Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcription of Arabic and Turkish Music Using Convolutional Neural Networks

Automatic music transcription is considered a complex operation, especially in polyphonic music tracks, in addition. However, most of the previous studies hasn't taken into account quarter notes detection which is considered the most important feature in Arabic and Turkish music. In this paper, a complete polyphonic pitch tracking system has been built for Arabic, Turkish, and Western music which is able to detect notes and framewise from piano music tracks. This model combines both signal processing and deep learning techniques to provide more accurate results. In the first stage, constant Q Transformation is applied to the input musical track and then passed to the next stage which consists of two convolutional neural networks (CNNs). The first network is designed to detect notes onset and the other network is for framewise pitch detection. In the end, the output of the neural network is processed to generate MIDI file for the input Music track.
Image Segmentation Using Cloud Model and Data Field

An image thresholding method is proposed to select the optimal threshold for image segmentation. The data field is introduced to map the original image from grayscale space to the corresponding potential space by the proposed method,and the relative and the absolute data fields are produced with two different mass functions. Then,by considering the features of the data fields and combining the global and the local statistical characteristics of the image,a potential threshold for data field can be yielded. Next,the pixels are divided into possible backgrounds and objects, which are represented with background and object cloud models generated by backward cloud generator. According to the membership degrees of pixels over two cloud models,the final result of image thresholding is obtained by maximum determination method. It is indicated by the experiments that the proposed method yields accurate and robust result,and it is reasonable and effective.
Leaf anatomy for delimiting Atlantic Forest species of Psidium (Myrtaceae)

Abstract Leaf anatomical features are widely used to better understand angiosperm taxonomy. However, such information is scarce for the family Myrtaceae. Aiming to fill this knowledge gap, we studied anatomical and micromorphological leaf characters of ten species of Psidium: P. cattleyanum, P. cauliflorum, P. corynanthum, P. guajava, P. guineense, P. macahense, P. myrtoides, P. oligospermum, P. ovale and P. sartorianum. Uniseriate epidermis, paracytic stomata, secretory cavities, and adaxial hypodermis are common among the studied species and are typical characteristics of Myrtaceae. The presence of three or more layers of palisade parenchyma and the absence of sclerenchyma are diagnostic characters of P. guajava. The abaxial epidermis of Psidium cattleyanum and P. macahense possess curved walls. Psidium corynanthum and P. macahense are the only species with sinuous anticlinal walls on both sides of the epidermis, with all other species having straight or curved walls. Open bicollateral vascular bundles are present in all the studied species except P. guineense. With the exception of P. cauliflorum, all the studied species possess druses. The absence of collenchyma in the adaxial face is exclusive to P. ovale. The leaf anatomy of P. macahense, P. corynanthum, P. oligospermum and P. ovale are described for the first time here.
Active Control of Variable DC-Link for Maximum Efficiency of Traction Motor Drives

Modern electric vehicles often interpose a DC/DC converter between traction battery and inverter, boosting the supply voltage of the drive. The power losses in the two converters and in the electric motor significantly vary with the DC-link voltage amplitude. In this work, a novel control algorithm is proposed to adapt online the DC-link voltage during vehicle operation, pursuing the maximum efficiency of the DC/DC converter and traction inverter without affecting the motor control dynamic. The key principle of the proposal, suitable for 3-phase and multi-three-phase drives, relies on the DC-link voltage minimization on varying the drive operating conditions. Among its advantages, the proposed variable DC-link control is independent of the motor parameters, the adopted torque/speed control strategy and the number of 3-phase sets of the drive. Although originally developed for electric vehicles, it can be adopted in a wide number of applications. Straightforward calibration roles are also provided. The proposed algorithm is deeply validated in simulation and experiments using a full-scale 135 kW 6-phase traction motor drive at TRL6.
Linking Structure and Function of Complex Cortical Networks

The recent discovery of an intricate and nontrivial interaction topology among the elements of a wide range of natural systems has altered the manner we understand complexity. For example, the axonal fibres transmitting electrical information between cortical regions form a network which is neither regular nor completely random. Their structure seems to follow functional principles to balance between segregation (functional specialisation) and integration. Cortical regions are clustered into modules specialised in processing different kinds of information, e.g. visual or auditory. However, in order to generate a global perception of the real world, the brain needs to integrate the distinct types of information. Where this integration happens, nobody knows. We have performed an extensive and detailed graph theoretical analysis of the cortico-cortical organisation in the brain of cats, trying to relate the individual and collective topological properties of the cortical areas to their function. We conclude that the cortex possesses a very rich communication structure, composed of a mixture of parallel and serial processing paths capable of accommodating dynamical processes with a wide variety of time scales. The communication paths between the sensory systems are not random, but largely mediated by a small set of areas. Far from acting as mere transmitters of information, these central areas are densely connected to each other, strongly indicating their functional role as integrators of the multisensory information. In the quest of uncovering the structure-function relationship of cortical networks, the peculiarities of this network have led us to continuously reconsider the stablished graph measures. For example, a normalised formalism to identify the “functional roles” of vertices in networks with community structure is proposed. The tools developed for this purpose open the door to novel community detection techniques which may also characterise the overlap between modules. The concept of integration has been revisited and adapted to the necessities of the network under study. Additionally, analytical and numerical methods have been introduced to facilitate understanding of the complicated statistical interrelations between the distinct network measures. These methods are helpful to construct new significance tests which may help to discriminate the relevant properties of real networks from side-effects of the evolutionary-growth processes.
Developable Bezier function surface

Developable surface plays an important role in engineering practice. And Bezier function surfaces on the rectangular and triangular domains are common representation forms in a computer aided geometric design system. However, there are no studies about developable Bezier function surface up to now. General characterizations of developable Bezier function surfaces of arbitrary degree on the rectangular and triangular domains are presented. It is proved that a developable Bezier function surface of degree 2 on the triangular domain must be a parabolic cylinder. The construction methods of developable Bezier function surfaces of degree 3 on the triangular domain and of degree (2,2) on the rectangular domain are presented. The conclusions can be easily extended to bivariate polynomial function surface.
Theory of Transfer, Storage and Dissipation of Energy in Circuits

Abstract Energy transfer accompanying with current is usually described by using Poynting’s vector. Here, combining Kirchhoff’s law, Joule’s law and Slepian’s postulation, we demonstrate that, for the case of a current travels along a wire, component of total energy flow flux parallel to the wire (CTEFFPW) may be equivalently described by using product of current intensity and electric potential (voltage), furthermore, the law of conversion and conservation of energy accompanying with current, which is equivalent to Poynting’s theorem, may be obtained based on circuit method. Noting that product of current intensity and voltage relates to CTEFFPW instead of the electric power, physical meaning of usual definitions of powers adopted in electric power theory are readdressed. Our work may provide possibility to achieve the long-time expectation that power properties of power systems are described on the basis of Poynting’s theorem and Poynting’s vector, and to address the unsolved problems arised in the electric power theory.
Dynamic model of isothermal moving bed reducer for chemical looping hydrogen production

This paper investigates process modelling and reactor design for the reducer in the chemical looping hydrogen production (CLHP) process. The CLHP process adopts a three-reactor technology that can provide an efficient and sustainable alternative to the current hydrogen production technology via steam methane reforming (SMR), which suffers from several limitations during industrial operation. CLHP can achieve higher thermal efficiency than SMR and provide a carbon capture and storage (CCS) system. So far, no report on the modelling analysis of the reducer despite its critical dependence on temperature. The modelling study adopts the modified pellet-grain model at the micro-scale and counter-current moving bed model reactor at the reactor level. Simulation results of the gas-solid behavior based on the multi-scale model agree with the literature evidence. Critical information from the model revealed that the oxygen carriers (solids) can attain a desired state, but the syngas remains underutilized. The model simulation further suggests that lowering the gas-solid velocity ratio (Vgs) can substantially promote the syngas conversion. However, the Vgs value must remain above a threshold value (170), defined through the limitation of gas-solid velocities in a moving bed reactor. Since a CCS system requires high purity (>95%) of the product gas, rigorous temperature-pellet size optimization is vital to achieving the target purity while maintaining desired solid state.
Synthesis of Graphene Oxide/ Poly(Vinyl Alcohol) Composite and Investigation of Graphene Oxide Effect on Diameter and Pore Size of Poly(Vinyl Alcohol) Nanofibers

The ultrafine fibers of Poly Vinyl Alcohol (PVA) /Graphene Oxide (GO) composite were prepared by using a homemade electrospinning set-up at 12.5 kV and 12 cm with different concentrations of GO (1g/L, 0.75g/L, and 0.5g/L) in PVA. The effect of GO concentrations in 10% PVA solution on the diameter of fibers was investigated. Fourier Transform Infrared (FTIR) Spectroscopy was used to analyze the functional groups. Ultraviolet (UV)-visible spectra of GO suspension showed the absorption peak at 232 nm. The morphology of the nanofibers was analyzed by Scanning Electron Microscopy (SEM). The X-ray diffraction (XRD) technique was used to analyze the crystalline nature of this material. The diameter of nanofibers decreased with improved crystallinity, thus, increasing the concentration of GO in PVA.
Modeling and Control of Modular Multilevel Matrix Converter for Low-Frequency AC Transmission

The modular multilevel matrix converter (M3C) is the core component in low-frequency AC (LFAC) transmission, which is a competitive scheme for offshore wind power integration. In this paper, the M3C control strategy with the reduced switching frequency SM voltage balancing method is proposed. First, based on the conventional αβ0 and dq transformations, the M3C mathematical model is derived. Then, the dual-loop control structure with outer loop and inner loop controllers commonly used in voltage source converters is applied to the M3C. The inner loop controller consists of the current tracking controller in the dq reference frame and the circulating current suppressing controller in the αβ0 reference frame; the outer loop controller is proposed for the offshore wind farm LFAC integration scenario. Additionally, according to the operating characteristics of full-bridge sub-modules (FBSMs), three characteristic variables are defined and a reduced switching frequency SM voltage balancing method based on the nearest level control (NLC) is proposed. Finally, time-domain simulations in PSCAD/EMTDC demonstrate the feasibility of the proposed control strategy.
Brownian flow on a finite interval with jump boundary conditions

We consider a stochastic flow in an interval $[-a,b]$, where $a,b>0$. Each point of the interval is driven by the same Brownian path and jumps to zero when it reaches the boundary of the interval. Assuming that $a/b$ is irrational we study the long term behavior of a random measure $\mu_t$, the image of a finite Borel measure $\mu_0$ under the flow. We show that if $\mu_0$ is absolutely continuous with respect to the Lebesgue measure then the time averages of the variance of $\mu_t$ converge to zero almost surely. We also prove that for an arbitrary finite Borel measure $\mu_0$ the Lebesgue measure of the support of $\mu_t$ decreases to zero as $t\to\infty$ with probability one.
Missing data matter: an empirical evaluation of the impacts of missing EHR data in comparative effectiveness research

OBJECTIVES The impacts of missing data in comparative effectiveness research (CER) using electronic health records (EHRs) may vary depending on the type and pattern of missing data. In this study, we aimed to quantify these impacts and compare the performance of different imputation methods. MATERIALS AND METHODS We conducted an empirical (simulation) study to quantify the bias and power loss in estimating treatment effects in CER using EHR data. We considered various missing scenarios and used the propensity scores to control for confounding. We compared the performance of the multiple imputation and spline smoothing methods to handle missing data. RESULTS When missing data depended on the stochastic progression of disease and medical practice patterns, the spline smoothing method produced results that were close to those obtained when there were no missing data. Compared to multiple imputation, the spline smoothing generally performed similarly or better, with smaller estimation bias and less power loss. The multiple imputation can still reduce study bias and power loss in some restrictive scenarios, eg, when missing data did not depend on the stochastic process of disease progression. DISCUSSION AND CONCLUSION Missing data in EHRs could lead to biased estimates of treatment effects and false negative findings in CER even after missing data were imputed. It is important to leverage the temporal information of disease trajectory to impute missing values when using EHRs as a data resource for CER and to consider the missing rate and the effect size when choosing an imputation method.
Analytical solutions of linear and nonlinear Klein-Fock-Gordon equation

Abstract In this paper, we deal with some linear and nonlinear Klein-Fock-Gordon (KFG) equations, which is a relativistic version of the Schrödinger equation. The approximate analytical solutions are obtained by using the homotopy analysis method (HAM). The efficiency of the HAM is that it provides a practical way to control the convergence region of series solutions by introducing an auxiliary parameter }. Analytical results presented are in agreement with the existing results in open literature, which confirm the effectiveness of this method.
Partial Discharge Data Augmentation and Pattern Recognition for Unbalanced and Small Sample Scenarios

To improve the accuracy of partial discharge pattern recognition under unbalanced and small sample conditions, a method of partial discharge data augmentation and pattern recognition using the generative adversarial network embedded deep auto-encoder (DAE-GAN) is proposed. First, deep Auto-encoder (DAE) is embedded into a Generative Adversarial Network (GAN), and DAE is used to guide the generation process to improve the authenticity of generated samples. Second, complement samples of PD samples are added to the training process of the Generative Adversarial Network to solve the problem of small PD samples. Finally, extended equalization training samples are used to fine-tune the discriminator of the model to realize PD pattern recognition. DAE-GAN is used for data augmentation and pattern recognition of partial discharge experimental signals. The results show that, compared with other algorithms, the authenticity and probability distribution fitting accuracy of partial discharge samples generated by DAE-GAN are higher and the accuracy of partial discharge recognition is improved by 8.24% after data augmentation.
A Method for Judging the Arc-Extinction Time of Resonant Grounding System Based on Frequence Difference

In the resonant grounding system, the accurate judgment of arc-extinction time has guiding significance for the line selection of grounding fault, the evaluation of the arc suppression effect, and the extraction and utilization of transient information after arc extinction. Aiming at the single-phase grounding fault of resonant grounding system, this paper analyzes the frequence change characteristics before and after arc extinction. It is found that the frequence of zero-sequence electrical quantity before arc extinction is power frequence, and it changes after arc extinction. It is used to construct single-frequence methods and dual-frequence methods for judging arc-extinction time. As a tool for dynamic frequence measurement, SOGI-FLL is utilized to realize the engineering application of the method for judging arc-extinction time. The method’s accuracy is proved by Matlab/Simulink simulation and field test.
Erratum: “Relating Energetic Ion Spectra to Energetic Neutral Atoms” (2023, ApJ, 944, 198)

The descriptions about the energetic neutral atom ( ENA ) data in Section 3.2 were described incorrectly and some references inadvertently omitted. Accordingly, with this erratum, we replace the descriptions in the published article as follows. In Section 3.2, paragraph 2, the ﬁ rst three sentences should be revised to: “ Figure 2 shows the calculated ENA ﬂ ux in the inertial frame for different proton distributions in the heliosheath, together with the 0.52 – 6 keV ENAs at 1 au measured by IBEX-Hi ( Funsten et al. 2009; McComas et al. 2009, 2014 ) , and the 5.2 – 55 keV ENAs at ∼ 10 au from Cassini / INCA ( Krimigis et al. 2004, 2009; Dialynas et al. 2017, 2022 ) . The measurements of ENAs from IBEX-Hi and INCA are over the years 2009 – 2012 along the Voyager 2 direction and are taken from Dialynas et al. ( 2020 ) . The ENA ﬂ ux data are drawn from the IBEX-Hi Data Release 16, which are survival probability and Compton – Getting corrected ( McComas et al. 2020 ) . The effects of radiation pressure are negligible for ENAs above a few hundred eV ( Dayeh et al. 2012 ) . These corrections are negligible for the > 5.2 keV neutrals that INCA measures ( Roelof et al. 2012; Dialynas et al. 2017, 2019, 2020 ) . ” Our results and conclusions are
Nature of Intense Magnetism and Differential Rotation in Convective Dynamos of M-dwarf Stars with Tachoclines

Many of the M-dwarf stars, though they are tiny and dim, are observed to possess strong surface magnetic fields and exhibit remarkably intense flaring. Such magnetism may severely impact habitability on the exoplanets now discovered nearby. The origin of the magnetism must rest with dynamo action achieved by turbulent convection coupled to rotation within the M-dwarfs. To further explore the nature and diversity of the magnetism that can result, we turn here to an extensive set of 45 global MHD simulations to explore dynamos operating within deep convective envelopes of rapidly rotating M2 (0.4 M ⊙) stars. We observe a wide range of cycle periods present in the convection zones, whose durations we find to scale with the Rossby number as Ro−1.66±0.07 in concurrence with scalings identified in simulations of more massive stars. We find a unifying relationship between the ratio of magnetic to convective kinetic energy (ME/CKE) and the degree to which the differential rotation is quenched by magnetic fields. We show that the presence of a tachocline in these model stars enhances their axisymmetric magnetic field components, leading to a surface dipole fraction on average 78% greater than an equivalent star with only a CZ, potentially shedding light on the nature of the tachocline divide through resultant effects on the spin-down rate.
Bi-directional Optical Flow-based Feature Point Tracking Method

In order to improve the robustness of the SLAM system based on the optical flow method, we propose a feature point tracking method with a bi-directional optical flow. The method first couples the forward LK optical flow and the reverse LK optical flow. Then, the feature points are screened and tracked by coupling the bidirectional optical flow. If the screened feature points do not reach the set threshold, they can be supplemented with either Fast points or Harris points. The experimental validation of the above method by VINS-Mono with the EuRoC dataset shows that VINS-Mono using this method significantly improves the accuracy of localization without increasing the running time cost compared with the original VINS-Mono.
Non-equilibrium quantum domain reconfiguration dynamics in a two-dimensional electronic crystal: experiments and quantum simulations

Relaxation dynamics of complex many-body quantum systems brought out of equilibrium and subsequently trapped into metastable states is a very active field of research from both the theoretical and experimental point of view with implications in a wide array of topics from macroscopic quantum tunnelling and nucleosynthesis to non-equilibrium superconductivity and new energy-efficient memory devices. Understanding the dynamics of such systems is crucial for exploring fundamental aspects of many-body non-equilibrium quantum physics. In this work we investigate quantum domain reconfiguration dynamics in the electronic superlattice of a quantum material where classical dynamics is topologically constrained. The crossover from temperature to quantum fluctuation dominated dynamics in the context of environmental noise is investigated by directly observing charge reconfiguration with time-resolved scanning tunneling microscopy. The process is modelled using a programmable superconducting quantum simulator in which qubit interconnections correspond directly to the microscopic interactions between electrons in the quantum material. Crucially, the dynamics of both the experiment on the quantum material and the simulation is driven by spectrally similar pink noise. We find that the simulations reproduce the emergent time evolution and temperature dependence of the experimentally observed electronic domain dynamics remarkably well. The combined experiment and simulations lead to a better understanding of noise-driven quantum dynamics in open quantum systems. From a practical viewpoint, the results are important for understanding the origin of the retention time in non-volatile memory devices such as those based on 1T-TaS2.