This paper reports a large‐scale magnetospheric line radiation (MLR) event during a moderate geomagnetic storm on 11 September 2018, which was well recorded by the China‐Seismo‐Electromagnetic ...Satellite (CSES) in the upper ionosphere. The event shows a symmetrical propagation feature at the conjugated locations between the two hemispheres, exhibiting a large spatial extension roughly from the latitudes 54°N to 53°S. The parallel structures are visible both in the electric and magnetic fields at a frequency band ranging from the local proton cyclotron frequency to ∼1.6 kHz. The wave intensity of parallel spectral lines was primarily enhanced in high latitude regions, gradually weakening at mid‐low latitudes, and then got absorbed in the equatorial region, presenting a distinct V‐shaped structure. The frequency spacings between neighboring spectral lines roughly vary from ∼80 to 110 Hz at the high latitudes and ∼80–130 Hz at the low latitudes, suggesting a slight variation feature with latitude. The parallel spectral structures of MLR drift between ∼0.39 and 0.57 Hz/s at high latitudes and ∼0.18–0.19 Hz/s at low latitudes. The wave vector analysis shows that the MLR waves are right‐hand polarized, obliquely propagating toward the Earth and in the azimuthal direction, where the Poynting flux is primarily oriented perpendicular to the ambient magnetic field. The other large‐scale MLR events all exhibit similar parallel structures and polarization characteristics, suggesting the universality of such a phenomenon. However, the azimuthal angles differ among different events, showing complex features.
Plain Language Summary
Magnetospheric line radiation (MLR) is a unique electromagnetic wave distinguished by parallel spectral lines. This study reports a large‐scale MLR event that occurred in the dayside ionosphere. The event shows a symmetrical propagation feature, with a large spatial extension between latitudes 54°N and 53°S. The parallel structures are visible both in the electric and magnetic spectrogram, ranging from the local proton cyclotron frequency to ∼1.6 kHz. The MLR structures were primarily enhanced in high latitude regions, gradually weakening at mid‐low latitudes, and then got absorbed in the equatorial region, presenting a distinct V‐shaped structure. The frequency spacings of MLR roughly vary from ∼80 to 110 Hz in the high latitudes and from ∼80 to 130 Hz in the mid‐low latitude region, slightly varying with latitude. The MLR structures drift between ∼0.39 and 0.57 Hz/s at high latitudes and ∼0.18–0.19 Hz/s at low latitudes. This MLR event is right‐hand polarized, obliquely propagating toward the Earth and in the azimuthal direction, and the Poynting flux is primarily oriented perpendicular to the ambient magnetic field. However, the azimuthal angles differ among different events, indicating the complexity of the wave propagation feature.
Key Points
A large‐scale magnetospheric line radiation (MLR) event shows a symmetrical propagation feature in two hemispheres, presenting a distinct V‐shaped structure
Both the frequencies of the parallel spectral lines and their frequency spacings slightly drift with latitudes
The MLR waves are right‐hand polarized, obliquely propagating toward the Earth and azimuthal direction
Post-classification with multi-temporal remote sensing images is one of the most popular change detection methods, providing the detailed “from-to” change information in real applications. However, ...due to the fact that it neglects the temporal correlation between corresponding pixels in multi-temporal images, the post-classification approach usually suffers from an accumulation of misclassification errors. In order to solve this problem, previous studies have separated the change and non-change candidates with change vector analysis, and they have only updated the classes of the changed pixels with the post-classification; however, this approach with thresholding loses the continuous change intensity information, where larger values indicate higher probability to be changed. Therefore, in this paper, a new post-classification method with iterative slow feature analysis (ISFA) and Bayesian soft fusion is proposed to obtain reliable and accurate change detection maps. The proposed method consists of three main steps: 1) independent classification is implemented to obtain the class probability for each image; 2) the ISFA algorithm is used to obtain the continuous change probability map of multi-temporal images, where the value of each pixel indicates the probability to be changed; and 3) based on Bayesian theory, the a posteriori probabilities for the class combinations of coupled pixels are calculated to integrate the class probability with the change probability, which is named as Bayesian soft fusion. The class combination with the maximum a posteriori probability is then determined as the change detection result. In addition, a class probability filter is proposed to avoid the false alarms caused by the spectral variation within the same class. Two experiments with multi-temporal Landsat Thematic Mapper (TM) images indicated that the proposed method achieves a clearly higher change detection accuracy than the current state-of-the-art methods. The proposed method based on Bayesian theory and ISFA was also verified to have the ability to improve the change detection rate and reduce the false alarms at the same time. Given its effectiveness and flexibility, the proposed method could be widely applied in land-use/land-cover change detection and monitoring at a large scale.
•A new post-classification method was proposed for accurate change map.•Iterative slow feature analysis was utilized to get the change probability.•Class probability from classification was integrated with change probability.•Bayesian soft fusion was proposed to fuse the probability information.•The accuracies of change detection and transition identification are improved.
A novel multiscale morphological compressed change vector analysis (M 2 C 2 VA) method is proposed to address the multiple-change detection problem (i.e., identifying different classes of changes) in ...bitemporal remote sensing images. The proposed approach contributes to extend the state-of-the-art spectrum-based compressed change vector analysis (C 2 VA) method by jointly analyzing the spectral-spatial change information. In greater details, reconstructed spectral change vector features are built according to a morphological analysis. Thus more geometrical details of change classes are preserved while exploiting the interaction of a pixel with its adjacent regions. Two multiscale ensemble strategies, i.e., data level and decision level fusion, are designed to integrate the change information represented at different scales of features or to combine the change detection results obtained by the detector at different scales, respectively. A detailed scale sensitivity analysis is carried out to investigate its impacts on the performance of the proposed method. The proposed method is designed in an unsupervised fashion without requiring any ground reference data. The proposed M 2 C 2 VA is tested on one simulated and three real bitemporal remote sensing images showing its properties in terms of different image size and spatial resolution. Experimental results confirm its effectiveness.
•This case report assessed the use of teduglutide in a patient with short bowel syndrome undergoing hemodialysis.•A complete nutritional assessment was performed using bioelectrical impedance vector ...analysis.•Teduglutide treatment was successful after a 1-y follow-up.•A complete nutritional assessment including bioelectrical impedance vector analysis, blood tests, and anthropometry can be good practice for monitoring nutrition in patients with short bowel syndrome and chronic kidney disease requiring hemodialysis.
We present the case of a 35-y-old woman with short bowel syndrome secondary to extensive intestinal resection with associated chronic kidney disease who was undergoing hemodialysis. This patient required permanent supplementation with intradialytic parenteral nutrition because of a high-output end-jejunostomy. The patient was a candidate for treatment with teduglutide, a glucagon-like peptide 2 analog, intending to increase intestinal absorption. A complete nutritional assessment was performed using bioelectrical impedance vector analysis. Teduglutide treatment was successful, and after a 1-y follow-up, the patient had considerably reduced end-jejunostomy output (reduction of 6 L/d) and an improved nutritional status (9.1 kg weight gain, 1.4 kg fat-free mass gain, and a 2.2-degree increase in bioimpedance phase angle). However, we have been unable to reduce intradialytic parenteral nutrition, which the patient requires thrice weekly. No significant secondary effects have occurred because of teduglutide administration. This may be the first reported use of teduglutide in a patient with short bowel syndrome undergoing hemodialysis who was monitored using bioelectrical impedance data during follow-up.
We revise the problem of extracting one independent component from an instantaneous linear mixture of signals. The mixing matrix is parameterized by two vectors: one column of the mixing matrix, and ...one row of the demixing matrix. The separation is based on the non-Gaussianity of the source of interest, while the remaining background signals are assumed to be Gaussian. Three gradient-based estimation algorithms are derived using the maximum likelihood principle and are compared with the Natural Gradient algorithm for Independent Component Analysis and with One-Unit FastICA based on negentropy maximization. The ideas and algorithms are also generalized to the extraction of a vector component when the extraction proceeds jointly from a set of instantaneous mixtures. Throughout this paper, we address the problem concerning the size of the region of convergence for which the algorithms guarantee the extraction of the desired source. We show that the size is influenced by the signal-to-interference ratio on the input channels. Simulations comparing several algorithms confirm this observation. They show a different size of the region of convergence under a scenario in which the source of interest is dominant or weak. Here, our proposed modifications of the gradient methods, taking into account the dominance/weakness of the source, show improved global convergence.
Change detection is a research hotspot in the remote sensing field. In this letter, an unsupervised change detection method was proposed by optimizing two critical steps, i.e., the generation and ...analysis of difference image. First, the difference vectors of features are calculated using the simple differencing method. Some changed and unchanged pixels are generated by the majority voting on the results produced by clustering the difference vectors and then are used for the weight calculation of difference vectors. The weights are calculated by means of F-Score and considered in the weighted change vector analysis to produce a discriminative difference image. Finally, the change map is obtained by the improved Markov random field which takes the difference in the neighborhood pixel values into account. Experimental results on three data sets demonstrated that the proposed method outperformed six unsupervised change detection methods in terms of overall accuracy.
An optical vector analyzer assisted by stimulated Brillouin scattering (SBS) processing is proposed and experimentally demonstrated. Benefitting from the selective amplification and attenuation ...achieved by the SBS processing, the proposed OVA has enhanced dynamic range and measurement accuracy. An electro-optic modulator produces an intensity-modulated optical double-sideband (ODSB) signal. During the SBS processing, the +1st-order sideband of the ODSB signal is amplified while the -1st-order sideband is attenuated. Thus, an optical single-sideband signal owning a large sideband suppression ratio is achieved, which is then served as the probe signal and passes through an optical device-under-test. Then, by square-law detection, a photocurrent carrying the frequency responses is generated. Receiving and detecting the photocurrent, the multi-dimensional frequency responses, including magnitude, delay, and phase responses, are obtained. In an experiment, 34.05 dB amplification and 22.85 dB attenuation are achieved by the SBS processing. A dynamic range enhancement of 14.01 dB is obtained by measuring an optical bandpass filter, which is well coincident with the theoretical result. The comparative optical transfer delay measurement of a high-precision variable optical delay line indicates accuracy improvement.
The localization of brain sources based on EEG measurements is a topic that has attracted a lot of attention in the last decades and many different source localization algorithms have been proposed. ...However, their performance is limited in the case of several simultaneously active brain regions and low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a space–time–frequency (STF) or space–time–wave–vector (STWV) tensor and decomposing it using the Canonical Polyadic (CP) decomposition. In this paper, we present a new algorithm for the accurate localization of extended sources based on the results of the tensor decomposition. Furthermore, we conduct a detailed study of the tensor-based preprocessing methods, including an analysis of their theoretical foundation, their computational complexity, and their performance for realistic simulated data in comparison to conventional source localization algorithms such as sLORETA, cortical LORETA (cLORETA), and 4-ExSo-MUSIC. Our objective consists, on the one hand, in demonstrating the gain in performance that can be achieved by tensor-based preprocessing, and, on the other hand, in pointing out the limits and drawbacks of this method. Finally, we validate the STF and STWV techniques on real measurements to demonstrate their usefulness for practical applications.
•Localization of spatially distributed sources using tensor-based preprocessing•Performance analysis of two tensor-based preprocessing methods•Numerical complexity of tensor-based and conventional algorithms•Performance comparison on realistic simulated EEG data•Validation on real EEG data from an epilepsy patient
•Introduces eye blink detection algorithm while outperforming most of the related work.•Introduces the largest real-world dataset on eye blink detection with more than 1800 annotated eye ...blinks.•Proposes the way how to evaluate eye blink detection algorithms.
A new eye blink detection algorithm is proposed. Motion vectors obtained by Gunnar–Farneback tracker in the eye region are analyzed using a state machine for each eye. Normalized average motion vector with standard deviation and time constraint are the input to the state machine. Motion vectors are normalized by the intraocular distance to achieve invariance to the eye region size. The proposed method outperforms related work on the majority of available datasets. We extend the way how to evaluate eye blink detection algorithms without the impact of algorithms used for face and eye detection. We also introduce a new challenging dataset Researcher’s night, which contains more than 100 unique individuals with 1849 annotated eye blinks. It is currently the largest dataset available.
Detailed textural and compositional study of calc-alkaline lamprophyres and minettes from Zeneta, SE Spain Neogene Volcanic Province (NVP) are used to unravel the magma sources and differentiation ...processes involved in their formation. The presence of xenocrysts of various origins indicates a hybrid nature involving mantle-derived alkaline lamproitic and continental crust-derived granitic parental magmas. A new U-Th-Pb zircon age of Zeneta minettes allows contextualizing their generation in time and space during regional lamproite magma intrusion and crustal anatexis in the NVP. Interaction and mixing of these compositionally contrasted magmas resulted in the formation of hybrid calc-alkaline lamprophyre minette. This process is reflected by the phases that crystallized from the hybrid magma, particularly phlogopite, and by the whole-rock composition of the less fractionated rocks. The calculated contribution of lamproitic and crustal-derived magma end-members in minette formation are 30-40% and 60-70%, respectively. Mixing of end-member magmas of contrasting rheological properties was possible only in a calculated thermal-window of 1025-1125°C, after cooling of intruding lamproitic magma and heating of host granitic anatectic region. The calculated thermal window fits with the estimated rheological properties of Zeneta minettes and the crystallization temperature of early minette-derived phlogopite. Furthermore, fractional crystallization was identified for the first time in the Zeneta minettes, based on the observed whole-rock line of descent from the less evolved mixed magmas through intermediate to felsic minettes and associated textural and compositional features of late crystallized phases. Polytope Vector Analysis allowed an integrated quantitative characterization of magma differentiation, including magma mixing and subsequent fractional crystallization. The identification of mixing and fractionation processes in calc-alkaline minettes genesis, which otherwise does not show spatial and temporal association in the field with granitic bodies, opens a new scenario to be considered in understanding the petrogenesis of these rocks.
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