Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental study of vortex ring impingement on concave hemispherical cavities

Abstract Discrete vortex rings impinging on concave hemispherical cavities were explored experimentally. Planar laser-induced fluorescence, two-dimensional particle image velocimetry and flow visualization techniques were employed. Five different ratios of vortex ring to hemisphere cavity radius ($\gamma$) were investigated, namely, $\gamma = 1/4,1/3,2/5,$$1/2, 2/3$. For $\gamma = 1/4,1/3, 2/5$, the geometric confinement of the primary ring due to the hemispherical cavity induced loop-like instabilities in the secondary ring, which led to head-on collision and ejection of the looped ends as they orbited the primary ring. As the hemispherical cavity decreased in diameter (increasing $\gamma$), the dynamics were altered significantly due to the increased generation of vorticity along the edge of the hemisphere. For $\gamma = 1/2$, vorticity produced at the edge/lip of the hemisphere ultimately disrupted the classical formation of a secondary vortex ring from the wall-bounded vorticity. For $\gamma = 2/3$, the primary ring and hemisphere radius were close enough in size that the interaction was dominated by direct impact of the primary ring with the lip of the cavity. The primary vortex ring produced a vortex ring at the lip of the hemisphere that ultimately separated from the cavity, orbited around the primary ring, and then self-advected in the direction opposite to the primary vortex ring trajectory. A detailed investigation of the dynamics provided.
Surface-Based Microwave Humidity Retrievals over the Equatorial Indian Ocean: Applications and Challenges

The interactions between equatorial convection and humidity as a function of height, at a range of time scales, remain an important research frontier. The ability of surface-based microwave radiometry to contribute to such research is assessed using retrievals of the vertical structure of atmospheric humidity above the equatorial Indian Ocean, developed as part of the Dynamics of Madden–Julian Oscillation field campaign. The optimally estimated humidity retrievals are based on radiances at five frequencies spanning 20–30 GHz and are constrained by radiometer-derived water vapor paths that compare well to radiosonde values except in highly convective conditions. The moisture retrievals possess a robust 2 degrees of freedom, allowing the atmosphere to be treated as two independent layers. A mean bias of 1 g kg−1 contains a vertical structure that is removed in the assessments. The retrieved moisture profiles are able to capture humidity variability within two layer averages at intraseasonal, synoptic, and daily time scales. The retrieved humidity profiles at hourly scales are qualitatively correct under synoptically suppressed conditions but with an exaggerated vertical bimodality. The retrievals do not match radiosonde profiles within most of the day prior to/after convection. This analysis serves to better delineate applications for radiometers. Radiometers can usefully augment more expensive radiosonde networks for longer-term monitoring given careful cross-instrument calibration. At shorter time scales, a synergism with additional instruments can likely increase the realism of the retrievals.
Reduced complexity blind unitary prewhitening with application to blind source separation

Eigenvalue decomposition (EVD) of the sample data covariance matrix is, typically, used for calculating the whitening matrix and prewhitening the noisy signals. An important problem here is to reduce the computational complexity of the EVD of the complex-valued sample data covariance matrix. In this paper, we show that the complexity of the prewhitening step for complex-valued signals can be reduced approximately by a factor of four when the real-valued EVD is used instead of the complex-valued. Such complexity reduction can be achieved for any axis-symmetric array. For such class of arrays it enables real-time implementation of the prewhitening step for complex-valued signals. The performance of the proposed procedure is shown in application to a blind source separation (BSS) problem
Portfolio procurement policies for budget-constrained supply chains with option contracts and external financing

This study investigates a budget-constrained retailer's optimal financing and portfolio order policies in a supply chain with option contracts. To this end, we develop two analytical models: a basic model with wholesale price contracts as the benchmark and a model with option contracts. Each model considers both the financing scenario and the no-financing scenario. Our analyses show that the retailer uses wholesale price contracts for procurement, instead of option contracts, when its budget is extremely tight. The retailer starts to use a combination of these two types of contracts when the budget constraint is relieved. As the budget increases, the retailer adjusts the procurement ratio through both types until it can implement the optimal ordering policy with an adequate budget. In addition, the condition for seeking external financing is determined by the retailer's initial budget, financing cost, and profit margin.
Non-commutative homometric musical structures and chord distances in geometric pitch spaces

Nous etudions deux thematiques principales : l'homometrie non-commutative dans des produits semi-directs, et une notion de distance entre accords musicaux. deux melodies sont dites homometriques si elles possedent le meme ensemble d'intervalles : nous transposons cette notion a un enchainement d'accords et plus generalement a des produits semi-directs, ce qui permet d'elaborer un cadre pour l'etude de l'homometrie dans des groupes non-commutatifs, tels que le groupe diedral. nous definissons dans une deuxieme partie une mesure de distances entre des accord musicaux n'ayant pas le meme nombre de notes, a partir d'une distance basee sur le concept de voice-leading.
Quasi-synchronisation of fractional-order memristor-based neural networks with parameter mismatches

This study addresses the problem of quasi-synchronisation of fractional-order memristor-based neural networks (FMNNs) with time delay in the presence of parameter mismatches. Under the framework of fractional-order differential inclusions and set-valued maps, quasi-synchronisation of delayed FMNNs is discussed and quasi-synchronisation criteria are established by means of constructing suitable Lyapunov function, together with introducing some fractional-order differential inequalities. A new lemma on the estimate of Mittag–Leffler function is derived first, which extends the application of Mittag–Leffler function and plays a key role in the estimate of synchronisation error bound. Then, linear state feedback combined with delayed state feedback control law is designed, which guarantees that for a predetermined synchronisation error bound, quasi-synchronisation of two FMNNs with mismatched parameters will be achieved provided that the feedback gains satisfy the newly-proposed criteria. The obtained results extend and improve some previous published works on synchronisation of FMNNs. Finally, two numerical examples are given to demonstrate the effectiveness of the obtained results.
Shear Layer Development, Separation, and Stability Over a Low-Reynolds Number Airfoil

The authors gratefully acknowledge the support of the Natural Sciences and Engineering Research Council (NSERC), the Southern Ontario Smart Computing Innovation Platform (SOSCIP), and the Ontario Graduate Scholarship (OGS) program. Computations were performed on the GPC and BGQ supercomputers at the SciNet HPC Consortium, which includes support from the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund—Research Excellence; and the University of Toronto. SOSCIP is funded by the Federal Economic Development Agency of Southern Ontario, IBM Canada Ltd., Ontario Centres of Excellence, Mitacs and 14 academic member institutions.
Mathematical analysis of cardiac electromechanics with physiological ionic model

This paper is concerned with the mathematical analysis of a coupled elliptic-parabolic system modeling the interaction between the propagation of electric potential coupled with general physiological ionic models and subsequent deformation of the cardiac tissue. A prototype system belonging to this class is provided by the electromechanical bidomain model, which is frequently used to study and simulate electrophysiological waves in cardiac tissue. The coupling between muscle contraction, biochemical reactions and electric activity is introduced with a so-called active strain decomposition framework, where the material gradient of deformation is split into an active (electrophysiology-dependent) part and an elastic (passive) one. We prove existence of weak solutions to the underlying coupled electromechanical bidomain model under the assumption of linearized elastic behavior and a truncation of the updated nonlinear diffu-sivities. The proof of the existence result, which constitutes the main thrust of this paper, is proved by means of a non-degenerate approximation system, the Faedo-Galerkin method, and the compactness method.
Steady detonation propagation in a circular arc: a Detonation Shock Dynamics model

We study the physics of steady detonation wave propagation in a two-dimensional circular arc via a Detonation Shock Dynamics (DSD) surface evolution model. The dependence of the surface angular speed and surface spatial structure on the inner arc radius ( $R_{i}$ ), the arc thickness ( $R_{e}-R_{i}$ , where $R_{e}$ is the outer arc radius) and the degree of confinement on the inner and outer arc is examined. We first analyse the results for a linear $D_{n}$ – $\unicode[STIX]{x1D705}$ model, in which the normal surface velocity $D_{n}=D_{CJ}(1-B\unicode[STIX]{x1D705})$ , where $D_{CJ}$ is the planar Chapman–Jouguet velocity, $\unicode[STIX]{x1D705}$ is the total surface curvature and $B$ is a length scale representative of a reaction zone thickness. An asymptotic analysis assuming the ratio $B/R_{i}\ll 1$ is conducted for this model and reveals a complex surface structure as a function of the radial variation from the inner to the outer arc. For sufficiently thin arcs, where $(R_{e}-R_{i})/R_{i}=O(B/R_{i})$ , the angular speed of the surface depends on the inner arc radius, the arc thickness and the inner and outer arc confinement. For thicker arcs, where $(R_{e}-R_{i})/R_{i}=O(1)$ , the angular speed does not depend on the outer arc radius or the outer arc confinement to the order calculated. It is found that the leading-order angular speed depends only on $D_{CJ}$ and $R_{i}$ , and corresponds to a Huygens limit (zero curvature) propagation model where $D_{n}=D_{CJ}$ , assuming a constant angular speed and perfect confinement on the inner arc surface. Having the normal surface speed depend on curvature requires the insertion of a boundary layer structure near the inner arc surface. This is driven by an increase in the magnitude of the surface wave curvature as the inner arc surface is approached that is needed to meet the confinement condition on the inner arc surface. For weak inner arc confinement, the surface wave spatial variation with the radial coordinate is described by a triple-deck structure. The first-order correction to the angular speed brings in a dependence on the surface curvature through the parameter $B$ , while the influence of the inner arc confinement on the angular velocity only appears in the second-order correction. For stronger inner arc confinement, the surface wave structure is described by a two-layer solution, where the effect of the confinement on the angular speed is promoted to the first-order correction. We also compare the steady-state arc solution for a PBX 9502 DSD model to an experimental two-dimensional arc geometry validation test.
Model Building in the LHC Era: Vector-like Leptons and SUSY GUTs

In this thesis, we study the phenomenology of some models beyond the Standard Model (SM). First, we analyze a model in which the SM is extended by a family of vector-like (VL) leptons. We find that the strongest constraints are coming from the muon g − 2, Rμμ = Γ(h → μμ)/Γ(h → μμ)SM, Rγγ , and BR(μ → eγ). Although VL leptons couple to all three families of the SM leptons, electron-VL couplings are highly constrained. The second model that we consider is a three family SO(10) SUSY GUT with Yukawa unification. We perform a global χ2 analysis and show that SUSY effects do not decouple even though the best fit universal scalar mass parameter at the GUT scale is m16 ≈ 25 TeV. The fit to sin(2β), and up and down quark masses of this model, however, are not great. We show that the fits can be improved by choosing a Pati-Salam (PS) group as the gauge group and modifying the Yukawa sector. The best-fit point, consistent with the bound obtain from reinterpreting gluino simplified model analyses by the ATLAS and CMS collaborations, has gluino mass Mg̃ = 1.9 TeV and χ 2/dof ≈ 1.12. Finally, we study the reheating and the baryogenesis (via leptogenesis) of this PS model extended by an inflation sector. This model reheats via instant preheating due to bosonic and fermionic broad parametric resonances. The lepton asymmetry is obtained from the CP asymmetric right-handed neutrino (RHN) decay. The leptogenesis analysis is performed by including all three families of the RHNs because, by fitting to the low-energy observables, the heaviest RHN decays to produce a lepton asymmetry with the correct sign, while the two lighter RHNs decay to produce the wrong sign.
Xrn1 biochemically associates to the eisosome after the post diauxic shift in yeast

mRNA degradation is one of the main steps of gene expression, and a key player is the 5’-3’ exonuclease Xrn1. In Saccharomyces cerevisiae, it was previously shown, by a microscopy approach, that Xrn1 is located to different cellular compartments, depending on physiological state. During exponential growth, Xrn1 is distributed in the cytoplasm, while it is present in the eisosomes after the post-diauxic shift (PDS). Here, we biochemically characterized the Xrn1-associated complexes in different cellular states. We demonstrate that, after PDS, Xrn1 but not the decapping (DCP), nor Lsm1-7/Pat1 complexes, was sequestered in the eisosomes, thus preserving mRNAs from degradation.
Determination of Reservoir Lithology from Seismic Data by a 2D Hidden Markov Random Field Model

Summary In this study, geological prior information is incorporated in the classification of reservoir lithologies using the Markov Random Field (MRF) technique. The prediction of hidden lithologies in seismic data is based on measured observations such as seismic inversion results, which are associated with the latent categorical variables derived from the distribution of Gaussian assumptions. The Hidden Markov Random Field (HMRF) approach can connect similar lithologies laterally (horizontally) while ensure a geologically reasonable stratigraphic (vertical) ordering. It is, therefore, able to exclude randomly appearing lithologies caused by errors in the inversion. In HMRF, the prior information consists of a Gibbs distribution function and transition probability matrices. The Gibbs distribution connects similar lithologies and does not need a geological definition derived from non-case-related information. The transition matrices provide preferential transitions between different lithologies and an estimation of these matrices implicitly depends on the depositional environments and juxtaposition rules between different lithologies.
Active material, optical mode and cavity impact on nanoscale electro-optic modulation performance

Abstract Electro-optic modulation is a key function in optical data communication and possible future optical compute engines. The performance of modulators intricately depends on the interaction between the actively modulated material and the propagating waveguide mode. While a variety of high-performance modulators have been demonstrated, no comprehensive picture of what factors are most responsible for high performance has emerged so far. Here we report the first systematic and comprehensive analytical and computational investigation for high-performance compact on-chip electro-optic modulators by considering emerging active materials, model considerations and cavity feedback at the nanoscale. We discover that the delicate interplay between the material characteristics and the optical mode properties plays a key role in defining the modulator performance. Based on physical tradeoffs between index modulation, loss, optical confinement factors and slow-light effects, we find that there exist combinations of bias, material and optical mode that yield efficient phase or amplitude modulation with acceptable insertion loss. Furthermore, we show how material properties in the epsilon near zero regime enable reduction of length by as much as by 15 times. Lastly, we introduce and apply a cavity-based electro-optic modulator figure of merit, Δλ/Δα, relating obtainable resonance tuning via phase shifting relative to the incurred losses due to the fundamental Kramers-Kronig relations suggesting optimized device operating regions with optimized modulation-to-loss tradeoffs. This work paves the way for a holistic design rule of electro-optic modulators for high-density on-chip integration.
Solar and atmospheric influences in the cosmic ray intensity

Cosmic ray intensity at Earth changes with time and presents variations associated with the 11yr solar cycle, with interplanetary coronal mass ejections (ICME) arriving on the Earth’s magnetosphere, and with energetic particles produced during large solar flares. Studies also show that the cosmic rays can be related with atmospheric phenomena. Since cosmic rays are the main source of ionization between ~4 and ~60 km, they may influence climate phenomena as global cloud coverage and rain precipitation rate. Meteorological and atmospheric processes, such as changes in the ambient pressure and temperature, rain precipitation and variations of the atmospheric electric field can affect the cosmic ray counts observed by ground based detectors. In this work we present the results obtained with the CARPET charged particle detector installed at Astronomical Complex El Leoncito (CASLEO) in San Juan Argentina, since April 2006. We show and discuss the long term modulation of the cosmic ray flux associated with solar phenomena, like the 11-yr solar cycle and seasonal variations that can be related to changes in the atmospheric temperature. We also correct cosmic ray data for the barometric effect in order to discuss short time increases of the cosmic ray intensity in association to rain precipitation and changes in the atmospheric electric field.
Squeeze and Excitation Rank Faster R-CNN for Ship Detection in SAR Images

Synthetic aperture radar (SAR) ship detection is an important part of marine monitoring. With the development in computer vision, deep learning has been used for ship detection in SAR images such as the faster region-based convolutional neural network (R-CNN), single-shot multibox detector, and densely connected network. In SAR ship detection field, deep learning has much better detection performance than traditional methods on nearshore areas. This is because traditional methods need sea–land segmentation before detection, and inaccurate sea–land mask decreases its detection performance. Though current deep learning SAR ship detection methods still have many false detections in land areas, and some ships are missed in sea areas. In this letter, a new network architecture based on the faster R-CNN is proposed to further improve the detection performance by using squeeze and excitation mechanism. In order to improve performance, first, the feature maps are extracted and concatenated to obtain multiscale feature maps with ImageNet pretrained VGG network. After region of interest pooling, an encoding scale vector which has values between 0 and 1 is generated from subfeature maps. The scale vector is ranked, and only top $K$ values will be preserved. Other values will be set to 0. Then, the subfeature maps are recalibrated by this scale vector. The redundant subfeature maps will be suppressed by this operation, and the detection performance of detector can be improved. The experimental results based on Sentinel-1 images show that the detection performance of the proposed method achieves 0.836 which is 9.7% better than the state-of-the-art method when using F1 as matric and executes 14% faster.
A CNN-based probability hypothesis density filter for multitarget tracking

Recently, the probability hypothesis density filter (PHD) shows excellent multiple targets tracking performance, and it has been applied for tracking targets in video. The PHD filter usually needs to integrate other feature for image object tracking. However, the single hand-crafted feature shows poor robustness while utilizing multiple features fusion will increase the complexity. To alleviate the above problems, a deep convolutional neural networks (CNN) based PHD filter is proposed in this paper. The proposed method utilizes the impressive representability of the CNN feature to improve the robustness without increasing the complexity. Besides this, we also revise the update process of the standard PHD filter to output the continuous track and new birth targets, directly. The experiment tested on MOT17 dataset validate the efficacy of the proposed method in multitarget tracking in image sequences.
High-precision 3D shape measurement based on time-resolved VCSEL

High-speed and high-precision human face 3D shape measurement plays a very important role in diverse applications such as human-computer interaction, 3D face recognition, Virtual Reality. This paper introduces a structured light system based on VCSEL(Vertical Cavity Surface Emitting Laser) with one simulated projectors and two camera for human face 3D shape measurement. Large-scale production cost of VCSEL is low, because of the manufacturing process compatible with LED. VCSEL has the advantages of projecting a large area of diffractive structure light and easy to integrate into lens array internally. The process of VCSEL projecting the structural light that changes over time to human face is simulated by computer. The ICP algorithm is used to match the image of single frame structure light from the right camera to the left camera. A single frame image of three-dimensional face point cloud is obtained by using binocular stereo vision principle. The multi-frame images of point cloud that change along time series are superposed to obtain higher density point cloud data and improve the measurement accuracy. This 3D measurement based on VCSEL has advantages of low cost, high precision, and small size and should be useful for practical applications.
Modal analysis of a box-shape girder by numerical method

Ахмад Рахбар-Ранжі. Модальний аналіз коробчастої балки за допомогою чисельних методів. Для розрахунку власних частот і форм коливань виконано модальний аналіз структур. Ці параметри є основною технічною інформацією, необхідною для аналізу і розробки будь-яких структур. Інформація про них додатково необхідна для розуміння і моделювання динамічної поведінки структур. Для прогнозування цих параметрів в простих структурах може бути використаний теоретичний підхід, однак для складних структур необхідно використовувати чисельні методи. Заявлено, що для складних структур аналітичне рішення може бути використано для прогнозування власної частоти моди першого порядку за допомогою спрощення складних структур до простих. У даній роботі проведено чисельні дослідження модального аналізу коробчастої балки, а також проведено порівняльний аналіз з моделлю двоопорної балки, яка має аналогічні характеристики поперечного перерізу. Виявлено, що за допомогою моделі двоопорної балки можна прогнозувати вібрації першого порядку, за умови адекватного врахування граничних умов.