but incredibly powerful infection structure appressoria to facilitate attachment and penetration. Appressoria are indispensable for many diseases, such as rusts, powdery mildews, and blast diseases, as well as devastating oomycete diseases. Investigation into the formation of plant–pathogen appressoria contributes to improving the understanding of the molecular mechanisms of plant–pathogen interactions. Fungal host attachment is a vital step of fungal pathogenesis. Here, we review recent advances in the molecular mechanisms regulating the formation of appressoria. Additionally, some biocontrol agents were revealed to act on appressorium. The regulation of fungal adhesion during the infective process by acting on appressoria formation is expected to prevent the occurrence of crop disease caused by some pathogenic fungi.
Cardiovascular Risk Assessment in Rheumatoid Arthritis: Accelerated Atherosclerosis, New Biomarkers, and the Effects of Biological Therapy

Rheumatoid arthritis (RA), one of the most common of the chronic inflammatory autoimmune diseases (CIADs), is recognized as an independent cardiovascular risk factor. Traditional risk factors such as smoking, arterial hypertension, dyslipidemia, insulin resistance, and obesity are frequently found in RA. Given the increased risk of mortality and morbidity associated with cardiovascular disease (CVD) in RA patients, screening for risk factors is important. Moreover, there is a need to identify potential predictors of subclinical atherosclerosis. Recent studies have shown that markers such as serum homocysteine, asymmetric dimethylarginine, or carotid intima–media thickness (cIMT) are correlated with cardiovascular risk. Although RA presents a cardiovascular risk comparable to that of diabetes, it is not managed as well in terms of acute cardiovascular events. The introduction of biological therapy has opened new perspectives in the understanding of this pathology, confirming the involvement and importance of the inflammatory markers, cytokines, and the immune system. In addition to effects in inducing remission and slowing disease progression, most biologics have demonstrated efficacy in reducing the risk of major cardiovascular events. Some studies have also been conducted in patients without RA, with similar results. However, early detection of atherosclerosis and the use of targeted therapies are the cornerstone for reducing cardiovascular risk in RA patients.
Ion-neutral collisions in a 22-pole trap at very low energies

This contribution concentrates on the use of an ion trapping technique which has been developed for studying collision processes and chemical reactions at low temperatures and which utilizes inhomogeneous radio frequency fields. Special emphasis is put onto recent progress achieved with a cryo cooled 22-pole ion trap. Experimental results, measured at a nominal temperature of 10 K, are presented for radiative association of CH3+ and C2H2+ with H2. Another group of results discussed in this paper deals with the dynamics of the growth of hydrogen clusters starting from H3+. In all cases, the influence of H2 rotation was examined by utilizing p-H2 and n-H2. Also the process of isotope fractionation in the presence of HD and D2 is briefly mentioned.
The generalized Ohm’s law in collisionless magnetic reconnection

The generalized Ohm’s law and the force balance near neutral lines in collisionless magnetic reconnection is studied based on two-dimensional full particle simulations in which the ion–electron mass ratio is set to be 1836. The off-diagonal elements of a plasma pressure tensor are found to be responsible for the breakdown of the frozen-in condition in collisionless reconnection. While the off-diagonal elements of the electron pressure tensor are dominant terms in the generalized Ohm’s law near neutral lines, the ion off-diagonal pressure terms are of significant importance when ions are main current carriers. The spatial scale of electron off-diagonal pressure term Pxy(e) is also found to be proportional to the Dungey length scale, (meEy/eβ2)1/3, where β=∂Bz/∂x.
Spectrum of a passive scalar in moderate Reynolds number homogeneous isotropic turbulence

For moderate Reynolds numbers, the spectral scaling exponents of both velocity [E(k)∝k−mu] and the transported passive scalar [Eθ(k)∝k−mθ] fields exhibit departures from the asymptotic prediction mu=mθ=5/3. However, at the same Reynolds number, the passive scalar spectrum for homogeneous isotropic turbulence is closer to the universal asymptotic state than the dynamic velocity field that transports it. This paper provides a possible explanation for this behavior, in the case of a gaseous mixing with Prandtl (or Schmidt) number Pr≃1. A scenario of the scalar energy transfer toward higher wavenumbers is proposed and validated using experimental data, in which the velocity field itself is actively involved via its characteristic time. A direct relationship between velocity and scalar spectra and therefore between mu and mθ is thus established.
Impact of in-vivo Low-Level Laser therapy combined with Rabbit Bone Marrow Mesenchymal Stem Cells to promote Bone Regeneration. Morphological and Gene Expression Assessments.

Background: Regenerative procedures are intended to restore both function and architecture of the destroyed periodontal tissue. Bone marrow mesenchymal stem cells (BMMSCs) showed high efficacy in the potentiation of bone regeneration. Additionally, Low-level laser therapy (LLLT) enhances tissue repair. Purpose: This study aims to compare the regenerative impact via LLLT, BMMSCs in chitosan carrier gel either alone or in combination of both treatments on rabbit femoral bony defects. Materials and Methods: 12 New Zealand albino rabbits were enrolled in the study. Two holes were drilled in each femur of all rabbits. The rabbit population was divided into 4 groups. Group A injected with chitosan carrier gel; Group B was injected with Rabbit-BMMSCs in chitosan; Group C where LLLT (diode laser, 980 nm, 0.3 W, continuous mode, and 250 mW) was applied on each hole loaded with chitosan carrier gel. Finally, Group D received both treatments in group B and C. Rabbits were sacrificed after 8 weeks. Morphological and genetic assessments were performed. All data were statistically analyzed. Results: Best bone healing results were seen in the combined group of LLLT with BMMSCs followed by the BMMSCs group alone. LLLT group showed inferior healing to the BMMSCs group but still better than the control group. These findings were confirmed by RT-PCR which revealed the highest OC and ALP and lowest OPG in the combination group followed by BMMSCs, LLLT, and control groups in descending order. Conclusion : The combination of LLLT application to the BMMSCs transplanted in the rabbit femur defects provided the greatest bone regeneration results.
Tunable dielectric BIC metasurface for high resolution optical filters

The dielectric metasurface has become a powerful tool for compact optical components with various wavefront controlling functionalities accompanied by negligible losses at the corresponding working frequencies. In this work, we propose a tunable all-dielectric metasurface as an optical filter with high resolution covering different optical communication bands, where tunability is realized by a combination of changing the incident angle and modulating the refractive index of an optical phase changing material (OPCM). When the incident angle varies, our optical filter based on a two-dimensional bound state in continuums (BIC) metasurface can achieve sequential, extremely sharp resonances. In addition, the resonance peaks could be further shifted to a different frequency band by the refractive index change of OPCM via pulsed laser heating. The proposed scheme can offer optical filters with high spectral resolution and large tunable working wavelength range, which greatly benefits from the topological property of BIC and large modulation depth of OPCM.
Convex Polyhedra with Regular Faces

An interesting set of geometric figures is composed of the convex polyhedra in Euclidean 3-space whose faces are regular polygons (not necessarily all of the same kind). A polyhedron with regular faces is uniform if it has symmetry operations taking a given vertex into each of the other vertices in turn (5, p. 402). If in addition all the faces are alike, the polyhedron is regular. That there are just five convex regular polyhedra—the so-called Platonic solids—was proved by Euclid in the thirteenth book of the Elements (10, pp. 467-509). Archimedes is supposed to have described thirteen other uniform, “semi-regular” polyhedra, but his work on the subject has been lost.
Growth of Fe doped semi-insulating GaN by metalorganic chemical vapor deposition

Iron doped GaN layers were grown by metalorganic chemical vapor deposition (MOCVD) using ferrocene as the Fe precursor. Specular films with concentrations up to 1.7×1019 cm−3, as determined by secondary ion mass spectrometry, were grown. The Fe concentration in the film showed a linear dependence on the precursor partial pressure, and was insensitive to growth temperature, pressure, and ammonia partial pressure. Memory effects were observed, similar to Mg doping of GaN by MOCVD. The deep acceptor nature of Fe was used for growth of semi-insulating GaN films on sapphire substrates. A 2.6-μm-thick GaN film with a resistivity of 7×109 Ω/sq was attained when the first 0.3 μm of the film was Fe doped. X-ray diffraction rocking curves indicated high crystalline quality, very similar to an undoped film, showing that Fe doping did not affect the structural properties of the film. Fe doping allows for growth of semi-insulating GaN on sapphire without the high threading dislocation densities and/or high carbon leve.
Highly Uniform 1.5 µm Wavelength Deeply Etched Semiconductor/Benzocyclobutene Distributed Bragg Reflector Lasers

The lasing performance of deeply etched distributed Bragg reflector (DBR) lasers was improved to a threshold current as low as 7.2 mA and a differential quantum efficiency as high as 50% with high uniformity. The reflectivity of the 15-DBR reflector was estimated to be as high as 95% from the threshold current dependence on the active region length. A preliminary test under room-temperature CW operation showed stable operation for a duration in excess of 4000 hours.
Multi-Exposure Image Compression Considering Rate-Distortion Optimization in Rendered High Dynamic Range Image

High-dynamic range (HDR) images,which provide realistic visual perception, have attracted considerable attention in various applications. A simple method for obtaining HDR images is to fuse multiple low-dynamic range (LDR) images captured under varying exposures. We proposed a method of efficiently encoding multi-exposure images using multi-view High Efficiency Video Coding (MV-HEVC) along with intensity mapping function (IMF) to create high-quality HDR images. The inter-view prediction in MV-HEVC eliminates redundancy between multi-exposure images. To achieve high-efficiency MV-HEVC-based multi-exposure image coding, two modifications to the rate-distortion optimization (RDO) process performed during encoding were proposed. First, the distortion in the rendered HDR image is used to replace the original distortion, which depends on the LDR image. Second, to balance distortion and rate in RDO, a new Lagrange multiplier is derived from the derivative of the new distortion with respect to the rate. A model of the distortion in the HDR domain was constructed and expressed as a function of the distortion in the LDR domain. The proposed scheme utilizes the conventional 8-bit codec to compress multi-exposure LDR images and generate an HDR image in the decoder. The experimental results indicate that the proposed technique outperforms HDR image coding schemes in which HEVC Range Extension and JPEG-XT coding standards are used.
Control for Nonlinear Fuzzy Time-Delay Multiagent Systems: Two Kinds of Distributed Saturation-Constraint Impulsive Approach

The impulsive consensus problems of nonlinear time-delay multiagent system under communication constraints are analyzed and investigated in this article. In view of the limited communication channel, global input saturation constraint is integrated into the design of impulse control protocol. Furthermore, in order to reduce energy consumption and communication cost, two kinds of impulsive control protocols are designed that conclude general impulsive control protocols and event-triggered impulsive control protocols. For event-triggered impulsive control protocols, by setting event decision time at impulse time, this novel consensus control protocols not only decrease communication frequency and energy consumption but also avoid “Zeno behavior. ” Through theoretical derivation, some sufficient conditions that guarantee the leader-following consensus of multiagent system are presented. In the end, for the sake of explaining the superiority of impulse control combined with event-triggered control strategy in more detail, the simulations of two control methods are given, respectively, for the same multiagent system, which can be better compared and explained.
The maximum principle for an optimal solution to a differential inclusion with end points constraints

We derive Pontryagin’s maximum principle for a general optimal control problem using the set-valued version of variational equation. We achieve this aim by exploiting an adequate differential calculus of set-valued maps. Furthermore, the calmness condition is replaced by a surjectivity condition involving reachable sets of the “set-valued linearization” of the initial control problem. Duality then provides both the “adjoint differential inclusion” and the maximum principle.
ASCA Observations of Type 2 Seyfert Galaxies. I. Data Analysis Results

We present ASCA spatial, temporal, and spectral data for a sample of 26 observations of 25 type 2 active galactic nuclei (AGNs), composed of 17 Seyfert 2 galaxies and eight narrow emission line galaxies (NELGs). Twenty-four of the 25 sources were detected. The ASCA images are generally consistent with emission from point sources at energies above ~3 keV. We use archival ROSAT data to examine each field at high spatial resolution and to check for the presence of sources that would contaminate the ASCA data. Of the five sources bright enough for 128 s temporal analysis, three are variable at >99% confidence, with characteristics consistent with those observed in Seyfert 1 galaxies. Analysis on a timescale of 5760 s reveals six sources variable at >99% confidence, and comparison with previous X-ray results shows most of the sample to be variable in hard X-ray flux on timescales of years. Simple continuum models are fitted to the sample spectra to characterize the variety of spectral forms and hence to determine the fundamental nature of the X-ray spectrum of each source. No single spectral model provides an adequate fit to all the sample sources. Thirty-six percent of the sample cannot be adequately fitted by any of our test models (all rejected at >95% confidence). Approximately half of the sample have an iron Kα line with an equivalent width consistent with an origin in the line-of-sight absorber; the remaining lines must be produced in material out of the line of sight. Absorbing columns up to 1024 atoms cm-2 are detected, and even larger columns are inferred for some sources. The mean underlying hard X-ray power-law index is Γ ~ 2. Many X-ray emission lines were detected at high levels of confidence. The iron K-shell regime is dominated by emission from "neutral" material. Many data sets also show evidence for complexity in the iron Kα profile, which may be interpreted as evidence for broad-line profiles, including flux both redward and blueward of the line peak, and/or for the existence of hydrogen-like and helium-like iron K lines. Hydrogen-like and helium-like lines are detected from Fe, Ne, Si, S, and Ar in addition to Mg lines. While almost half of the sample have an estimated starburst contribution of >30% in the 0.5-4.5 keV bandpass, the soft X-ray emission lines are not solely associated with a strong starburst component.
Heavy ion radiation damage simulations for CMOS image sensors

Damage in CMOS image sensors caused by heavy ions with moderate energy (~10MeV) are discussed through the effects on transistors and photodiodes. SRIM (stopping and range of ions in matter) simulation results of heavy ion radiation damage to CMOS image sensors implemented with standard 0.35μm and 0.18μm technologies are presented. Total ionizing dose, displacement damage and single event damage are described in the context of the simulation. It is shown that heavy ions with an energy in the order of 10 MeV cause significant total ionizing dose and displacement damage around the active region in 0.35μm technology, but reduced effects in 0.18μm technology. The peak of displacement damage moves into the substrate with increasing ion energy. The effect of layer structure in the 0.18 and 0.35 micron technologies on heavy ion damage is also described.
Predicting Six-Month Re-Admission Risk in Heart Failure Patients Using Multiple Machine Learning Methods: A Study Based on the Chinese Heart Failure Population Database

Since most patients with heart failure are re-admitted to the hospital, accurately identifying the risk of re-admission of patients with heart failure is important for clinical decision making and management. This study plans to develop an interpretable predictive model based on a Chinese population for predicting six-month re-admission rates in heart failure patients. Research data were obtained from the PhysioNet portal. To ensure robustness, we used three approaches for variable selection. Six different machine learning models were estimated based on selected variables. The ROC curve, prediction accuracy, sensitivity, and specificity were used to evaluate the performance of the established models. In addition, we visualized the optimized model with a nomogram. In all, 2002 patients with heart failure were included in this study. Of these, 773 patients experienced re-admission and a six-month re-admission incidence of 38.61%. Based on evaluation metrics, the logistic regression model performed best in the validation cohort, with an AUC of 0.634 (95%CI: 0.599–0.646) and an accuracy of 0.652. A nomogram was also generated. The established prediction model has good discrimination ability in predicting. Our findings are helpful and could provide useful information for the allocation of healthcare resources and for improving the quality of survival of heart failure patients.
Time series forecasting with SOM and local non-linear models - Application to the DAX30 index prediction

A general method for time series forecasting is presented. Based on the splitting of the past dynamics into clusters, local models are built to capture the possible evolution of the series given the last known values. A probabilistic model is used to combine the local predictions. The method can be applied to any time series prediction problem, but is particularly suited to data showing non-linear dependencies and cluster effects, as many financial series do. The method is applied to the prediction of the returns of the DAX30 index.
Relaxed Incomplete Cholesky Factorization Preconditioned Symmetric LBCG Algorithm for Solving Electromagnetic Problems

The symmetric linear biconjugate gradient (S-LBCG) iterative algorithm combined with modified relaxed incomplete Cholesky (RIC) preconditioner is proposed for solving large sparse complex symmetric and highly indefinite systems, which results from the use of edge-based finite-element method (FEM) on the analysis of electromagnetic problems. The S-LBCG iterative algorithm is derived from the linear biconjugate gradient iterative algorithm. It contains only one matrix-vector product per iteration for solving complex sparse symmetric systems. The preconditioner is derived from the relaxed incomplete Cholesky factorization with diagonal compensation. More robust and efficient RIC preconditioner can be achieved by employing preprocessing scheme of scaling and reordering before the incomplete factorization. Numerical tests on analysis of time-harmonic electromagnetic field problems show that this RIC preconditioned S-LBCG algorithm performs excellently both on reducing the memory requirement and on convergence rate.
From monitoring data to regional distributions: a practical methodology applied to water risk assessment

During the last decade, the assessment of concentration levels of chemical substances in the environment has become a major issue for defining actual exposure in risk evaluation processes. Currently, different approaches are proposed to achieve this assessment. The first one, widely used, relies on multi‐media fate models. On the other hand, monitoring data begin also to be used for this purpose but, up to now, few statistical methods have been proposed to validate and summarize them adequately at a local or regional level. A crucial characteristic of monitoring data is that many observations stay below the detection limits of the measurement devices and therefore the data are highly censored.
A Classification Method for Ranking and Selection with Covariates

Ranking & selection (R&S) procedures are simulation-optimization algorithms for making one-time decisions among a finite set of alternative system designs or feasible solutions with a statistical assurance of a good selection. R&S with covariates (R&S+C) extends the paradigm to allow the optimal selection to depend on contextual information that is obtained just prior to the need for a decision. The dominant approach for solving such problems is to employ offline simulation to create metamodels that predict the performance of each system or feasible solution as a function of the covariate. This paper introduces a fundamentally different approach that solves individual R&S problems offline for various values of the covariate, and then treats the real-time decision as a classification problem: given the covariate information, which system is a good solution? Our approach exploits the availability of efficient R&S procedures, requires milder assumptions than the metamodeling paradigm to provide strong guarantees, and can be more efficient.