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Harmonic retrieval (HR) has a wide range of applications in the scenes where signals are modelled as a summation of sinusoids. Past works have developed a number of approaches to recover the original signals. Most of them rely on classical singular value decomposition, which are vulnerable to unexpected outliers. In this paper, to overcome this deficiency, we propose a new random-access HR model and develop robust algorithms combining L 1 -Tucker decomposition methods of Hankel tensor and novel frequency recovery techniques to solve such HR problem. Simulations are designed to compare our proposed methods with some existing tensor-based algorithms for HR. The numerical results demonstrate the outlier-insensitivity of our methods. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration. [ABSTRACT FROM AUTHOR]

In Lin (Calc. Var. Partial Differential Equations 60:196, 2021), the first author proved the Steiner's projection inequality and the Petty projection inequality for sets of finite perimeter but didn't characterize their cases of equality. In this paper, we characterize the case of equality in the Steiner's projection inequality. Moreover, we give a new proof of the equality case in the Petty projection inequality, which was characterized by Wang (Adv. Math. 230:2457–2473, 2012). [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to examine the associations between body composition and temporal eating patterns, including time of first eating occasion, time of last eating occasion, eating window, and eating jet lag (the variability in meal timing between weekdays and weekends).A total of 131 participants were included in the study. Temporal eating pattern information was collected through consecutive 7-day eat timing questionnaires and photographic food records. Body composition was assessed by bioelectrical impedance analysis. Multiple linear regression models were used to evaluate the relationships of temporal eating patterns with body composition, and age was adjusted. Eating midpoint was additionally adjusted in the analysis of eating window.On weekdays, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with lower body fat percentage. On weekends, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with higher FFMI. Longer first eating occasion jet lag was associated with lower lean mass.Our study suggested that earlier and more regular eating patterns may have a benefit on body composition.Methods: The aim of this study was to examine the associations between body composition and temporal eating patterns, including time of first eating occasion, time of last eating occasion, eating window, and eating jet lag (the variability in meal timing between weekdays and weekends).A total of 131 participants were included in the study. Temporal eating pattern information was collected through consecutive 7-day eat timing questionnaires and photographic food records. Body composition was assessed by bioelectrical impedance analysis. Multiple linear regression models were used to evaluate the relationships of temporal eating patterns with body composition, and age was adjusted. Eating midpoint was additionally adjusted in the analysis of eating window.On weekdays, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with lower body fat percentage. On weekends, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with higher FFMI. Longer first eating occasion jet lag was associated with lower lean mass.Our study suggested that earlier and more regular eating patterns may have a benefit on body composition.Results: The aim of this study was to examine the associations between body composition and temporal eating patterns, including time of first eating occasion, time of last eating occasion, eating window, and eating jet lag (the variability in meal timing between weekdays and weekends).A total of 131 participants were included in the study. Temporal eating pattern information was collected through consecutive 7-day eat timing questionnaires and photographic food records. Body composition was assessed by bioelectrical impedance analysis. Multiple linear regression models were used to evaluate the relationships of temporal eating patterns with body composition, and age was adjusted. Eating midpoint was additionally adjusted in the analysis of eating window.On weekdays, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with lower body fat percentage. On weekends, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with higher FFMI. Longer first eating occasion jet lag was associated with lower lean mass.Our study suggested that earlier and more regular eating patterns may have a benefit on body composition.Conclusion: The aim of this study was to examine the associations between body composition and temporal eating patterns, including time of first eating occasion, time of last eating occasion, eating window, and eating jet lag (the variability in meal timing between weekdays and weekends).A total of 131 participants were included in the study. Temporal eating pattern information was collected through consecutive 7-day eat timing questionnaires and photographic food records. Body composition was assessed by bioelectrical impedance analysis. Multiple linear regression models were used to evaluate the relationships of temporal eating patterns with body composition, and age was adjusted. Eating midpoint was additionally adjusted in the analysis of eating window.On weekdays, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with lower body fat percentage. On weekends, both later first eating occasion and last eating occasion were associated with lower lean mass, and longer eating window was associated with higher FFMI. Longer first eating occasion jet lag was associated with lower lean mass.Our study suggested that earlier and more regular eating patterns may have a benefit on body composition. [ABSTRACT FROM AUTHOR]

The Orlicz Minkowski problem is a generalization of the L p Minkowski problem. For a class of appropriate functions and discrete measures that have no essential subspaces, the existence is demonstrated for the discrete Orlicz Minkowski problem. This is a non-trivial extension of the discrete L p Minkowski problem for p < 0 . [ABSTRACT FROM AUTHOR]

Positron generation by an ultra-short ultra-intense laser in an indirect manner has been studied with two-dimensional particle-in-cell (PIC) and Monte Carlo (MC) simulations. In this generation scheme, positrons are produced with energetic electrons accelerated by an ultra-shot laser pulse propagating through an underdense plasma. The dependence of the positron beam properties on the plasma length and secondary target (converter) thickness was investigated in detail. The simulation results reveal that the positron yield is strongly correlated with the total energy of laser-accelerated electrons; both the temperature and divergence of the positron beam are sensitive to the plasma length; and the positron beam has a pulse duration comparable to the incident electron beam. In addition, it is indicated that even with the optimal converter thickness, only a small fraction (11.4%) of positrons can escape out and most of the detected positrons originate from the back edge of the converter. [ABSTRACT FROM AUTHOR]