Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Analysis of Back-Iron for Axial-Flux PM High-Speed Machines

Back-iron plays a vital role in electrical machines as they are normally designed to complete the magnetic circuit. Although laminated steel sheets have been used in traditional machines, they are not appropriate for high-speed rotating structure since they are exposed to high centrifugal forces which may cause mechanical failure. Rigidity, mechanical integrity and robustness are important factors that must be taken into account while designing the back-iron. This paper presents the utilization of annulus disc type back-iron fitted at the back of PM rotor for high rotational speed. Structural integrity of the disc is investigated and realized by performing stress and modal analysis using ANSYS FE modeling. Moreover, natural frequencies, vibration mode shapes, and participation factors are extracted from the FE results. Back-iron size, hence weight is optimized without degrading the flux density levels. Analysis results showed the validity of the proposed back-iron design for the intended application. Stress and vibration analysis results showed safe design structure as stress levels are well below 350 MPa and natural frequencies are all above the operating frequency of 833 Hz.
Attention-aware Memory Aggregation Network for Hyperspectral Image Classification

Among remote sensing imagery, hyperspectral image has become the centre of attention among researchers due to its wide applications. A hyperspectral image is a three-dimensional image composed of 2D spatial and 1D spectral de-tails. The low availability of these images and spectral correlation problems make the classification of HSI difficult. Traditional classification approaches utilize convolutional models that use local kernel filters achieving good accuracy in performance metrics. Therefore, we introduce Memory Aggregation Networks (MAN), an in-network attention-based approach towards HSI classification globally extracting spectral-spatial features. We plug soft and hard attention mechanisms as a part of the network architecture leveraging short-term dependencies. The fusion of ConvLSTM cells learns both long-term and short-term information by exploring different receptive regions. The adaptive memory aggregation module exploits maximum pixel information reducing the loss of spectral-spatial domain features. Empirical analysis against various methods indicates the superiority of our network in terms of various performance metrics.
Earthquake Magnitude Prediction in Chile Using Neural Network

In this study, we implement an earthquake magnitude prediction model using a neural network for a test region in Chile. For this, the epicenter of earthquake is located on a mesh with dimensions of 1°×1°. We adopt a zonation scheme originally proposed by Reyes and Cardenas [1]. The scheme uses increments in b−value and other input parameters to incorporate G-R linear relation and Bath’s law. The model enables the prediction of the maximum magnitude for a given cell within the next five days. Common seismological parameters are used for the performance evaluation of the model. Results show satisfactory performance of the proposed model in comparison to other existing models.
EEG Artifact Removal Based on Brain Dipoles' Regions Using ICA and Dipfit in Motor Imagery Tasks

In this article, a new semi-automatic Electroencephalogram (EEG) artifact removal has been proposed for Motor Imagery (MI) tasks to improve the system's performance. There are eight reference clusters whose locations have been calculated based on the precise coordinates of a copious amount of brain dipoles acquired from a large number of users performing MI tasks. In this method, called 8 Ref-Clusters, a kind of Blind Source Separation (BSS) algorithm along with the DIPFIT plugin of the EEGLAB platform take on a decisive role. These eight clusters demonstrate which dipoles are brain sources and which ones are artifacts to eliminate. In the case of improving the performance of a system for a particular subject, we defined a specific threshold that could alter the size of clusters in three dimensions. The elaborate threshold pointed out above is unquestionably user-dependent. Having made a comparison between results before and after applying the 8-Ref-Clusters on the BCI-Competition IV 2a datasets, the average performance increased by roughly 4% which is promising when the datasets used in these evaluations had been filtered, between 8 and 30 Hz, only before applying Independent Component Analysis (ICA). Making a comparison between the results of the proposed method and those of other CSP-based methods shows that applying the proposed artifact removal only before CSP can significantly enhance the performance of the system at about 15.6%, in the case of the mCSP method. All in all, the proposed artifact removal method is a semi-automatic method that is computationally fast and able to detect the various types of artifacts like a heartbeat, muscle and head movements, eye blink, line noise, and so on.
Transient Ice Events of Underwater Ambient Noise in the Arctic Ocean

A large number of transient ice events exist in underwater ambient noise in the Arctic Ocean, and they are believed to be the main contributor to underwater noise different from contributors in other oceans. This paper studied the underwater ambient noise (CHINARE18 and CHINARE20) recorded during the 9th Chinese National Arctic Research Expedition and the 11th Chinese National Arctic Research Expedition. The time-frequency analysis of two 7-s-long ice noise samples in the two experiments shows that ice transient events have impulsivity and wide spectrum. The statistical result of transient ice events in different frequency bands reveals that these events mainly contribute to the high-frequency component of under-ice ambient noise. It can be seen in the power spectrum that transient energy is apparent in the 90th and 99th percentile curves. Due to the influence of ice transient events, the CHINARE18 has obvious fluctuations in the spectral kurtosis in a certain frequency band (4kHz-8kHz).
Investigation of Incoherent Gamma-Ray Scattering Potential for the Fluid Density Measurement

Incoherent gamma ray scattering is a method that can be applied for the fluid parameter characterization. The aim of the present work is to study the potential usage of the incoherent gamma ray scattering measurements to evaluate the fluid density based on the Monte Carlo approach. Enlarging the density of a fluid results in a significant reduction in the intensity of the detected gamma scattering. The difference of the simulation curve slope results in the gamma transmission mode its about 0.02 compared to the experimental result.
Permeability measurement on composites made of oriented metallic wires from 0.1 to 18 GHz

In this paper, we study the microwave properties of strongly anisotropic materials made of orientated conducting wires. We have developed a broad band method to determine their permeability /spl mu//spl par/ parallel to the direction of the wires. We investigate the magnetic properties of strongly anisotropic composites made of different types of paramagnetic and ferromagnetic wires. A simple model is proposed to account for the skin effect, and agrees with our observations. This leads to a unique broad band method for measuring the permeability of thin conducting wires.
Synchronization for two coupled oscillators with inhibitory connection

In this paper we present an oscillatory neural network composed of two coupled neural oscillators with inhibitory connections. Each of the oscillators describes the dynamics of average activities of excitatory and inhibitory populations of neurons. Regarding time delays τ as the bifurcation parameter, we not only obtain the existence of Hopf bifurcations but also investigate the bifurcation direction and stability of bifurcated periodic solutions by employing normal form theory and center manifold reduction. Finally, numerical simulations are provided to illustrate the theoretical results. Copyright © 2009 John Wiley & Sons, Ltd.
Synchronization and desynchronization of complex dynamical networks: an engineering viewpoint

We study synchronization and desynchronization of a complex network of chaotic dynamical systems, in both continuous-time and discrete-time cases. With proved synchronization conditions, we illustrate network synchronization and desynchronization processes by a prototype composing of Henon maps in a scale-free network. We show that synchronization and desynchronization of such a complex dynamical network can be determined by the network topology and the maximum Lyapunov exponent of the individual chaotic nodes.
Intense-field dissociation dynamics of D+2 molecular ions using ultrafast laser pulses

The dynamics of dissociation of pre-ionized D+2 molecules using intense (1012–1015 W cm−2), ultrashort (50 fs), infrared (λ = 790 nm) laser pulses are examined. Use of an intensity selective scan technique has allowed the deuterium energy spectrum to be measured over a broad range of intensity. It is found that the dominant emission shifts to lower energies as intensity is increased, in good agreement with corresponding wavepacket simulations. The results are consistent with an interpretation in terms of bond softening, which at high intensity (approximately >3 × 1014 W cm−2) becomes dominated by dissociative ionization. Angular distribution measurements reveal the presence of slow molecular dissociation, an indication that vibrational trapping mechanisms occur in this molecule.
Scaling and Numerical Model Evaluation of Snow-Cover Effects on the Generation and Modification of Daytime Mesoscale Circulations.

Abstract Consideration of the sensible heat flux characteristics over a snow surface suggests a significant diminution in the magnitude of the flux, compared to that over a snow-free surface under the same environmental conditions. Consequently, the existence of snow-covered mesoscale areas adjacent to snow-free areas produces horizontal thermal gradients in the lower atmosphere during the daytime, possibly resulting in a “snow breeze. ” In addition, suppression of the daytime thermally induced upslope flow over snow-covered slopes is likely to occur. The present paper provides scaling and modeling evaluations of these situations, with quantification of the generated and modified circulations. These evaluations suggest that under ideal situations involved with uniform snow cover over large areas, particularly in late winter and early spring, a noticeable “snow breeze” is likely to develop. Additionally: suppression of the daytime thermally induced upslope flow is significant and may even result in a daytim.
Response of the atmosphere–ocean mixed‐layer system to anomalous ocean heat‐flux convergence

We investigate the role of the extratropical oceans in climate variability. Rather than following the traditional approach of studying the atmospheric response to prescribed sea‐surface‐temperature (SST) anomalies, we focus on the role of anomalous ocean heat transport. We employ an atmosphere model coupled to a fixed‐depth (‘slab’) ocean mixed‐layer model, forced by a field of ocean heat‐flux convergence (OHFC). We study the response of this coupled atmosphere–ocean mixed‐layer system to an idealized OHFC anomaly.
Development and applications of paleontological computed tomography

The traditional serial grinding method used to investigate the internal structure of fossils cannot be readily applied to valuable fossil specimens due to its destructive and time-consuming nature. Computed tomography (CT) is an ideal non-destructive technique for investigating the internal structure of fossils, in which thousands of serial images are obtained and used to produce an accurate reconstruction of the internal morphology. This paper reviews the design, development and applications of the first CT system in China dedicated exclusively to scanning fossils. The 225 kV three-dimensional (3D) fossil micro-CT (225-3D-μCT) is capable of high-resolution volumetric imaging, with a resolution up to 5 μm, and can accommodate specimens measuring up to 100 mm in diameter and 100 mm in length. The 450 kV ordinary fossil CT (450-TY-ICT) can produce high signal-to-noise ratio (SNR) images of specimens ranging up to 800 mm in diameter and 1000 mm in length, with a resolution up to 200 μm. Two paleontological CT facilities represent a high-performance platform offering the functional diversity needed to meet the demands of studying fossils at a variety of different scales. The two machines have become indispensable for paleontological research in China.
Detection of Electromyography Signal using Dry and Disposable Electrodes on the Bicep Muscle While Lifting Weights

One of the biosignals used to identify human muscle impulses is electromyography. Electromyographic signals are often used as input and are designed to help people with disabilities or help the healing process after stroke therapy. According to research, this incident has led to the development of various electromyography module sensor designs to meet different purposes. This research was conducted to make two different electromyography module designs and test these modules simultaneously when the biceps lifted a weight of 3Kg. The aim of this study was to compare the use of disposable and dry electrodes from the two electromyographic sensor module designs that were made. using root mean square (RMS) to find out the difference in tension generated when lifting the barbell. each module detects the biceps signal simultaneously. The biceps are part of the upper limb muscles. Based on the findings of this study, both E1 and E2 electromyography modules with disposable electrodes produced data with a p-value of 0.001766368 less than 0.05. while for the t-test of the two Electromyography modules E1 and E2 with dry electrodes it is 0.001766368 which is less than 0.05. Therefore, it can be concluded that there is a significant difference between the E1 and E2 modules. there is an average amplitude difference of 10mV between E1 and E2 modules when using both types of electrodes. and there is a difference in the average amplitude using dry and disposable electrodes of 30mV. The results of this study can be used to provide insight into the detection of electromyography signals, while the two module designs developed can be applied in future studies to detect electromyography.
Horizontal localization and hearing in noise ability in adults with sensorineural hearing loss using hearing aids with binaural processing.

The purpose of the study was to determine whether hearing aids with binaural processing improve performance during a localization and a hearing in noise task. The study included 15 participants between the ages of 29 and 68 who had a bilateral symmetrical sensorineural hearing loss and who had no prior hearing aid experience. Participants were fitted with Oticon Epoq XW receiver‐in‐the‐ear hearing aids bilaterally. The participants completed a horizontal localization task and a hearing in noise task with three listening conditions: (1) without hearing aids (NO), (2) with hearing aids that were not linked (BIL), and (3) with hearing aids that were linked (BIN). For the horizontal localization task, 1.5‐s pink noise bursts were used as the stimulus. Sentences from the Hearing in Noise Test were used as target stimuli for the hearing in noise task. Continuous discourse by one male and two female talkers was recorded and used as maskers. The specific aim of the localization and hearing in noise tasks was to d.
Calculation of the energy per ion pair for α-particles in helium

The average energy per ion pair, W, for the ionization of helium by 1 to 6 MeV α-particles is calculated using the Born approximation, the number of ion pairs produced by secondary, tertiary, etc., electrons being calculated from an integral equation which is solved numerically. The calculated W is nearly constant over this energy range, with average W = 41∙1 eV. This agrees well with the value, W = 42∙7 eV, measured recently by Jesse & Sadauskis for 5∙3 MeV α-particles in helium, and supports their suggestion that the earlier measured values of W for α-particles in helium may have been spuriously low owing to the presence of small amounts of other gases.
Lattice-dynamical and ground-state properties ofCaF2studied by inelastic neutron scattering and density-functional methods

We report results on the lattice dynamics of the superionic conductor CaF 2 from experiment and theory. Coherent inelastic neutron scattering between room temperature and 1000°C gives an unusually large temperature dependence of the phonon frequencies (dispersion) and widths. Electronic and lattice-dynamical properties are obtained from ab initio density-functional theory employing pseudopotentials and plane-wave basis sets, the electronic properties also from full-potential linearized augmented plane waves-linearized muffin-tin orbital methods. From density-functional perturbation theory we have calculated the dispersion of the phonon frequencies and of the mode-Gruneisen parameters. The contribution from thermal expansion to the experimental line shift is separated from the other anharmonic (phonon-phonon) contributions by comparison with the theoretical line shift from the volume expansion. The temperature dependence of the line broadening can in most cases be rationalized in terms of the two-phonon combined density of states, but the width of the zone-boundary X' 2 mode is unexpectedly large, even though the two-phonon combined density of states shows that there are only few two-phonon decay channels. and the frequency becomes critically soft at higher volumes. The effective charges and the dielectric constant depend nonlinearly on volume.
Efficient Estimation of Average Treatment Effects with Mixed Categorical and Continuous Data

In this article, we consider the nonparametric estimation of average treatment effects when there exist mixed categorical and continuous covariates. One distinguishing feature of the approach presented herein is the use of kernel smoothing for both the continuous and the discrete covariates. This approach, together with the cross-validation method. which we use for selecting the smoothing parameters, has the ability to automatically remove irrelevant covariates. We establish the asymptotic distribution of the proposed average treatment effects estimator with data-driven smoothing parameters. Simulation results show that the proposed method is capable of performing much better than the conventional kernel approach whereby one splits the sample into subsamples corresponding to “discrete cells. ” An empirical application to a controversial study that examines the efficacy of right heart catheterization on medical outcomes reveals that our proposed nonparametric estimator overturns the controversial findings of Connors et al. (1996), suggesting that their findings may be an artifact of an incorrectly specified parametric model.
Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels

Automated segmentation of myocardial fibrosis in late gadolinium enhancement (LGE) cardiac MRI (CMR) has the potential to improve efficiency and precision of diagnosis and treatment of cardiomyopathies. However, state-of-the-art Deep Learning approaches require manual pixel-level annotations. Using weaker labels can greatly reduce manual annotation time and expedite dataset curation, which is why we propose fibrosis segmentation methods using either slice-level or stack-level fibrosis labels. 5759 short-axis LGE CMR image slices were retrospectively obtained from 482 patients. U-Nets with slice-level and stack-level supervision are trained with 446 weakly-labeled patients by making use of a myocardium segmentation U-Net and fibrosis classification Dilated Residual Networks (DRN). For comparison, a U-Net is trained with pixel-level supervision using a training set of 81 patients. On the proprietary test set of 24 patients, pixel-level, slice-level and stack-level supervision reach Dice scores of 0.74, 0.70 and 0.70, while on the external Emidec dataset of 100 patients Dice scores of 0.55, 0.61 and 0.52 were obtained. Results indicate that using larger weakly-annotated datasets can approach the performance of methods using pixel-level annotated datasets and potentially improve generalization to external datasets.
Perovskite oxide tricolor superlattices with artificially broken inversion symmetry by interface effects

We have designed and fabricated spin superlattices composed of three kinds of perovskite oxides: ferromagnetic La0.6Sr0. 4MnO3 (LSMO) sandwiched by two nonmagnetic insulators, SrTiO3 (STO), and LaAlO3 (LAO). Conventional superlattices, structured as alternating stack of two components, preserve centrosymmetry. By stacking three compounds repeatedly in an asymmetric sequence such as (LAO/LSMO/STO)n, one can break the inversion symmetry. Magnetic and transport properties of the superlattices clearly indicate that the STO and LAO layers modulate the ferromagnetic spin order in LSMO layers adjacent to the interfaces in a different manner, giving rise to broken inversion symmetry of magnetic structure in the (LAO/LSMO/STO)n superlattices.
The Important Role of m6A-Modified circRNAs in the Differentiation of Intramuscular Adipocytes in Goats Based on MeRIP Sequencing Analysis

Intramuscular fat contributes to the improvement of goat meat quality. N6-Methyladenosine (m6A)-modified circular RNAs play important roles in adipocyte differentiation and metabolism. However, the mechanisms by which m6A modifies circRNA before and after differentiation of goat intramuscular adipocytes remain poorly understood. Here, we performed methylated RNA immunoprecipitation sequencing (MeRIP-seq) and circRNA sequencing (circRNA-seq) to determine the distinctions in m6A-methylated circRNAs during goat adipocyte differentiation. The profile of m6A-circRNA showed a total of 427 m6A peaks within 403 circRNAs in the intramuscular preadipocytes group, and 428 peaks within 401 circRNAs in the mature adipocytes group. Compared with the intramuscular preadipocytes group, 75 peaks within 75 circRNAs were significantly different in the mature adipocytes group. Furthermore, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of intramuscular preadipocytes and mature adipocytes showed that the differentially m6A-modified circRNAs were enriched in the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption, lysine degradation, etc. m6A-circRNA–miRNA–mRNA interaction networks predicted the potential m6A-circRNA regulation mechanism in different goat adipocytes. Our results indicate that there is a complicated regulatory relationship between the 12 upregulated and 7 downregulated m6A-circRNAs through 14 and 11 miRNA mediated pathways, respectively. In addition, co-analysis revealed a positive association between m6A abundance and levels of circRNA expression, such as expression levels of circRNA_0873 and circRNA_1161, which showed that m6A may play a vital role in modulating circRNA expression during goat adipocyte differentiation. These results would provide novel information for elucidating the biological functions and regulatory characteristics of m6A-circRNAs in intramuscular adipocyte differentiation and could be helpful for further molecular breeding to improve meat quality in goats.