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Abstract The fusion of multiple monitoring sensors is crucial to improve the accuracy and robustness of machinery fault diagnosis. However, existing fault diagnosis methods may underestimate the interference of noise in the multi‐sensor fusion process, leading to unsatisfied performance. To handle this problem, this paper proposes a deep model based on the frequency adaptive wavelet pyramid. First, an adaptive frequency selection strategy is designed to prune the seriously polluted frequencies and only retain some key frequencies. Then, the self‐attention mechanism is used to perform information fusion on the selected frequency bands of different sensors. Finally, a wavelet fusion pyramid is adopted by repeating the fusion process at multiple wavelet decomposition levels. In this way, different sensors can be fused in a more fine‐grained manner. The experimental results on two multi‐sensor‐based fault diagnosis datasets demonstrate the anti‐noise capability of the proposed method.

Infrared small target superresolution (SR) aims to recover a reliable and detailed high-resolution image with high-contrast targets from its low-resolution counterparts. Since the infrared small target lacks color and fine structure information, it is significant to exploit the supplementary information among sequence images to enhance the target. In this article, we propose the first infrared small target SR method named local motion and contrast prior driven deep network (MoCoPnet) to integrate the domain knowledge of the infrared small target into deep network, which can mitigate the intrinsic feature scarcity of infrared small targets. Specifically, motivated by the local motion prior in the spatio-temporal dimension, we propose a local spatio-temporal attention module to perform implicit frame alignment and incorporate the local spatio-temporal information to enhance the local features (especially for small targets). Motivated by the local contrast prior in the spatial dimension, we propose a central difference residual group to incorporate the central difference convolution into the feature extraction backbone, which can achieve center-oriented gradient-aware feature extraction to further improve the target contrast. Extensive experiments have demonstrated that our method can recover accurate spatial dependence and improve the target contrast. Comparative results show that the MoCoPnet can outperform the state-of-the-art video SR and single image SR methods in terms of both SR performance and target enhancement. Based on the SR results, we further investigate the influence of SR on infrared small target detection and the experimental results demonstrate that the MoCoPnet promotes the detection performance.

Abstract Background Long non-coding RNAs (lncRNAs) regulate adipose tissue metabolism, however, their function on testosterone deficiency related obesity in humans is less understood. For this research, intact and castrated male pigs are the best model animal because of their similar proportional organ sizes, cardiovascular systems and metabolic features. Results We identified lncRNAs in subcutaneous adipose tissue by deep RNA-sequencing using the intact and castrated Huainan male pigs. The results showed that castration reduced serum testosterone but increased body fatness-related traits (serum triglyceride levels, backfat thickness, intramuscular fat content, and adipocyte size). Meanwhile, 343 lncRNAs from subcutaneous adipose tissue were identified, including 223 intergenic lncRNAs (lincRNAs), 68 anti-sense lncRNAs, and 52 intronic lncRNAs. It was predicted that there were 416 recognition sites for C/EBPα in the 303 lncRNA promoter region, and 13 adipogenesis-promoting miRNAs and five adipogenesis-depressing miRNAs target these lncRNAs. Eighteen lncRNAs, including nine up- and nine down-regulated had more than 2-fold differential expression between the castrated and intact male pigs (q-value

Koopmans' theorem implies that the Hartree-Fock quasiparticle gap in a closed-shell system is equal to its single-particle energy gap. In this work, the theorem is generalized to optical transitions in the Hubbard model of graphene nanodots. Based on systematic configuration interaction calculations, it is proposed that the optical gap of a closed-shell graphene system within the Hubbard model is equal to its tight-binding single-particle energy gap in the absence of electron correlation. In these systems, the quasiparticle energy gap and exciton binding energy are found to be dominated by the long-range Coulomb interaction, and thus, both become small when only on-site Hubbard interactions are present. Moreover, the contributions of the quasiparticle and excitonic effects to the optical gap are revealed to nearly cancel each other, which results in an unexpected overlap of the optical and single-particle gaps of the graphene systems. [ABSTRACT FROM AUTHOR]

Spin-polarized electron transport through zigzag-edged graphene nanoislands is studied within the framework of the Pariser-Parr-Pople Hamiltonian. By including both short- and long-range electron-electron interactions, the electron conductance is calculated self-consistently for the hexagonal model on various substrates from which we are able to identify the effects of the many-body interactions in the electron transport. For the system in its lowest antiferromagnetic (AFM) state, the long-range interactions are shown to have negligible effect on the electron transport in the low-energy region in which the conductance is found quenched mainly by the short-range interactions. As the system is excited to its second AFM state, the short- and long-range interactions are found to have opposite effects on the electron transmission, i.e., the electron transmission is found to increase with either the suppression of the long-range interactions or the enhancement of the short-range interactions. When the system moves further into the ferromagnetic state, the conductance becomes spin dependent and its resonance is shown to exhibit a blue shift in an environment with stronger long-range interactions. The distinct impact of short- and long-range electron-electron interactions are attributed to their different effects on the spin polarization in the model system. [ABSTRACT FROM AUTHOR]

A microscopic theory is presented for electron cotunneling through quantum dots in the Coulomb blockade regime. Beyond the semiclassic framework of phenomenological models, a fully quantum mechanical solution for cotunneling of electrons through a one-dimensional quantum dot is obtained by using a quantum transmitting boundary method without any fitting parameters. Elastic and inelastic cotunneling conductance is calculated as a function of the energy of the incident electron. It is revealed that the cotunneling current contains a significant term proportional to V2 (V being the bias voltage) in additional to the well-known V3 term. The result also indicates that the cotunneling conductance exhibits little dependence on the spin configuration of the incident and confined electrons. [ABSTRACT FROM AUTHOR]

An exact diagonalization method is used for studying a [D.sup.-] system in noncircular quantum dots. The results have shown the interplay between the electron-impurity and electron-electron interactions, quantum confinement and external magnetic fields in a few-electron system in quantum dots.

By employing a configuration interaction approach, we study the spin polarization induced by an electric field applied to graphene nanodots. The evolution of both the ground and excited states of the graphene nanodot with the applied electric field is calculated systematically. Three clearly separated field regimes have been identified for the spin gap in the model system, namely, (a) nearly constant in the nonmagnetic phase, (b) rapidly decreasing in the antiferromagnetic phase, and (c) exponential decay in the ferromagnetic phase. It is therefore demonstrated that ferromagnetism can be induced purely by applying an electric field to a nonmagnetic graphene nanodot. Electron-electron interactions which are greatly modified by the applied electric field are believed to account for the two consecutive magnetic phase transitions. [ABSTRACT FROM AUTHOR]

Hund's rule of maximum multiplicity controls the spin configuration of a system with degenerate midgap states, while Lieb's theorem determines the total spin of the ground state of a bipartite lattice. Most of graphene nanostructures follow both Hund's rule and Lieb's theorem, except that a number of nanoflakes with degenerate midgap states violates Hund's rule by exhibiting antiferromagnetic ground states as predicted by Lieb's theorem. To determine why Hund's rule fails and Lieb's theorem can predict correct spin configuration beyond the Hubbard model for which it was proved, we solve the strongly correlated electron states in such graphene nanoflakes where Hund's rule is violated by using a full configuration interaction approach. We find that long-range electron-electron interactions are quenched in both the ground and low-lying excited states of these systems. As there are no interactions between electrons with parallel spins in the system where long-range interactions are absent, we point out that a graphene nanoflake with degenerate midgap states and an antiferromagnetic ground state, in fact, falls very close to an ideal Hubbard system. Quenching of long-range interactions is therefore believed to be the natural explanation for the advantage of Lieb's theorem over Hund's rule in graphene nanostructures. [ABSTRACT FROM AUTHOR]

The problem of super-resolution and tracking for midcourse closely spaced objects (CSO) is examined using a space-based infrared sensor. Within a short time window, the midcourse CSO trajectories on the focal plane can be modeled as following a straight line with a constant velocity. Thus, the object's initial state (location and velocity on the focal plane) exclusively corresponds to its trajectory on the focal plane. Thereupon, the objects number, intensities and initial states, as well as the sensor noise variances, are considered random variables, and a Bayesian model is proposed which is utilized to define a posterior distribution on the joint parameter space. To maximize this distribution, reversible jump Markov chain Monte Carlo algorithm is adopted to perform the Bayesian computation. The proposed approach simultaneously used the multiple time-consecutive frame data to estimate model parameters. Compared with the single-frame method, it not only gains the super-resolution capability but also can directly estimate focal plane trajectories without using explicit data association techniques. Results show that the performance (estimation precision of objects number, focal plane locations, intensities and ballistic trajectories for the CSO, together with the computation load) of the proposed approach outperforms the conventional single-frame and multiframe approaches. [ABSTRACT FROM AUTHOR]

Electron transport in a graphene nanoisland with mixed edge profiles is studied by using the spin-unrestricted Hubbard model. The dumbbell-shaped device consists of two hexagonal nanoislands with zigzag edges connected by a armchair nanoribbon. Including the nearest-neighbor hopping and on-site Coulomb repulsion, the self-consistent calculation shows that two distinct ferromagnetic configurations allowed for the proposed device act like ON and OFF states for spin-polarized electrons. Furthermore, the spin-valve effect is demonstrated, as a proof of concept, in the device occupied by one ferromagnetic configuration without resorting to external magnetic or electric fields. [ABSTRACT FROM AUTHOR]

The possibility of electrical tuning of exciton g-factors in self-assembled InAs/GaAs quantum dots is explored theoretically by means of a tight-binding-like effective bond-orbital approach. The electron g-factor in the dots of various sizes is found to exhibit very little change over a broad range of the field strength. In contrast, the ground hole state in the dots of high aspect ratio is seen very sensitive to the applied field, its g-factor even changes the sign with the field. The distinct behavior of the electron and hole g-factors in the presence of electric field is explained in terms of nonzero envelope orbital angular momentum carried by the hole states. [ABSTRACT FROM AUTHOR]

We present a theoretical study of electron and hole g factors in stacked self-assembled InAs/GaAs quantum dots. The exciton ground and first excited states in the quantum dot molecules are found to exhibit opposite resonances in their g factors in the presence of a small vertical electric field, which is very different from the monotonic behavior of their counterparts in single quantum dots. While the g factor of the electronic ground state is seen to have little variation as the applied electric field increases, the relocalization of the hole states in coupled quantum dots is found to account for the resonant behavior of the exciton g factors. Our theoretical result agrees well with a recent experiment. [ABSTRACT FROM AUTHOR]

Electron g-factors in self-assembled InAs/GaAs quantum dots are studied theoretically by means of a tight-binding method. The anisotropy in the electron g-factor, induced by the band-mixing effect, is found to be much more sensitive to the chemical composition of the dot than the aspect ratio of the structure. The modulus of the vertical electron g-factor is usually seen smaller than the in-plane component in pure InAs dots while the situation could be reversed in highly intermixing InGaAs dots. A microscopic theory is presented to reveal the dependence of the anisotropy in the electron g-factor on the proportion of the valence-band components in the electronic states. Our study indicates the possibility of tuning electron g-factor anisotropy in quantum dots. [ABSTRACT FROM AUTHOR]

The magnetic properties of a hexagonal graphene nanodot are investigated using a configuration-interaction approach. The phase diagram of the nanodot system is obtained for a wide range of Coulomb interaction strengths and dielectric environments, and shows that the magnetic phase transition can be effectively tailored by changing the dielectric environment. Selective magnetic phase between non-magnetic and ferromagnetic could therefore be achieved simply by changing to an appropriate substrate for the graphene nanodot. [ABSTRACT FROM AUTHOR]

The magnetic state of a spintronic device is usually controlled by magnetic contacts or a transverse electric field generated by side gates. In this work, we consider a graphene nanojunction in the presence of a bias voltage that leads to magnetic phase transitions in the system. Combining the non-equilibrium Green’s function with the Hubbard model, our self-consistent calculation reveals that an increasing bias voltage induces consecutive transitions among antiferromagnetic and ferromagnetic states. It is further shown that the graphene nanojunction is turned off in the antiferromagnetic state when the bias voltage is low and can then be switched on to the ferromagnetic state by a high bias voltage. We therefore demonstrate that the magnetic state of the graphene system can be controlled by the bias voltage without resorting to any transverse gates. [ABSTRACT FROM AUTHOR]

We have measured at low temperatures the conductance of electron waveguides fabricated from modulation-doped quantum wells by wet etching and regrowth. We have found that, for a waveguide with abruptly changed geometry at the entrance and exit, the conductance shows oscillations, which are superimposed on a conventional conductance plateau structure. The periods and amplitudes of conductance oscillations depend on the length to width aspect ratio of the waveguide. In addition, the amplitudes of conductance oscillations decrease with increasing temperature. We propose that the observed oscillations are caused by the formation of longitudinal resonant electron states in the waveguide, in analogy with optical Fabry-Perot effects. © 2000 American Institute of Physics. [ABSTRACT FROM AUTHOR]