Miracle-dz/UniFAR-FTUs huggingface dataset:
Using TEC and radio scintillation data from the CITRIS radio beacon receiver to study low and midlatitude ionospheric irregularities

Unique data on ionospheric plasma irregularities from the Naval Research Laboratory Scintillation and TEC Receiver in Space (CITRIS) instrument is presented. CITRIS is a multiband receiver that recorded Total Electron Content (TEC) and radio scintillations from Low‐Earth Orbit (LEO) on STPSat1. The 555 ± 5 km altitude 35° inclination orbit covers low and midlatitudes. The measurements require propagation from a transmitter to a receiver through the F region plasma. CITRIS used both 1) satellite beacons in LEO and 2) the French sponsored global network of ground‐based Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) beacons. This paper is both a brief review of the CITRIS experiment and the first combined TEC and scintillation study of ionospheric irregularities using a satellite‐borne beacon receiver. It primarily focuses on CITRIS/DORIS observations and is a case study of the ionospheric irregularities and associated scintillation characteristics at 401.25 MHz during the 2008 equinox solar minimum. In addition, CITRIS was operated in a complementary fashion with the Communication/Navigations Outages Forecasting System (C/NOFS) satellite during C/NOFS' first year of operations and comparison with measured C/NOFS irregularity characteristics are made. Several types of irregularities have been studied including Spread–F and the newly discovered dawn‐side depletions.
Electrical failure in blends of chemically identical, soft thermoplastic elastomers with different elastic stiffness

Investigations on the effect of stiffness on breakdown strength in polymer materials are typically performed indirectly by variation of temperature. Here, the stiffness is varied directly using blends of chemically identical, physically crosslinking elastomers, thus avoiding possible temperature-induced variations in electric and ionic conductivity. Avoiding a chemically crosslinking system rules out variations due to crosslinkers or initiators. Measurements were carried out with a hemispherical indenter resting on a slab of the material with constant load. A theory recently proposed by Zhao and Suo was adapted to the experimental conditions and found to apply well, with no free fitting parameters.
FPChecker: Floating-Point Exception Detection Tool and Benchmark for Parallel and Distributed HPC

Floating-point arithmetic is fundamental to many areas including high-performance computing and machine learning. In order to ensure the numerical integrity of the overall computation, numerical exceptions (such as NaNs) must be detected and suitably reported to the user. Unfortunately, today’s best available methods and tools are not general-enough. Moreover, there are no comprehensive benchmarks today that can be compiled to intermediate representations such as LLVM and analyzed at that level. In this paper, we contribute the first such benchmark suite that spans five HPC proxy applications plus eight public benchmarks that run on CPU multicores under MPI, OpenMP, and performance portability layers. We also release our tool (also called LLFPX) that is up to 7.9× faster on many important benchmarks and overall more comprehensive with respect to exception variety coverage. This paper presents the tool, its design, and evaluation on our benchmarks, with the tool, benchmarks, and a facility to examine results on the web available for public use upon acceptance. Other result highlights include the effect of compiler optimizations on exceptions.
BaggedUNet: Deep Machine Vision approach for Polyps Segmentation in Gastrointestinal Tract

Polyps segmentation is one of the key medical challenges in the gastrointestinal (GI) tract. Polyps segmentation provides the early-stage diagnosis of polyps which may lead to colon cancer in the GI tract. Deep learning models such as U-Net can segment polyps with good performance. But individual deep learning models may suffer from generalization problems. Deep ensemble learning combines the power of both deep and ensemble learning so that the final combined model has better generalization ability. In this paper, a bagging based U-Net architecture (BaggedUNet) is proposed to improve the polyps segmentation in GI-Tract. Our proposed BaggedUNet model trains several lighter U-Net architectures. Decisions from various models are then combined using majority voting. The proposed method is compared with recent deep learning architectures: U-Net and ResUNet++. The evaluation of models is performed using quantitative metrics including Dice coefficient and mean Intersection over Union (mIoU). The proposed BaggedUNet architecture was able to achieve 3 %-9 % improvement on different evaluation metrics on two publicly available datasets for polyps segmentation.
A study on the mixed convection boundary layer flow and heat transfer over a vertical slender cylinder

In this investigation, the series solutions of mixed convection boundary layer flow over a vertical permeable cylinder are constructed. Two types of series as well numerical solutions are presented by choosing exponential and rational bases. The resulting differential system are solved by employing homotopy analysis method and Pade technique which have been proven to be successful in tackling non-linear problems. We offer various verifications of the solutions by comparing to existing, documented results and also mathematically, through reduction of sundry parameters. The convergence of the series solutions have been discussed explicitly. Comparison with existing results reveal that the series solutions are not only valid for large (aiding flow) but also for small values (opposing flow) of l and the dual solutions do not obtain in both cases.
Separable non-linear least-squares minimization-possible improvements for neural net fitting

Neural network minimization problems are often ill-conditioned and in this contribution two ways to handle this will be discussed. It is shown that a better conditioned minimization problem can be obtained if the problem is separated with respect to the linear parameters. This will increase the convergence speed of the minimization. The Levenberg-Marquardt minimization method is often concluded to perform better than the Gauss-Newton and the steepest descent methods on neural network minimization problems. The reason for this is investigated and it is shown that the Levenberg-Marquardt method divides the parameters into two subsets. For one subset the convergence is almost quadratic like that of the Gauss-Newton method, and on the other subset the parameters do hardly converge at all. In this way a fast convergence among the important parameters is obtained.
The Extragalactic Distance Scale Key Project. XVI. Cepheid Variables in an Inner Field of M101

We report on the identification of 255 candidate variable stars in a field located some 1. ′7 from the center of the late-type spiral galaxy M101 = NGC 5457, based on observations made with the Wide Field and Planetary Camera 2 on board the Hubble Space Telescope. Photometric measurements in the F555W and F814W filters—analyzed independently with the DAOPHOT/ALLFRAME and DoPHOT software suites—have been transformed to the Johnson V and Kron-Cousins I standard magnitude systems. Periods and intensity-averaged mean magnitudes for 61 carefully selected candidate Cepheid variables with periods in the range 10-48 days indicate a reddening-corrected mean distance modulus (m - M)0 = 29.05 ± 0.14 (if the true modulus of the Large Magellanic Cloud is 18.50 ± 0.10, and if there is no dependence of the period-luminosity relation on metal abundance); results consistent with this are obtained whether or not the sample is expanded to include a larger fraction of the candidates. Applying a metallicity-dependent correction of +0.16 ± 0.10 mag would increase this estimate to (m - M)0 = 29.21 ± 0.17 mag.
MTFed-NILM: Multi-Task Federated Learning for Non-Intrusive Load Monitoring

Non-intrusive Load Monitoring (NILM) models aim to decompose the reading of mains to identify energy demands and behaviours of the individual appliance for better energy efficiency. The mutual information between appliances is conducive to a better load disaggregation when such information is adequately integrated into NILM models. Using real data to construct deep neural networks (DNN) as NILM models also raises concerns about privacy leakage. This paper proposes a multi-task federated learning algorithm (MTFed-NILM) to estimate energy consumption and identify the operational states of appliances from the mains by exploiting the dependencies among multiple tasks while preserving the users’ privacy. Our approach uses U-Net to properly extract shared features and identify different usage patterns for appliances across households. A comprehensive evaluation indicates that MTFed-NILM is capable of achieving multiple objectives while showing promising performance. Our results also reveal the preferable hyper-parameters used in the MTFed-NILM model to produce better results.
Vibrations of cylindrical shells with intermediate supports

This paper is concerned with the free vibrations of circular cylindrical shells with rigid intermediate supports. The simplest form of thin shell theory according to Donnell and the reputed best first order approximation theory of Sanders are considered. An automated Rayleigh-Ritz method is adopted to evaluate the natural frequencies and the mode shapes of the structures. A proposed unified set of Ritz functions is used to span the displacement fields of various types and combinations of end boundary conditions. Comparison and convergence studies are carried out to verify and establish the appropriate number of Ritz functions to produce results with an acceptable order of accuracy. Shells with any number of intermediate supports and any combination of end boundary conditions can be analyzed by the proposed method. Effects of intermediate supports and their locations on natural frequencies of the shells are studied and the results presented for easy access by design engineers.
Lack of Iron Abundance Evolution in High-Redshift QSOs

We analyze the spectra of 12 high-redshift QSOs in the region of Mg II λ2798. Two six-spectrum composites, with ⟨z⟩=4.47 and 3.35, are compared with the Francis et al. Large Bright Quasar Survey (LBQS) composite (⟨z⟩~0.8) and show remarkable similarity. The equivalent width of Mg II is somewhat larger in the LBQS composite than in the high-redshift composites; this may be identified as a weak Baldwin effect. The equivalent width of the Fe II blends to either side is the same in the ⟨z⟩=3.35 composite as in the LBQS composite and marginally larger in the ⟨z⟩=4.47 composite. We derive strong confidence limits on the absence of a significant increase in either the Fe II equivalent width or the Fe II/Mg II line ratio from the earliest epoch to the present. Hamann & Ferland predicted that the Fe II/Mg II ratio at high redshift should be a factor of ~3 lower than for low-redshift QSOs if the age of the universe at the earlier epoch is much less than 1 Gyr. This is due to the delayed contribution of supernovae type Ia to the iron abundance. A 1 Gyr minimum age of the universe at z=4.47 gives interesting upper limits to q0 for a given H0 (e.g., q0<0.20 for H0=75 km s-1 Mpc-1). The lack of change in Fe II/Mg II between the two high-redshift epochs indicates that 1 Gyr may be an underestimate of the universe age at z=4.47. We also discuss alternate explanations. The abundance evolution in the central regions of galaxies that host QSOs may follow a significantly different path to that in the solar neighborhood, perhaps from the dominance of short-lived type Ia supernovae progenitors or through the lack of any significant type Ia contribution, in which case we are yet underestimating the efficiency of Fe+ ions in QSO broad-line clouds for production of the observed Fe II. Cosmologies with terms beyond zero-pressure matter are also briefly discussed. These considerations notwithstanding, the lack of observed Fe II evolution at high redshifts puts unique constraints on luminous QSO broad-line physics, nucleosynthesis in the QSO host galaxies, and/or cosmological parameters.
Effects of High Pass and Low Pass Filtering on the Intelligibility of Speech in Noise

The effect on intelligibility of eliminating either the high frequency speech sounds or the low frequency speech sounds was determined by standardized articulation testing procedures under the special circumstance of a background of white masking noise. In general, it was found that intelligibility increased as the frequency range and the intensity level of the speech signal were increased. Contours are presented which describe the interrelations among (1) the frequency range of the speech signal, (2) the intensity level of the speech signal, and (3) articulation efficiency.For each of the experimental conditions, the articulation index—a measure developed by the Bell Telephone Laboratories—was computed. It was found that the scatter of the computed indices, when plotted against the scores actually obtained, was of the same order of magnitude as the intrinsic variability of typical articulation scores. This result indicates that the computational procedures are an acceptable substitute for time‐consuming .
Velocity angular distribution of ground level atomic silicon in the plume of laser ablated silica

Polished silica (synthetic SiO2 glass) samples were ablated to vacuum by 266 nm laser pulses at a flounce of 110 J/cm2. The concentration of ground level atomic silicon in the plume was measured as a function of time, by laser-induced fluorescence (LIF), at distances of 5–7 mm from the ablated point. The angular velocity distribution was found to be highly asymmetric with respect to surface normal, as the LIF signal dropped abruptly at angles approaching the laser direction. The symmetric morphology of the craters that were formed by ablation indicates that the above asymmetry is not likely to be attributed to the interaction of the laser or the ablated plume with the surface. Therefore, it is suggested that the silicon atoms, ejected in the direction of the incident laser beam, were preferentially ionized via a multiphoton off-resonance absorption process. The velocity of the silicon atoms was detected in the 1–13 km/s range. Since the velocity distribution for a thermal ablation process is expected to e.
Performance Mapping of InP QDs Passively Monolithic ModeLocked Lasers

We propose a novel semi-empirical approach for mapping the performance of InP quantum dots passively monolithic two-section mode-locked lasers (MLLs). A prediction of the mode-locking regimes for varying reverse-bias conditions and saturable absorber to gain section length ratios has been determined for 3mm InP MLLs.
Periodic Flap Control of a Helicopter Blade in Forward Flight

The primary objective of this paper is to present new periodic control strategies for the control of flapping motion of an individual helicopter rotor blade in forward flight, which is represented by a differential equation with periodic coefficients. First, an algebraic procedure based on Chebyshev polynomial expansion is employed to control the periodic flapping motion. In this approach, the state vector and the elements of the periodic system matrix have been expanded in terms of shifted Chebyshev polynomials of the first kind over the principal period. Later, optimal control theory in conjunction with Floquet theory has been used to design full-state and observer-state feedback controllers. In the second method, the feedback controllers have been designed in the time-invariant domain through the application of a linear, invertible, periodic transformation known as Liapunov-Floquet (L-F) transformation to the periodic system model. It is shown that by using both methods the periodic control gains can be obtained as explicit functions of time and, therefore, a control scheme more suitable for real-time implementation can be achieved. The design procedures have been found to be much simpler in character when compared to those techniques that have appeared in the literature.
Spectrum of periodic elliptic operators with distant perturbations in space

A periodic selfadjoint differential operator of even order and with distant perturbations in a multidimensional space is treated. The role of perturbations is played by arbitrary localized operators. The localization is described by specially chosen weight functions. The behavior of the spectrum of the perturbed operator is studied under the condition that the distance between the domains where the perturbation are localized tends to infinity. It is shown that there exists a simple isolated eigenvalue of the perturbed operator that tends to a simple isolated eigenvalue of the limit operator. Series expansions are obtained for this eigenvalue of the perturbed operator and for the corresponding eigenfunction. Uniform convergence for these series is shown and formulas for their terms are deduced. §
Short-term Power Load Forecasting Based on Temporal Convolutional Network

For the problem of short-term power load forecasting, a numerical algorithm is presented based on Temporal Convolutional Network (TCN) and XGBoost. Firstly, correlations between load and influencing factors are analyzed so as to extract important features by XGBoost. Secondly, residual blocks in TCN mainly deal with gradient disappearance or explosion for the long time series. Combined with attention mechanism, important feature vectors may be benefit to advance the accuracy of forecasting results. Short-term power load forecasting is carried out with multiple scales by two groups of public data. Compared with TCN, Gate Recurrent Unit (GRU) and Long Short-Term Memory (LSTM), the presented algorithm needs less time when high-frequency or high-dimensional data appears.
The impact of uncertainty on shape optimization of idealized bypass graft models in unsteady flow

It is well known that the fluid mechanics of bypass grafts impacts biomechanical responses and is linked to intimal thickening and plaque deposition on the vessel wall. In spite of this, quantitative information about the fluid mechanics is not currently incorporated into surgical planning and bypass graft design. In this work, we use a derivative-free optimization technique for performing systematic design of bypass grafts. The optimization method is coupled to a three-dimensional pulsatile Navier–Stokes solver. We systematically account for inevitable uncertainties that arise in cardiovascular simulations, owing to noise in medical image data, variable physiologic conditions, and surgical implementation. Uncertainties in the simulation input parameters as well as shape design variables are accounted for using the adaptive stochastic collocation technique. The derivative-free optimization framework is coupled with a stochastic response surface technique to make the problem computationally tractable. Two .
Performance Analysis of Cooperative NOMA Systems in Cognitive Radio Network

In the existing underlay cognitive radio literature, the outage performance of the secondary network is severely degraded due to the interference from the primary network and the interference threshold limit of the primary receiver to the secondary transmit power. In this paper, a cooperative Non-orthogonal multiple access (NOMA) based cognitive radio network is proposed, where multiple half-duplex (HD) relays are employed to extend the coverage area of the network. This proposed scheme allows the secondary transmitter (ST) to access the licensed spectrum but not while primary transmitter (PT) is transmitting. Hence, the secondary network can eliminate the PT interference at the relay node, which improves the outage performance of the secondary network. In addition, the closed-form expression for outage probability and ergodic rate for both primary and secondary network are derived. Through numerical results, it is shown that the performance of the secondary network is improved significantly. Furthermore, Monte Carlo simulation results are presented to validate the derived mathematical framework.
Internal waves, turbulence and mixing in stratified flows: a report on Euromech Colloquium 339

Euromech colloquium 339 was organized by C. Staquet in Lyon (France) from September 6 to 9, 1995. It involved seventy-six participants from fourteen countries. Papers were presented on various aspects of stably stratified flows: (i) internal waves, their generation mechanisms, propagation and reflection properties, their instabilities leading to breaking; (ii) vortex structures in stably stratified fluids, which can be slow layerwise structures, or small intense vortices, appearing for instance in shear flow instabilities; (iii) statistical properties of random wave fields or stratified turbulence; (iv) mixing properties resulting from internal wave fields and stratified turbulence. These quite different dynamical regimes are often closely connected in actual flow problems, and one purpose of this colloquium was to better understand these connections. Participants were interested in fundamental aspects or in more specific applications, in engineering, geophysics and astrophysics. The colloquium was a rare opportunity to gather together scientists with these different points of view, to compare approaches and results, and to highlight general problems.
Recruitment of the cardiac conduction system for optimal resynchronization therapy in failing heart

Heart failure (HF) is a leading health burden around the world. Although pharmacological development has dramatically advanced medication therapy in the field, hemodynamic disorders or mechanical desynchrony deteriorated by intra or interventricular conduction abnormalities remains a critical target beyond the scope of pharmacotherapy. In the past 2 decades, nonpharmacologic treatment for heart failure, such as cardiac resynchronization therapy (CRT) via biventricular pacing (BVP), has been playing an important role in improving the prognosis of heart failure. However, the response rate of BVP-CRT is variable, leaving one-third of patients not benefiting from the therapy as expected. Considering the non-physiological activation pattern of BVP-CRT, more efforts have been made to optimize resynchronization. The most extensively investigated approach is by stimulating the native conduction system, e.g., His-Purkinje conduction system pacing (CSP), including His bundle pacing (HBP) and left bundle branch area pacing (LBBAP). These emerging CRT approaches provide an alternative to traditional BVP-CRT, with multiple proof-of-concept studies indicating the safety and efficacy of its utilization in dyssynchronous heart failure. In this review, we summarize the mechanisms of dyssynchronous HF mediated by conduction disturbance, the rationale and acute effect of CSP for CRT, the recent advancement in clinical research, and possible future directions of CSP. Graphical Abstract Emerging strategies for cardiac resynchronization for dyssynchronous heart failure.